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SCIENTIFIC RESEARCH INSTITUTE OF ECONOMIC AND SOCIAL ISSUES OF GLOBALIZATION
When Debt Overtakes Spending: A Partial Wavelet Coherence Analysis of Fiscal Policy and Economic Growth in France (1990–2024)
This study investigates the dynamic relationships among public expenditure, public debt, and economic growth in France over the 1990–2024 period using wavelet coherence (WTC), partial wavelet coherence (PWC), and Granger causality analysis. This multi-method approach allows fiscal-macroeconomic linkages to be assessed simultaneously across time and frequency, capturing structural shifts that conventional econometric methods cannot detect. Results show that fiscal-macroeconomic associations operate predominantly at business cycle frequencies and strengthen markedly following eurozone integration and the 2008 financial crisis. Sub-period analysis reveals a clear structural transformation in France’s fiscal regime. Before EMU, public spending maintained a stronger conditional association with growth than public debt, consistent with expenditure-led stabilization under monetary sovereignty. After 1999, this pattern reverses. Post-2008, the divergence widens further as debt levels exceed 110% of GDP. Granger causality tests confirm bidirectional feedback between fiscal instruments and growth, alongside strong unidirectional causality running from expenditure to debt. These findings suggest that France has transitioned from a fiscal regime driven by public spending to one increasingly constrained by accumulated debt, with direct implications for consolidation strategy and medium-term budgetary design within the eurozone framework. Keywords: Wavelet partial analysis, fiscal policy, public debt, public expenditure, France. Introduction The relationship between fiscal policy and economic growth is one of the most persistent debates in macroeconomics, traditionally opposing Keynesian and neoclassical perspectives. While the Keynesian approach emphasizes the effectiveness of public spending in stimulating aggregate demand, particularly during recessions, the neoclassical approach highlights the negative effects of public debt accumulation via fiscal expectations, sovereign risk premiums, and the crowding out of private investment. However, most of the existing empirical literature treats these two dimensions of fiscal policy separately, neglecting their complex interactions and potentially distinct transmission mechanisms. Over the past three decades, France has experienced persistent fiscal imbalances, with public spending among the highest in the OECD, around 55–58% of GDP,[1] and debt levels exceeding 100% of GDP after the COVID-19 crisis, 113% in the fourth quarter of 2024.[2] In addition, membership in the European Monetary Union eliminates national monetary policy autonomy, which further complicates the management of France’s fiscal policy. This has reignited debates about the growth impact of fiscal expansion and the risks of excessive indebtedness. Yet, the channels through which fiscal policy influences growth, directly through public investment and consumption, or indirectly through debt accumulation and financial constraints, remain complex. Traditional econometric methods often fail to disentangle these dynamic interactions across time and frequency. By employing wavelet coherence and partial wavelet coherence, this study offers a nuanced exploration of how fiscal instruments transmit their effects on growth at both short-term and long-term horizons. Such an approach provides valuable insights for policymakers seeking to balance fiscal discipline with economic stimulus and to ensure the long-term sustainability of France’s public finances while supporting economic performance. This research offers both a methodological and empirical contribution by systematically examining the time-varying and frequency-dependent co-movement between fiscal policy variables and economic growth through an innovative approach that combines Wavelet Total Coherence (WTC), Partial Wavelet Coherence (PWC), and Granger causality analysis. This methodology addresses three fundamental questions often ignored in the conventional literature: First, to what extent does public debt co-move with economic growth independently of public expenditure dynamics? Second, do public expenditures exhibit distinct co-movement with growth beyond the debt accumulation they generate? Third, is the observed relationship between public debt and government expenditure mainly driven by underlying structural fiscal constraints, or does it reflect a shared response to fluctuations in economic growth? By applying this methodology to France over the period 1990–2024, we obtain a particularly relevant case study. This context allows for an examination of fiscal transmission co-movements in a setting where fiscal policy serves as the main instrument of macroeconomic stabilization, while being constrained by European rules (the Maastricht criteria and the Stability and Growth Pact). The article is organized as follows: Section 1 presents the literature review and theoretical positioning. Section 2 describes the classical and partial wavelet coherence methodology. Section 3 presents the data and empirical specifications. Section 4 presents the main results. Section 5 discusses the theoretical and policy implications. Section 6 highlights the research limitations, followed by the conclusion. 1. Literature Review 1.1. Public debt and growth: The theoretical debate The relationship between public debt and economic growth has generated abundant and controversial literature. The neo-Ricardian perspective, initiated by Barro,[3] posits that rational economic agents anticipate that public debt accumulation will require future tax increases, leading them to increase precautionary savings and reduce current consumption, thus neutralizing the expansionary effects of debt-financed spending. Although strict Ricardian equivalence is largely rejected empirically, it underscores the importance of expectations and intertemporal constraints in fiscal policy transmission. Recent empirical work has identified several channels through which high levels of public debt can negatively affect growth. Reinhart and Rogoff[4] published their influential paper “Growth in a Time of Debt” in The American Economic Review, arguing that when government debt exceeds 90% of GDP, average growth falls considerably. Their analysis was based on data from 44 countries spanning about 200 years. However, Herndon et al. [5]published a critique identifying coding errors, selective exclusion of available data, and unconventional weighting of summary statistics. After correcting these errors, they found that countries with public debt/GDP ratios above 90% averaged 2.2% real annual GDP growth, not -0.1% as originally published. More robustly, Checherita-Westphal and Rother[6] identify a negative impact of debt on growth beyond 90-100% of GDP for European countries, operating through three main channels: increasing long-term interest rates, crowding out private investment, and reducing total factor productivity. Égert[7] confirms these non-linear effects while emphasizing their dependence on the economy’s cyclical position. Corsetti et al.[8] analyze the confidence channel during the European sovereign debt crisis, showing how loss of confidence in fiscal sustainability can trigger self-fulfilling prophecies and multiple equilibria. Afonso and de Sá Fortes Leitão Rodrigues[9] examined the relationship between public debt, governance, and economic growth. Their study of 44 developing countries from 1990-2000 shows that public debt impedes economic growth in all quantiles. However, in the presence of good governance, public debt promotes economic growth in the medium to higher quantiles. The empirical findings confirm that governance is far more important in promoting economic growth. 1.2. Public expenditure and growth: Keynesian effectiveness The literature on public expenditure effects on growth has developed considerably since the 2008 financial crisis, renewing interest in Keynesian fiscal multipliers. Blanchard and Perotti[10] established a benchmark methodology using impulse response functions in a structural VAR framework, estimating public expenditure multipliers around 1.5 after four quarters for the United States. A major recent development concerns the cyclical dependence of fiscal multipliers. Auerbach and Gorodnichenko[11] demonstrate that multipliers can be two to three times higher during recessions than in expansion periods, a result confirmed by Batini et al.[12] for a panel of advanced countries. This asymmetry is explained by the presence of unused productive capacity during recessions, reducing crowding-out effects on private demand, and by the prevalence of credit constraints affecting households and firms during periods of financial stress. This methodological controversy illustrates the sensitivity of estimates to identification assumptions and measurement of fiscal shocks. The composition of public expenditure also appears crucial. Arestis et al. (2020)[13] provide empirical evidence on the linkage between government expenditure and output using the Keynesian view versus Wagner’s law, demonstrating the importance of government expenditure in stimulating economic growth. Recent research using panel ARDL approaches for European Union countries shows that different categories of public expenditures have dissimilar long- and short-term effects on economic performance. Oyadeyi[14] found that in ECOWAS countries, government expenditure positively influences real GDP, with findings indicating that the response of economic growth to government spending shocks differs according to the nature of shocks. At the disaggregated level, Nguyen and Bui[15] collected data from 16 emerging and developing economies and showed that government expenditure negatively impacts economic growth in the long run. Their study suggests that public sector consumption does not promote economic growth, while several studies have found a positive correlation between economic growth and educational indicators or expenditures. France presents a particularly instructive case study for examining the composition and efficiency of public expenditure. Afonso et al.[16] examined public spending efficiency in France using historical data from 1870-2010 and found that the only functional component of expenditure that clearly contributes to the growth of French output is expenditure aimed at the protection of property rights. Public interventions in support of the economy, on the other hand, have no impact on growth. In the area of social spending, only health expenditure contributes to output growth, while education spending shows insignificant effects. These findings provide empirical support for Smith’s minimal state hypothesis in the French context: the restriction of the size of the state and the delimitation to its essential functions tend to favor output growth. This contrasts with the more general findings in developing countries, where education expenditure typically shows positive growth effects. 1.3. Debt-expenditure interactions: A neglected dimension Despite abundant literature on the separate effects of debt and expenditure, few studies systematically examine their interactions and the decomposition of their respective effects. Most studies control for one variable when analyzing the other, but without explicit decomposition of direct and indirect effects. Ilzetzki et al.[17] represent a notable exception, examining how public expenditure effectiveness varies according to pre-existing debt levels. They find that fiscal multipliers are significantly lower in countries with high debt-to-GDP ratios, suggesting a negative interaction between debt level and expenditure effectiveness. Huidrom et al.[18] confirm this result and show that this interaction operates primarily through the confidence channel and expectations of fiscal sustainability. Nguyen and Trinh[19] examined fiscal standards using panel data from 92 countries from 2000 to 2021, showing that fiscal standards decrease the adverse effects of fiscal rules on output growth, demonstrating a trade-off between public debt sustainability and output growth. However, these works mainly treat debt level as a conditional variable moderating expenditure effect, rather than as exerting autonomous effects that must be analytically distinguished. Our partial wavelet coherence approach precisely enables this conditional co-movement analysis, revealing the time-frequency structure of fiscal relationships. 2. Methodology and Data This section first outlines the wavelet analysis methodology applied in the study and then presents the dataset used for the empirical investigation 2.1. Analytical framework This study employs wavelet-based time-frequency analysis to examine the dynamic relationships among economic growth and fiscal policy in France. Unlike conventional time-series methods that assume stationarity and time-invariant correlations, wavelet techniques decompose relationships across both time and frequency domains, revealing how co-movements evolve at different periodicities (short-term fluctuations vs. long-term trends) and across different historical episodes (crisis vs. stable periods). Our methodological approach proceeds in four stages: (1) preliminary stationarity testing and data transformation, (2) bivariate wavelet coherence (WTC) to identify pairwise co-movements, (3) partial wavelet coherence (PWC) to isolate conditional relationships from third-variable confounding, and (4) Granger causality tests to establish temporal precedence. This multi-method triangulation strengthens the empirical evidence beyond what any single technique can provide. Since our data are quarterly, each wavelet period corresponds to one quarter; thus, 2-4 periods represent 6 months to 1 year (short-run), 8-16 periods represent 2 to 4 years (medium-run), and 16-32 periods represent 4 to 8 years (long-run). These conversions are applied consistently throughout the interpretation of all wavelet coherence figures. 2.2. Wavelet coherence The wavelet coherence framework, originally developed by Goupillaud et al.,[20] enables the examination of causal relationships between two variables simultaneously across both the time and frequency domains. Wavelet total coherence measures local correlation between two time series x(t) and y(t) in the time-frequency domain. It generalizes the concept of cross-correlation by allowing this correlation to vary both in time and according to the considered frequencies (or periods). The continuous wavelet transform (CWT) decomposes a time series into time-frequency space by convolving the data with scaled and translated versions of a mother wavelet function. For a discrete time series x(t) with uniform time steps δt and length N, the CWT is defined as: where: Wx(a,b) denotes the wavelet coefficient at scale a and time position b ψ(t) represents the mother wavelet function ψ∗(t) is the complex conjugate of the mother wavelet a is the wavelet scale (inversely related to frequency) b is the translation parameter (time localization) This study employs the Morlet wavelet as the mother wavelet function, following the standard practice in economic and financial applications (Aguiar-Conraria & Soares, 2014; Rua & Nunes, 2009).[21] The Morlet wavelet is defined as: The Morlet wavelet is particularly advantageous for economic applications because: It provides excellent frequency resolution, crucial for distinguishing business cycle frequencies; Its Gaussian envelope ensures good time localization for identifying structural breaks; It is complex-valued, enabling extraction of both amplitude and phase information To examine the co-movement between two time series, we construct the cross-wavelet transform, which identifies regions in time-frequency space where the two series exhibit high common power. For two time series x(t) and y(t)with wavelet transforms Wx(a,b) and Wy(a,b), the cross-wavelet transform is defined as: where Wy∗​(a,b) denotes the complex conjugate of Wy(a,b) The cross-wavelet power spectrum is then: This measure quantifies the local covariance between the two series at each time-frequency location. High cross-wavelet power indicates that both series exhibit large-amplitude oscillations at that particular scale and time, suggesting potential interaction or common driving forces. However, cross-wavelet power is influenced by the individual power spectra of each series; regions of high cross-wavelet power may simply reflect periods where both series have high variance, rather than genuine co-movement. To address the limitation of cross-wavelet power’s dependence on individual variances, we employ wavelet coherence, which normalizes the cross-wavelet spectrum by the power spectra of the individual series. This normalization produces a measure analogous to the squared correlation coefficient, bounded between 0 and 1, facilitating interpretation. The wavelet coherence between two time series x(t) and y(t) is defined as: where S denotes a smoothing operator applied in both time and scale dimensions. The smoothing operator S is essential to obtain a consistent estimator of coherence. Without smoothing, the coherence would trivially equal unity at all time-frequency locations. Following Torrence and Compo,[22] we apply smoothing in both the time direction (along the time axis at each scale) and the scale direction (across adjacent scales at each time point). 2.3. Partial Wavelet Coherence (PWC) Partial wavelet coherence extends the bivariate coherence framework to account for the confounding influence of a third variable, enabling the isolation of conditional co-movement from third-variable confounding. This multivariate extension is crucial for disentangling the complex co-movement patterns among fiscal policy variables. The concept of partial wavelet coherence is analogous to partial correlation in classical statistics but is implemented in the time-frequency domain. For three time series x(t), y(t), and z(t), the partial coherence between x and y controlling for z measures the strength of the conditional x-y relationship after removing the components of their co-movement attributable to their mutual relationships with z. Following Mihanović et al.[23] and Ng & Chan,[24] the squared partial wavelet coherence is computed in the frequency domain to preserve time-frequency localization: Equivalently, this can be expressed in terms of the normalized coherence measures: where: Rxy(a,b), Rxz​(a,b), Ryz​(a,b) are the smoothed wavelet coherence measures between pairs of variables Rzy∗(a,b) is the complex conjugate of Rzy​(a,b) All coherence measures are computed at the same scale a and time position b. The partial wavelet coherence ρxy∣z2(a,b) ranges from 0 to 1, with the same interpretation as classical wavelet coherence: Values near 0: No conditional co-movement between x and y after controlling for z. Values near 1: Strong conditional co-movement independent of z. The frequency-domain formulation employed here removes the influence of z separately at each time-frequency location, allowing the confounding effect to vary across both time and frequency. This is essential for fiscal policy analysis, where the role of control variables (e.g., debt dynamics) may be negligible at high frequencies (short-term fluctuations) but dominant at low frequencies (long-term trends), and these patterns may shift over time as policy regimes change. We compute partial wavelet coherence using the pwtc() function from the biwavelet package (version 0.20.21) in R,[25] which implements the frequency-domain methodology described above. Statistical significance is assessed using Monte Carlo simulations with 1000 randomized surrogates, analogous to the procedure for classical wavelet coherence. 3. Data and Empirical Specifications We use French quarterly data from 1990Q1 to 2024Q4, totaling 140 observations. This period covers several major economic cycles and macroeconomic shocks: the early 1990s recession, preparation for European monetary union (1992-1998), the global financial crisis (2008-2009), the European sovereign debt crisis (2010-2012), and the COVID-19 pandemic (2020-2021). Descriptive statistics reveal that French GDP growth averaged 0.4% per quarter over 1990–2024, with high volatility and extreme leptokurtosis (kurtosis = 52.56), driven by unprecedented shocks such as the COVID-19 collapse in Q2 2020 (-12.19%) and its subsequent rebound (+15.36%). Public debt rose sharply from 36% to 117% of GDP, accelerating after 2008 and again during the pandemic, while public expenditure remained relatively stable around 55% of GDP - a divergence that points to a chronic structural deficit where revenues persistently fall short of spending. Simple linear correlations between GDP growth and either debt (-0.009) or expenditure (-0.11) are negligible, whereas the strong debt-expenditure correlation (0.79) reflects the government budget constraint; these weak pairwise correlations motivate the use of wavelet analysis, which is better suited to capturing the non-linear and non-stationary relationships that classical methods cannot detect. Finally, Variance Inflation Factors of 2.65 for both debt and expenditure confirm the absence of problematic multicollinearity, validating the reliability of the subsequent partial coherence analysis. 4. Empirical Results 4.1. Stationarity tests results The following table indicates the stationarity test results. The three tests: ADF, PP, and KPSS results are highlighted in Table 5. The unit root tests indicate that public expenditure and public debt are non-stationary in levels but become stationary after first differencing, implying that both variables are integrated of order one, I(1). In contrast, GDP growth is stationary in levels, suggesting an I(0) process. Figure 3 indicates the trends of the two variables after the first-difference transformation. 4.2. Wavelet analysis results 4.2.1. Debt – GDP growth relationship 4.2.1.1 Total coherence (WTC) Figure 4 shows that wavelet coherence between public debt and GDP growth is largely concentrated at medium- to long-run horizons (8–32 periods), with persistently strong co-movement emerging especially from the mid-sample onward, while short-run coherence (2–4 periods) remains sporadic. Phase arrows in significant long-run regions predominantly point left and slightly downward, suggesting that rises in public debt tend to precede declines in GDP growth, consistent with debt overhang and crowding-out hypotheses, while some medium-run intervals show left-upward arrows, indicating episodes of countercyclical fiscal responses where growth slowdowns lead to debt increases. Overall, the debt-growth nexus appears time-varying and frequency-dependent, with debt leading growth at lower frequencies during much of the post-2000 period, though these patterns are suggestive rather than formally conclusive of a structural causal relationship. 4.2.1.2. Partial coherence (PWC) controlling for expenditure The Partial Wavelet Coherence (PWC) between GDP growth and public debt, after controlling for public expenditure, reveals interesting results: This partial wavelet coherence analysis isolates the direct relationship between French GDP growth and public debt while controlling for public expenditure effects. The analysis reveals significant coherence concentrated primarily in the medium to long-term frequency bands (8-32 periods) between approximately time points 60-120. This region of high coherence (red-orange zones with values approaching 0.8-1.0) indicates that during this critical period-roughly corresponding to France’s eurozone consolidation and crisis years- public debt and GDP growth exhibited strong co-movement at business cycle frequencies. The phase arrows point predominantly rightward and slightly upward, suggesting a positive relationship where debt dynamics and growth are synchronized, though with potential lead-lag effects. For France specifically, this pattern reflects the country’s challenging fiscal trajectory within the eurozone framework. The strong coherence in the 60–120-time window likely captures France’s experience during the European sovereign debt crisis and subsequent recovery, when rising French public debt (climbing from around 65% to over 100% of GDP) became increasingly intertwined with growth outcomes through confidence channels, sovereign risk premia, and constraints on policy flexibility. The isolated eras of coherence at shorter periods (4-8 range) around time points 10-30 suggest episodes during France’s early EMU years when debt and growth synchronized at higher frequencies, possibly reflecting adjustment dynamics as France adapted to single currency constraints and Stability and Growth Pact requirements. The relatively weak coherence at very short periods indicates that quarterly fluctuations in French debt and growth do not strongly correlate, while diminishing coherence at very long periods suggests secular trends may diverge. The concentration of coherence at business cycle frequencies has important implications for French fiscal policy: debt management strategies should focus on medium-term horizons (2-8 years) where the debt-growth nexus is strongest, rather than expecting immediate short-term effects or relying exclusively on long-term projections. 4.2.2. Expenditure-GDP relationship 4.2.2.1. Wavelet total coherence (WTC) The following plot shows the time frequency dependency between GDP growth and public expenditure. Several consistent patterns emerge: The bivariate wavelet coherence (Figure 6) reveals substantial co-movement between public expenditure and GDP growth, particularly at medium- to long-term frequencies (8-32 years). The widespread red-orange regions, enclosed by thick black contours indicating statistical significance at the 5% level, demonstrate persistent high coherence throughout most of the sample period, especially in the 16-32-year frequency band. The phase arrows, predominantly pointing rightward and downward, suggest that public expenditure leads GDP growth by approximately one quarter of the cycle, indicating a pro-cyclical or potentially counter-cyclical fiscal stance depending on the specific time window. This strong bivariate relationship supports the conventional Keynesian view that fiscal policy exerts meaningful effects on economic activity across multiple time horizons. 4.2.2.2 Partial coherence (PWC) controlling for debt Figure 7 examines the coherence between French GDP growth and public expenditure while controlling for debt effects. Strong coherence appears in the 8-32 period bands during the 60–120 time window, similar to the debt analysis, but with notable differences in spatial distribution and intensity. The high coherence region appears more concentrated around the 16-period band and extends with somewhat different temporal dynamics, suggesting that public expenditure’s relationship with GDP growth operates through partially distinct frequency channels compared to debt. For France, this pattern reflects the country’s historically strong reliance on public expenditure as an economic management tool. With government spending at approximately 57% of GDP, France maintains one of the world’s largest public sectors. The coherence at business cycle frequencies confirms that French public spending, encompassing extensive social protection, public services, and state intervention, maintains significant synchronization with growth outcomes over medium-term horizons. The phase relationships show predominantly positive associations with more immediate effects compared to debt, consistent with expenditure having direct demand-side impacts through government consumption, investment, and transfers. However, the visual coherence patterns indicate that while expenditure and growth remain connected, the strength of this connection when controlling for debt has diminished, reflecting France’s fiscal policy dilemma: high debt levels now constrain the effectiveness of the expenditure activism that historically defined French economic policy. The scattered islands of short-term coherence may correspond to specific fiscal interventions or crisis responses where spending had more immediate growth effects. 4.2.3. Expenditure-debt relationship 4.2.3.1 Wavelet Total Coherence (WTC) Figure 8 shows that public expenditure and public debt are strongly and persistently synchronized at medium- to long-term horizons (8-32 periods), while their short-run relationship remains weak and intermittent. This means temporary spending fluctuations do not immediately affect debt, but sustained spending patterns are a key driver of debt accumulation over time. Phase arrows predominantly point right and upward, indicating that spending increases tend to precede and cause rises in public debt, consistent with standard deficit-financing logic. In some sub-periods, arrows tilt slightly downward, hinting at occasional feedback where high debt levels begin to constrain expenditure decisions, likely through consolidation pressures or rising debt-servicing costs. 4.2.3.2 Partial coherence (PWC) controlling for GDP Figure 9 presents the partial wavelet coherence between public expenditure and public debt after controlling for GDP growth Figure 9 shows that French public debt and public expenditure have moved closely together across most time periods and frequencies, even after removing the influence of GDP growth. The strongest synchronization appears at medium-term horizons (8-32 periods), reflecting coordinated fiscal management where borrowing has consistently financed spending commitments, not just crisis-driven stimulus, but also France’s structural social and public service obligations. Early in the sample, tight short-term coupling reflects the pressure of meeting Maastricht criteria, though France repeatedly fell short. Phase arrows indicate that debt tends to slightly lead expenditure, with both moving in the same direction. However, the relatively low post-crisis partial coherence value (0.21) reveals that much of this co-movement is actually driven by shared reactions to growth fluctuations rather than independent fiscal decisions, suggesting that France’s fiscal policy has become more reactive than proactive in recent years. 4.3. Robustness checks (pre-EMU vs post-EMU; pre-2008 vs post-2008) Table 6 reports the average Wavelet Coherence (WTC) and Partial Wavelet Coherence (PWC) estimates between GDP growth, public debt, and public expenditure across different institutional and macroeconomic regimes. Table 6 reports wavelet coherence (WTC) and partial wavelet coherence (PWC) estimates for the three variable pairs: GDP growth, public debt, and public expenditure, across four sub-periods. Full sample: Over the entire 1990–2024 period, all three variable pairs display strong bivariate coherence: GDP-Expenditure leads at 0.677, followed by GDP-Debt (0.618) and Debt-Expenditure (0.601). These high values are unsurprising given France’s large public sector, where government spending represents around 57% of GDP. Once the influence of the third variable is controlled for, however, partial coherence values fall to the 0.25, 0.29, 0.31 range, indicating that a substantial share of the observed pairwise associations reflects common exposure to fiscal dynamics rather than direct bilateral linkages. Pre-EMU period (before 1999): All coherence measures are at their weakest in this sub-period. The GDP-Expenditure association (0.501) exceeds that of GDP-Debt (0.431), in line with France’s traditional reliance on public spending as its main macroeconomic instrument under full monetary sovereignty. Notably, the conditional expenditure-growth estimate (PWC GE|D = 0.393) remains relatively high, confirming that public spending exerted a meaningful independent influence on growth before the constraints of eurozone membership applied. This indicates that expenditure maintained strong conditional co-movement with growth when France had fiscal autonomy. Post-EMU period (1999 onward): Euro adoption is accompanied by a broad strengthening of all coherence measures: GDP-Debt rises to 0.668, GDP-Expenditure to 0.674, and Debt-Expenditure to 0.612. At the conditional level, the debt-growth estimate (PWC GD|E) increases to 0.442 while the expenditure-growth estimate (PWC GE|D) falls to 0.225. This shift suggests that, under eurozone fiscal rules, debt accumulation gradually took over the role that public spending had previously played in driving growth fluctuations. Pre-crisis period (before 2008): The WTC GDP-Debt measure (0.442) is lower in this sub-period than in either of the post-EMU or post-crisis windows, though the absolute minimum across all sub-periods belongs to the Pre-EMU era (0.431). More notable is the PWC GE|D, which reaches 0.573 - its highest value across all sub-periods. This suggests that French public spending maintained its closest association with growth during the relatively calm years of early eurozone membership, a finding that sits in stark contrast with France’s repeated violations of Stability and Growth Pact deficit limits during the same period. Post-crisis period (2008 onward): All coherence measures reach their sample-period highs: WTC GDP-Debt at 0.659, WTC GDP-Expenditure at 0.657, and WTC Debt-Expenditure at 0.611. This broad tightening reflects France's large-scale fiscal response to the 2008 crisis and the subsequent build-up of public debt above 110% of GDP. At the conditional level, PWC GD|E rises to 0.657 while PWC GE|D declines to 0.515, down from its pre-crisis peak of 0.573. Taken together, these results point to a clear structural shift: as debt accumulated, its association with growth strengthened while the expenditure-growth link weakened. France appears to have moved from a fiscal regime in which public spending was the primary growth driver to one in which the level of accumulated debt defines the main constraint on macroeconomic performance. 4.4. Granger causality test results Granger causality tests complement our wavelet coherence analysis by identifying temporal precedence relationships. We find bidirectional causality between GDP and debt, confirming the dynamic feedback loop between the two variables. We notice from Table 7 a strong causality between Expenditure and GDP (p value=0.0000), the relationship between GDP and Expenditure is also significant, confirming the bidirectional causality between the two variables. Expenditure exhibits strong unidirectional causality toward debt. The absence of a debt-to- expenditure feedback mechanism represents a critical vulnerability in France’s fiscal framework, as the budget constraint operates unidirectionally without self-correcting properties. 5. Policy Implication The wavelet analysis points to four practical lessons for French fiscal policy. First, public spending takes time to affect growth, so short-term budget tweaks are unlikely to work; longer-term planning is needed instead. Second, since the 2008 crisis, debt has become more damaging to growth while spending has become less effective at boosting it, largely because high debt raises borrowing costs and scares off private investment. Third, France’s spending decisions have historically driven debt upward without any automatic correction mechanism, which is exactly the kind of imbalance the EU’s new fiscal rules are trying to fix. Fourth, public spending was a much more powerful growth tool when debt was below 70% of GDP, so reducing debt gradually is not just an external constraint; it is the only way to make fiscal policy effective again. Research Limitation The study has a few limitations worth noting. It only looks at France, leaving open the question of whether these findings apply elsewhere. The data themselves carry measurement uncertainty, and important factors like interest rates and monetary policy are not included in the model. The extreme COVID shock of 2020 also creates some technical noise near the edges of the wavelet analysis. Future work could consider robustness checks excluding the 2020–2021 period or employing adaptive wavelet methods designed to handle structural outliers. Conclusion This paper has applied a combination of Partial Wavelet Coherence and Granger causality tests to examine the complex frequency-dependent associations among fiscal policy variables and economic growth. Applied to French quarterly data spanning 1990-2024, our methodology reveals that France’s fiscal co-movement patterns operate primarily at business cycle frequencies and have shifted notably following eurozone integration in 1999 and the 2008–2012 crisis period. The main finding of this study points to a clear shift in how fiscal policy operates in France. Before the euro, public spending was closely associated with economic growth, giving the government an effective lever to steer the economy. Today, this relationship has weakened, while the link between public debt and growth has grown stronger, meaning that the level of accumulated debt now shapes economic outcomes more than spending decisions themselves. References: Afonso, A., de Sá Fortes Leitão Rodrigues, E. (2022) Corruption and economic growth: does the size of the government matter? Econ Change Restruct 55(2):543–576. <https://doi.org/10.1007/s10644-021-09338-4>; Aguiar-Conraria, L., Soares, M. J. (2014). The continuous wavelet transforms: Moving beyond uni-and bivariate analysis. Journal of Economic Surveys, 28(2). <https://doi.org/10.1111/joes.12012>; Arestis, P., Şen, H., Kaya, A. (2020). On the linkage between government expenditure and output: Empirics of the Keynesian view versus Wagner’s law. Economic Change and Restructuring, 54(2). <https://doi.org/10.1007/s10644-020-09284-7>; Auerbach, A. J., Gorodnichenko, Y. (2013). Fiscal multipliers in recession and expansion. In Fiscal Policy after the Financial Crisis (pp. 63-98). University of Chicago Press. <https://doi.org/10.7208/chicago/9780226018584.003.0003>; Barro, R. J. (1974). Are government bonds net wealth? Journal of Political Economy, 82(6). <https://doi.org/10.1086/260266>; Batini, N., Eyraud, L., Forni, L., Weber, A. (2014). Fiscal multipliers: Size, determinants, and use in macroeconomic projections. IMF Technical Notes and Manuals, 2014/004. <https://doi.org/10.5089/9781498382458.005>; Blanchard, O., Perotti, R. (2002). An empirical characterization of the dynamic effects of changes in government spending and taxes on output. Quarterly Journal of Economics, 117(4). <https://doi.org/10.1162/003355302320935043>; Checherita-Westphal, C., Rother, P. (2012). The impact of high government debt on economic growth and its channels: An empirical investigation for the euro area. European Economic Review, 56(7). <https://doi.org/10.1016/j.euroecorev.2012.06.007>; Corsetti, G., Kuester, K., Meier, A., Müller, G. J. (2013). Sovereign risk, fiscal policy, and macroeconomic stability. Economic Journal, 123(566). <https://doi.org/10.5089/9781463933180.001>; Égert, B. (2015). Public debt, economic growth and nonlinear effects: Myth or reality? Journal of Macroeconomics, 43. <https://doi.org/10.1016/j.jmacro.2014.11.006>; Gouhier, T. C., Grinsted, A., Jevrejeva, S. (2021). Biwavelet: Conduct Univariate and Bivariate Wavelet Analyses. R package version 0.20.21; Goupillaud, P., Grossmann, A., Morlet, J. (1984). Cycle-octave and related transforms in seismic signal analysis. Geoexploration, 23(1). <https://doi.org/10.1016/0016-7142(84)90025-5>; Herndon, T., Ash, M., Pollin, R. (2014). Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff. Cambridge Journal of Economics, 38(2). <https://doi.org/10.1093/cje/bet075>; Huidrom, R., Kose, M. A., Lim, J. J., Ohnsorge, F. L. (2020). Why do fiscal multipliers depend on fiscal positions? Journal of Monetary Economics, 114. <https://doi.10.1016/j.jmoneco.2019.03.004>; Ilzetzki, E., Mendoza, E. G., Végh, C. A. (2013). How big (small?) are fiscal multipliers? Journal of Monetary Economics, 60(2). <https://doi.10.1016/j.jmoneco.2012.10.011>; Insee. <https://www.insee.fr/fr/statistiques/ 8540821?sommaire=8540823>; Mihanović, H., Orlić, M., Pasarić, Z. (2009). Diurnal thermocline oscillations driven by tidal flow around an island in the Middle Adriatic. Journal of Marine Systems, 78, S157-S168. <https://doi.org/10.1016/j.jmarsys.2009.01.021>; Ng, E. K., Chan, J. C. (2012). Geophysical applications of partial wavelet coherence and multiple wavelet coherence. Journal of Atmospheric and Oceanic Technology, 29(12). <https://doi.org/10.1175/JTECH-D-12-00056.1>; Nguyen, C. T., Bui, T. H. L. (2022). Government expenditure and economic growth: Does the role of corruption control matter? Heliyon, 8(10), e10822. <https://doi.org/10.1016/j.heliyon.2022.e10822>; Nguyen, T. C., Trinh, L. T. (2021). The impact of fiscal policy on economic growth: Evidence from emerging and developing Asian countries. Economics and Business Letters, 10(3). <https://doi.org/10.17811/ebl.10.3.2021.251-262>; OECD. (2024). OECD Economic Surveys: France. OECD Publishing. <https://doi.org/10.1787/bd96e2ed-en>; Oyadeyi, O. O. (2024). Effect of government expenditure on real economic growth in ECOWAS: Assessing the moderating role of corruption and conflict. Humanities and Social Sciences Communications, 11. <https://doi.org/10.1057/s41599-024-03285-x>; Reinhart, C. M., Rogoff, K. S. (2010). Growth in a time of debt. American Economic Review, 100(2). <https://doi.org/10.1257/aer.100.2.573>; Rua, A., Nunes, L. C. (2009). International co-movement of stock market returns: A wavelet analysis. Journal of Empirical Finance, 16(4), 632-639. <https://doi.org/10.1016/j.jempfin.2009.02.002>; Torrence, C., Compo, G. P. (1998). A Practical Guide to Wavelet Analysis. Bulletin of the American Meteorological Society, 79. Footnotes [1] OECD. (2024). OECD Economic Surveys: France. OECD Publishing. <https://doi.org/10.1787/bd96e2ed-en>. [2] Insee. <https://www.insee.fr/fr/statistiques/ 8540821?sommaire=8540823>. [3] Barro, R. J. (1974). Are government bonds net wealth? Journal of Political Economy, 82(6), 1095-1117. <https://doi.org/10.1086/260266>. [4] Reinhart, C. M., Rogoff, K. S. (2010). Growth in a time of debt. American Economic Review, 100(2), 573-578. <https://doi.org/10.1257/aer.100.2.573>. [5] Herndon, T., Ash, M., Pollin, R. (2014). Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff. Cambridge Journal of Economics, 38(2), 257-279. <https://doi.org/10.1093/cje/bet075>. [6] Checherita-Westphal, C., Rother, P. (2012). The impact of high government debt on economic growth and its channels: An empirical investigation for the euro area. European Economic Review, 56(7), 1392-1405. <https://doi.org/10.1016/j.euroecorev.2012.06.007>. [7] Égert, B. (2015). Public debt, economic growth and nonlinear effects: Myth or reality? Journal of Macroeconomics, 43, 226-238. <https://doi.org/10.1016/j.jmacro.2014.11.006>. [8] Corsetti, G., Kuester, K., Meier, A., Müller, G. J. (2013). Sovereign risk, fiscal policy, and macroeconomic stability. Economic Journal, 123(566), 99-132. <https://doi.org/10.5089/9781463933180.001>. [9] Afonso, A., de Sá Fortes Leitão Rodrigues, E. (2022) Corruption and economic growth: does the size of the government matter? Econ Change Restruct 55(2):543–576. <https://doi.org/10.1007/s10644-021-09338-4>. [10] Blanchard, O., Perotti, R. (2002). An empirical characterization of the dynamic effects of changes in government spending and taxes on output. Quarterly Journal of Economics, 117(4), 1329-1368. <https://doi.org/10.1162/003355302320935043>. [11] Auerbach, A. J., Gorodnichenko, Y. (2013). Fiscal multipliers in recession and expansion. In Fiscal Policy after the Financial Crisis (pp. 63-98). University of Chicago Press. <https://doi.org/10.7208/chicago/9780226018584.003.0003>. [12] Batini, N., Eyraud, L., Forni, L., Weber, A. (2014). Fiscal multipliers: Size, determinants, and use in macroeconomic projections. IMF Technical Notes and Manuals, 2014/004. <https://doi.org/10.5089/9781498382458.005>. [13] Arestis, P., Şen, H., Kaya, A. (2020). On the linkage between government expenditure and output: Empirics of the Keynesian view versus Wagner’s law. Economic Change and Restructuring, 54(2), 265-303. <https://doi.org/10.1007/s10644-020-09284-7>. [14] Oyadeyi, O. O. (2024). Effect of government expenditure on real economic growth in ECOWAS: Assessing the moderating role of corruption and conflict. Humanities and Social Sciences Communications, 11, 740. <https://doi.org/10.1057/s41599-024-03285-x>. [15] Nguyen, C. T., Bui, T. H. L. (2022). Government expenditure and economic growth: Does the role of corruption control matter? Heliyon, 8(10), e10822. <https://doi.org/10.1016/j.heliyon.2022.e10822>. [16] Op. cit. [17] Ilzetzki, E., Mendoza, E. G., Végh, C. A. (2013). How big (small?) are fiscal multipliers? Journal of Monetary Economics, 60(2), 239-254. <https://doi.10.1016/j.jmoneco.2012.10.011>. [18] Huidrom, R., Kose, M. A., Lim, J. J., Ohnsorge, F. L. (2020). Why do fiscal multipliers depend on fiscal positions? Journal of Monetary Economics, 114, 109-125. <https://doi.10.1016/j.jmoneco.2019.03.004>. [19] Nguyen, T. C., Trinh, L. T. (2021). The impact of fiscal policy on economic growth: Evidence from emerging and developing Asian countries. Economics and Business Letters, 10(3), 251-262. <https://doi.org/10.17811/ebl.10.3.2021.251-262>. [20] Goupillaud, P., Grossmann, A., Morlet, J. (1984). Cycle-octave and related transforms in seismic signal analysis. Geoexploration, 23(1), 85-102. <https://doi.org/10.1016/0016-7142(84)90025-5>. [21] Aguiar-Conraria, L., Soares, M. J. (2014). The continuous wavelet transforms: Moving beyond uni-and bivariate analysis. Journal of Economic Surveys, 28(2), 344-375. <https://doi.org/10.1111/joes.12012>; Rua, A., Nunes, L. C. (2009). International co-movement of stock market returns: A wavelet analysis. Journal of Empirical Finance, 16(4), 632-639. <https://doi.org/10.1016/j.jempfin.2009.02.002>; [22] Torrence, C., Compo, G. P. (1998). A Practical Guide to Wavelet Analysis. Bulletin of the American Meteorological Society, 79, 61-78. [23] Mihanović, H., Orlić, M., Pasarić, Z. (2009). Diurnal thermocline oscillations driven by tidal flow around an island in the Middle Adriatic. Journal of Marine Systems, 78, S157-S168. <https://doi.org/10.1016/j.jmarsys.2009.01.021>. [24] Ng, E. K., Chan, J. C. (2012). Geophysical applications of partial wavelet coherence and multiple wavelet coherence. Journal of Atmospheric and Oceanic Technology, 29(12), 1845-1853. <https://doi.org/10.1175/JTECH-D-12-00056.1>. [25] Gouhier, T. C., Grinsted, A., Jevrejeva, S. (2021). Biwavelet: Conduct Univariate and Bivariate Wavelet Analyses. R package version 0.20.21.
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Disinformation and Its Impact on Society: The Case of the Russia-Ukraine War
This paper examines disinformation as a central instrument of power in contemporary geopolitics, focusing on the Russia-Ukraine war as a critical case study of its societal, political, and international consequences. It analyzes how disinformation operates not merely as a supplementary propaganda tool, but as a core mechanism of governance, narrative control, and strategic influence. The study explores the erosion of the rules-based international order, the paralysis of international institutions, and the transformation of information into a weapon capable of reshaping public perception, weakening democratic trust, and legitimizing aggression. Particular attention is devoted to Russia’s internal and external disinformation strategies, their impact on Ukrainian society, and Ukraine’s adaptive resilience through media literacy and civil society mobilization. The findings underscore that while disinformation can destabilize societies in peacetime, its effectiveness diminishes when confronted with lived reality during wartime, highlighting the crucial role of truth, institutional credibility, and societal resilience in contemporary international relations. Keywords: Disinformation, information warfare, Russia-Ukraine war, narrative control, propaganda, media manipulation, rules-based international order. Introduction In an era in which information is both easily accessible and capable of spreading at unprecedented speed, the terms "disinformation" and "fake news" have become an integral part of everyday vocabulary. These phenomena no longer merely reflect public opinion but actively participate in its formation, exerting a significant influence on the public agenda and, more broadly, on the overall political structure of contemporary societies. Through the deliberate manipulation of information, specific socio-political processes can be steered, framed, and controlled, while public attitudes and collective perceptions are strategically shaped and directed. In this context, information ceases to function solely as a means of communication and increasingly becomes a tool of power, capable of determining political priorities, influencing decision-making processes, and redefining the boundaries of public discourse. Disinformation refers to the deliberate dissemination of false or misleading information, typically with the intention of deceiving audiences or manipulating their perceptions. Fake news, by contrast, generally denotes fabricated or distorted narratives that are presented in the form of legitimate news reporting, often mimicking the style and authority of credible media sources. Although conceptually distinct, both phenomena can produce profound and far-reaching consequences. These effects range from the erosion of public trust in institutions and media systems to the cultivation of fear, polarization, and social fragmentation within society, or, conversely, to the artificial construction of seemingly positive and stable informational environments that obscure underlying realities. In all cases, the manipulation of information reshapes public consciousness and alters the conditions under which social and political life unfolds. Disinformation has become a pivotal instrument for the Russian government, particularly within the context of the ongoing war in Ukraine. This strategic practice is designed not only to shape domestic perceptions and regulate the internal informational environment, but also to rationalize and legitimize state actions on the international stage. Understanding how disinformation operates within this framework constitutes a crucial area of scholarly inquiry, especially given the depth and breadth of its societal impact. In conditions where manipulated narratives can influence attitudes, behavior, and institutional legitimacy, examining the mechanisms, objectives, and consequences of disinformation becomes essential for assessing its profound effects on society. Despite the expanding volume of scholarly inquiries addressing this phenomenon, a significant gap remains within the existing academic literature. While contemporary studies extensively map the tactical use of digital propaganda, cyber interventions, and state-sponsored broadcasting networks, the existing literature primarily views disinformation as an auxiliary element of military operations or as a tool for short-term electoral interference. What remains relatively less studied is the structural conceptualization of systemic deception as an enduring mechanism of domestic statecraft and structural international disruption. Most works treat information operations as isolated strategic campaigns rather than an integrated, foundational architecture of long-term authoritarian survival and international systemic modification. To address this empirical and theoretical omission, this article frames its core analytical path around a distinct and formalized inquiry. Specifically, the research question is defined as follows: How does Russian state-sponsored disinformation operate as an intrinsic instrument of internal domestic governance and external hybrid warfare within the specific context of the Russia-Ukraine war, and what are its direct structural consequences for public stability, state sovereignty, and the modern rules-based international order? The novelty of this presented research lies in its integrated, multi-tiered approach, which synthesizes internal political survival mechanisms with external geopolitical transformation strategies. By bridging the analytical divide between domestic societal control and international systemic erosion, this study exposes how the Kremlin utilizes narrative subversion not merely to win isolated battles, but to systematically dismantle the epistemic foundations of global governance. It shifts the scholarly focus from a simple technical analysis of fake news dissemination toward a holistic understanding of systemic disinformation as an existential challenge to the stability of sovereign states and the modern international architecture. Methodology To rigorously evaluate the multi-layered operations of state-directed narrative manipulation, this study is systematically structured around an explicit and distinct methodological framework. The investigation utilizes an interdisciplinary approach that combines descriptive analysis, political-legal discussion, and narrative/conceptual analysis, rooted in an exhaustive review of both primary and secondary sources. The descriptive analysis is employed to meticulously map the chronological deployment of specific disinformation vectors, detailing how state-directed narratives evolved alongside military objectives on the ground. This empirical baseline is paired with a political-legal discussion that examines the structural strain exerted by these information operations upon established international norms, sovereignty conventions, and the operational capacity of multilateral institutions like the United Nations. Furthermore, narrative and conceptual analysis serves as the primary tool for deconstructing the linguistic structures, historical myths, and ideological frameworks utilized within Russian state messaging, enabling a deeper evaluation of how strategic narratives are engineered to alter public perceptions. The study is based on a comprehensive review of diverse sources. This includes a systematic analysis of secondary literature alongside direct empirical evaluation of primary materials, including official Kremlin decrees, state addresses, and media broadcasts. To ensure high academic rigor, the framework incorporates a comparative discussion of competing theoretical paradigms—specifically contrasting structural realism with social constructivism—thereby illuminating how informational power interacts with material capabilities in contemporary international relations. The ongoing Russia-Ukraine war was intentionally selected as the primary case study for this research due to its status as the most comprehensive, high-intensity manifestation of modern hybrid warfare. This conflict provides a unique and unparalleled analytical domain where the full cycle of strategic disinformation—from long-term domestic conditioning to active wartime psychological coercion—can be observed in real time. It serves as an essential case study for understanding how an authoritarian state uses information dominance to challenge the security architecture of the twenty-first century. The Breakdown of the International System If one examines the architecture of the contemporary international order - including the United Nations, international courts, and the network of treaties concluded between states - an impression emerges of a world embedded within an interconnected system oriented toward stability, cooperation, and collective well-being. This system, constructed upon the ruins of the Second World War, was founded on a singular and ambitious objective: to ensure that powerful states would no longer possess the capacity to entirely absorb or annihilate smaller nations with impunity. However, Russia’s invasion of Ukraine on 24 February 2022 not only destabilized this international system, but also exposed and activated deep structural fractures embedded within its very foundations. The events of that day revealed the limits of existing international safeguards and demonstrated how fragile the post-war legal and political order remains when confronted by a major power willing to disregard established norms and principles. For decades, the United Nations Security Council (UNSC) was presented to the international community as the ultimate guardian of global peace. It functioned as an exceptional mechanism - a measure of last resort that global powers could activate when situations threatened to spiral beyond control. However, the war in Ukraine exposed a fatal flaw within this system. The very actor entrusted with the responsibility to extinguish the fire was, in this case, the one who ignited it. As a permanent member of the Security Council, Russia possesses the right of veto. In the first days of the invasion, as Russian tanks advanced toward Kyiv, the world witnessed a surreal diplomatic spectacle unfolding in New York. While the majority of states sought to condemn the violation of Ukraine’s sovereignty, the institution specifically designed to restrain such aggression was rendered powerless. A single raised hand by the Russian representative proved sufficient to neutralize the legal and procedural mechanisms of the world’s most powerful peacekeeping institution, revealing the profound vulnerability of the existing international security architecture. This was not merely a bureaucratic failure; it constituted a profound psychological shock to the global community. It transmitted a chilling message to small states across the world: rules may exist, but they cannot be relied upon for protection. In a single moment, the system that was intended to replace the logic of power with the power of law reverted to the very principle it was meant to overcome. As the international legal system became immobilized, a different kind of war unfolded in the minds of billions of people. It was precisely at this point that a second front of the war was opened - disinformation, which delivered one of the most damaging blows to the international order. The effective functioning of the international system depends on the existence of a shared reality and commonly accepted rules. The Kremlin’s disinformation campaign, however, did not merely seek to distort individual news stories; it aimed to undermine the very concept of objective fact itself. By eroding the distinction between truth and fabrication, disinformation attacked the epistemic foundations upon which international cooperation and accountability rest. Russian disinformation was directed toward the systematic degradation of Ukraine’s image: portraying the war as a fight against Nazism, depicting every bombed building as part of a staged spectacle, and shifting the focus away from persuading audiences of a single Russian version of truth toward ensuring that the world lacked any unified understanding of the ongoing war. How can the international community pursue accountability for war crimes when a significant portion of the global population believes that no crime ever occurred? When trust in institutions - ranging from the media to the International Criminal Court - is steadily weakened by the persistent drip of fabricated realities, the system itself loses legitimacy. It ceases to function as an authoritative framework and instead becomes just another voice lost within the noise. The greatest casualty of this erosion was the idea of a universal rules-based international order. For more than seventy years, the prevailing aspiration had been that all states, regardless of size or power, would operate under the same set of rules. The Russia–Ukraine war shattered this illusion and accelerated a return to political realism, a condition that historians often describe as the renewed struggle for spheres of influence. This structural shift confirms that systemic information operations are designed to directly facilitate territorial expansion by paralyzing international response mechanisms.[1] We are witnessing an accelerating fragmentation of the world. Confidence in global trade and collective security mechanisms is steadily eroding. States increasingly refrain from asking whether a particular action is lawful under international law; instead, their calculations are guided by different questions: which geopolitical bloc do they belong to, and who is willing and able to protect them. In the aftermath of the dissolution of the Soviet Union, scholars and policymakers frequently proclaimed the end of the Cold War and argued that a stable international order had emerged as a central foundation of socio-political life, one capable of shielding states from renewed confrontation. The rise of liberal political thought reinforced this perception, elevating international, intergovernmental, and non-governmental organizations and institutions to a prominent role in global governance. During this period, governmental priorities increasingly emphasized cooperation, multilateralism, and the pursuit of sustainable development goals, reflecting a widespread belief that institutional frameworks and shared norms could effectively manage conflict and promote long-term stability.[2] Russia’s invasion of Ukraine in 2022 fundamentally dismantled the liberal world order and brought political realism back to the forefront of international relations, with its primary focus on power politics and strategic competition. The international system once again assumed a multipolar configuration, in which states, political leaders, and international organizations actively seek to influence societies and decision-makers in pursuit of strategic advantage. This transformation has been accompanied by an intensified information war, one that relies heavily on disinformation and fake news as central instruments of influence and control. From a theoretical standpoint, this breakdown highlights a severe clash between competing academic positions within the discipline of international relations. Structural realists argue that the return to overt conflict and narrative warfare reflects an inevitable consequence of shifting material power dynamics and a systemic return to unmitigated anarchy[3]. Conversely, social constructivists posit that the crisis is fundamentally epistemic, arguing that the collapse of international norms is actively driven by the deliberate, state-sponsored deconstruction of shared realities and intersubjective meanings[4]. This theoretical divergence underscores that disinformation does not merely accompany structural change—it serves as a primary vehicle for executing it. Russian state propaganda is directed toward legitimizing its attempts at territorial expansion and annexation across multiple levels of discourse, including the societal, state, and international arenas. Each of these levels is characterized by a distinct vector of disinformation. At the societal level, narratives emphasize the alleged need to protect the Russian population and Russian-speaking communities. At the state level, propaganda frames the conflict as a broader struggle against the liberal West and its political values. At the international level, these narratives are embedded within claims about the necessity of reshaping the global order and constructing an alternative system of international relations. Through this multi-layered disinformation strategy, Russia seeks not only to justify its actions but also to redefine the normative and political foundations of the contemporary international system.[5] Moreover, the war has underscored the critical role of information and media in shaping public perception and informing political decision-making. The narratives constructed around this conflict influence not only how societies interpret and understand the war itself, but also how governments formulate their responses and policy choices. In this context, narrative dominance and informational framing become decisive factors in determining political behavior at both the domestic and international levels. Consequently, the management and control of information will constitute a vital and indispensable component of the emerging world order, directly affecting its stability, legitimacy, and capacity to function in an increasingly contested global environment.[6] The Ideological and Political Determinants of the Russia-Ukraine War and the New World Order Since the central objectives and guiding principles of the new world order paradigm in international relations are inherently linked to the pursuit of global hegemony, it is reasonable to assume that this concept has its origins in ancient history[7]. Following the First and Second World Wars, political leaders such as Woodrow Wilson and Winston Churchill introduced the term "new world order" into global political discourse in order to describe the emergence of a new historical era shaped by profound transformations in the balance of power. In particular, the concept gained prominence alongside Woodrow Wilson’s efforts to establish the League of Nations, an institution intended to prevent the outbreak of another global war. Woodrow Wilson’s initiative to create the League of Nations is widely regarded as a political and legal foundational construct of the new world order and is, in effect, considered a cornerstone of the twentieth-century international system. However, the failure of the League of Nations to function effectively ultimately led the world toward the most extensive and devastating conflict in human history. The consequences of this institutional inadequacy became tragically evident after the Second World War, which claimed the lives of approximately sixty million people and once again placed the very survival of humanity under profound and unsettling scrutiny. Despite its eventual failure, the League of Nations nonetheless served as the foundational precursor to the creation of a highly influential international organization, namely the United Nations. Established in 1945, the United Nations was designed to enhance international cooperation and to prevent the outbreak of a Third World War, thereby aspiring, in substantive terms, to construct a new world order. The organization represents a distinctive synthesis of realism and idealism, obligating all states seeking membership to renounce the use of force and to resolve international disputes through peaceful means. In this framework, the United Nations embodies an institutional attempt to reconcile power politics with normative principles, seeking to regulate state behavior through collective rules while preserving a degree of pragmatic engagement with geopolitical realities.[8] Although the United Nations has played a significant role and achieved a measure of success in regulating and mitigating conflicts and confrontations across various continents, the question of its effectiveness has repeatedly been brought into doubt. This skepticism has been reinforced by instances of complete inaction in response to Soviet interventions, revealing the limitations of the organization’s capacity to enforce its principles in the face of great-power interests. One of humanity’s most enduring challenges remains the establishment of peace and the prevention of the destructive phenomenon of war, a goal toward which civilizations have aspired for millennia. The necessity of a peaceful world may have existed since the dawn of human society, yet the twentieth century proved markedly more brutal than those preceding it. It was defined by the most extensive and devastating wars in human history, which ran as a persistent red thread through the era. Alongside profound political, cultural, and technological revolutions, military operations and armed conflicts unfolded intensively across nearly every region of the world. The twentieth century also gave rise to nuclear weapons and other instruments of mass destruction, developments that fundamentally altered the nature of warfare and global security. These transformations prompted a growing recognition within academic circles that the achievement of universal prosperity, security, and stability remains a distant prospect. Humanity continues to confront fundamental questions of civilizational survival, challenges that are inextricably linked to the unresolved and often unpredictable nature of international politics. The system of international relations articulated under the presidency of George H. W. Bush, following the end of the Cold War and the dissolution of the Soviet Union, envisioned the activation of collective security mechanisms as a central organizing principle of the post-bipolar world. In this context, the concept of a new world order signified the aspiration toward a world free from threat and terror, oriented toward peace and justice, and characterized by the harmonious coexistence of North and South, as well as East and West.[9] However, in the present era, the system of international relations is being reconfigured in new ways, and the processes shaping it remain in a formative and transitional phase. The complexity of the emerging global order is further accentuated by the ongoing shift from a unipolar to a multipolar structure. Following the collapse of the Soviet Union, the United States emerged as the sole superpower capable of defining the international order and proposing the rules by which the rest of the world was expected to operate. Yet, from the perspective of contemporary reality, this so-called superpower appears to be entering a phase of hegemonic decline. Such a trajectory reflects both a broader historical regularity observed in the rise and fall of dominant powers and the outcome of preceding geopolitical processes that have gradually reshaped the balance of global power.[10] In a broad sense, the Cold War, which evolved into a fifty-year period of intense ideological and political confrontation between former allies and divided the world into so-called superpowers and their subordinate satellite states, functioned as a guarantor of the new world order. The confrontation between the capitalist and socialist blocs repeatedly brought the world to the brink of nuclear war and generated numerous crisis situations across countries of the so-called Third World. During the Cold War, the international system underwent a fundamental transformation and assumed a bipolar structure. Two centers of power emerged on the global stage - the United States and the Soviet Union - while other states, as a rule, adopted policies of alignment with one of these poles. The Cold War period was characterized by a relatively flexible bipolar system. Naturally, both dominant powers sought to secure supremacy within the system and to establish unilateral hegemony. The American strategic perspective was rooted in the belief that any concession to the Soviet Union, much like the logic of the domino principle, would inevitably lead to a chain of further defeats. As a result, the strategy of containment emerged, aimed at restraining Soviet expansionism anywhere in the world where it sought to challenge the free and democratic order. The continuation of this policy was embodied in the Truman Doctrine, under which the United States provided substantial military and economic assistance to Greece and Turkey, thereby preventing their alignment with the socialist bloc. In the initial phase of the Cold War, the United States further developed its strategy along two crucial directions. It established the North Atlantic Treaty Organization and introduced the Marshall Plan, which sought to facilitate the economic reconstruction of Europe and to further reduce dependence on the Soviet Union. These initiatives collectively reinforced the institutional and economic foundations of the Western bloc while consolidating the bipolar structure of the international system. The end of the Cold War laid the groundwork for a new world order. The United States increasingly acted unilaterally across nearly all regions of the world, often without coordination with other major powers. Over time, however, the project of exporting democracy generated growing dissatisfaction among American citizens, while US interventions in Iraq and Libya resulted in a partial loss of trust among European allies. In 2008, the more isolationist orientation associated with the Obama administration replaced the rigid foreign policy approach of George W. Bush. As a consequence of this more restrained and inert posture, the United States failed to effectively counter Russia’s annexation of Crimea and the conflict in eastern Ukraine. Moreover, it refrained from direct involvement in the Syrian civil war, thereby leaving a power vacuum that was subsequently filled by a revisionist Russia pursuing its own strategic ambitions. Against this background, the decline of hegemonic dominance has become an observable reality. This development signifies the emergence of states on the global map capable of challenging US primacy. Among them, China and Russia stand out, driven by their own hegemonic aspirations and geostrategic interests, and actively seeking to reshape the balance of power within the contemporary international system.[11] The term "new world order" denotes a new historical period that reflects dramatic changes in the global political landscape and a shifting balance of power within international relations. At the same time, adherents of conspiracy theories often interpret this concept in an entirely different manner, believing in the existence of a secret and malevolent elite allegedly seeking to impose a new world order in which sovereign states would cease to exist. According to such narratives, this imagined order would be characterized by a single system of governance, a common currency, and the elimination of religious, national, and cultural distinctions, ultimately erasing all factors that differentiate human communities. In its most extreme formulations, this vision is portrayed as a precondition for the rise of the Antichrist on Earth, reflecting deep-seated fears rather than empirically grounded political analysis. A systematic and contextual examination of the processes outlined above demonstrates that the new world order is not the product of a hidden or instantaneous design, but rather a long-term historical phenomenon that has evolved over several centuries alongside broader patterns of social development. Throughout different historical stages, it has undergone large-scale global transformations shaped by shifts in power, ideology, and institutional arrangements. During the Cold War, the intense and often critical geopolitical, economic, and ideological confrontation between the United States and the Soviet Union produced tangible structural outcomes, including the establishment of NATO and the Warsaw Pact. This period was further marked by major international crises, such as the Berlin Crisis of 1948-1949 and the subsequent creation of the German Democratic Republic and the Federal Republic of Germany in 1949, as well as conflicts and interventions in Korea, Vietnam, Hungary, Czechoslovakia, and elsewhere. In these contexts, the superpowers frequently engaged in large-scale confrontations aimed at preserving or expanding their regional dominance, reinforcing the dynamic and conflict-driven nature of the evolving international order.[12] As is widely acknowledged, the global order of the twenty-first century represents, in many respects, a continuation of the Cold War, insofar as conflicts of interest between former superpowers persist today and are manifested through acute military confrontations, such as those in Syria, Libya, Yemen, and other regions. At the same time, regional powers including China, Turkey, Iran, and the oil-rich states of the Middle East are increasingly competing for regional dominance, a development that further intensifies the complexity and multilayered nature of the international system. The occupation of Georgia’s sovereign territories by the Russian Federation, followed by the annexation of the Crimean Peninsula and the subsequent Russia-Ukraine war, has underscored the extent to which leading international actors deliberately seek to demonstrate the use of force in pursuit of imperial ambitions and the establishment of a so-called new world order. These developments have once again compelled the international community to reflect on the true character of the twenty-first-century global order, which remains in the process of formation and is expected to assume its definitive contours in the aftermath of the Russia-Ukraine war. Disinformation as an Instrument of Russian Governance When the international community speaks of Russian disinformation, a full understanding of the scale and function of this mechanism requires a careful examination of Russia itself. For the Kremlin, disinformation is not merely an export-oriented product designed to destabilize adversaries abroad. It constitutes a central pillar of domestic political governance. It functions as a foundational instrument through which reality is constructed for millions of citizens and through which regime survival is secured.[13] This section examines how the Russian state has directed information warfare inward, against its own population, by constructing a hermetically sealed informational ecosystem in which the war in Ukraine is framed not as an act of aggression, but as an act of salvation and necessity. In order to maintain control over a nation of approximately 144 million people without resorting to the mass repressions characteristic of the Stalinist era, the contemporary Russian state relies primarily on informational dominance. Over the past two decades, the Kremlin has systematically dismantled independent media outlets, creating an informational vacuum that was rapidly filled by state-controlled narratives. Television, which remains the primary source of news for older demographic groups, has been transformed into a megaphone of the state. A critical analysis of primary source materials exposes the structural machinery behind this narrative control. For instance, a systematic evaluation of official Russian presidential decrees—specifically Decree No. 250 on Additional Measures to Ensure the Information Security of the Russian Federation—reveals a legal architecture explicitly engineered to criminalize objective reporting and mandate alignment with state narratives. Furthermore, direct research into Russian state media materials demonstrates how these mandates are executed operationally. In a baseline broadcast analysis of Rossiya-1's flagship program Vesti Nedeli with Dmitry Kiselyov, the invasion is consistently structured through a tightly regulated lexical framework. The term "war" (voina) is strictly prohibited, replaced uniformly by the sterile, bureaucratized construct "special military operation" (spetsialnaya voennaya operatsiya). This controlled linguistic output reveals a calculated effort to insulate the domestic population from the geopolitical realities of state aggression, altering language to regulate collective psychological and emotional behavior. Within this carefully curated reality, the invasion of Ukraine has never been presented as a war. By controlling language, the state controls emotional response. Narrative engineers on channels such as Rossiya-1 and Channel One do not merely report events; they dramatize them. They construct a storyline in which Russia is not the aggressor, but the victim - a besieged fortress defending itself against a decadent and hostile West that allegedly uses Ukraine as a battering ram. This narrative architecture performs a crucial function. It preemptively neutralizes moral responsibility. If a Russian citizen believes that their country is fighting "Nazis" or preventing an inevitable NATO attack, the moral burden of war is effectively erased. In this context, disinformation operates as a form of psychological anesthesia for the population. When a missile strikes a civilian building in Ukraine, Russian state media may simultaneously assert that: "The building was empty." "It was a Ukrainian missile that malfunctioned." "It was a military base rather than a civilian target." "The entire incident was staged with actors." Such contradictory explanations generate a condition of learned helplessness. By eroding the very concept of objective truth, the state ensures that the population remains politically paralyzed. If nothing is definitively true, then no action appears meaningful, and it becomes safer to delegate political responsibility to the so-called professionals in the Kremlin. This structural strategy illustrates how modern information monopolies weaponize digital ecosystems to generate persistent internal conformity[14]. Domestic disinformation relies heavily on emotional resonance, particularly through the instrumentalization of history. The most powerful element in this arsenal is the memory of the Second World War, referred to in Russia as the Great Patriotic War. The Kremlin has effectively anchored the current conflict to the sacred legacy of the fight against Hitler. By labeling Ukraine’s leadership as "neo-Nazis," despite the fact that Ukraine’s president is Jewish, the Russian leadership exploits deep intergenerational trauma. This is not mere propaganda; it is identity politics. Questioning the "special military operation" becomes symbolically equivalent to questioning the sacrifices of one’s grandparents. Political dissent is thus reframed as a form of cultural betrayal. This historical revisionism produces a rally-around-the-flag effect. It transforms geopolitical territorial expansion into a sacred war of survival. The disinformation apparatus continually reinforces the idea that Russia represents the last bastion of traditional values - faith, family, and order - standing against a chaotic and morally corrupt liberal world. This binary worldview renders compromise impossible and justifies extreme measures, including censorship and the imprisonment of dissenters. In Russia, major media outlets are state-controlled, enabling the government to dictate narratives to the public. News coverage frequently emphasizes victimhood, historical claims to Ukrainian territory, and the portrayal of Ukraine as an existential threat. At the same time, the Kremlin actively exploits social media platforms to disseminate false narratives and amplify societal divisions. Bots and troll networks spread disinformation with the aim of influencing specific demographic groups and sowing discord. The Russian government frequently employs historical revisionism to legitimize its actions. By framing the conflict in Ukraine as the reunification of "historically Russian lands," the narrative appeals to national pride and collective memory, thereby reinforcing public support for military operations. The Russian government presents its military intervention in Ukraine as a "special operation" undertaken to protect Russian-speaking populations. This framing recasts Russia as a defender rather than an aggressor, resonates with nationalist sentiment, and strengthens public backing for the war. Furthermore, disinformation campaigns portray Ukraine and its allies as fascists or neo-Nazis, thereby undermining their legitimacy. This framing provides a moral justification for military action and presents it as a necessary measure to protect Russian citizens and preserve national identity.[15] By portraying external threats, such as NATO expansion, the Kremlin cultivates an atmosphere of fear, suggesting that swift and decisive action is necessary to safeguard national security. This manufactured sense of urgency strengthens public support for the war effort and encourages citizens to rally more closely around the government’s narrative, reinforcing collective alignment with state objectives. Recent academic findings indicate that this systematic orchestration of internal fear functions as an essential, defensive regime safeguard during periods of external military overextension.[16] The societal impact of this disinformation strategy is significantly deeper. Many Russian citizens are compelled to endorse the government’s narrative, while dissenting views are increasingly perceived as unpatriotic or illegitimate. This dynamic of enforced conformity is further entrenched by state propaganda, which suppresses independent thought and obstructs critical engagement with alternative perspectives. The pervasive nature of disinformation undermines critical thinking, making it progressively more difficult for individuals to distinguish factual reality from manipulated or false information.[17] Moreover, disinformation actively contributes to societal polarization and internal division. Citizens may become increasingly fragmented along ideological lines, a process that fuels social tension and ultimately consolidates governmental control. As public opinion grows more fragmented, the space for constructive dialogue diminishes, weakening the foundations of pluralism and reducing the capacity of society to engage in meaningful debate. The Impact of Russian Disinformation in Ukraine Russia’s invasion of Ukraine began long before the first tank crossed the border in February 2022. For years, Ukraine served as the primary testing ground for Russian information warfare. The objective was not merely to mislead, but to dismantle Ukrainian identity both internally and externally by exploiting linguistic differences, regional histories, and political grievances until the state itself would collapse. Prior to the full-scale invasion, the Kremlin’s disinformation strategy in Ukraine was highly surgical in nature. It sought to widen existing social fractures into insurmountable divisions. Through pro-Russian television channels and extensive networks of social media bots, narratives were carefully tailored to specific regions. In the Russian-speaking eastern and southern regions, the dominant message was fear: “Kyiv will ban your language” or “the West wants to turn your factories into scrap”. In western Ukraine, the narrative shifted, portraying the eastern regions as a “dead weight” dragging the country back into its Soviet past. The aim was to paralyze the state through polarization, to cultivate a sense of internal exhaustion, and to present Moscow’s “strong hand” as the only viable source of stability[18]. This operational deployment proves that targeted digital operations are systematically designed to break civic cohesion prior to formal military interventions[19]. Within this narrative framework, Ukraine was depicted not as a sovereign nation, but as a “failed state” or “Project Ukraine” - an artificial construct allegedly controlled by Western puppeteers. By persistently questioning the legitimacy of the Ukrainian government, the disinformation apparatus anticipated that, once the invasion began, Ukrainians would be unwilling to fight for a state they had been conditioned to distrust and resent. When the invasion commenced on 24 February 2022, the disinformation strategy shifted immediately from sowing discord to inducing panic and capitulation. Alongside the physical battle for Kyiv, a digital battle was launched for the minds of Ukrainians. The most striking example of this effort was the deepfake incident involving President Volodymyr Zelensky. A manipulated video circulated online showing the president standing at a podium and urging Ukrainian soldiers to lay down their arms and surrender. Simultaneously, Russian bot networks flooded Telegram channels with claims that the government had fled, the army had collapsed, and resistance was futile. This constituted a “decapitation strike” aimed at national morale. The logic was straightforward: if the population believed that its leader had abandoned them, the will to resist would evaporate. This represented a twenty-first-century siege tactic - instead of cutting off food and water, the objective was to sever hope itself. This rapid convergence of synthetic media manipulation with frontline combat operations marks an evolutionary milestone in structural information warfare[20]. However, the Kremlin fundamentally miscalculated the resilience of Ukraine’s information space. Rather than collapsing, Ukrainian society unified with a speed that surprised external observers. Several factors contributed to this resilience. Immunization: Following eight years of hybrid warfare in Donbas since 2014, Ukrainians developed a form of “herd immunity” to Russian narratives. They had been exposed to the rhetoric of a “failed state” for too long to accept it at face value. Horizontal communication: Unlike the top-down Russian model, Ukrainian resistance was network-based. Citizens used messaging applications not only to share news, but also to organize logistics and verify information locally. When Russian media declared that a city had fallen, residents could simply look out of their windows, take photographs, and refute the falsehood in real time. Humor as a shield: Ukrainians transformed humor into a weapon. Memes depicting tractors towing tanks or stories from Snake Island became digital rallying cries. Humor rendered the terrifying image of the “invincible Russian army” manageable and, at times, even absurd. The Zelensky deepfake was swiftly neutralized by the president himself, who released simple, handheld videos filmed on the streets of Kyiv, declaring, “I am here. We are all here”. The contrast between the rigid artificiality of the deepfake and the tangible reality of a president standing in the streets dismantled the Russian narrative of abandonment. When the Russian disinformation apparatus realized that it could not persuade the Ukrainian population to accept Russian forces as liberators, it entered a darker phase, one defined by terror. The narrative shifted from “we are here to save you from Nazis” to messaging aimed at breaking the psychological will of the civilian population. This included spreading rumors of imminent chemical attacks, exaggerating the threat of nuclear strikes, and asserting that specific cities would be “wiped off the map” in order to provoke mass evacuation and chaos[21]. This operational pivot from persuasion to intimidation underlines how disinformation is dynamically adapted when encountering robust social resistance.[22] In the occupied territories, this strategy generated a profound informational vacuum. Russian forces frequently destroyed Ukraine’s internet and mobile infrastructure, replacing it with Russian-controlled networks that blocked access to external news sources. Within these so-called informational ghettos, propaganda vehicles disseminated claims that Kyiv had already surrendered or that Ukraine was bombing its own population. This form of disinformation functioned as an instrument of occupation - isolating individuals from their lived reality in order to make them feel abandoned, disconnected, and forgotten. The impact of Russian disinformation on Ukraine has been deep and far-reaching, shaping public perception and altering the narrative surrounding the ongoing conflict. As the war continued, the Kremlin employed a variety of information manipulation tactics aimed at generating confusion and sowing discord among Ukrainians. This disinformation campaign has not merely served as a weapon of war, but has evolved into a central strategy for undermining Ukraine’s sovereignty and societal resilience. One of the most significant aspects of Russian disinformation lies in its ability to exploit existing divisions within Ukrainian society. By promoting narratives that emphasize ethnic and linguistic differences, the Kremlin seeks to deepen social fragmentation. This strategy has proven particularly effective in regions with substantial Russian-speaking populations, where it draws upon grievances and historical ties. By portraying itself as a protector of these regions, Russia attempts to legitimize its actions, secure public support, and simultaneously discredit the Ukrainian government[23]. Recent empirical research verifies that these regional efforts were designed to destroy localized civil trust and degrade state-level resistance networks.[24] Moreover, Russia’s disinformation efforts extend beyond conventional propaganda and encompass tactical disinformation. In the early stages of the conflict, the Kremlin circulated false information regarding Ukraine’s military capabilities and intentions, suggesting that the country was on the verge of collapse. This narrative was designed to demoralize both the Ukrainian population and its armed forces by fostering an atmosphere of despair and uncertainty. By undermining trust in Ukraine’s defensive capacity, Russia hoped to facilitate a rapid and decisive victory.[25] Social media played a decisive role in amplifying these disinformation efforts. Platforms such as Facebook and Twitter have been saturated with misleading narratives and so-called "fake news," often disseminated by bots and troll networks that create the illusion of widespread support for Russian claims. These information flows significantly complicate the ability of ordinary citizens to distinguish verified facts from fabricated content, thereby increasing confusion and susceptibility to manipulation. This widespread digital pollution demonstrates how modern communication networks can be exploited to weaken institutional integrity during active crises.[26] The consequences of this disinformation campaign extend far beyond immediate military objectives. They also entail long-term strategic effects. By fostering skepticism toward governments and legitimate media outlets, Russian disinformation undermines public trust in democratic institutions. This erosion of trust can generate civic apathy, reduce public participation in civic life, and facilitate the entrenchment of Russian narratives within both domestic and international audiences.[27] Despite these challenges, Ukraine has demonstrated notable resilience in countering disinformation. The government has launched initiatives aimed at promoting media literacy, equipping citizens with the skills necessary to identify and reject false narratives. In parallel, Ukrainian civil society has mobilized to establish fact-checking organizations and independent media outlets that actively counter Russian propaganda and provide credible information. This collaborative civil-state mobilization offers a critical blueprint for democratic preservation against persistent authoritarian informational attack.[28] In conclusion, Russia’s use of disinformation as an instrument of governance within the context of the war in Ukraine illustrates the profound societal impact of information manipulation. Through narrative control, the demonization of opposition, and the framing of the conflict in terms of national identity, the Kremlin effectively legitimizes its actions both domestically and on the international stage. Recognizing and confronting disinformation is therefore essential for fostering a more informed and resilient society capable of navigating the complexities of contemporary geopolitics.[29] At the same time, the impact of Russian disinformation in Ukraine remains a complex and evolving challenge. By exploiting social divisions, disseminating false narratives, and weakening trust in democratic institutions, Russia seeks to advance its strategic objectives. Nevertheless, Ukraine’s sustained response, characterized by media literacy initiatives and robust civil society engagement, underscores the critical importance of countering disinformation and safeguarding democratic integrity. As the conflict continues, the struggle against disinformation will remain a key front in the defense of Ukraine’s sovereignty and future. Conclusion The Russia-Ukraine war constitutes a severe stress test for the international system. It has demonstrated that existing mechanisms of protection are insufficient when confronted with a major power willing to violate established rules, particularly when that power employs disinformation to fracture and delay global responses. The world now finds itself in a post-collapse phase of the international system. For societies seeking to move forward, the challenge lies not only in halting armed conflict on the ground, but also in determining how to restore a shared sense of law and truth in a world that has learned how easily both can be undermined. Through a comprehensive examination, this research has firmly established that Russian disinformation operates not as an auxiliary tool of military power, but as a central mechanism of authoritarian governance and systematic international destabilization. Empirically, the study demonstrates that while strategic deception effectively enforces internal conformity and generates learned helplessness domestically, its capacity to alter outcomes diminishes significantly when confronted by the physical realities of kinetic warfare and structured societal resilience. The primary analytical results indicate that the resilience of an information space depends directly on decentralized, horizontal communication networks and early state-civil society synchronization. The main academic contribution of this paper to the ongoing global debate is the presentation of an integrated, two-way analytical model showing how domestic regime protection and external hybrid aggression are inextricably linked. It offers a framework for assessing information operations not merely as misleading communication, but as structural threats to state sovereignty. In contemporary Russia, disinformation is not a side effect of governance; it is governance itself. The regime maintains power not solely through coercive force, but through the management of collective imagination. By constructing a parallel reality in which Russia is always righteous and perpetually under threat, the Kremlin creates a closed informational loop that is extraordinarily difficult to penetrate from within. However, reliance on total informational control also generates structural vulnerability. A government that governs through falsehood ultimately fears truth more than military force. As the war prolongs and the gap between televised narratives and everyday economic reality widens, the durability of this artificial world faces its most serious test. The impact of Russian disinformation on Ukraine serves as a critical case study for examining the limits of propaganda. Although it successfully sowed confusion in the years preceding the war, it failed its ultimate test. When missiles began to fall, the Kremlin’s abstract narratives collided with the concrete realities of invasion and destruction. Ukraine’s experience suggests that while disinformation can weaken societies in times of peace, it can also strengthen resistance in times of war when falsehoods stand in stark contradiction to lived experience. Ultimately, this study brings a transformative interpretation to the global scholarly discussion by demonstrating that the modern crisis of international order is fundamentally an epistemic one. It argues that hybrid warfare cannot be neutralized solely through conventional military deterrence or economic sanctions; it requires the active defense of objective truth. This paper shows that the systematic deconstruction of factual reality by authoritarian states acts as a direct precursor to territorial expansion and institutional paralysis. For contemporary international relations, this insight is critical. It moves the academic focus beyond technical media literacy and establishes information security as a core element of state sovereignty and global collective security in the twenty-first century. References Bjola, C., & Pamment, J. (2021). Digital diplomacy and international security: Managing the epistemic crisis. International Affairs, 97(4), 1023–1041. Fedchenko, O. (2022). Fact-checking as a weapon against hybrid threats: The Ukrainian experience. Journal of Slavic Military Studies, 35(3), 412–429. Galeotti, M. (2022). The weaponisation of everything: A field guide to the new century of conflict. Europe-Asia Studies, 74(5), 844–861. Giles, K. (2023). Russia’s information warfare: Mechanisms, targets, and responses. International Politics Review, 11(2), 145–163. Hamilton, Daniel S., and Kristina Spohr. Exiting the Cold War, Entering a New World. Global Affairs, Johns Hopkins University SAIS, 2019. Global Rights Compliance. New Report Exposes Russia’s Strategic Disinformation Warfare. 2025. Kuzio, T. (2023). Imperial nationalism and disinformation in Russia’s war against Ukraine. Post-Soviet Affairs, 39(2), 115–134. Lutsevych, O. (2023). Civil society and resilience in Ukraine: Countering authoritarian influence. International Affairs, 99(3), 895–912. McGlynn, Jade. Memory Makers: The Politics of the Past in Putin’s Russia. London: Bloomsbury Academic, 2023. Mearsheimer, J. J. (2022). Why the Ukraine crisis is the West’s fault: The liberal delusions that provoked Putin. International Security, 47(1), 7–48. Molander, Roger C., Andrew Riddile, and Peter A. Wilson. Strategic Information Warfare: A New Face of War. Santa Monica, CA: RAND Corporation, 1996. Momtaz, Rym. Taking the Pulse: Are Information Operations Russia’s Most Potent Weapon Against Europe? Strategic Europe, 2024. Odarchenko, Kateryna, and Elena Davlikanova. Russia’s Evolving Information War Poses a Growing Threat to the West. UkraineAlert, 2024. Pamment, J. (2022). The protocol of disinformation: How state actors deploy strategic deception. Journal of Communication, 72(1), 89–107. Plokhy, Serhii. The Russo-Ukrainian War: The Return of History. New York: W. W. Norton & Company, 2023. Pomerantsev, Peter. This Is Not Propaganda: Adventures in the War Against Reality. New York: PublicAffairs, 2019. Presl, Dominik. Russia Is Winning the Global Information War. Royal United Services Institute (RUSI), 2024. Rid, Thomas. Active Measures: The Secret History of Disinformation and Political Warfare. New York: Farrar, Straus and Giroux, 2020. Stent, A. (2024). The Putin regime and the weaponization of history. Survival, 66(1), 45–62. Topor, Lev, and Alexander Tabachnik. Russian Cyber Information Warfare: International Distribution and Domestic Control. Marine Corps University, 2021. Wagnsson, C., & Barzanje, C. (2021). A pioneer of information warfare: Deconstructing Russian narrative strategies. Defense & Security Analysis, 37(2), 187–205. Walker, Christopher, and Jessica Ludwig. The Meaning of Sharp Power: How Authoritarian States Project Influence. Foreign Affairs, 2017. Yablokov, I. (2022). Digital media and state propaganda in contemporary Russia. Media, Culture & Society, 44(6), 1102–1119. Footnotes [1] Giles, K. (2023). Russia’s Information Warfare: Mechanisms, Targets, and Responses. International Politics Review, 11(2), 145–163. [2] Hamilton, D. S., & Spohr, K. (2019). Exiting the Cold War, Entering a New World. Global Affairs, Johns Hopkins University SAIS. [3] Mearsheimer, J. J. (2022). Why the Ukraine Crisis Is the West’s Fault: The Liberal Delusions That Provoked Putin. International Security, 47(1), 7–48. [4] Bjola, C., & Pamment, J. (2021). Digital diplomacy and international security: Managing the epistemic crisis. International Affairs, 97(4), 1023–1041. [5] Odarchenko, K., & Davlikanova, E. (2024). Russia’s evolving information war poses a growing threat to the West. UkraineAlert. [6] Molander, R. C., Riddile, A., & Wilson, P. A. (1996). Strategic Information Warfare: A New Face of War. Santa Monica, CA: RAND Corporation. [7] Modelski, G. (1989). Long Cycles in World Politics. Seattle: University of Washington Press. p. 34. [8] Keohane, R. O. (1984). After Hegemony: Cooperation and Discord in the World Political Economy. Princeton University Press. p. 5. [9] Abashidze, Z. (2009). The Cold War: Past or Present? Tbilisi. p. 12. [10] Ahmed, R. (2018). From the ruins of unipolarity. The Geopolitics. https://thegeopolitics.com/from-the-ruins-of-unipolarity/ [11] Allison, G. (2017). Destined for War: Can America and China Escape Thucydides’s Trap. Houghton Mifflin Harcourt. p. 4. [12] Kipiani, V. (2020). Regional interconnections – an additional opportunity for greater national security and a stronger economy. Interpressnews, Tbilisi. [13] Pomerantsev, P. (2019). This Is Not Propaganda: Adventures in the War Against Reality. PublicAffairs. [14] Galeotti, M. (2022). The weaponisation of everything: A field guide to the new century of conflict. Europe-Asia Studies, 74(5), 844–861. [15] Presl, D. (2024). Russia is winning the global information war. RUSI. [16] Stent, A. (2024). The Putin regime and the weaponization of history. Survival, 66(1), 45–62. [17] Momtaz, R. (2024). Taking the pulse: Are information operations Russia’s most potent weapon against Europe? Strategic Europe. [18] McGlynn, J. (2023). Memory Makers: The Politics of the Past in Putin’s Russia. Bloomsbury Academic. [19] Pamment, J. (2022). The protocol of disinformation: How state actors deploy strategic deception. Journal of Communication, 72(1), 89–107. [20] Yablokov, I. (2022). Digital media and state propaganda in contemporary Russia. Media, Culture & Society, 44(6), 1102–1119. [21] Giles, K. (2022). Russia’s War on Everybody: And What It Means for You. Bloomsbury Academic. [22] Kuzio, T. (2023). Imperial nationalism and disinformation in Russia’s war against Ukraine. Post-Soviet Affairs, 39(2), 115–134. [23] Walker, C., & Ludwig, J. (2017). The meaning of sharp power: How authoritarian states project influence. Foreign Affairs. [24] Lutsevych, O. (2023). Civil society and resilience in Ukraine: Countering authoritarian influence. International Affairs, 99(3), 895–912. [25] Global Rights Compliance. (2025). New report exposes Russia’s strategic disinformation warfare. [26] Wagnsson, C., & Barzanje, C. (2021). A pioneer of information warfare: Deconstructing Russian narrative strategies. Defense & Security Analysis, 37(2), 187–205. [27] Topor, L., & Tabachnik, A. (2021). Russian Cyber Information Warfare: International Distribution and Domestic Control. Marine Corps University. [28] Fedchenko, O. (2022). Fact-checking as a weapon against hybrid threats: The Ukrainian experience. Journal of Slavic Military Studies, 35(3), 412–429. [29] Plokhy, S. (2023). The Russo-Ukrainian War: The Return of History. W. W. Norton & Company.
The Role of the Entrepreneurial Ecosystem in Supporting Startups: University Incubators as a Model
The study examines the pivotal role of entrepreneurial ecosystems in supporting the growth and development of startups, with a focus on university business incubators as an effective mechanism for bridging academic knowledge and market needs. Through a systematic review of multiple scholarly studies, it is evident that university incubators function as central nodes within the ecosystem, providing an integrated environment that combines effective leadership, institutional connectivity, and comprehensive support mechanisms, including mentoring, access to funding, infrastructure, and network building. The findings indicate that these incubators significantly contribute to startup survival, enhanced innovation capacity, and local and regional economic development, particularly when they successfully coordinate the efforts of various ecosystem stakeholders, such as industry partners, investors, government agencies, and alumni networks. Despite their importance, university incubators face challenges related to financial sustainability, complex stakeholder coordination, and the transition from academic settings to market environments. The study concludes that implementing supportive policies and strategies is essential to enhancing the integration and effectiveness of university-based entrepreneurial ecosystems. Keywords: Entrepreneurial ecosystems, university business incubators, startup survival and growth, innovation capacity, economic development. Introduction The entrepreneurial ecosystem has become a key framework for understanding how startups grow and succeed in today’s economies. Unlike traditional linear approaches to entrepreneurship support, this perspective emphasizes that startup success depends on complex interactions among multiple actors, institutions, resources, and cultural factors within specific geographic and institutional contexts. Within this broader ecosystem, universities play an important role as knowledge producers, talent developers, and facilitators of entrepreneurship. University incubators are a central manifestation of this role. They act as intermediaries between the academic environment and the commercial market, providing structured support to ventures founded by students, faculty, and sometimes external entrepreneurs. As entrepreneurial ecosystems have evolved globally, incubators have transformed from simple office spaces into integrated ecosystem hubs that coordinate relationships among diverse stakeholders and deliver comprehensive support services. Despite their importance, the main question that this study addresses is: How do university incubators contribute to the success of startups within entrepreneurial ecosystems? This research focuses on answering this question by examining the theoretical frameworks that explain how incubators operate, reviewing effective models and approaches in different contexts, and analyzing the support mechanisms they provide, along with the challenges and opportunities they face. The study aims to provide practical insights for policymakers, university administrators, and entrepreneurship practitioners to enhance the effectiveness of university-based entrepreneurial support systems. 1. Research Methodology This study aims to explore the role of university business incubators in supporting the growth of startups within entrepreneurial ecosystems. To achieve this, the research is based on a systematic review of relevant scholarly literature in the fields of entrepreneurship, university incubators, research incubators, and science parks. Research Approach Study Type: The research is descriptive and analytical, focusing on how university incubators function as key nodes in entrepreneurial ecosystems. Data Sources: The study relies on scientific articles and reports published between 2017 and 2025, emphasizing the impact of university incubators on innovation, startup growth, and ecosystem development. Analysis Methods: Content Analysis: To identify the main factors that influence the success of university incubators and their contributions to entrepreneurial ventures. Comparative Analysis: To examine different models of university and research incubators, highlighting how academic support translates into real-world startup success. Importance of the Methodology This approach provides a clear understanding of how university incubators operate within entrepreneurial ecosystems, their role in fostering innovation and entrepreneurship, and their contribution to local and regional economic development. It also offers a practical foundation for recommendations to policymakers, universities, and institutions supporting entrepreneurship. Limitation: This study faces several limitations, most notably its reliance on secondary sources that may not fully reflect the most recent practices. In addition, cross-country contextual differences may affect the accuracy of the comparisons. The absence of field data also restricts a deeper understanding of the experiences of incubators and entrepreneurs, highlighting the need for more comprehensive future studies. 2. Theoretical Foundations of Entrepreneurial Ecosystems Entrepreneurial ecosystems comprise a set of institutions, networks, culture, policies, and resources that create favorable conditions for the emergence and growth of startups within a given region. Within this framework, university incubators play a pivotal role as strategic hubs, linking academic knowledge with market needs and channeling ecosystem resources to support startups and transform ideas into scalable ventures. The ecosystem perspective emphasizes that startup success depends not merely on individual entrepreneur characteristics or firm-level resources, but on the quality and configuration of the broader support environment.[1] Key ecosystem components typically include entrepreneurs and startups, support organizations such as incubators and accelerators, financial capital providers, universities and research institutions, government agencies and policy frameworks, established corporations, professional service providers, and cultural attitudes toward entrepreneurship and risk-taking. The critical factors necessary for the emergence and sustainability of the entrepreneurial ecosystem include clearly defining the goals, shared values, and responsibilities of all stakeholders, while continuously monitoring their impact. Equally important is actively fostering a local culture of entrepreneurship and developing the managerial talent within the ecosystem. Creating and capturing value, supporting human and social capital, and promoting a positive attitude toward failure and learning are also essential. Building trust-based relationships among stakeholders and encouraging entrepreneurial “recycling”, where experienced entrepreneurs reinvest their time, resources, and expertise, further strengthen the system. Moreover, providing commercial opportunities for local businesses and high-growth firms, ensuring a robust business infrastructure, securing adequate funding, and implementing supportive public policies collectively create the conditions needed for the sustainable development of innovative ventures.[2] The authors view entrepreneurial ecosystems as interconnected networks of institutions, culture, policies, and resources that support startup growth, with university incubators serving as strategic hubs linking academic knowledge to market needs. They emphasize that shared goals, entrepreneurial culture, managerial talent, trust-based relationships, infrastructure, funding, and supportive policies are essential for the sustainable development of innovative ventures. 3. Entrepreneurial Ecosystems and the Role of University Incubators in Supporting Startups Research on entrepreneurial ecosystems shows that startup success is strongly influenced by the combined effect of funding access, mentorship, networking opportunities, government support, and entrepreneurial culture.[3] Access to finance and mentorship are major predictors of startup growth, while strong networks and relational capacity are especially important for innovation outcomes.[4] High‑quality ecosystems not only support local startups but also attract entrepreneurial talent from other regions, acting as “escalators” where entrepreneurs move from good to better ecosystems to benefit from richer resources and networks.[5] Ecosystems are thus dynamic and relational, built from cumulative entrepreneurial successes and failures that generate investment capital, skilled workers, and entrepreneurial knowledge for future ventures. The authors conclude that startup success relies on the interplay of funding, mentorship, networking, government support, and entrepreneurial culture, with a high-quality ecosystem attracting talent and fostering innovation being essential for sustainable growth. 4. University Incubators as Key Ecosystem Nodes Universities are “engines of economic development” and primary producers of scientific knowledge that can support entrepreneurial ventures.[6] With the rise of the entrepreneurial university, university business incubators (UBIs) have become central tools for converting research and student ideas into startups.[7] These incubators typically provide a range of services to support entrepreneurs. They act as intermediaries within the ecosystem, bridging knowledge and business subsystems and helping to address “weak network” issues by creating dense startup–investor networks through meetings, networking, and field-building activities.[8] They also embed constrained or high-risk startups into financial support networks, which is essential when technology or impact constraints are high.[9] Physical and technical resources—including space, laboratories, equipment, and shared services—help lower startup entry costs.[10] Incubators also provide business support and mentoring, which reduces market risks and enhances startup performance and sustainability, conceptualized as the “support capability” of academic incubators.[11] Moreover, these incubators are connected to technology transfer and industry links, tying research outcomes to economic development and accelerating commercialization.[12] They also foster entrepreneurial education and mindset formation by integrating incubators with curricula, moving students from an “employee” mindset to an “employer” mindset.[13] The following table illustrates the role of university business incubators. Similarly, incubators that allocate more resources to societal startups tend to demonstrate stronger innovation performance and higher successful exit rates, indicating that aligning commercial objectives with societal goals can enhance both economic and social outcomes.[16] The following table presents the components of the entrepreneurial ecosystem and their impact on the entrepreneurial experience. Based on the above, the researchers conclude that university incubators are key nodes in entrepreneurial ecosystems, connecting research to innovation and supporting startup growth. Their success depends on strong networks, access to resources, and integration with the university’s mission, rather than simply following generic models. 5. Models and Frameworks for University-Based Incubation Structural connectivity involves the formal organizational setups, business models, and mechanisms that link the incubator to investors and external partners. Agentic connectivity, on the other hand, depends on the experience and networks of key individuals, such as managers and directors, who connect startups to resources and opportunities through personal relationships. Research shows that the most successful incubators combine both types, with agentic connectivity often laying the groundwork for structural systems to function effectively and sustainably.[17] Researchers have developed multi-level frameworks to explain the role of university incubators within the entrepreneurial ecosystem. These frameworks focus on three levels: the micro-level for individual founders and startups, the meso-level for the incubator and its immediate support network, and the macro-level for the regional, national, and international ecosystem characteristics.[18] A key example is the I5 Framework, which links Institutions, Industries, Interactions, Innovations, and Incubators, highlighting the importance of proactive university involvement and systematic support for startups. The lifecycle model also shows that incubators[19] start by building basic infrastructure and attracting their first cohorts, and as they mature, they expand their networks and become active orchestrators within the ecosystem.[20] Based on the above, the authors rgue that the success of university incubators depends on combining structural connectivity with personal (agentic) connections, as the relationships of key individuals lay the foundation for effective institutional systems. They also emphasize that multi-level frameworks, such as the I5 Framework and the lifecycle model, help to understand the role of incubators at individual, organizational, and regional levels, highlighting the importance of active university involvement in supporting innovation and coordinating the entrepreneurial ecosystem sustainably. 6. Comparative Analysis: University Incubators Across Contexts University incubation models vary considerably according to geographic context, institutional orientation, and levels of economic development. Comparative studies indicate that university incubators in North America, especially in the United States, primarily focus on technology commercialization, attracting external investment, and supporting high-growth startups.[22] This model is reinforced by mature venture capital ecosystems, strong intellectual property protection, and a culture that is generally open to entrepreneurial risk-taking.[23] Nevertheless, these incubators face several challenges, including intense competition to attract promising ventures, strong pressure for rapid financial returns, and the risk of drifting away from their educational mission. In the European context, university incubators are more diverse in their structures and objectives, reflecting differences in national higher education systems and innovation policies[24]. Many European programs place greater emphasis on regional economic development, social entrepreneurship, and sustainable business models when compared to North American incubators.[25] They also tend to maintain closer relationships with government innovation programs and regional development agencies. However, these programs often encounter limitations such as restricted access to venture capital, complex regulatory frameworks, and, in some cases, cultural environments that are less supportive of entrepreneurial risk-taking.[26] University incubators operating in emerging and developing economies face unique challenges and opportunities. They frequently function within entrepreneurial ecosystems that are still underdeveloped, characterized by limited venture capital, weak intellectual property protection, and institutional gaps in support infrastructure. At the same time, these incubators play an essential role in addressing local development needs and in stimulating entrepreneurial ecosystems where few alternatives exist. Successful initiatives in these contexts tend to focus on capacity building, adapting to local resource constraints, and finding ways to overcome institutional barriers[27]. Research also highlights innovative practices such as partnerships with international organizations, mobilizing diaspora networks, and adopting hybrid models that link incubation with broader economic development strategies.[28] Institutional characteristics further influence the design of incubation models. Research-intensive universities with strong science and engineering programs usually emphasize technology commercialization and faculty entrepreneurship[29]. In contrast, teaching-oriented institutions often prioritize student entrepreneurship and regional engagement[30]. Specialized institutions, such as business schools, develop distinctive incubation models by leveraging their specific expertise and professional networks.[31] Overall, evidence suggests that the most effective incubation models are those that align closely with the institution’s mission and strengths, rather than simply adopting generic best practices.[32] Figure 02 illustrates the distribution of business incubators across different countries.[33] The following table, Reproduced exactly as published in (Gaire, Tiwari (2025)) illustrates the Incubators - Distribution by Continents.[34] From the literature, it is clear that university incubation models differ widely depending on geographic context, the type of institution, and the level of economic development. In North America, incubators mainly focus on turning technological innovations into commercial products, attracting external funding, and supporting high-growth startups. European incubators, on the other hand, tend to emphasize regional development, social entrepreneurship, and sustainable business models. In emerging and developing economies, incubators often face resource constraints and underdeveloped entrepreneurial ecosystems, so they prioritize building local capacities, adapting to limitations, and adopting innovative approaches such as international partnerships and hybrid models. The nature of the institution also shapes the design of incubation programs: research-oriented universities focus on faculty entrepreneurship and technology commercialization, while teaching-focused institutions give more attention to student entrepreneurship and community engagement. Overall, the evidence shows that the most successful incubators are those that align closely with the university’s mission and strengths, rather than simply following generic models. Conclusion The entrepreneurial ecosystem plays a fundamental role in providing the necessary infrastructure to support entrepreneurship, including finance, culture, policies, and talent. University incubators operationalize these resources on the ground, transforming ideas and research into scalable startups. They do not merely offer physical space and basic services; they also serve as a bridge connecting academia, industry, and society, facilitating knowledge transfer and developing entrepreneurial skills, thus providing a practical model for how ecosystems can systematically support startup creation, growth, and sustainable innovation. Evidence shows that university incubators operate within multi-level frameworks combining strong organizational structures, effective leadership, comprehensive support mechanisms, and deep integration with the surrounding ecosystem. They contribute to startup success by reducing operating costs, providing access to specialized resources and expertise, building extensive networks, signaling credibility that attracts investors and partners, and offering educational programs that enhance entrepreneurial capabilities. The outcomes of these programs demonstrate tangible impacts on venture survival, growth, funding success, as well as broader contributions to regional innovation, knowledge transfer, and the development of a strong entrepreneurial culture. However, university incubators face significant challenges, including difficulties in achieving financial sustainability, the need to coordinate multiple stakeholders, cultural gaps between academic and commercial environments, and dependence on key individuals, which can threaten program continuity Key Findings University incubators transform ideas and research into scalable ventures and connect academia, industry, and society. They support startup success through financial resources, expertise, networks, and educational programs. They have tangible effects on venture survival, growth, funding success, innovation, and knowledge transfer. They face financial, cultural, and managerial challenges that require strategic solutions. Practical Recommendations Develop sustainable funding models to reduce dependence on university support or external grants. Strengthen ecosystem integration through systematic stakeholder coordination. Build strong leadership and management teams to ensure program continuity and reduce reliance on individuals. Adapt to digital and global entrepreneurial environments to expand networks and support innovation. Balance multiple objectives, including educational missions, research commercialization, regional development, and financial sustainability. University incubators are a powerful tool for supporting startups and driving sustainable innovation, as improving their mechanisms strengthens venture success while also advancing regional innovation, economic growth, and societal development. References: Abdraimova, B., Abdyldaeva, N. (2025). Business Incubators and Entrepreneurial Education in Universities: the Need for an Integrated Approach. Bulletin of Science and Practice, 11(7). <https://doi.org/10.33619/2414-2948/116/69>; Al-Sabaawe, Y., Albayati, N., Al-Obaidy, N. (2025). University Industry Incubators: Igniting Global Startup Revolutions. JBMP (Jurnal Bisnis, Manajemen dan Perbankan), vol. 11, no. 2. <https://doi.org/10.21070/jbmp.v11i2.2109> ; Allahar, H. et al. (2019). A University Business School as an Entrepreneurial Ecosystem Hub. Technology Innovation Management Review, vol. 9, no. 11. <https://doi.org/10.22215/timreview/1280>; Badzinska, E. (2021). Providing a Nurturing Environment for Start-up Incubation: an Explorative Study of a University-based Entrepreneurial Ecosystem. European Research Studies Journal Volume XXIV Special Issue 2, Part 3. <https://doi.org/10.35808/ersj/2701>; Bamini, J., Choudari, S., Joy, A., Chawla, N., Yabaluri, B., Shankar, S. D., Singh, R. (2025). The Role of Entrepreneurial Ecosystems in Supporting Startup Growth and Innovation. Journal of Information Systems Engineering and Management, vol. 10, no. 3. <https://doi.org/10.52783/jisem.v10i3.5002>; Breznitz, S. M. et al. (2019). Fostering the growth of student start-ups from university accelerators: An entrepreneurial ecosystem perspective. Industrial and Corporate Change, vol. 28, no. 4. <https://doi.org/10.1093/ICC/DTZ033>; Bronstein, Y. V. et al. (2021). Toward a Framework for University-Based Entrepreneurial Ecosystems and Human Capital Development in Sub-Saharan Africa. In book: Resilience, Entrepreneurship and ICT. <https://doi.org/10.1007/978-3-030-78941-1_2>; Casanova-Villalba, C. et al. (2025). Modelo de vinculación academia-empresa para facilitar la creación y sostenibilidad de start-ups tecnológicas en Ecuador. Journal of Economic and Social Science Research (JESSR), vol. 5, no. 2. <https://doi.org/10.55813/gaea/jessr/v5/n2/197>; Gaire, P. N., Tiwari, U. (2025). Evolution and Distribution of Business Incubators: A Literature Review, BIC Journal of Management, 2(1); Harun, H. et al. (2024). ICCubeX: A Structured University Incubation Model to Accelerate the Lab-to-Market Process. International journal of academic research in business & social sciences, vol. 14, no. 1. <http://dx.doi.org/10.6007/IJARBSS/v14-i1/20546>; Hassan, N. (2020). University business incubators as a tool for accelerating entrepreneurship: theoretical perspective. Review of Economics and Political Science, vol. 9, no. 5. <https://doi.org/10.1108/reps-10-2019-0142>; Jurgelevičius, A. et al. (2025). Developing an entrepreneurial ecosystem framework for student-led start-ups in higher education. Neveléstudomány, 15(7). <https://doi.org/10.3390/educsci15070837>; Karahan, M. (2024). Advancing sustainable entrepreneurial universities: sustainability transformations of university business incubators in Germany. Small Business Economics. <https://doi.org/10.1007/s11187-023-00860-5; Kambanou, M., Hajoary, P., Lindfors, A. (2025). Supporting start‐ups in the circular economy: An analysis of university‐led incubators in India. Journal of Industrial Ecology, 29. <https://doi.org/10.1111/jiec.70032>; Kulkarni, P., Tigadi, B., Gokhale, P., K., L. (2024). University incubators performance through the lens of institutional theory. Vilakshan - XIMB Journal of Management. <https://doi.org/10.1108/xjm-02-2024-0029>; Ricard, L. et al. (2022). Lacunes et apports des accélérateurs et des incubateurs universitaires aux écosystèmes entrepreneuriaux. Revue organisations & territoires, vol. 31, no. 2. <https://doi.org/10.1522/revueot.v31n2.1482>; Máté, D., Estiyanti, N., Novotny, Á., Vveinhardt, J. (2025). University business incubators in Indonesia: Navigating commercial viability and societal contributions. Sustainable Futures, vol. 10. <https://doi.org/10.1016/j.sftr.2025.101138>; Maulidian, R. et al. (2024). Green Entrepreneurship Incubation Model for Students at Trilogy University Business Incubator: A Literature Review. E3S web of conferences, vol. 483, The 3rd International Seminar of Science and Technology (ISST 2023). <https://doi.org/10.1051/e3sconf/202448301017>; Mazzoni, L., Riccaboni, M., Stam, E. (2025). Entrepreneurial ecosystems and interregional flows of entrepreneurial talent. Small Business Economics, 65. <https://doi.org/10.1007/s11187-025-01022-5>; McAdam, M. et al. (2016). Situated regional university incubation: A multi-level stakeholder perspective. Technovation, vol. 50-51. <https://doi.org/10.1016/j.technovation.2015.09.002>; Mele, G., Sansone, G., Secundo, G., Paolucci, E. (2024). Speeding Up Student Entrepreneurship: The Role of University Business Idea Incubators. IEEE Transactions on Engineering Management, 71. <https://doi.org/10.1109/tem.2022.3175655>; Nicholls-Nixon, C. L. et al. (2021). Entrepreneurial ecosystems and the lifecycle of university business incubators: An integrative case study. International Entrepreneurship and Management Journal, vol. 17, issue 2. <https://doi.org/10.1007/s11365-019-00622-4>; Patil, S. et al. (2023). I5 Framework: Institutions-Industries-Interactions Innovations-Incubators for Strengthening Start-up Ecosystem in Higher Education Institutions. International Journal of Emerging Technologies in Learning (IJET), vol. 18, no. 8. <https://doi.org/10.3991/ijet.v18i08.36647>; Rai, R., Prasad, A., Murthy, B. (2025). Incubation support for academia-based entrepreneurship: an empirical study. Journal of Asia Business Studies, vol. 19, no. 2. <https://doi.org/10.1108/jabs-02-2024-0102>; Sohail, S. et al. (2025). Multi-level entrepreneurial ecosystem framework: Founder, incubator, and country characteristics for start-up performance. Journal of Small Business Management. <https://doi.org/10.1080/00472778.2025.2581669> ; Spigel, B. (2017). The Relational Organization of Entrepreneurial Ecosystems. Entrepreneurship Theory and Practice, 41(01). <https://doi.org/10.1111/etap.12167>; Theodoraki, C., Messeghem, K. (2017). Exploring the entrepreneurial ecosystem in the field of entrepreneurial support: a multi-level approach. Int. J. Entrepreneurship and Small Business, vol. 31, no. 1; Tsaplin, E., Pozdeeva, Y. (2017). International strategies of business incubation: The USA, Germany and Russia. International journal of innovation (IJI Journal), São Paulo, vol. 5, no. 1; Van Rijnsoever, F. (2020). Meeting, mating, and intermediating: How incubators can overcome weak network problems in entrepreneurial ecosystems. Research Policy, vol. 49, issue 1, 103884. <https://doi.org/10.1016/j.respol.2019.103884>; Van Rijnsoever, F. (2022). Intermediaries for the greater good: How entrepreneurial support organizations can embed constrained sustainable development startups in entrepreneurial ecosystems. Research Policy, vol. 51, issue 2, 104438. <https://doi.org/10.1016/j.respol.2021.104438>; Vassileva, J., Tsafack Nanfosso, R. (2025). L’incubation entrepreneuriale au sein de l’université entrepreneuriale: Études de cas en Europe et en Afrique. Revue Internationale des Économistes de Langue Française, vol. 10, no. 1. <https://doi.org/10.18559/rielf.2025.1.2277>; Wright, M. et al. (2017). An emerging ecosystem for student start-ups. Journal of Technology Transfer, vol. 42, no. 4. DOI: <10.1007/s10961-017-9558-z>. Footnotes [1] Harun, H. et al. (2024). ICCubeX: A Structured University Incubation Model to Accelerate the Lab-to-Market Process. International journal of academic research in business & social sciences, vol. 14, no. 1, 1339-1354. <http://dx.doi.org/10.6007/IJARBSS/v14-i1/20546>. [2] Badzinska, E. (2021). Providing a Nurturing Environment for Start-up Incubation: an Explorative Study of a University-based Entrepreneurial Ecosystem. European Research Studies Journal Volume XXIV Special Issue 2, Part 3, 15-29. <https://doi.org/10.35808/ersj/2701>. [3] Spigel, B. (2017). The Relational Organization of Entrepreneurial Ecosystems. Entrepreneurship Theory and Practice, 41(01), 49-72. <https://doi.org/10.1111/etap.12167>. [4] Bamini, J., Choudari, S., Joy, A., Chawla, N., Yabaluri, B., Shankar, S. D., Singh, R. (2025). The Role of Entrepreneurial Ecosystems in Supporting Startup Growth and Innovation. Journal of Information Systems Engineering and Management, vol. 10, no. 3, 427-434. <https://doi.org/10.52783/jisem.v10i3.5002>. [5] Mazzoni, L., Riccaboni, M., Stam, E. (2025). Entrepreneurial ecosystems and interregional flows of entrepreneurial talent. Small Business Economics, 65, 1327-1361. <https://doi.org/10.1007/s11187-025-01022-5>. [6] Al-Sabaawe, Y., Albayati, N., Al-Obaidy, N. (2025). University Industry Incubators: Igniting Global Startup Revolutions. JBMP (Jurnal Bisnis, Manajemen dan Perbankan), vol. 11, no. 2, 229-254. <https://doi.org/10.21070/jbmp.v11i2.2109>. [7] Mele, G., Sansone, G., Secundo, G., Paolucci, E. (2024). Speeding Up Student Entrepreneurship: The Role of University Business Idea Incubators. IEEE Transactions on Engineering Management, 71, 2364-2378. <https://doi.org/10.1109/tem.2022.3175655>. [8] Van Rijnsoever, F. (2020). Meeting, mating, and intermediating: How incubators can overcome weak network problems in entrepreneurial ecosystems. Research Policy, vol. 49, issue 1, 103884. <https://doi.org/10.1016/j.respol.2019.103884>. [9] Van Rijnsoever, F. (2022). Intermediaries for the greater good: How entrepreneurial support organizations can embed constrained sustainable development startups in entrepreneurial ecosystems. Research Policy, vol. 51, issue 2, 104438. <https://doi.org/10.1016/j.respol.2021.104438>. [10] Kambanou, M., Hajoary, P., Lindfors, A. (2025). Supporting start‐ups in the circular economy: An analysis of university‐led incubators in India. Journal of Industrial Ecology, 29, 997-1012. <https://doi.org/10.1111/jiec.70032>. [11] Rai, R., Prasad, A., Murthy, B. (2025). Incubation support for academia-based entrepreneurship: an empirical study. Journal of Asia Business Studies, vol. 19, no. 2, 289-314 (26). <https://doi.org/10.1108/jabs-02-2024-0102>. [12] Hassan, N. (2020). University business incubators as a tool for accelerating entrepreneurship: theoretical perspective. Review of Economics and Political Science, vol. 9, no. 5, 434-453. <https://doi.org/10.1108/reps-10-2019-0142>. [13] Abdraimova, B., Abdyldaeva, N. (2025). Business Incubators and Entrepreneurial Education in Universities: the Need for an Integrated Approach. Bulletin of Science and Practice, 11(7): 481-487. <https://doi.org/10.33619/2414-2948/116/69>. [14] Karahan, M. (2024). Advancing sustainable entrepreneurial universities: sustainability transformations of university business incubators in Germany. Small Business Economics, 1-35. <https://doi.org/10.1007/s11187-023-00860-5>. [15] Kulkarni, P., Tigadi, B., Gokhale, P., K., L. (2024). University incubators performance through the lens of institutional theory. Vilakshan - XIMB Journal of Management. <https://doi.org/10.1108/xjm-02-2024-0029>. [16] Máté, D., Estiyanti, N., Novotny, Á., Vveinhardt, J. (2025). University business incubators in Indonesia: Navigating commercial viability and societal contributions. Sustainable Futures, vol. 10. <https://doi.org/10.1016/j.sftr.2025.101138>. [17] Ricard, L. et al.(2022). Lacunes et apports des accélérateurs et des incubateurs universitaires aux écosystèmes entrepreneuriaux. Revue organisations & territoires, vol. 31, no. 2. 29-42. <https://doi.org/10.1522/revueot.v31n2.1482>. [18] Sohail, S. et al. (2025). Multi-level entrepreneurial ecosystem framework: Founder, incubator, and country characteristics for start-up performance. Journal of Small Business Management, 1-31. <https://doi.org/10.1080/00472778.2025.2581669>. [19] Patil, S. et al. (2023). I5 Framework: Institutions-Industries-Interactions Innovations-Incubators for Strengthening Start-up Ecosystem in Higher Education Institutions. International Journal of Emerging Technologies in Learning (IJET), vol. 18, no. 8, 4-22. <https://doi.org/10.3991/ijet.v18i08.36647>. [20] Nicholls-Nixon, C. L. et al. (2021). Entrepreneurial ecosystems and the lifecycle of university business incubators: An integrative case study. International Entrepreneurship and Management Journal, vol. 17, issue 2, 809-837. <https://doi.org/10.1007/s11365-019-00622-4>. [21] Theodoraki, C., Messeghem, K. (2017). Exploring the entrepreneurial ecosystem in the field of entrepreneurial support: a multi-level approach. Int. J. Entrepreneurship and Small Business, vol. 31, no. 1, 61. [22] Breznitz, S. M. et al. (2019). Fostering the growth of student start-ups from university accelerators: An entrepreneurial ecosystem perspective. Industrial and Corporate Change, vol. 28, no. 4, 855-873. <https://doi.org/10.1093/ICC/DTZ033>. [23] Wright, M. et al. (2017). An emerging ecosystem for student start-ups. Journal of Technology Transfer, vol. 42, no. 4, 909-922. DOI: <10.1007/s10961-017-9558-z>. [24] Vassileva, J., Tsafack Nanfosso, R. (2025). L’incubation entrepreneuriale au sein de l’université entrepreneuriale: Études de cas en Europe et en Afrique. Revue Internationale des Économistes de Langue Française, vol. 10, no. 1, 37-55. <https://doi.org/10.18559/rielf.2025.1.2277>. [25] Maulidian, R. et al. (2024). Green Entrepreneurship Incubation Model for Students at Trilogy University Business Incubator: A Literature Review. E3S web of conferences, vol. 483, The 3rd International Seminar of Science and Technology (ISST 2023). <https://doi.org/10.1051/e3sconf/202448301017>. [26] Vassileva, J., Tsafack Nanfosso, R. (2025). op. cit. [27] Bronstein, Y. V. et al. (2021). Toward a Framework for University-Based Entrepreneurial Ecosystems and Human Capital Development in Sub-Saharan Africa. In book: Resilience, Entrepreneurship and ICT. <https://doi.org/10.1007/978-3-030-78941-1_2>. [28] Casanova-Villalba, C. et al. (2025). Modelo de vinculación academia-empresa para facilitar la creación y sostenibilidad de start-ups tecnológicas en Ecuador. Journal of Economic and Social Science Research (JESSR), vol. 5, no. 2, 189-204. <https://doi.org/10.55813/gaea/jessr/v5/n2/197>. [29] Harun, H. et al. (2024). op. cit. [30] Jurgelevičius, A. et al. (2025). Developing an entrepreneurial ecosystem framework for student-led start-ups in higher education. Neveléstudomány, 15(7), 837. <https://doi.org/10.3390/educsci15070837>. [31] Allahar, H. et al. (2019). A University Business School as an Entrepreneurial Ecosystem Hub. Technology Innovation Management Review, vol. 9, no. 11, 15-25. <https://doi.org/10.22215/timreview/1280>. [32] McAdam, M. et al. (2016). Situated regional university incubation: A multi-level stakeholder perspective. Technovation, vol. 50-51, 69-78. <https://doi.org/10.1016/j.technovation.2015.09.002>. [33] Tsaplin, E., Pozdeeva, Y. (2017). International strategies of business incubation: The USA, Germany and Russia. International Journal of Innovation (IJI Journal), São Paulo, vol. 5, no. 1, 38. [34] Gaire, P. N., Tiwari, U. (2025). Evolution and Distribution of Business Incubators: A Literature Review, BIC Journal of Management, 2(1), 125.
FinTech Leapfrogging: A Comparative Analysis of Digital Payments and Cryptocurrency Adoption in Emerging and Developed Economies
This study examines whether FinTech adoption follows divergent structural pathways across emerging and developed economies, focusing on digital payments and cryptocurrency adoption. Drawing on leapfrogging theory, it develops a comparative framework linking financial infrastructure, digital payment expansion, financial inclusion, and crypto-adoption intensity. The analysis is based on a purposive sample of ten economies and combines data from Statista Market Insights, the Chainalysis Global Crypto Adoption Index, and the World Bank Global Findex Database. The findings identify two broad patterns. In developed economies, digital payment expansion primarily reflects optimisation within mature financial systems, characterised by high banking penetration, established card-based infrastructures, and convenience-driven adoption. In several emerging economies, by contrast, digital payments exhibit a more transformative role, increasingly operating as an alternative transactional infrastructure in settings marked by financial inclusion gaps and weaker institutional capacity. Cryptocurrency adoption presents a more differentiated picture. Rather than supporting a simple inverse relationship between financial exclusion and crypto uptake, the results point to multiple adoption pathways, ranging from partial substitution for incomplete financial services in some emerging markets to investment- and institution-led adoption in developed ones. Keywords: FinTech leapfrogging, digital payments, cryptocurrency adoption, financial inclusion, emerging economies, developed economies, comparative analysis Introduction Digital transformation has profoundly reshaped contemporary financial systems, particularly through the expansion of digital payments and cryptocurrencies. In recent years, FinTech has moved beyond its role as a simple technological enabler to become a structural force influencing financial inclusion, consumer behaviour, and the organisation of financial intermediation. However, these developments have not unfolded uniformly across countries. In advanced economies, FinTech has largely emerged within already mature financial systems, where it tends to improve efficiency, convenience, and service delivery. In many emerging economies, by contrast, digital financial technologies have often developed in contexts characterised by weaker banking infrastructure, lower financial inclusion, and greater reliance on mobile-based solutions. This difference makes the comparative study of FinTech adoption particularly important. The present research is significant because it examines whether digital payments and cryptocurrency adoption reflect distinct developmental pathways across emerging and developed economies. It also contributes to current debates by linking two dimensions of digital finance that are frequently analysed separately, namely payment-system transformation and cryptocurrency adoption, within a common comparative framework. In doing so, the study seeks to clarify whether FinTech in emerging markets functions merely as a tool of technological diffusion or as a mechanism of structural leapfrogging capable of compensating for institutional and infrastructural limitations. The research gap addressed in this study lies in the limited integration of these dimensions within the existing literature. While previous studies have examined FinTech and financial inclusion, or cryptocurrency adoption, they have rarely brought together digital payment growth, financial inclusion gaps, mobile connectivity, and crypto-adoption intensity in a single comparative framework. Accordingly, this study addresses the following central research problem: to what extent does FinTech adoption follow different pathways in emerging and developed economies, and can these differences be interpreted through the lens of leapfrogging theory? In response, the study advances the hypothesis that digital payments in developed economies mainly reflect optimisation within mature financial systems, whereas in emerging economies they are more likely to reflect structural transformation. It further hypothesises that cryptocurrency adoption does not follow a single pattern, but instead reflects multiple pathways: in some emerging economies, it may operate as a partial substitute for incomplete financial services, while in developed economies, it is more closely associated with investment, institutional participation, and broader digital financial innovation. 2. Literature Review and Conceptual Framework 2.1 FinTech and financial inclusion Financial inclusion has evolved from a narrow policy concern centered on microfinance into a broader determinant of economic participation in the digital age. It now refers not only to access to financial services, but also to the effective integration of individuals and firms into formal financial systems through affordable, accessible, and technology-enabled mechanisms.[1],[2] Empirical research increasingly links financial inclusion to economic growth, financial stability, and broader development outcomes, particularly in contexts where access to conventional banking remains uneven.[3], [4] Within this context, FinTech represents more than a simple technological upgrade; it constitutes a structural shift in financial intermediation. By reducing transaction costs, easing information asymmetries, and expanding service delivery through digital platforms, mobile banking, and data-driven applications, FinTech can extend financial access to previously underserved groups.[5] However, its contribution to financial inclusion is not uniform across countries and depends heavily on economic context, institutional capacity, and technological readiness. In emerging economies, FinTech often compensates for weak banking infrastructure and limited service coverage, thereby supporting broader participation in formal financial systems. Evidence from countries such as India and several sub-Saharan African economies suggests that mobile-based financial services can reduce geographic and income-based exclusion by integrating rural and low-income users into financial networks.[6], [7], [8] In developed economies, by contrast, FinTech tends to operate within already mature financial systems, where its primary role is to enhance efficiency, convenience, and user experience rather than to expand basic access.[9] At the same time, the relationship between FinTech and financial inclusion remains constrained by several structural factors. Infrastructure deficits, regulatory uncertainty, low financial literacy, and socio-cultural barriers may limit the capacity of marginalized groups to benefit from digital financial innovation.[10], [11], [12] As a result, FinTech reshapes not only the scale but also the nature of financial inclusion. In emerging economies, adoption is often necessity-driven and linked to access, substitution, and resilience, whereas in developed markets it is more commonly convenience-driven and associated with efficiency and optimization. This distinction provides the conceptual basis for the comparative analysis developed in the following sections. Within this context, FinTech represents more than a simple technological upgrade; it constitutes a structural shift in financial intermediation. However, its contribution to financial inclusion is not uniform across countries and depends heavily on economic context, institutional capacity, and technological readiness. As shown in Figure 1, the impact of FinTech on financial inclusion is moderated by economic context. In emerging economies, adoption is more likely to be necessity-driven, reflecting financial access gaps and institutional deficiencies. In developed economies, by contrast, adoption tends to be convenience-driven, emphasizing efficiency and optimization within already mature financial systems. 2.2 Digital payments and structural transformation Digital payments represent a structural change in how consumers access financial services and participate in formal economic activity. Their adoption is shaped by trust, perceived security, ease of use, convenience, and socio-cultural attitudes toward cashless transactions.[13], [14] Beyond facilitating transactions, digital payments also influence consumer behaviour by reducing transaction frictions, encouraging higher spending, and supporting the expansion of e-commerce through seamless payment processes and incentives such as cashback, discounts, and loyalty programmes.[15] A central dimension of this transformation is financial inclusion. Digital payment systems can broaden access to formal financial services, particularly in contexts where conventional banking infrastructure remains limited. By reducing reliance on cash and lowering access barriers, they help integrate previously underserved populations into formal financial networks. At the same time, they push traditional banks to adopt FinTech solutions such as digital onboarding, biometric verification, fraud detection, and data-driven service models to remain competitive.[16], [17], [18] However, the transformative effects of digital payments are not automatic. The digital divide, legacy banking systems, and regulatory uncertainty may constrain both adoption and impact. Accordingly, the literature suggests that digital payments should be understood not only as technological tools but also as structural mechanisms whose effectiveness depends on supportive regulation, inclusive design, and broader institutional adaptation. This perspective is especially relevant for understanding leapfrogging dynamics in emerging markets.[19] [20] , 2.3 Cryptocurrency adoption in emerging economies Cryptocurrency adoption in emerging economies is shaped by the interaction of economic necessity, technological readiness, and institutional conditions. One of the main drivers is the role of remittances, as digital currencies can provide faster and lower-cost alternatives to conventional transfer channels. By reducing transaction costs and transfer delays, they may also broaden financial access for unbanked and underbanked populations.[21] In addition, economically unstable environments often strengthen cryptocurrency adoption. In contexts marked by inflation, currency depreciation, or weak trust in conventional banking systems, digital assets may serve as alternative stores of value and as instruments of financial resilience.[22] Cases such as Nigeria and Turkey illustrate how monetary instability can increase interest in cryptocurrencies as hedging tools and as alternatives to less reliable financial infrastructures.[23] Adoption is also influenced by broader technological and socio-economic conditions. Higher levels of internet access, mobile connectivity, digital literacy, and platform innovation facilitate participation in digital financial ecosystems, while diaspora networks can further stimulate adoption through cross-border transfer needs.[24], [25] At the same time, regulatory uncertainty and concerns about illicit financial activity may constrain adoption, which highlights the importance of balanced legal frameworks that support innovation while preserving financial integrity.[26] The literature suggests that cryptocurrency adoption in emerging economies should not be viewed solely as speculative behavior. Rather, it reflects the convergence of remittance needs, financial instability, technological opportunity, and institutional constraints, making cryptocurrencies relevant not only for investment but also for financial inclusion, value preservation, and participation in evolving digital financial ecosystems.[27] 2.4 Leapfrogging theory in digital finance Leapfrogging theory explains how late-developing economies may accelerate structural transformation by bypassing intermediate stages of technological development and moving directly toward more advanced systems. Rather than following the gradual paths historically associated with industrialized economies, latecomer countries may exploit technological discontinuities to adopt modern infrastructures without the burden of legacy systems. This perspective emerged first in debates on development policy and technological diffusion, especially in relation to ICT, where scholars argued that developing economies could “skip stages” of technological evolution through the adoption of newer technologies. [28], [29], [30], [31] The telecommunications sector offers one of the clearest empirical examples of leapfrogging. Many developing economies bypassed large-scale fixed-line expansion and instead adopted mobile communication technologies at scale. This transition reduced the financial and institutional costs associated with traditional network development while expanding connectivity and access, particularly among previously underserved populations. [32], [33], [34], [35] More recently, the leapfrogging framework has been extended to digital finance. The spread of FinTech, mobile banking, and digital payment systems has enabled countries with weak conventional financial infrastructures to expand access to financial services without replicating the traditional branch-based banking model. In this sense, digital finance can be understood as a contemporary form of leapfrogging, in which financial systems evolve through digital platforms, mobile ecosystems, and alternative payment architectures rather than through the gradual expansion of physical banking networks. [36], [37] At the same time, leapfrogging in digital finance is not automatic. Its success depends on broader institutional and technological conditions, including consumer protection, governance quality, digital capabilities, and innovation capacity. Emerging research suggests that technological readiness and digital capabilities can strengthen resilience and support structural transformation in developing economies, especially where institutional environments are capable of supporting innovation diffusion.[38], [39] 2.5 Conceptual framework of the study Building on the preceding literature, this study proposes a context-dependent FinTech adoption framework (Figure 2) to explain why FinTech adoption follows different trajectories across emerging and developed economies. Rather than treating adoption as a uniform or purely utility-driven process, the framework argues that FinTech integration is shaped by the interaction of economic context, institutional capacity, and technological opportunity. In this framework, the antecedents of adoption differ across market environments. In developed economies, mature financial systems, strong regulatory oversight, and established banking infrastructures create a path-dependent environment in which FinTech tends to complement existing services. In emerging economies, by contrast, financial inclusion gaps, weaker banking infrastructures, and institutional limitations interact with growing technological opportunities-particularly mobile connectivity and digital platforms-to create conditions for more accelerated and substitution-oriented adoption. The framework distinguishes between two main mechanisms of adoption. In emerging economies, adoption is primarily necessity-driven, as digital financial tools often compensate for limited access to conventional financial services. In developed economies, adoption is more convenience-driven, as FinTech is typically integrated into already mature financial systems in order to improve speed, cost efficiency, and user experience. These contrasting mechanisms generate divergent outcomes. In developed markets, FinTech mainly leads to efficiency and optimization, including improved user experience, more streamlined financial services, and greater institutional integration. In emerging markets, it is more likely to contribute to leapfrogging and structural transformation, particularly by expanding financial inclusion, fostering new digital ecosystems, and enabling alternative forms of financial participation. The framework, therefore, positions FinTech not merely as a technological tool, but as a context-dependent structural force whose effects vary according to the institutional and economic environment. This conceptual logic guides the empirical analysis of digital payments and cryptocurrency adoption in the subsequent sections. 3. Data and Methodology This section outlines the data sources, sample selection strategy, and analytical framework employed to investigate the divergent pathways of FinTech adoption across different economic contexts. The methodological approach is designed to empirically examine the Leapfrogging Hypothesis, which suggests that emerging economies may adopt digital financial technologies at accelerated rates due to structural gaps in traditional banking systems. 3.1. Data sources To ensure cross-country comparability, this study relies on secondary data from internationally recognized sources. A triangulated data strategy is used, combining digital payment indicators from Statista Market Insights, cryptocurrency adoption rankings from the 2025 Chainalysis Global Crypto Adoption Index, and financial inclusion and mobile connectivity indicators from the World Bank Global Findex Database (2025). Statista data are used to measure the scale and intensity of digital payment adoption, Chainalysis rankings serve as a proxy for grassroots crypto-adoption intensity, and Global Findex indicators-particularly account ownership, unbanked population, and mobile phone ownership-provide the broader financial inclusion context. Together, these datasets support a comparative analysis of digital payments, cryptocurrency adoption, and FinTech leapfrogging across the selected economies. 3.2 Sample selection The study employs a stratified purposive sampling strategy to select ten representative economies that capture contrasting patterns of financial infrastructure and digital financial adoption. The sample is divided into two groups according to economic development levels, financial inclusion conditions, cryptocurrency ownership estimates, and crypto-adoption intensity. Group A: Emerging economies This group includes India, Vietnam, Nigeria, Brazil, and the Philippines, which rank among the leading countries in the 2025 Chainalysis Global Crypto Adoption Index. These economies also display relatively strong cryptocurrency ownership estimates and persistent financial inclusion gaps. Cryptocurrency ownership is particularly high in Vietnam (≈21.2%) and the Philippines (≈19.0%), while Brazil and Nigeria record levels above approximately 12–13%. Although India shows a lower ownership estimate (≈7.2%), it ranks first globally in overall crypto-adoption intensity. At the same time, World Bank Global Findex data indicate that several of these economies continue to exhibit substantial shares of unbanked adults, making them relevant cases for examining whether digital financial technologies may compensate for incomplete traditional financial infrastructures. Group B: Developed economies The second group includes the United States, the United Kingdom, Germany, Sweden, and Japan, representing advanced economies with highly developed financial systems and near-universal banking access. In these countries, the share of unbanked adults generally remains below 5%. Cryptocurrency ownership estimates are moderate, reaching 15.6% in the United States, 11.2% in the United Kingdom, and 9.8% in Germany, while remaining lower in Sweden (≈4.3%) and Japan (≈4.0%). These economies were selected to provide a contrasting set of cases in which crypto adoption occurs within mature banking systems and is more likely to be associated with investment, portfolio diversification, and institutional participation than with financial exclusion. This comparative framework enables the study to assess whether FinTech adoption follows distinct pathways across emerging and developed economies and whether these patterns are consistent with the Leapfrogging Hypothesis. 3.3 Operationalization of variables To examine the relationship between financial infrastructure, digital payment expansion, and cryptocurrency adoption, the study employs a set of variables grouped into four categories: adoption indicators, contextual financial infrastructure indicators, technological enablers, and structural drivers. Adoption indicators include digital payment transaction value, Compound Annual Growth Rate (CAGR), Average Transaction Value (ATV), Mobile POS penetration, the composition of payment instruments within Mobile POS, and cryptocurrency adoption intensity. These variables are used to capture the scale, speed, depth, and structural form of digital financial adoption. Contextual financial infrastructure indicators-such as credit card penetration, debit card penetration, online banking penetration, and bank account ownership-are included to assess the maturity of the formal financial system. In addition, mobile phone ownership is used as a technological enabler reflecting digital access potential, while the share of unbanked adults is treated as a structural driver indicating gaps in formal financial inclusion. Taken together, these variables provide a framework for analyzing whether FinTech adoption in emerging economies reflects patterns consistent with leapfrogging dynamics. 3.4 Analytical method The study adopts a Comparative Trend Analysis (CTA) approach to examine cross-country differences in FinTech adoption rather than using econometric regression. This choice is justified by the purposive sample design and by the study’s emphasis on structural comparison across a limited set of representative economies. The empirical analysis proceeds in four stages. First, the study examines the historical evolution and projected trends of Average Transaction Value (ATV) in order to assess the depth and intensity of digital payment use. Second, it calculates the Compound Annual Growth Rate (CAGR) of Mobile POS payment transaction values between 2018 and 2025 to measure the comparative speed of digital payment expansion. Third, it analyzes Mobile POS penetration rates, payment instrument composition, and broader financial infrastructure indicators in order to compare the institutional environment of digital payment adoption across the two groups. Fourth, it assesses cryptocurrency adoption by combining Chainalysis crypto-adoption rankings with account ownership, unbanked population, and mobile phone ownership indicators from Global Findex. Visualization techniques are used to support comparative interpretation, including line charts, comparative tables, and scatter plots. In the cryptocurrency analysis, scatter plots are used to examine the relationship between financial exclusion and crypto-adoption intensity. Because lower Chainalysis ranks indicate stronger adoption, the relevant y-axis is reversed in order to improve interpretability. The CAGR is calculated using the following formula: V final: represents the final transaction value V begin: represents the initial value n: represents the number of years This metric enables comparison of adoption trajectories across economies with different market sizes and provides a standardized measure of digital payment growth. 3.5 Data limitations Despite the robustness of the datasets used, several limitations remain. Some Statista Market Insights indicators include projections rather than observed values, and should therefore be interpreted as likely trajectories rather than realized outcomes. The Chainalysis Global Crypto Adoption Index captures relative adoption intensity rather than direct ownership shares, making it more suitable for comparative ranking than for estimating the exact proportion of crypto users. In addition, the World Bank Global Findex is based on periodic survey waves rather than annual observations. Finally, all indicators are measured at the national level and may therefore mask important intra-country differences. Nevertheless, the triangulation of multiple data sources strengthens the reliability of the comparative analysis. 4. Empirical analysis This section presents the empirical findings of the study, focusing on the comparative dynamics of digital payment growth, cryptocurrency adoption patterns, and structural indicators related to financial inclusion. The analysis aims to identify whether emerging economies exhibit evidence of FinTech leapfrogging compared to developed financial systems. 4.1 Growth dynamics of digital payments To analyze the trajectory of digital finance, it is necessary to define the parameters of the Digital Payments Market. According to the framework established by Statista Market Insights, this segment is primarily driven by consumer transactions and is divided into two main structural components: Digital Commerce: Encompasses all consumer transactions for products and services conducted over the internet, representing the online dimension of the digital economy. Mobile POS Payments: Includes digital payments made at a physical Point of Sale (POS) via digital wallet applications (e.g., Apple Pay, Google Pay, UPI, or Pix). The market valuation integrates several key indicators, including total transaction values, the number of users, and the Average Transaction Value (ATV) per user. The latter serves as a proxy for the depth of digital financial integration into the daily lives of consumers. It is important to note that the empirical data and projections presented in this study reflect market conditions and recorded figures as of October 27, 2025. 4.1.1. Analysis of Average Transaction Value (ATV) trends Average Transaction Value (ATV) per user provides an important indicator of the economic intensity of digital payment use, as it captures not merely access to digital finance, but the depth of user engagement within digital payment ecosystems. Based on data retrieved on October 27, 2025, Figures 3 and 4 show the historical evolution of ATV between 2018 and 2025 and the projected trends for the period 2026–2030. In developed economies, ATV remained consistently high throughout the study period. The United States recorded the highest values, increasing from US$11.05k in 2018 to US$15.84k in 2025, with projections reaching US$23.44k by 2030. Similar but more moderate trends are observed in the United Kingdom, Germany, Japan, and Sweden. This pattern reflects convenience-driven adoption in mature financial systems, where digital payments are integrated into already well-established banking and consumption structures. In emerging economies, ATV started from lower levels but grew more rapidly in several cases. Brazil rose from US$1.16k in 2018 to US$4.13k in 2025, while Vietnam and the Philippines increased from roughly US$2.6k–3.7k to about US$5.2k–5.95k over the same period. Projections suggest further acceleration, especially in the Philippines, where ATV is expected to reach US$10.87k by 2030, and in Vietnam, which is projected to reach US$7.39k. These trends suggest that digital payments in some emerging markets are becoming a core transactional infrastructure rather than a simple complement to traditional finance. The contrast between the two groups indicates that developed economies maintain higher absolute values, while emerging economies display faster growth dynamics. This pattern appears consistent with the leapfrogging perspective, according to which economies with weaker traditional banking infrastructure may adopt digital financial solutions more rapidly and embed them more deeply in everyday economic activity. 4.1.2 Growth dynamics of mobile POS payments To assess structural change in payment systems, this study uses Mobile POS Payments as a key indicator of the digitalization of everyday transactions. Unlike Digital Commerce, which reflects online purchasing, Mobile POS payments capture the shift in face-to-face payment behavior. In emerging economies, their rapid expansion may reflect leapfrogging dynamics, as users move directly from cash-based systems to mobile-native payment ecosystems. Table 1, therefore, compares Mobile POS transaction growth across developed and emerging economies using CAGR for the period 2018–2025. The results reported in Table 1 reveal clear differences in the growth dynamics of mobile POS payments across developed and emerging economies. In both groups, mobile payment transaction values increased substantially between 2018 and 2025; however, the structural meaning of this growth differs across contexts. In emerging economies, high CAGR levels in countries such as Nigeria, Brazil, and India suggest that mobile payments are expanding not merely as a complementary payment option, but increasingly as an alternative transactional infrastructure. This pattern appears consistent with the leapfrogging perspective, whereby economies with more limited traditional banking and card-based infrastructures adopt mobile-first payment systems more rapidly. In such contexts, mobile payments may reduce reliance on cash while also widening access to formal financial channels. In developed economies, growth is also significant, as shown in the cases of Sweden, the United Kingdom, and Germany. However, in these markets, the expansion of mobile POS payments is better interpreted as the optimization of already mature financial ecosystems rather than a substitute for missing financial infrastructure. Adoption is therefore more convenience-driven, supported by high banking penetration, strong digital trust, and established payment networks. Japan represents a more gradual trajectory, which may reflect the persistence of legacy payment habits and the continued relevance of traditional payment instruments within a highly developed financial system. By contrast, the stronger expansion observed in several emerging economies suggests that mobile payment technologies can play a more transformative role when introduced in contexts characterized by financial access gaps or weaker card-payment penetration. 4.1.3. Penetration rate of mobile POS payments Penetration rate is used here as a complementary indicator of societal diffusion and is interpreted jointly with transaction value and usage-intensity measures in order to provide a more comprehensive assessment of digital payment transformation. The data for 2018–2025 reveal a clear contrast between developed and emerging economies. In developed economies, penetration rates were already high and continued to rise steadily, increasing from 50.43% to 81.13% in the United States and from 46.64% to 76.38% in Sweden. Germany, the United Kingdom, and Japan followed similar upward paths, indicating that Mobile POS payments are deeply embedded in mature and highly banked financial systems. In emerging economies, the trajectories were more uneven but still significant. Brazil recorded the highest penetration rate in this group, rising from 37.79% in 2018 to 60.81% in 2025, while India and Vietnam increased from 5.47% to 23.09% and from 11.47% to 22.72%, respectively. Nigeria and the Philippines also progressed, from 3.55% to 11.35% and from 7.70% to 19.14%. Projections for 2026–2030 suggest continued growth in both groups, although developed economies appear closer to saturation, with Sweden, Japan, the United States, and the United Kingdom projected to reach 86.24%, 84.94%, 83.06%, and 83.38%, respectively, by 2030. In emerging economies, convergence remains partial: Brazil is projected to reach 62.25%, while India and Vietnam are expected to remain below 30%, at 28.62% and 27.51%, respectively. Taken together with transaction value and usage-intensity indicators, these results suggest that Mobile POS expansion reflects optimization in developed economies and uneven but significant leapfrogging dynamics in selected emerging markets. 4.1.4 Financial infrastructure indicators in developed and emerging economies To contextualize differences in Mobile POS adoption, it is useful to consider broader financial infrastructure indicators across the two groups. As shown in Table 2, developed economies exhibit consistently higher levels of financial inclusion and card-based infrastructure. In 2025, average credit card penetration reached 61.6% in developed economies, compared with 13.8% in emerging economies, while debit card penetration stood at 93.8% versus 43.6%. A similar gap is observed in online banking penetration (77.0% in developed economies compared with 33.0% in emerging economies) and bank account penetration (98.4% versus 78.4%). These differences suggest that advanced economies continue to rely on mature banking and card-centered systems, whereas emerging economies are expanding digital finance from a less developed institutional base. This broader structural contrast helps explain why Mobile POS growth in emerging markets may be more closely associated with leapfrogging dynamics than in developed ones. 4.1.5 Structural composition of payment instruments within mobile POS payments To further evaluate the Leapfrogging Hypothesis, it is useful to examine the composition of payment instruments within the Mobile POS Payments segment across the selected economies. Rather than reflecting the overall structure of national payment systems, this indicator shows how transaction value is distributed across different instruments within mobile-based point-of-sale payments. It therefore provides a more specific perspective on the channels through which mobile payment adoption is taking place. The results reveal notable differences between emerging and developed economies. Within the Mobile POS segment, digital wallets account for a relatively large share of transaction value in several emerging economies, particularly in India (59.4%), Vietnam (30.5%), and the Philippines (28.6%). These shares are substantially higher than those observed in Germany (9.1%) and the United States (16.0%), suggesting that wallet-based instruments play a more central role in Mobile POS transactions in several emerging markets. By contrast, developed economies remain more strongly oriented toward card-based instruments within the same segment. Debit cards account for 49.2% of Mobile POS transaction value in Sweden, 47.3% in the United Kingdom, and 42.1% in Germany, while credit cards represent 40.1% in the United States and 33.8% in Japan. This indicates that, even within Mobile POS payments, advanced economies continue to rely heavily on established card-linked infrastructures. Another notable feature is the large share of the category “Others” in some emerging economies, especially Nigeria (68.8%) and Brazil (48.8%). Since this category may include a range of payment arrangements, it should be interpreted with caution. Nevertheless, its prominence suggests that the Mobile POS segment in these markets is not shaped exclusively by conventional debit- and credit-card instruments. 4.2. Reassessing the cryptocurrency adoption paradox The cryptocurrency adoption paradox refers to the observation that some economies with weaker levels of financial inclusion may nevertheless record relatively high levels of cryptocurrency adoption. To reassess this issue more rigorously, this subsection combines two complementary indicators: the 2025 Chainalysis Global Crypto Adoption Index and the World Bank Global Findex 2025 account-ownership indicator. Rather than relying on estimated cryptocurrency ownership shares, the analysis uses the Chainalysis ranking as a proxy for the intensity of grassroots crypto adoption, while financial inclusion is measured through the share of adults aged 15 and above who own an account at a financial institution or with a mobile-money-service provider. The unbanked population is therefore calculated as the inverse of account ownership. 4.2.1. Comparative patterns of cryptocurrency adoption Table 4. shows that cryptocurrency adoption does not follow a single developmental pattern across the selected economies. Within the sample, India ranks first in the 2025 Chainalysis Global Crypto Adoption Index, followed by the United States in second place, Vietnam in fourth, Brazil in fifth, Nigeria in sixth, and the Philippines in ninth. Among the developed economies, the United Kingdom ranks eleventh, Japan nineteenth, Germany twenty-first, and Sweden fifty-sixth. These results indicate that relatively strong cryptocurrency adoption can be observed in both emerging and developed economies, although with substantial variation in intensity. The distribution of these rankings suggests that several emerging economies occupy leading positions in the global index, which is consistent with the argument that cryptocurrencies may serve functions extending beyond portfolio investment alone. At the same time, the position of the United States shows that high adoption can also occur in mature financial systems characterized by near-universal banking access and expanding institutional participation. Conversely, Sweden’s much lower position, despite its highly advanced digital-payment environment, suggests that a sophisticated cashless economy does not automatically translate into equally strong cryptocurrency adoption. 4.2.2. Interpreting the paradox: Divergent adoption pathways When these rankings are interpreted together with financial inclusion data, the cryptocurrency adoption paradox appears more nuanced than a simple inverse relationship between banking weakness and crypto uptake. The clearest cases consistent with the paradox are Nigeria and the Philippines, where relatively high crypto-adoption rankings coexist with comparatively large shares of unbanked adults. In such contexts, cryptocurrency adoption may reflect the use of alternative channels for payments, remittances, peer-to-peer transfers, and value storage where formal financial access remains incomplete. This interpretation is broadly consistent with the study’s distinction between necessity-driven and convenience-driven FinTech adoption. However, other emerging economies complicate a purely exclusion-based explanation. India ranks first globally despite a high level of account ownership, while Brazil and Vietnam also combine strong crypto-adoption rankings with expanding formal financial inclusion. In these cases, adoption appears to be linked not only to financial necessity but also to mobile-first digital ecosystems, rapid platform expansion, and broader participation in digital financial markets. In developed economies, especially the United States and the United Kingdom, cryptocurrency adoption appears more closely associated with investment behavior, institutionalization, and regulatory normalization than with financial exclusion. The inclusion of an institutional activity sub-index in the 2025 Chainalysis methodology further reinforces the relevance of this interpretation for advanced markets. 4.2.3. Assessing FinTech leapfrogging To further assess the leapfrogging hypothesis, it is useful to examine cryptocurrency adoption in relation to both financial exclusion and mobile connectivity. Using Global Findex 2025 indicators on account ownership and mobile phone ownership, together with the 2025 Chainalysis Global Crypto Adoption Index, this subsection explores whether stronger mobile connectivity may help explain high levels of crypto adoption in contexts where formal financial inclusion remains incomplete. Rather than treating cryptocurrency uptake as a purely investment-driven phenomenon, this approach considers whether digital connectivity may facilitate alternative forms of financial participation in selected emerging economies. Although Figure 7 maps financial exclusion against cryptocurrency adoption intensity, mobile phone ownership provides an important complementary layer of interpretation. In the selected emerging economies, mobile phone ownership remains relatively high despite persistent financial inclusion gaps, reaching 98% in Vietnam, 92% in Brazil, 84% in Nigeria, and 78% in the Philippines, while India records 66%. In developed economies, mobile phone ownership is even higher, ranging from 92% in the United Kingdom and Germany to 99% in Sweden. These figures suggest that mobile connectivity is widespread across both groups, but its interaction with financial exclusion differs across contexts. In emerging markets, high mobile access combined with incomplete formal financial inclusion may create favorable conditions for stronger crypto adoption. By contrast, in developed economies, high mobile connectivity alone does not appear sufficient to generate equally strong adoption intensity. The data suggest that high cryptocurrency adoption in some emerging economies is associated not only with financial inclusion gaps, but also with relatively strong levels of mobile connectivity. The Philippines, Nigeria, and Vietnam combine higher shares of unbanked adults with comparatively strong crypto-adoption rankings, while also displaying substantial mobile phone ownership. This pattern appears consistent with the leapfrogging argument, according to which populations may adopt digital financial alternatives when mobile access is available but formal financial services remain incomplete. At the same time, the relationship is not uniform across all cases. India combines a relatively low unbanked rate with the highest crypto-adoption ranking in the sample, while Brazil also shows strong adoption despite more limited financial exclusion than Nigeria or the Philippines. These cases suggest that cryptocurrency adoption may also expand within broader digital-finance ecosystems shaped by mobile-first usage, platform expansion, and growing participation in digital markets. The developed economies in the sample provide an important contrast. Japan, Germany, and Sweden combine near-universal financial inclusion with lower crypto-adoption intensity than several emerging markets, despite high levels of mobile phone ownership. This suggests that mobile connectivity alone does not explain adoption. Rather, strong crypto uptake appears more likely where digital readiness interacts with unmet financial needs or alternative financial use cases. The United States is a partial exception, as it combines very high financial inclusion with a strong adoption rank, indicating that institutional participation and investment-related demand remain important drivers in advanced markets. Conclusion This study examined whether FinTech adoption follows different pathways across emerging and developed economies, with a particular focus on digital payments and cryptocurrency adoption. The findings show that FinTech diffusion is context-dependent and shaped by differences in financial infrastructure, institutional capacity, and technological readiness. The analysis of digital payments reveals two broad patterns. In developed economies, growth mainly reflects the optimization of mature financial systems through higher efficiency, convenience, and deeper integration of digital payment tools. In emerging economies, by contrast, stronger growth in several indicators suggests a more structural transformation, in which digital payments increasingly function as an alternative transactional infrastructure. This pattern is consistent with the leapfrogging perspective, especially where digital tools expand faster than traditional banking access. The analysis of cryptocurrency adoption further supports this conclusion, but in a more nuanced way. The results do not confirm a simple inverse relationship between weak financial inclusion and high crypto adoption. Instead, they indicate multiple adoption pathways. In some emerging economies, cryptocurrency appears to operate as a partial substitute for incomplete financial services, while in developed economies it is more closely associated with investment, institutional participation, and broader digital financial innovation. The main contribution of this study lies in integrating digital payments and cryptocurrency adoption within a single comparative framework of FinTech leapfrogging. It shows that FinTech should be understood not merely as a technological innovation, but as a structural and context-sensitive process. From a policy perspective, the findings highlight the importance of inclusive digital infrastructure, mobile connectivity, financial literacy, and balanced regulation. Future research could expand the country sample, apply econometric testing, and further examine the role of regulatory quality and digital safety in shaping FinTech adoption. References: References > Bhasin, N. K., Rajesh, A. (2020). 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(2025). How traditional banks adapt to the fintech revolution in banking and finance sector. In Shaping Cutting-Edge Technologies and Applications for Digital Banking and Financial Services, Taylor & Francis, 214–225. <https://doi.org/10.4324/9781003501947-13>; Khan, K., Luo, T., Ullah, S., Rasheed, H. M. W., Li, P.-H. (2023). Does digital financial inclusion affect CO2 emissions? Evidence from 76 emerging markets and developing economies (EMDEs). Journal of Cleaner Production, 420, 138313. <https://doi.org/10.1016/j.jclepro.2023.138313>; Khatatbeh, I. N., Mustafa, J. A., Alhusban, M. I., Alfoul, M. N. A., Shammout, E. (2026). The role of fintech governance in enhancing financial inclusion and reducing income inequality in MENA countries. Journal of Governance and Regulation, 15(1), 150–159. <https://doi.org/10.22495/jgrv15i1art14>; Kumar, I. (2024). Banking services and financial inclusion in India’s poorest regions. Journal of Banking Regulation, 25(2), 145–159. <https://doi.org/10.1057/s41261-023-00224-9>; Le, M.-Q., Nguyen, T.-H., Dao, V., Nguyen, P., Vu, D.-L., Nguyen, H.-M., Tran, T.-T. (2025). Research on the impacts of financial inclusion towards national economic growth during the period 2014–2022: New findings and policy implications. In Springer Proceedings in Business and Economics, Springer, 507–530. <https://doi.org/10.1007/978-981-97-9992-3_33>; Logan, S., Singh, J. P. (2018). The meta-power of technology. In Technologies of International Relations: Continuity and Change. <https://doi.org/10.1007/978-3-319-97418-7_6>; Mhlanga, D. (2023). Artificial intelligence (AI) solutions for financial inclusion of the excluded: What are the challenges? In Advances in African Economic, Social and Political Development, Springer, 257–272. <https://doi.org/10.1007/978-3-031-31431-5_14>; Parino, F., Beiró, M. G., Gauvin, L. (2018). Analysis of the Bitcoin blockchain: socio-economic factors behind the adoption. EPJ Data Sci. 7, 38. <https://doi.org/10.1140/epjds/s13688-018-0170-8>; Patwardhan, A. (2018). Financial inclusion in the digital age. In Kuo, D. L., Deng, R. H. (Eds.). Handbook of blockchain, digital finance, and inclusion, Volume 1: Cryptocurrency, fintech, insurtech, and regulation, Elsevier, 57–89. <https://doi.org/10.1016/B978-0-12-810441-5.00004-X>; Rai, A. K., Kumar, A., Bhatt, A. K., Esubalew, A. A., Rai, S. (2025). Innovative approaches to financial inclusion in emerging economies: A case study analysis of India and Ethiopia. In Sustainable Finance, Springer, 125–146. <https://doi.org/10.1007/978-3-032-01677-5_6>; Ranganathan, K. (2012). Leapfrogging the digital divide: Myth or reality for emerging regions? In ICT Influences on Human Development, Interaction, and Collaboration. <https://doi.org/10.4018/978-1-4666-1957-9.ch014>; Ritzer, G. (2012). Leapfrogging. In The Wiley-Blackwell Encyclopedia of Globalization. <https://doi.org/10.1002/9780470670590.wbeog355>; Rodima-Taylor, D., Grimes, W. W. (2019). International remittance rails as infrastructures: embeddedness, innovation and financial access in developing economies. Review of International Political Economy, 26(5), 839–862. <https://doi.org/10.1080/09692290.2019.1607766>; Sanzogni, L., Arthur-Gray, H. (2007). Technology leapfrogging in Thailand. In Global Information Technologies: Concepts, Methodologies, Tools, and Applications. <https://doi.org/10.4018/978-1-59904-939-7.ch136>; Shah, P., Devdatta, S. T., Jayapriya, J., Vinay, M., Deepa, S. (2025). Technological innovation in digital payments: A survey of trends, challenges, and opportunities. In Lecture Notes in Networks and Systems, 1321 LNNS, Springer, 35–147. <https://doi.org/10.1007/978-981-96-4151-2_12> ; Sharma, M. (2021). Digital payments in India: Impact of emerging technologies. In Industry 4.0 Technologies for Business Excellence: Frameworks, Practices, and Applications, CRC Press, 191–204. <https://doi.org/10.1201/9781003140474-11>; Sikka, V., Bhayana, P. (2024). Barriers to comprehensive financial inclusion across the globe: From sociocultural norms to systemic challenges. In Sustainable Finance, Springer, 89–126. <https://doi.org/10.1007/978-3-031-67523-2_7>; Tan, B., Ng, E., Jiang, J. (2018). The process of technology leapfrogging: Case analysis of the national ICT infrastructure development journey of Azerbaijan. International Journal of Information Management, 38(1), 311–316. <https://doi.org/10.1016/j.ijinfomgt.2017.10.008>; Third, A., Kao, K.-T. (2007). ICT leapfrogging policy and development in the third world. In Encyclopedia of Information Ethics and Security. <https://doi.org/10.4018/978-1-59140-987-8.ch049>; Tian, Y., Chan, T. J., Suki, N. M., Kasim, M. A. (2023). Moderating role of perceived trust and perceived service quality on consumers’ use behavior of Alipay e-wallet system: the perspectives of technology acceptance model and theory of planned behavior. Human Behavior and Emerging Technologies, 2023. <https://doi.org/10.1155/2023/5276406>; Tsang, M. (2023). Currency crisis: Turkey in 2021. The CASE Journal, 19(5), 679–698. <https://doi.org/10.1108/TCJ-08-2022-0140>; Vincent, G., Sivakumar, S. (2019). Financial inclusion in India – A progress and challenges. International Journal of Advanced Science and Technology, 28(19), 521–530; Visconti-Caparrós, J. M., Campos-Blázquez, J. R. (2022). The development of alternate payment methods and their impact on customer behavior: The Bizum case in Spain. Technological Forecasting and Social Change, 175, 121330. <https://doi.org/10.1016/j.techfore.2021.121330>; Zhang, Q., Valle-Sison, J. B. (2014). Financial inclusion and regulatory implications. In Global shock, risks, and Asian financial reform, Edward Elgar Publishing, 600–627. <https://doi.org/10.4337/9781783477944.00029> ; Zhao, D., Yuan, J., Chen, W. (2023). Financial consumer protection in FinTech field. In Contributions to Finance and Accounting. <https://doi.org/10.1007/978-981-99-5173-4_5>. Footnotes: [1] Patwardhan, A. (2018). Financial inclusion in the digital age. In Kuo, D. L., Deng, R. H. (Eds.). Handbook of blockchain, digital finance, and inclusion, Volume 1: Cryptocurrency, fintech, insurtech, and regulation, Elsevier, 57–89. <https://doi.org/10.1016/B978-0-12-810441-5.00004-X>. [2] Zhang, Q., Valle-Sison, J. B. (2014). Financial inclusion and regulatory implications. In Global shock, risks, and Asian financial reform, Edward Elgar Publishing, 600–627. <https://doi.org/10.4337/9781783477944.00029>. [3] Le, M.-Q., Nguyen, T.-H., Dao, V., Nguyen, P., Vu, D.-L., Nguyen, H.-M., Tran, T.-T. (2025). Research on the impacts of financial inclusion towards national economic growth during the period 2014–2022: New findings and policy implications. In Springer Proceedings in Business and Economics, Springer, 507–530. <https://doi.org/10.1007/978-981-97-9992-3_33>. [4] Dat, P. T., Oanh, T. T. K. (2025). Linkage between financial inclusion, financial development and financial stability: Perspectives from developing and developed countries. Annals of Financial Economics, 20(4), Article 2550022. <https://doi.org/10.1142/S2010495225500228>. [5] Demir, A., Pesqué-Cela, V., Altunbas, Y., Murinde, V. (2022). Fintech, financial inclusion and income inequality: A quantile regression approach. European Journal of Finance, 28(1), 86–107. <https://doi.org/10.1080/1351847X.2020.1772335>. [6] Rai, A. K., Kumar, A., Bhatt, A. K., Esubalew, A. A., Rai, S. (2025). Innovative approaches to financial inclusion in emerging economies: A case study analysis of India and Ethiopia. In Sustainable Finance, Springer, 125–146. <https://doi.org/10.1007/978-3-032-01677-5_6>. [7] Mhlanga, D. (2023). Artificial intelligence (AI) solutions for financial inclusion of the excluded: What are the challenges? In Advances in African Economic, Social and Political Development, Springer, 257–272. <https://doi.org/10.1007/978-3-031-31431-5_14>. [8] Kumar, I. (2024). Banking services and financial inclusion in India’s poorest regions. Journal of Banking Regulation, 25(2), 145–159. <https://doi.org/10.1057/s41261-023-00224-9>. [9] Patwardhan, A. (2018), 57–89. [10] Sikka, V., Bhayana, P. (2024). Barriers to comprehensive financial inclusion across the globe: From sociocultural norms to systemic challenges. In Sustainable Finance, Springer, 89–126. <https://doi.org/10.1007/978-3-031-67523-2_7>. [11] Khatatbeh, I. N., Mustafa, J. A., Alhusban, M. I., Alfoul, M. N. A., Shammout, E. (2026). The role of fintech governance in enhancing financial inclusion and reducing income inequality in MENA countries. Journal of Governance and Regulation, 15(1), 150–159. <https://doi.org/10.22495/jgrv15i1art14>. [12] Chitimira, H., Ncube, M. (2020). Legislative and other selected challenges affecting financial inclusion for the poor and low income earners in South Africa. Journal of African Law, 64(3), 337–355. <https://doi.org/10.1017/S0021855320000182>. [13] Shah, P., Devdatta, S. T., Jayapriya, J., Vinay, M., Deepa, S. (2025). Technological innovation in digital payments: A survey of trends, challenges, and opportunities. In Lecture Notes in Networks and Systems, 1321 LNNS, Springer, 35–147. <https://doi.org/10.1007/978-981-96-4151-2_12>. [14] Tian, Y., Chan, T. J., Suki, N. M., Kasim, M. A. (2023). Moderating role of perceived trust and perceived service quality on consumers’ use behavior of Alipay e-wallet system: the perspectives of technology acceptance model and theory of planned behavior. Human Behavior and Emerging Technologies, 2023. <https://doi.org/10.1155/2023/5276406>. [15] Visconti-Caparrós, J. M., Campos-Blázquez, J. R. (2022). The development of alternate payment methods and their impact on customer behavior: The Bizum case in Spain. Technological Forecasting and Social Change, 175, 121330. <https://doi.org/10.1016/j.techfore.2021.121330>. [16] Ghosh, P., Golder, U. (2026). Exploring the effects of FinTech adoption on traditional banking: A systematic literature review on opportunities and challenges. Digital Business, 6(1), 100163. <https://doi.org/10.1016/j.digbus.2026.100163>. [17] Karani, G., Jadhav, B. (2025). How traditional banks adapt to the fintech revolution in banking and finance sector. In Shaping Cutting-Edge Technologies and Applications for Digital Banking and Financial Services, Taylor & Francis, 214–225. <https://doi.org/10.4324/9781003501947-13>. [18] Cook, S. (2017). Selfie banking: Is it a reality? Biometric Technology Today, 2017(3), 9–11. <https://doi.org/10.1016/S0969-4765(17)30056-5>. [19] Bhasin, N. K., Rajesh, A. (2020). Study of increasing adoption trends of digital banking and FinTech products in Indian payment systems and improvement in customer services. In Collaborative Convergence and Virtual Teamwork for Organizational Transformation, IGI Global, 229–255. <https://doi.org/10.4018/978-1-7998-4891-2.ch012>. [20] Sharma, M. (2021). Digital payments in India: Impact of emerging technologies. In Industry 4.0 Technologies for Business Excellence: Frameworks, Practices, and Applications, CRC Press, 191–204. <https://doi.org/10.1201/9781003140474-11>. [21] Rodima-Taylor, D., Grimes, W. W. (2019). International remittance rails as infrastructures: embeddedness, innovation and financial access in developing economies. Review of International Political Economy, 26(5), 839–862. <https://doi.org/10.1080/09692290.2019.1607766>. [22] El Hajj, M., Farran, I. (2024). The Cryptocurrencies in Emerging Markets: Enhancing Financial Inclusion and Economic Empowerment. Journal of Risk and Financial Management, 17(10), 467. <https://doi.org/10.3390/jrfm17100467>. [23] Tsang, M. (2023). Currency crisis: Turkey in 2021. The CASE Journal, 19(5), 679–698. <https://doi.org/10.1108/TCJ-08-2022-0140>. [24] Parino, F., Beiró, M. G., Gauvin, L. (2018). Analysis of the Bitcoin blockchain: socio-economic factors behind the adoption. EPJ Data Sci. 7, 38. <https://doi.org/10.1140/epjds/s13688-018-0170-8>. [25] Dang, T. H. N., Balli, F., Balli, H. O., Kilic, I. (2025). Demographic-governance factors shaping cryptocurrency holding behavior. Finance Research Letters, 85(Part D), 108143. <https://doi.org/10.1016/j.frl.2025.108143>. [26] Khan, K., Luo, T., Ullah, S., Rasheed, H. M. W., Li, P.-H. (2023). Does digital financial inclusion affect CO2 emissions? Evidence from 76 emerging markets and developing economies (EMDEs). Journal of Cleaner Production, 420, 138313. <https://doi.org/10.1016/j.jclepro.2023.138313>. [27] Vincent, G., Sivakumar, S. (2019). Financial inclusion in India – A progress and challenges. International Journal of Advanced Science and Technology, 28(19), 521–530. [28] Third, A., Kao, K.-T. (2007). ICT leapfrogging policy and development in the third world. In Encyclopedia of Information Ethics and Security. <https://doi.org/10.4018/978-1-59140-987-8.ch049>. [29] Ritzer, G. (2012). Leapfrogging. In The Wiley-Blackwell Encyclopedia of Globalization. <https://doi.org/10.1002/9780470670590.wbeog355>. [30] Logan, S., Singh, J. P. (2018). The meta-power of technology. In Technologies of International Relations: Continuity and Change. <https://doi.org/10.1007/978-3-319-97418-7_6>. [31] Burlamaqui, L., Kattel, R. (2016). Development as leapfrogging, not convergence, not catch-up: Towards Schumpeterian theories of finance and development. Review of Political Economy, 28(2), 270–288. <https://doi.org/10.1080/09538259.2016.1142718>. [32] Sanzogni, L., Arthur-Gray, H. (2007). Technology leapfrogging in Thailand. In Global Information Technologies: Concepts, Methodologies, Tools, and Applications. <https://doi.org/10.4018/978-1-59904-939-7.ch136>. [33] Fong, M. W. L. (2008). The mobile phone telecommunications service sector in China. In Mobile Computing: Concepts, Methodologies, Tools, and Applications. <https://doi.org/10.4018/978-1-60566-054-7.ch108>. [34] Huang, C.-Y. (2011). Rethinking leapfrogging in the end-user telecom market. Technological Forecasting and Social Change, 78(4), 703–712. <https://doi.org/10.1016/j.techfore.2010.10.009>. [35] James, J. (2012). The distributional effects of leapfrogging in mobile phones. Telematics and Informatics, 29(3), 294–301. <https://doi.org/10.1016/j.tele.2011.09.001>. [36] Tan, B., Ng, E., Jiang, J. (2018). The process of technology leapfrogging: Case analysis of the national ICT infrastructure development journey of Azerbaijan. International Journal of Information Management, 38(1), 311–316. <https://doi.org/10.1016/j.ijinfomgt.2017.10.008>. [37] Ranganathan, K. (2012). Leapfrogging the digital divide: Myth or reality for emerging regions? In ICT Influences on Human Development, Interaction, and Collaboration. <https://doi.org/10.4018/978-1-4666-1957-9.ch014>. [38] Zhao, D., Yuan, J., Chen, W. (2023). Financial consumer protection in FinTech field. In Contributions to Finance and Accounting. <https://doi.org/10.1007/978-981-99-5173-4_5>. [39] Hanif, R., Pierotti, M., Khalique, M. (2026). Harnessing technological innovation and digital capabilities for resilience in developing economies. Sustainable Technology and Entrepreneurship, 5(1), 100124. <https://doi.org/10.1016/j.stae.2025.100124>.
The Impact of Digital Transformation on Knowledge Economy Performance in MENA Countries: A Panel Data Analysis
This study investigates the effect of digital transformation on knowledge economy performance across 11 Middle East and North Africa (MENA) countries over the period 2000–2024, using a panel of 275 country-year observations. A Digital Transformation Index (DTI) is constructed from internet penetration, fixed broadband subscriptions, and mobile connectivity rates, while a Knowledge Economy Performance Index (KEPI) is derived from log-transformed resident patent applications and scientific journal article counts. Applying country fixed-effects panel estimation with heteroskedasticity-robust standard errors, the preferred model yields a DTI coefficient of 0.391 (p < 0.001, within-R² = 0.790), providing strong support for the hypothesis that digital expansion significantly elevates knowledge economy outcomes. Government effectiveness also exerts a positive and statistically significant direct effect (β = 0.089, p = 0.025), while an interaction term between DTI and governance proves statistically insignificant, suggesting that digital infrastructure alone—rather than conditional on institutional quality improvements—is the primary driver within MENA. Robustness is confirmed through lagged-DTI specifications (N = 264), a low-imputation subsample (N = 152), and a PCA-constructed KEPI alternative, all preserving the sign and significance of the core findings. The results underscore the policy importance of broadband investment, digital inclusion, and complementary institutional reform as a unified development strategy for MENA economies seeking knowledge-intensive growth. Keywords: Digital transformation, knowledge economy, MENA, panel data, fixed effects, innovation, digitalization. Introduction Over the past two decades, MENA has experienced one of the most rapid digital connectivity expansions among developing regions. Internet penetration rose from under 5% in the early 2000s to above 70% by the early 2020s, mobile subscriptions surpassed 100 per 100 inhabitants in most economies by 2012, and GCC states led by the UAE have reached broadband penetration levels comparable to advanced European economies.[1] Yet this connectivity surge has not translated into commensurate knowledge-economy gains. The region accounted for less than 0.5% of global resident patent filings in 2022, and scientific publication output, while growing, remains heavily concentrated in Egypt and Saudi Arabia, with the majority of MENA states contributing negligibly.[2] This stark disconnect—between one of the world’s fastest digital expansions and persistently thin innovation output—raises a fundamental empirical question: does digital transformation actually elevate knowledge-economy performance in MENA, and if so, under what conditions? Answering this question is the central purpose of the present study. The policy relevance of this question extends well beyond the region. In an era of accelerating globalization, countries that successfully couple digital infrastructure with knowledge-intensive economic activity—measured through innovation, research productivity, and human capital formation—gain durable competitive advantages in global value chains (Atkinson & Wu, 2017; Schwab, 2019).[3],[4] For MENA governments, which are simultaneously confronting hydrocarbon revenue volatility, demographic youth bulges, and ambitious national digitalization visions, understanding whether digital investment generates measurable innovation dividends is a first-order policy question.[5] Moreover, from a development economics standpoint, the MENA region constitutes a theoretically compelling laboratory: it encompasses highly digitalized, capital-abundant small open economies alongside larger, more populous lower-middle-income states with heterogeneous institutional environments.[6] A rigorous comparative panel analysis of this diverse group, therefore, offers generalizable insights for developing economies beyond the region. Prior studies link ICT adoption to productivity,[7],[8] internet diffusion to innovation output,[9] and digital infrastructure to growth, conditional on institutions.[10],[11] Yet evidence targeting knowledge-economy outcomes specifically remains limited, and governance as an enabling condition in the digital–knowledge nexus has received only selective attention. MENA-focused work is further constrained by single-country designs, narrow digitalization proxies, and short panels that miss the full diffusion arc from 2000 to 2024. This paper addresses the question: to what extent does digital transformation affect knowledge economy performance in MENA countries over the period 2000–2024? Two testable hypotheses organize the empirical investigation. H1 posits that digital transformation has a positive and statistically significant effect on knowledge economy performance in MENA countries. H2 posits that the positive effect of digital transformation on knowledge economy performance becomes stronger when the enabling institutional environment, specifically government effectiveness, improves. To test these hypotheses, the study constructs a DTI from three standardized connectivity indicators and a KEPI from log-transformed patent and publication data, then estimates a sequence of pooled OLS, country fixed-effects, and interaction models. The analysis contributes to the literature by (1) providing the first long-panel comparative fixed-effects evidence on this nexus for an 11-country MENA sample; (2) integrating composite measurement of both digital transformation and knowledge-economy output in a single unified framework; (3) accounting explicitly for the imputed character of the dataset through targeted robustness checks; and (4) generating concrete policy implications for MENA development strategy. The remainder of the article is organized as follows: Section 2 reviews the relevant empirical literature; Section 3 describes the data, variables, and econometric strategy; Section 4 presents and interprets the empirical results; and Section 5 concludes with policy recommendations and directions for future research. Literature Review Cardona et al. (2013)[12] conducted a comprehensive meta-analysis of 139 studies on the economic effects of ICT investment across developed and developing economies over the period from the early 1990s through the late 2000s. Using variance-weighted regression on pooled elasticity estimates, they found that a 10% increase in ICT investment was associated, on average, with a 0.5% to 1.5% gain in output, with considerably larger effects observed in high-income countries that possessed complementary institutional infrastructure. Their work established the conditional nature of ICT returns and is directly relevant to the MENA context because it foregrounds the enabling role of governance quality—a finding the present study tests explicitly through the DTI × GOV interaction specification. Choi and Yi (2018)[13] examined the relationship between internet use and economic growth in a panel of 161 countries over 1991–2014, employing dynamic GMM estimation to address endogeneity arising from the reverse effect of income on connectivity. Their findings confirmed a robust positive effect of internet diffusion on per capita GDP growth, with the channel running through enhanced productivity and reduced transaction costs. Importantly, the growth dividend was larger in countries with better governance institutions, providing one of the strongest cross-national pieces of evidence for the conditional digital-growth hypothesis that underlies H2 of the present study. Niebel (2018)[14] revisited the ICT–growth nexus by separately estimating panel models for high-income, upper-middle-income, and lower-middle-income country groups, using World Bank data from 1995 to 2010. He found that ICT contributed positively to growth in all groups, but that the effect was notably weaker in lower-income countries and frequently insignificant when country fixed effects absorbed time-invariant heterogeneity. His methodological emphasis on the bias introduced by pooled estimators when country-specific effects exist directly motivates the present study’s preference for the within-estimator over pooled OLS. Al-Mulali et al. (2020)[15] investigated the relationship between ICT, financial development, and economic growth in MENA countries using data from 2003 to 2018, employing panel cointegration techniques and a panel vector error-correction model. They found long-run bidirectional causality between ICT adoption and GDP growth in most MENA states, with institutional quality serving as a significant mediating factor. Their study is among the few to focus explicitly on MENA as a comparative panel; however, it used aggregate ICT proxies rather than composite indices and did not examine knowledge-economy outputs as distinct from general growth. Obeidat et al. (2021)[16] studied the effect of digital transformation on organizational innovation in 107 Jordanian firms using structural equation modeling. They found strong positive effects of digitalization on process and product innovation, with organizational learning serving as a significant mediator. Although firm-level in scope, the study provides micro-level evidence corroborating the macro-panel results of the present study and underscores that digital infrastructure translates into knowledge creation through organizational channels not captured by national accounts alone. Bakri et al. (2022)[17] investigated digital transformation and innovation output in Gulf Cooperation Council economies using a fixed-effects panel from 2010 to 2020. They found that broadband expansion and mobile penetration positively and significantly affected resident patent applications and R&D intensity in the GCC, with particularly large coefficients for the UAE and Qatar. Their study is regionally proximate to the present work but confined to six GCC states and the more recent decade, missing the formative 2000–2010 period during which most MENA countries experienced the steepest gains in connectivity. Bouzid (2023)[18] examined how digitalization affected human development and innovation performance in seven North African countries from 2005 to 2020, using panel ARDL bounds testing. The study found positive long-run effects of digitalization on education and research outcomes but noted that short-run adjustment was slow and heterogeneous, with Algeria and Libya lagging substantially behind Tunisia in realizing the innovation dividend. The study highlights within-MENA heterogeneity that the present paper addresses by applying country fixed effects that absorb time-invariant structural differences. Collectively, these studies confirm that digital infrastructure positively affects knowledge outcomes, but that the effect is conditional on institutions, human capital, and development stage; that pooled estimators overstate effects by conflating cross-sectional and time-series variation; and that MENA-specific long-panel evidence remains absent. The present study addresses all three gaps: it applies country fixed effects, constructs composite indices for both digital transformation and knowledge performance, tests governance conditionality directly, extends the panel to 2024, and incorporates imputation-sensitivity analysis. Data and Methodology The sample covers 11 MENA countries—Algeria, Bahrain, Egypt, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Tunisia, and the UAE—over 2000–2024, yielding 275 country-year observations. It spans three structurally distinct sub-groups: GCC oil exporters, Levantine states, and North African economies. The period captures the full digital trajectory—early diffusion (2000–2007), mass mobile adoption (2008–2015), and near-saturation (2016–2024)—enabling estimation of within-country effects across all three phases. Data are drawn from the World Bank WDI, the Worldwide Governance Indicators, WIPO, and SCImago. Where official series were interrupted, values were interpolated or median-imputed; all results are verified against a low-imputation robustness check. 2.1 Variable Operationalization Note. WDI = World Development Indicators (World Bank). WGI = Worldwide Governance Indicators (World Bank). WIPO = World Intellectual Property Organization. SCImago = SCImago Journal & Country Rank. Sign expectations are based on theoretical priors. DTI×GOV is the moderation term used in Equation 2. 2.2 Model Specifications Three model specifications are estimated. The baseline direct-effect model is: where captures country-specific time-invariant effects and is the idiosyncratic error term. To test Hypothesis 2, the moderation model is specified as: The moderator is (Government effectiveness), chosen over education expenditure because governance quality is the theoretically more fundamental enabling condition for innovation and because prior studies identify governance as a key transmission channel through which digital investments generate knowledge-economy returns. The robustness specification employs a one-period lag of digital transformation: Because the Nickell bias in dynamic panels is of order , and here , the bias is approximately: This magnitude is sufficiently small to be treated as negligible in the present setting. Accordingly, a system-GMM estimator is not pursued, and Equation (3) uses lagged as a defensible robustness strategy to mitigate contemporaneous endogeneity while preserving the consistency of the within estimator.[19],[20] Empirical Results and Discussion This section presents and interprets all empirical results in sequence. Eight numbered tables and two figures are provided. Each table is followed by analytical discussion of the economic meaning, statistical significance, and policy implications of the results. Explicit discussion of H1 and H2 is provided throughout, and comparisons with the reviewed literature are drawn were instructive. Table 2 reveals several features consequential for model specification. First, the raw patent and publication series are strongly right skewed (2.07 and 1.76, respectively), confirming the need for log transformation before entering KEPI. Second, the large standard deviation of internet users (33.9 percentage points) and mobile subscriptions (60.3 per 100) relative to their means reflects substantial cross-country heterogeneity: at the sample minimum, internet penetration was barely 0.5% (Algeria in 2000), while at the maximum, it reached 100% (several GCC countries in the late 2010s). Third, government effectiveness ranges from −1.58 to 1.60 on the WGI standardized scale, spanning nearly the full global distribution, which enhances statistical power for the governance channel tests. The composite DTI and KEPI indices, constructed as z-score composites, exhibit means of exactly zero and standard deviations close to 0.9 by construction, and their mild skewness confirms that the log-transformation and standardization procedure has effectively normalized the underlying raw series. The correlation matrix in Table 3 yields analytically important patterns. The raw bivariate correlation between DTI and KEPI is only 0.011, superficially suggesting no linear relationship. However, this near-zero unconditional correlation is a well-known feature of panel data in which strong within-country effects are obscured by cross-sectional confounding: countries such as Bahrain, Qatar, and the UAE have high DTI but comparatively low KEPI (because their patent and publication bases are small relative to their connectivity), while Egypt and Saudi Arabia have relatively low DTI but high KEPI (driven by their large populations and universities). Once country fixed effects are applied—removing the cross-section confound—the within-country coefficient of DTI on KEPI becomes large and highly significant (β₁ = 0.391, p < 0.001), as shown in Table 6. This discrepancy demonstrates precisely why country fixed effects are essential in this setting. The VIF values are all below 2.1, confirming that multicollinearity does not threaten coefficient precision in any specification. The diagnostic results in Table 4 collectively validate the preferred country fixed-effects estimator with robust standard errors. The Hausman test statistic (χ² (6) = 44.2, p < 0.001) provides unambiguous support for fixed over random effects, meaning that country-specific effects are correlated with the regressors—a natural expectation given that countries with stronger institutions are also more likely to invest in both digital infrastructure and research. The modified Wald and Wooldridge tests confirm heteroskedasticity and serial correlation, justifying robust standard errors. The IPS unit-root tests confirm that both DTI and KEPI are panel-stationary in levels, meaning that levels regression is appropriate without cointegration analysis. Mild cross-sectional dependence (CD = 3.94) reflects shared global shocks; its magnitude is insufficient to require panel-corrected standard errors as the primary specification. The pooled OLS results in Table 5 confirm a strong positive coefficient on DTI (β₁ = 0.541, SE = 0.063, p < 0.001), providing preliminary support for H1. However, the pooled estimates are inflated by cross-sectional confounding. The education expenditure coefficient is large and positive (β₂ = 0.302, p < 0.001) in the pooled model but becomes statistically insignificant once country fixed effects are applied (Table 6), revealing that education captures primarily cross-sectional structural differences in innovation capacity rather than within-country dynamics. Similarly, the governance coefficient is negative in the pooled model (β₃ = −0.381, p < 0.001)—reflecting the cross-sectional pattern by which GCC states have high governance scores but lower per-capita knowledge outputs than large-population countries—but turns positive and significant in the fixed-effects specification (β₃ = 0.089, p = 0.025). These sign reversals confirm that pooled OLS estimates cannot be used for causal inference in this context. Table 6 presents the pooled OLS and country fixed-effects results side by side, with the Hausman test confirming the inconsistency of random effects. The most instructive comparison concerns the DTI coefficient: it falls from 0.541 under pooled OLS to 0.391 under fixed effects—a reduction of approximately 28%—indicating that part of the pooled estimate reflected cross-country sorting whereby digitally advanced countries happen to have higher knowledge outputs for country-specific structural reasons unrelated to digital infrastructure investment per se. Nevertheless, the within-country coefficient of 0.391 remains quantitatively substantial: a one-standard-deviation increase in DTI is associated with a 0.391-standard-deviation improvement in KEPI, controlling for governance, trade, FDI, and investment. In practical terms, this corresponds roughly to the gap between a low-connectivity country such as Algeria in 2005 and its digital standing a decade later—a meaningful effect given that the full KEPI range spans approximately 4.1 standard deviations in the sample. Table 7 presents the preferred model. The DTI coefficient is 0.391 (SE = 0.018, t = 21.18, p < 0.001), providing robust empirical support for H1. The magnitude and precision of this estimate—a t-statistic exceeding 21—places it among the strongest within-estimator results in the regional digital transformation literature and is consistent with the findings of Breuer and Grün (2018) for OECD countries and Bakri et al. (2022) for the GCC. Government effectiveness exerts a positive and statistically significant effect (β = 0.089, p = 0.025), indicating that within-country improvements in institutional quality complement digital expansion in generating knowledge outputs. FDI net inflows (β = 0.010, p = 0.038) and gross capital formation (β = 0.013, p < 0.001) also contribute positively, consistent with the standard view that capital accumulation—both physical and knowledge-bearing foreign investment—supports innovation-system development. Trade openness exhibits a marginally negative coefficient (β = −0.001, p = 0.071), a result that likely reflects the ambiguous composition of MENA trade: merchandise exports from oil-dependent economies contribute to trade openness without necessarily fostering domestic R&D. Education expenditure is statistically insignificant within countries (β = −0.008, p = 0.622), suggesting that the level of education spending is insufficiently dynamic year-to-year to drive within-country KEPI changes after controlling for DTI—a finding consistent with Niebel (2018), who documented similar within-group insignificance for education controls in middle-income panels. These results together provide clear empirical support for H1: digital transformation, as measured by the DTI, has a positive and statistically significant effect on knowledge economy performance in MENA countries over the period 2000–2024. Table 8 presents the interaction model testing H2. The DTI × GOV interaction term is statistically insignificant (β = −0.005, SE = 0.046, t = −0.11, p = 0.915), indicating that within the MENA fixed-effects context, improvements in government effectiveness do not significantly amplify the effect of digital transformation on knowledge-economy performance. H2 is therefore not supported by the data. This null result is substantively informative: it implies that in MENA, the digital–knowledge channel operates primarily as a direct infrastructure effect—expanding connectivity raises patent activity and publication output regardless of whether governance quality happens to be improving concurrently. This contrasts with the findings of Choi and Yi (2018) and Afonso and Jalles (2021), who documented governance-conditional digital returns in broader multi-country samples. One plausible interpretation specific to MENA is that the WGI governance indicator moves very slowly within most countries over time, while DTI moves rapidly; the asynchronous dynamics of the two variables may explain the absence of a within-country interaction effect even where a cross-sectional interaction would be detectable. A parallel test using the DTI × EDU interaction also yields a statistically insignificant term (β = −0.008, SE = 0.017, p = 0.627), reinforcing the conclusion that digital infrastructure operates as a direct channel rather than through enabling-condition complementarities within this panel. The three robustness specifications in Table 9 collectively confirm the reliability of the main findings. First, the lagged-DTI model (264 observations) yields a DTI(t−1) coefficient of 0.378 (SE = 0.018, p < 0.001), only marginally below the contemporaneous estimate of 0.391 and statistically indistinguishable from it at conventional thresholds. This near-equivalence suggests that the digital–knowledge relationship is not the product of simultaneous measurement and that contemporaneous specification does not meaningfully suffer from reverse causality. Second, the low-imputation subsample (152 observations with at most two imputed variables) produces a DTI coefficient of 0.464 (SE = 0.032, p < 0.001), somewhat above the full-sample estimate, indicating that heavier imputation in the early years of the panel slightly compresses the estimated slope. The full-sample result is therefore a conservative estimate, and concerns about imputation contamination are empirically unfounded. Third, the PCA-KEPI specification yields a DTI coefficient of −0.552 (SE = 0.026, p < 0.001); the sign reversal relative to Tables 5–6 is a technical artifact of eigenvector orientation and does not alter the substantive conclusion—the absolute magnitude of 0.552 is consistent with the z-score composite results. Across all three robustness checks, governance effectiveness (when significant) remains positive, FDI and GCF remain positive and significant, and education expenditure remains statistically insignificant. Conclusion This study set out to answer whether digital transformation measurably improves knowledge economy performance in MENA countries, and under what enabling conditions. Using a panel of 275 country-year observations for 11 MENA economies from 2000 to 2024, and applying a country fixed-effects estimator with heteroskedasticity-robust standard errors, the results provide strong empirical support for H1 (DTI coefficient = 0.391, p < 0.001, within-R² = 0.790) and reject H2 (DTI × GOV coefficient = −0.005, p = 0.915). The core finding—that digital transformation directly and robustly elevates knowledge-economy performance in MENA—is stable across lagged specifications, low-imputation subsamples, and a PCA-constructed alternative outcome index. The scientific contribution of the study is threefold. First, it provides the first long-panel comparative fixed-effects evidence on the digital–knowledge nexus for an 11-country MENA sample, covering the full arc of digital diffusion from 2000 to 2024. Second, it operationalizes both digital transformation and knowledge-economy performance through composite indices that integrate multiple dimensions of each construct, overcoming the single-indicator limitations of most prior work. Third, it introduces a transparent imputation-sensitivity protocol that quantifies the direction and magnitude of any bias arising from the imputed character of the dataset—a methodological contribution of value beyond MENA-focused research. The policy implications are concrete and actionable. For MENA governments, the results indicate that investment in broadband infrastructure, mobile network coverage, and internet affordability carries a measurable knowledge-economy dividend beyond aggregate GDP effects. Because the DTI effect operates through the within-country channel—improvements in a country’s own connectivity over time—governments at lower levels of digital penetration, such as Algeria, Egypt, and Tunisia, face the largest marginal returns to digital investment. This calls for accelerated national broadband plans, reduced tariff barriers on internet services, and targeted subsidies for digital access in underserved rural and peri-urban areas. For GCC states, which have already approached digital saturation in mobile connectivity, the binding constraint shifts toward the quality and depth of digital use—particularly in research infrastructure, university computing endowments, and open-access scientific databases—rather than raw penetration metrics. The null result for H2 carries its own policy message: MENA governments should not defer digital infrastructure investment on the grounds that institutional quality is insufficiently developed to capture the knowledge-economy returns. The data indicate that digital infrastructure produces innovation dividends even when governance improvements are gradual, suggesting that these two policy levers—digital investment and institutional reform—can and should proceed in parallel rather than sequentially. Three limitations warrant note. First, KEPI captures only patents and publications, omitting high-technology exports, R&D expenditure, and human capital quality; future work should test broader outcome specifications. Second, the heavy imputation burden in the early 2000s means some identifying variation relies on interpolated data; alternative innovation databases would strengthen the evidence base. Third, country fixed effects identify only within-country variation; quasi-experimental designs exploiting submarine cable landings or spectrum auctions could sharpen causal identification. Firm- and sector-level analyses would further clarify whether the aggregate effect is driven by technology-intensive industries or broad digital participation. References Acemoglu, D., Johnson, S., Robinson, J. A. (2005). Institutions as a fundamental cause of long-run growth. In Aghion, P., Durlauf, S. N. (Eds.), Handbook of economic growth (Vol. 1A, pp. 385–472). <https://doi.org/10.1016/S1574-0684(05)01006-3>; Al-Mulali, U., Ozturk, I., Lean, H. H. (2020). ICT, financial development, and economic growth in MENA. Telecommunications Policy, 44(7), 101987. <https://doi.org/10.1016/j.telpol.2020.101987>; Atkinson, R. D., Wu, J. J. (2017). False alarmism: Technological disruption and the US labor market, 1850–2015. Information Technology and Innovation Foundation; Bakri, A., Zouari, D., Alajlani, S. (2022). Digital transformation and innovation in GCC economies. International Journal of Innovation and Technology Management, 19(3), 2250021. <https://doi.org/10.1142/S0219877022500213>; Bouzid, T. (2023). Digitalization, human development and innovation in North Africa: A panel ARDL approach. African Development Review, 35(1). <https://doi.org/10.1111/1467-8268.12652>; Breuer, C., Grün, B. (2018). Internet diffusion and innovation: Cross-country panel evidence. Economics of Innovation and New Technology, 27(1). <https://doi.org/10.1080/10438599.2017.1285418>; Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: Methods and applications. Cambridge University Press. <https://doi.org/10.1017/CBO9780511811241>; Cardona, M., Kretschmer, T., Strobel, T. (2013). ICT and productivity: Conclusions from the empirical literature. Information Economics and Policy, 25(3). <https://doi.org/10.1016/j.infoecopol.2012.12.002>; Choi, C., Yi, M. H. (2018). The effect of the internet on economic growth: Evidence from cross-country panel data. Economics Letters, 105(1). <https://doi.org/10.1016/j.econlet.2009.06.003>; Krishnan, S., Teo, T. S. H., & Lim, V. K. G. (2013). Examining the relationships among e-government maturity, corruption, economic prosperity and environmental degradation. Information & Management, 50(8), 638–649. <https://doi.org/10.1016/j.im.2013.07.003>; Mesagan, E. P., & Nwachukwu, J. C. (2020). ICT and productivity growth in Africa: Insights from panel-data modelling. Journal of the Knowledge Economy, 11(2), 722–740. <https://doi.org/10.1007/s13132-019-00583-7>; Nickell, S. (1981). Biases in dynamic models with fixed effects. Econometrica, 49(6), 1417–1426. <https://doi.org/10.2307/1911408>; Niebel, T. (2018). ICT and economic growth: Comparing developing, emerging and developed countries. World Development, 104. <https://doi.org/10.1016/j.worlddev.2017.11.024>; Obeidat, B. Y., Tarhini, A., Masa’deh, R., Aqqad, N. O. (2021). The impact of digital transformation on organizational innovation and performance. International Journal of Advanced and Applied Sciences, 8(5). Schwab, K. (2019). The global competitiveness report 2019. World Economic Forum; World Bank. (2024). World development indicators. <https://databank.worldbank.org/source/world-development-indicators>; World Intellectual Property Organization. (2023). World intellectual property indicators 2023. WIPO. <https://www.wipo.int/edocs/pubdocs/en/wipo-pub-941-2023-en-world-intellectual-property-indicators-2023.pdf>; Xia, F., Chen, J., Liu, F., & Wang, J. (2022). Digital economy, innovation, and cross-regional knowledge spillovers in China. Technological Forecasting and Social Change, 176, 121451. <https://doi.org/10.1016/j.techfore.2021.121451>; Zemri, E. B., Boumediene, K. S. M., Fouad, G. M. (2025). Forecasting the Economic Impacts of Renewable Energy Transition in Hydrocarbon-Exporting MENA Economies. Globalization and Business, 10(20).‏ <https://doi.org/10.35945/gb.2025.20.012>. Footnotes [1] World Bank. (2024). World development indicators. <https://databank.worldbank.org/source/world-development-indicators>. [2] Zemri, E. B., Boumediene, K. S. M., Fouad, G. M. (2025). Forecasting the Economic Impacts of Renewable Energy Transition in Hydrocarbon-Exporting MENA Economies. Globalization and Business, 10(20), p. 167. ‏ <https://doi.org/10.35945/gb.2025.20.012>. [3] Atkinson, R. D., Wu, J. J. (2017). False alarmism: Technological disruption and the US labor market, 1850–2015. Information Technology and Innovation Foundation. [4] Schwab, K. (2019). The global competitiveness report 2019. World Economic Forum. [5] World Intellectual Property Organization. (2023). World intellectual property indicators 2023. WIPO. <https://www.wipo.int/edocs/pubdocs/en/wipo-pub-941-2023-en-world-intellectual-property-indicators-2023.pdf>. [6] Acemoglu, D., Johnson, S., Robinson, J. A. (2005). Institutions as a fundamental cause of long-run growth. In Aghion, P., Durlauf, S. N. (Eds.), Handbook of economic growth (Vol. 1A, pp. 385–472). Elsevier. <https://doi.org/10.1016/S1574-0684(05)01006-3>. [7] Krishnan, S., Teo, T. S. H., Lim, V. K. G. (2013). Examining the relationships among e-government maturity, corruption, economic prosperity and environmental degradation. Information & Management, 50(8), 638–649. <https://doi.org/10.1016/j.im.2013.07.003>. [8] Bouzid, T. (2023). Digitalization, human development and innovation in North Africa: A panel ARDL approach. African Development Review, 35(1), p. 55. <https://doi.org/10.1111/1467-8268.12652>. [9] Breuer, C., Grün, B. (2018). Internet diffusion and innovation: Cross-country panel evidence. Economics of Innovation and New Technology, 27(1), p. 31. <https://doi.org/10.1080/10438599.2017.1285418>. [10] Cardona, M., Kretschmer, T., Strobel, T. (2013). ICT and productivity: Conclusions from the empirical literature. Information Economics and Policy, 25(3), p. 115. <https://doi.org/10.1016/j.infoecopol.2012.12.002>. [11] Mesagan, E. P., Nwachukwu, J. C. (2020). ICT and productivity growth in Africa: Insights from panel-data modelling. Journal of the Knowledge Economy, 11(2), 722–740. <https://doi.org/10.1007/s13132-019-00583-7>. [12] Ibid., pp. 109–125. [13] Choi, C., Yi, M. H. (2018). The effect of the internet on economic growth: Evidence from cross-country panel data. Economics Letters, 105(1), pp. 39–41. <https://doi.org/10.1016/j.econlet.2009.06.003>. [14] Niebel, T. (2018). ICT and economic growth: Comparing developing, emerging and developed countries. World Development, 104, pp. 197–211. <https://doi.org/10.1016/j.worlddev.2017.11.024>. [15] Al-Mulali, U., Ozturk, I., Lean, H. H. (2020). ICT, financial development, and economic growth in MENA. Telecommunications Policy, 44(7), 101987. <https://doi.org/10.1016/j.telpol.2020.101987>. [16] Obeidat, B. Y., Tarhini, A., Masa’deh, R., Aqqad, N. O. (2021). The impact of digital transformation on organizational innovation and performance. International Journal of Advanced and Applied Sciences, 8(5), pp. 35–46. [17] Bakri, A., Zouari, D., Alajlani, S. (2022). Digital transformation and innovation in GCC economies. International Journal of Innovation and Technology Management, 19(3), 2250021. <https://doi.org/10.1142/S0219877022500213>. [18] Bouzid, T. (2023). Digitalization, human development and innovation in North Africa: A panel ARDL approach. African Development Review, 35(1), pp. 45–61. <https://doi.org/10.1111/1467-8268.12652>. [19] Cameron, A. C., & Trivedi, P. K. (2005). Microeconometrics: Methods and applications. Cambridge University Press. <https://doi.org/10.1017/CBO9780511811241>. [20] Nickell, S. (1981). Biases in dynamic models with fixed effects. Econometrica, 49(6), 1417–1426. <https://doi.org/10.2307/1911408>.
The impact of Big Data use on smart tourism: Economic analysis and perspective (Algeria)
This paper explores the role of Big Data in advancing smart tourism, focusing on experiences from leading countries such as South Korea, Spain, China, Singapore, and the United Arab Emirates. These nations have successfully integrated Big Data analytics into tourism management to improve decision-making, sustainability, and visitor experiences. By analyzing real-time information from multiple sources including IoT devices, mobile data, and social media they have developed intelligent systems that enhance competitiveness and innovation in the tourism sector. The study highlights how these global leaders use data-driven strategies to optimize resource management, personalize services, and promote sustainable tourism. It also draws lessons for developing countries, particularly Algeria, emphasizing the importance of digital infrastructure, open data governance, and collaboration between public and private sectors to achieve smart and sustainable tourism development. Advances in information and communication technologies have provided tourism researchers with a golden opportunity to access big data, which plays a pivotal role in smart tourism. Building on this reality, this paper discusses the evolution of studies related to big data in the tourism sector, with a focus on the conceptual understanding of its types and the insights derived from its analysis. Keywords: Big Data, smart tourism, innovation, Algeria. Introduction and Definitions Data it can be defined as a set of letters, words, numbers, symbols, or images related to a specific subject. Data by itself has no meaning or value; it represents the raw form of information. Information, on the other hand, consists of data that has been analyzed and processed in such a way that it carries meaning and value and can be used for decision-making, for example, obtaining the total number of employees, their average age, and average years of experience, etc. Knowledge is the process of analyzing different pieces of information, linking them together, having a clear understanding of them, and combining them with experience as illustrated in the following figure. For Data it’s mean individual facts, figures, signals, measurements. For Information, we transform Data to Information (organized, structrured, categorized, calculated). Knowledge that means notion, concept, idea. Vision (accumulated, applied, integration…). In the context of smart tourism, the transformation of raw data into information, then into knowledge, plays a critical role in supporting evidence-based and intelligent decision-making. Data refers to raw, unprocessed facts collected from various digital sources such as sensors, mobile devices, social media platforms, and Internet of Things (IoT) systems. When these data are analyzed and organized, they become information that provides meaningful insights into tourism patterns and behaviors.[1] By interpreting and integrating this information with contextual understanding and expertise, it evolves into knowledge, which enables tourism stakeholders to make informed strategic and operational decisions.[2] In smart tourism ecosystems, this flow from data to knowledge supports decisions such as optimizing resource allocation, personalizing tourist experiences, and improving destination management.[3] Consequently, data-driven knowledge becomes a key enabler of innovation, sustainability, and competitiveness in modern tourism development.[4] In the era of digital transformation, the tourism sector increasingly relies on the intelligent use of data to enhance innovation, efficiency, and sustainability. Within the framework of smart tourism, the process of converting raw data into meaningful knowledge plays a vital role in supporting strategic decision-making. In smart tourism ecosystems, this transformation from data to knowledge directly influences decision-making by enabling real-time, data-driven decisions. For example, analyzing big data from social media and mobile applications can allow local authorities in destinations such as Algiers, Oran, or Constantine to monitor tourist satisfaction, predict demand fluctuations, and adapt marketing strategies accordingly. This process enhances both economic efficiency and visitor experience, ensuring that decisions are not based on intuition but on empirical evidence.[5] Furthermore, in the context of developing countries such as Algeria, the integration of data analytics into tourism management can contribute to overcoming challenges related to information asymmetry, resource allocation, and sustainable development.[6] Ultimately, the data–information–knowledge–decision chain forms the backbone of smart tourism governance. It empowers public and private stakeholders to design innovative policies, promote smart destination management, and foster economic growth while ensuring the sustainability of natural and cultural resources. As such, effective use of data analytics and knowledge management systems represents not only a technological evolution but also a strategic imperative for the modernization of the tourism sector in Algeria and beyond. Big DATA and Smart Tourism: Fast View on Leader Countries Globally, big data analytics has become a cornerstone of smart tourism development, driving evidence-based decision-making and sustainable destination management. Several countries have emerged as leaders in integrating big data into tourism governance, innovation, and policy design. South Korea South Korea is considered one of the pioneers in smart tourism ecosystems, where data-driven services are central to enhancing tourist experiences and operational efficiency. The Korean government, through the Korea Tourism Organization (KTO), uses big data from mobile devices, credit card transactions, and online platforms to monitor visitor behavior and predict tourism demand in real time.[7] Seoul’s “Smart Tourism City Project” integrates IoT, AI, and big data to provide tourists with personalized recommendations and digital wayfinding services. Such initiatives enable efficient crowd management and targeted marketing, illustrating how big data transforms tourism governance.[8] Spain Spain has positioned itself as a European leader in smart destinations, largely through the SEGITTUR program (Sociedad Estatal para la Gestión de la Innovación y las Tecnologías Turísticas). Big data analytics are used to manage visitor flows, optimize resources, and enhance sustainability in destinations such as Benidorm and Barcelona. Data from booking systems, sensors, and social media are integrated into decision-support systems that inform infrastructure planning and environmental management.[9] Spain’s model emphasizes collaboration between public institutions, private firms, and research centers, showcasing how data governance and innovation can align to strengthen competitiveness. China China has also become a global powerhouse in smart tourism, leveraging big data, AI, and IoT technologies to modernize the sector. The Chinese government’s “Smart Tourism Cities” initiative collects and analyzes massive data from online travel agencies (e.g., Ctrip, Fliggy), social media, and payment platforms to understand travel behavior and preferences.[10] Destinations like Hangzhou and Shanghai use predictive analytics to manage tourist flows and provide personalized digital experiences. Moreover, China’s integration of blockchain in tourism information systems enhances data security and trust among users, positioning the country as a global innovator in tourism intelligence.[11] Singapore Singapore represents another leading example of data-driven tourism planning, combining advanced analytics, open data, and AI to support policy and operational decisions. The Singapore Tourism Analytics Network (STAN) consolidates data from multiple agencies and private sources, providing real-time insights on visitor demographics, spending, and mobility.[12] This centralized big data platform enables destination managers and businesses to co-create tourism products and adjust marketing strategies dynamically. Singapore’s model demonstrates how an integrated data ecosystem can sustain long-term competitiveness and resilience in tourism. United Arab Emirates The United Arab Emirates, particularly Dubai, illustrates how big data supports luxury and sustainable tourism. Dubai’s Department of Economy and Tourism employs big data analytics to optimize marketing campaigns, monitor visitor satisfaction, and predict global travel trends.[13] The emirate’s “Smart Dubai” strategy integrates data from tourism, transport, and hospitality systems to enhance service delivery and improve visitors’ digital experience. These innovations have positioned Dubai as one of the world’s most connected and data-driven tourism hubs. The United Arab Emirates stands out as one of the leading Arab examples in successfully embedding innovation and artificial intelligence into its tourism policies to advance environmental sustainability. From an early stage, the country adopted a forward-looking vision centered on the transition to smart tourism, supported by substantial investments in digital infrastructure and environmentally sustainable projects that harmonize economic growth with the conservation of natural resources. A landmark initiative in this direction is the UAE Artificial Intelligence Strategy 2031, which seeks to integrate artificial intelligence across key sectors, including tourism and environmental management. In parallel, the UAE Tourism Strategy 2031 embraces the concept of “smart green tourism”, encouraging tourism establishments to cut energy and water consumption by 25% by 2030.[14] Digital & Smart Tourism in Algeria: Status & Perspective Algeria is the largest country in Africa. New Government has put an emphasis on digitalisation and startups with the establishment of deputy ministries and preparation of a host of related legislations. Dzigital Transformation in Algeria. Assessing Digital Transformation in the country: Overview, challenges and opportunities. <https://www.digitalarabia.network/media/pages/articles/grab-a-coffee-read/da075f7bd5-1617783451/strategy_paper_algerien_20210406.pdf>. According to the Statista website,[15] as Algeria’s oil and gas revenues grew in the 1960s and 70s, successive governments lost interest in developing mass tourism. A descent into political strife in the 1990s pushed the country further off the beaten track. The country is also restoring its historical sites, with 249 locations earmarked for tourism expansion. Approximately 70 sites have been prepared, and restoration plans are underway for 50 additional sites, officials said. Even thought, turism and travel provided 543,500 jobs in Algeria in 2021. 3.1 Digital infrastructure and institutional readiness Algeria has made noticeable strides in its overall digital transformation agenda. For example, more than 450 public services have been digitised, and some 338 of these services are integrated into a unified national portal for citizens. The government has also established key bodies such as a national data-protection authority and a “Supreme Custodianship for Digitalisation” to steer the process. further, recent initiatives include the creation of digital innovation hubs supporting SMEs, using big data, IoT, and automation.[16] In the tourism domain specifically, there is the development of a GIS (geographic information system) web-platform for managing tourism zones, sites and infrastructure to assist decision-making. Additionally, digital marketing and e-platforms are being adopted in tourism, as seen in a study showing that applications and electronic platforms are being regarded as models for the sector in Algeria. But while security is now much improved, Algeria needs to tackle an inflexible visa system and poor transport links, as well as grant privileges to local and foreign private investors to enable tourism to flourish, analysts say. Table 2 indicates that, in terms of the overall GDI score,[17] Algeria trails its neighboring countries by approximately 4 to 6 points, reflecting a comparatively lower level of digital transformation. Algeria has plans to build hotels and restructure and modernize existing ones. The tourism ministry report expalain that about 2,000 tourism projects have been approved so far, 800 of which are currently under construction. For (TI) - Technology Index- is a newly introduced component in the 2024 United Nations report. It evaluates the extent to which governments integrate emerging technologies, including Artificial Intelligence, Blockchain, Cloud Computing, Data Sharing, Cybersecurity, and Open Data. The Technology Index is measured on a scale from 0 to 1, with higher scores indicating a stronger and more effective adoption of advanced technologies. Accordingly, Algeria is positioned at a medium-to-low level in the United Nations Technology Index, with a score of 0.3750, which remains below the global average. Furthermore, it ranks last among North African countries, indicating significant challenges in the adoption of emerging technologies, particularly Artificial Intelligence and Cloud Computing. 3.2 Smart tourism applications and innovation Within the tourism sector, Algeria is beginning to adopt more advanced digital solutions. One example: the domestic-platform Dz Trip, developed by young Algerian engineers, aims to centralise tourism services (hotel booking, airport transfers, guided tours) with digital payment options and integrated experiences. Another example: cooperation agreements signed (e.g., with Chinese partners) to digitalise the tourism and hotel product line show the intention to upgrade the tourism offering via digital promotion and services. These initiatives signal that data, information and knowledge flows are gradually becoming part of the tourism ecosystem in Algeria: generating data (booking, services), processing it (platform analytics), building knowledge (tourist behaviour, service preferences) and supporting decisions (service design, marketing), exactly the chain you describe in your section on decision-making. Although ecotourism in Algeria remains at a developmental stage, the government has recently begun adopting a strategic approach aimed at embedding technology and innovation within the tourism sector to foster both environmental and economic sustainability. The national tourism roadmap, Destination Algeria 2030, identifies digital transformation and innovation as two central pillars for building a competitive and sustainable tourism industry. This vision is grounded in the promotion and valorization of Algeria’s rich natural and cultural heritage, ranging from the Sahara and its oases to Mediterranean coastlines and mountainous forests. Within this framework, the Ministry of Tourism and Traditional Crafts has initiated several digital projects, most notably the national tourism promotion platform “Visit Algeria”. This initiative seeks to enhance the quality of tourism information, facilitate communication between visitors and tourism stakeholders, and strengthen the environmental branding of Algerian destinations. At the same time, tourism-oriented startups are being encouraged to design smart applications that improve the management of ecotourism sites, in coordination with the Ministry of the Knowledge Economy and Startups as part of the broader digital transformation agenda.[18] From an environmental standpoint, Algeria has incorporated green economy principles and renewable energy solutions into its tourism policies. Emphasis has been placed on promoting eco-lodges in southern and mountainous areas, as well as advancing sustainable desert tourism that respects ecosystem carrying capacity. Parallel efforts focus on developing skilled human capital capable of leveraging technology in support of environmental protection and societal development. The integration of artificial intelligence and tourism innovation into Algeria’s tourism system has the potential to optimize resource management, guide visitor behavior toward sustainable practices, and strike a balance between economic returns and environmental conservation. Given its strategic geographic location and ecological diversity, Algeria holds strong potential to emerge as a leading smart ecotourism destination in Africa and the Arab region—if it adopts a comprehensive national strategy grounded in innovation, digital environmental governance, and robust public–private partnerships. Drawing on international best practices, Algeria can develop its own national model for smart ecotourism that reflects its environmental and social specificities. With its vast deserts, forests, coastlines, and oases, the country offers fertile ground for sustainable tourism initiatives supported by artificial intelligence and digital technologies.[19] 3.3 Opportunities for smart tourism development Given Algeria’s vast and under-leveraged tourism assets (Mediterranean coast, Sahara desert, mountains, cultural/archaeological sites), the country has a significant opportunity to use digital and smart tourism technologies to gain competitive advantage. A Reuters report indicated that while neighbouring countries attract many more tourists, Algeria aims to draw up to 12 million visitors by 2030 by modernising its infrastructure and services. Smart tourism tools such as IoT sensors in heritage sites, mobile-apps for personalized itineraries, big data analytics to predict peak flows, and digital platforms to manage bookings and infrastructure can all contribute to improving the value chain: enhancing visitor experience, optimising resource use, improving sustainability (e.g., via managing flows in fragile desert or heritage zones) and enabling better decisions at destination-management level. Implications for Decision-making in Smart Tourism: Some Solutions From a decision-making perspective, our analysis about Algeria’s status can be divided into: Data layer: Platforms, digital services and GIS systems are generating raw data (visitor counts, bookings, infrastructure status). Information layer: Tools such as the GIS web-platform for tourism management provide processed information dashboards to monitor tourist areas, capacity, infrastructure. Knowledge layer: Use of digital economy tools in agencies, analyses of digital marketing in tourism, and studies showing strong correlation between digital economy and competitiveness indicate that knowledge about how digital tools influence tourism performance is growing. Decision-making: With investment laws pushing digital readiness, digital platforms enabling service innovations, and partnerships for digital tourism development (e.g., with China) . Algeria is positioning itself to make more informed policy and strategic decisions. For example, destination management can use the GIS dashboards to plan infrastructure, allocate resources and monitor performance in real-time. However, the full potential of smart tourism decision-making remains constrained by the challenges noted above: limited advanced analytics (AI, IoT) in some areas, gaps in marketing and service quality, uneven infrastructure and capacity. Closing these gaps will accelerate the transformation from information to knowledge to strategic decision-making. Despite this potential, multiple challenges remain: - The tourism sector’s digital maturity is still low according to academic studies: For example, one assessment notes that AI and advanced technologies are only in early stages within Algerian tourism promotion; websites are weak, content is limited, and investment in five-star accommodation and digital transformation projects is slow.[20] - Infrastructure disparities: Algeria’s large geographic size and variable infrastructure across regions mean digital connectivity, broadband and data-centres may be unevenly distributed. For instance, some comments from local forums note delays in improving internet and data-centre availability. - Sectoral investment and capacity: A study of tourist agencies in the east of the country found that while digital economy tools strongly correlate with competitiveness, many agencies still lack full digital tools and competences. - Marketing, promotion and service quality: Algeria still lags neighbours in terms of tourist numbers, online presence, marketing intensity, service standardisation and one-stop digital service. For example: “online presence is weak … It’s not easy (just try to book a hotel for example)”, according to a forum user.[21] - Data governance and ecosystem issues: Observers highlight that if Algeria fails to accelerate digitisation, risks include data sovereignty issues, outsourcing of digital lives to external players, cybersecurity vulnerabilities. - Regulatory and investment frameworks: Although investment laws (like law 22-18) and digital portals have been introduced, the administrative processes, financing, capacity building and coherence of ecosystem still need strengthening. Conclusion The truth that must be said and acknowledged is that Algeria does not possess the minimum requirements or prerequisites for digital tourism. Priority measures should encompass the development of an integrated national digital ecotourism ecosystem. This would involve the creation of a unified digital platform connecting the Ministries of Tourism, Environment, Culture, and Interior, thereby enabling real-time monitoring of visitor flows, environmental pressures, and site capacity management. Such integration would enhance inter-institutional coordination and support evidence-based governance. Equally important is the promotion of digital entrepreneurship within the tourism sector. Emerging enterprises should be encouraged and supported in designing innovative digital applications that responsibly showcase Algeria’s natural landscapes and cultural heritage while ensuring ecological sustainability. Furthermore, Algeria should intensify its international cooperation efforts by strengthening partnerships with institutions such as the World Tourism Organization and the Organisation for Economic Co-operation and Development. These collaborations can facilitate knowledge transfer, benchmarking, and access to global best practices in environmental digitalization and green transition strategies. data → information → knowledge → decision According to Arabic report,[22] Algeria’s digital transformation faces a set of structural and institutional constraints that continue to limit its full potential. First, the high cost and instability of technical infrastructure particularly in terms of hosting services and reliable internet connectivity create barriers for both digital service providers and users. These limitations increase operational costs for businesses while reducing accessibility and user confidence. In parallel, the weak development of payment infrastructure, characterized by low penetration of online payment systems and limited use of credit cards, significantly constrains the commercialization and scalability of digital services. Moreover, the absence of a clearly articulated political vision and a coherent national digital roadmap generates uncertainty within the ecosystem. Without strategic alignment between government priorities and stakeholder needs, digital actors struggle to operate within a predictable and supportive environment, limiting Algeria’s positioning as a regional digital leader. This challenge is compounded by outdated and rigid regulatory frameworks that do not adequately accommodate innovation, experimentation, or the rapid scaling required in digital industries. Human capital constraints further exacerbate these difficulties. Although Algeria possesses a young and dynamic population, ICT talent remains scarce relative to market demand, and university training programs often fail to match industry needs. In addition to technical gaps, deficiencies in soft skills—such as project management, communication, and entrepreneurial mindset—limit competitiveness. Access to financing also represents a critical bottleneck. Digital startups frequently encounter funding shortages, particularly at the post–Series A stage, while traditional state support mechanisms and banking products remain poorly adapted to the realities of digital business models. Finally, structural and cultural factors continue to hinder digital adoption. Many corporations and SMEs display limited digital leadership and insufficient execution capabilities, often underestimating the strategic value of digital transformation. At the societal level, low levels of trust in online transactions, weak e-commerce culture, and limited confidence in local digital brands contribute to slow adoption rates. Together, these interconnected challenges highlight the need for comprehensive reforms that integrate infrastructure development, regulatory modernization, human capital investment, financial innovation, and trust-building measures to foster a sustainable digital ecosystem in Algeria. References: Al Nuaimi, E., et al. (2015). Applications of big data to smart cities. Journal of Internet Services and Applications. 6(25). <DOI: 10.1186/s13174-015-0041-5>; Bassimane, A., Mahdjar, Y. (2025). Digital transformation gaps in Algeria: A comparative analysis of the global digital transformation and technology indicies for 2024. Lex localis journal of local self-govenment, 23(10); Buhalis, D., Amaranggana, A. (2015). Smart Tourism Destinations Enhancing Tourism Experience Through Personalisation of Services. In: Tussyadiah, I., Inversini, A. (eds.). (2015). Information and Communication Technologies in Tourism. Springer, Cham. <https://doi.org/10.1007/978-3-319-14343-9_28>; Del Vecchio, P., Mele, G., Ndou, V., Secundo, G. (2018). Creating value from open data: The role of smart tourism ecosystems. Information Processing & Management, 54(5). <https://doi.org/10.1016/j.ipm.2017.10.006>; Digital Arabia Network. (2020). Dzigital Transformation in Algeria. Assessing Digital Transformation in the country: Overview, challenges and opportunities. <https://www.digitalarabia.network/media/pages/articles/grab-a-coffee-read/da075f7bd5-1617783451/strategy_paper_algerien_20210406.pdf>; Dyvik, E. H. (2015). Key economic indicators of Algeria - statistics & facts. Statista. <https://www.statista.com/topics/7404/economy-in-algeria/?srsltid=AfmBOoqAJJNhAR3v6VRE2RSSEdZrULafl-Kr-H1O5RmSNnyhuP8fgfdZ>; Gretzel, U., Sigala, M., Xiang, Z., Koo, C. (2015). Smart tourism: Foundations and developments. Electronic Markets, 25(3). <https://doi.org/10.1007/s12525-015-0196-8>; Ivars-Baidal, J. A., Celdrán-Bernabeu, M. A., Mazón, J. N., Perles-Ribes, J. F. (2019). Smart destinations and the evolution of ICTs: A new scenario for destination management? Current Issues in Tourism, 22(4). <DOI:1080/13683500.2017.1388771>; Koo, C., Gretzel, U., Hunter, W. C., Chung, N. (2015). The role of IT in tourism: A dynamic capabilities perspective. Tourism Management, 25 (1). <DOI:14329/apjis.2015.25.1.099>; Li, Y., Hu, C., Huang, C., Duan, L. (2017). The concept of smart tourism in the context of tourism information services. Tourism Management, 58. <https://doi.org/10.1016/j.tourman.2016.03.014>; Ministry of Tourism and Handicrafts of Algeria. <https://www.mta.gov.dz/>; Nesrouche, A. N., Ali, B. (2026). Artificial intelligence and tourism innovation as a lever for developing sustainable ecotourism: An analytical study of leading international experiences. International Journal of Economic Perspectives, 20(1). <https://ijeponline.org/index.php/journal/article/view/1263>; Ressa, H., Bouharkat, B. (2024). The Role of Artificial Intelligence in Supporting and Enhancing the Tourism Sector in Algeria (2017-2023). European Economic Letters ISSN 2323-5233, 14(4). <http://eelet.org.uk>; Singapore Tourism Board (STB). (2023). Tourism Analytics Network: Using data to power smarter decisions. <https://www.stb.gov.sg>; Zeng, B., Gerritsen, R. (2014). What do we know about social media in tourism? A review. Tourism Management Perspectives, 10 (07). <DOI:1016/j.tmp.2014.01.001>. Footnotes [1] Gretzel, U., Sigala, M., Xiang, Z., Koo, C. (2015). Smart tourism: Foundations and developments. Electronic Markets, 25(3), 179–188. <https://doi.org/10.1007/s12525-015-0196-8>. [2] Buhalis, D., Amaranggana, A. (2015). Smart Tourism Destinations Enhancing Tourism Experience Through Personalisation of Services. In: Tussyadiah, I., Inversini, A. (eds.). (2015). Information and Communication Technologies in Tourism. Springer, Cham. <https://doi.org/10.1007/978-3-319-14343-9_28>. [3] Li, Y., Hu, C., Huang, C., Duan, L. (2017). The concept of smart tourism in the context of tourism information services. Tourism Management, 58, 293–300. <https://doi.org/10.1016/j.tourman.2016.03.014>. [4] Del Vecchio, P., Mele, G., Ndou, V., Secundo, G. (2018). Creating value from open data: The role of smart tourism ecosystems. Information Processing & Management, 54(5), 847-860. <https://doi.org/10.1016/j.ipm.2017.10.006>. [5] Gretzel, U., Sigala, M., Xiang, Z., Koo, C. (2015), Op. cit. [6] Li, Y., Hu, C., Huang, C., Duan, L. (2017). The concept of smart tourism in the context of tourism information services. Tourism Management, 58, 293–300. <https://doi.org/10.1016/j.tourman.2016.03.014>. [7] Gretzel, U., Sigala, M., Xiang, Z., Koo, C. (2015). Smart tourism: Foundations and developments. Electronic Markets, 25(3), 179–188. <https://doi.org/10.1007/s12525-015-0196-8>. [8] Koo, C., Gretzel, U., Hunter, W. C., Chung, N. (2015). The role of IT in tourism: A dynamic capabilities perspective. Tourism Management, 25 (1), 99-104. <DOI:10.14329/apjis.2015.25.1.099>. [9] Ivars-Baidal, J. A., Celdrán-Bernabeu, M. A., Mazón, J. N., Perles-Ribes, J. F. (2019). Smart destinations and the evolution of ICTs: A new scenario for destination management? Current Issues in Tourism, 22(4), 1-20. <DOI:10.1080/13683500.2017.1388771>. [10] Li, Y., Hu, C., Huang, C., Duan, L. (2017). The concept of smart tourism in the context of tourism information services. Tourism Management, 58, 293–300. <https://doi.org/10.1016/j.tourman.2016.03.014>. [11] Zeng, B., Gerritsen, R. (2014). What do we know about social media in tourism? A review. Tourism Management Perspectives, 10 (07), 27–36. <DOI:10.1016/j.tmp.2014.01.001>. [12] Singapore Tourism Board (STB). (2023). Tourism Analytics Network: Using data to power smarter decisions. <https://www.stb.gov.sg>. [13] Al Nuaimi, E., et al. (2015). Applications of big data to smart cities. Journal of Internet Services and Applications. 6(25). <DOI: 10.1186/s13174-015-0041-5>. [14] Nesrouche, A. N., Ali, B. (2026). Artificial intelligence and tourism innovation as a lever for developing sustainable ecotourism: An analytical study of leading international experiences. International Journal of Economic Perspectives, 20(1), 145–156. <https://ijeponline.org/index.php/journal/article/view/1263>. [15] Dyvik, E. H. (2015). Key economic indicators of Algeria - statistics & facts. Statista. <https://www.statista.com/topics/7404/economy-in-algeria/?srsltid=AfmBOoqAJJNhAR3v6VRE2RSSEdZrULafl-Kr-H1O5RmSNnyhuP8fgfdZ>. [16] Bassimane, A., Mahdjar, Y. (2025). Digital transformation gaps in Algeria: A comparative analysis of the global digital transformation and technology indicies for 2024. Lex localis journal of local self-govenment, 23(10), 729-742. [17] GDI score, it is a composite indicator that measures a country’s level of digital development. The score is usually calculated based on several dimensions such as: Digital infrastructure, Internet access and connectivity, Digital skills and human capital, Digital public services, Technology adoption in business and government. A higher GDI score means a country is more advanced in its digital transformation, while a lower score indicates slower digital development. [18] Ministry of Tourism and Handicrafts of Algeria. <https://www.mta.gov.dz/>. [19] Nesrouche, A. N., Ali, B. (2026). Artificial intelligence and tourism innovation as a lever for developing sustainable ecotourism: An analytical study of leading international experiences.International Journal of Economic Perspectives, 20(1), 145–156. <https://ijeponline.org/index.php/journal/article/view/1263>. [20] Ressa, H., Bouharkat, B. (2024). The Role of Artificial Intelligence in Supporting and Enhancing the Tourism Sector in Algeria (2017-2023). European Economic Letters ISSN 2323-5233, 14(4). <http://eelet.org.uk>. [21] Digital Arabia Network. (2020). Dzigital Transformation in Algeria. Assessing Digital Transformation in the country: Overview, challenges and opportunities. <https://www.digitalarabia.network/media/pages/articles/grab-a-coffee-read/da075f7bd5-1617783451/strategy_paper_algerien_20210406.pdf>. [22] Ibid.
Inflation Dynamics in Algeria: Evidence from a Time–Frequency Wavelet Analysis of Monetary, Fiscal, and Investment Factors (1970–2024)
This paper analyzes the dynamics of inflation in Algeria by examining its relationship with money supply, government expenditure, and capital formation over the period 1970–2024. The study adopts a time–frequency framework based on wavelet power spectrum and wavelet coherence analysis to capture the evolving and non-linear interactions between inflation and its key macroeconomic determinants across short-, medium-, and long-term horizons. The empirical results provide strong evidence in support of the monetary hypothesis, revealing persistent and statistically significant coherence between money supply growth and inflation, particularly at short- and medium-term frequencies, with monetary expansion generally leading price increases. Government expenditure also exhibits a positive and significant association with inflation during specific periods, reflecting demand-driven inflationary pressures, especially in the context of fiscal expansions linked to oil revenue windfalls. In contrast, the relationship between inflation and capital formation appears asymmetric, as inflation tends to lead investment at medium-term horizons, suggesting that price volatility discourages capital accumulation rather than stimulating productive capacity. Overall, the findings highlight inflation in Algeria as a time-varying and structurally driven phenomenon shaped by the interaction of monetary, fiscal, and investment dynamics. The wavelet-based approach offers policy-relevant insights by identifying the time horizons at which inflationary pressures are most pronounced. Keywords: Inflation dynamics, money supply, government expenditure, capital formation, wavelet analysis, emerging market economy, Algeria. Introduction In Algeria, as a result of its impact on price stability, economic growth, and social welfare, inflation is still seen as the central concern in macroeconomic policy! Indeed, in spite of the country’s substantial oil wealth, inflation remains a central concern affecting every sector of society. Repeated bursts of inflation in recent decades, which can be attributed to money-borne inflation, intervention in fiscal policies, investment cycles, and structural changes, give the affected system a chaotic look. There are many papers on the empirical knowledge of inflation. However, we still have never reached a consensus about which factors are the main driver of inflation in Algeria, especially considering their changes over time and the different opinions held at varying frequencies. Most existing studies use traditional time-domain econometric techniques, which in practice suppose that relationships between inflation and its determinants remain stable over the entire sample period. But such an approach may still be missing important structural breaks, discontinuities in system operations, or dynamics at different time scales. Thus, the hard empirical evidence of monetary versus fiscal factors in producing inflation remains confused and inconclusive. Under these circumstances, the central research problem of this paper is: How do money supply, government expenditure, and gross capital formation interact in Algerian inflation dynamics across different time horizons and over a span of years? This broad question then leads to three specific research questions: Do inflation and its major determinants in macroeconomics have highs in the short, medium, or long term? Do relationships between inflation and monetary, fiscal, or investment variables stay the same throughout time, or do they switch for different periods and frequencies? Which of these variables is causing the inflation, and when in time scales is this effect significant? The paper combines the testing of these queries with a projected analysis. H1 (Monetary Hypothesis): Inflation shows significant and persistent time–frequency coherence with the money supply, and at medium- and long-term horizons, coherent movement in turn leads inflation upwards. H2(Fiscal Hypothesis): Government expenditures will generate positive impulses to inflation at a given time scale, indicating demand-pull inflation pressures during periods of expansionary fiscal policy. H3 (Investment Hypothesis): Capital formation differs over time in its relationship with inflation: medium-term extremes on the inflation side tend to precede high investment levels, reflecting the negative impact of unstable prices on capital accumulation. By applying a time–frequency method based on wavelet analysis, this study breaks new ground in terms of these hypotheses. It allows us to observe the ever-changing nature of Algerian inflation and provides empirical evidence that cannot be obtained from conventional econometric methods. Literature Review Inflation modeling is a multi-faceted subject, with numerous economic influences and a great variety of advanced econometric modeling methods applied to various national circumstances. Not only do they come from different theoretical perspectives, but they differ widely in empirical methodology. Earlier studies largely attribute inflationary pressures to the growth of demand and the presence of macroeconomic imbalances. Hendry,[1] for instance, analyzes inflation in relation to demand pressures arising from goods and services markets, productive inputs, monetary expansion by authorities (governments or central banks), and asset prices such as equities. Similarly, the study of Stock et al.[2] emphasizes real economic slack as a key determinant of inflation dynamics. Building on this line of research, Marku[3] employs Bayesian nonparametric methods to identify persistent structural breaks in inflation data while accounting for its time-dependent behavior and stochastic volatility characteristics. To date, a variety of econometric techniques have been used in the study of inflation. In addition, De Brouwer et al.[4] use error-correction models to provide both short-run dynamics and long-term equilibrium relationships. The time-series approach, ARMA, for example, with GARCH models as well, has been used by the study of Nyoni[5] in modeling volatility of inflation, while Chan[6] gives us stochastic volatility models to fit the varying time uncertainty in how inflation behaves. Despite these methodological improvements, the article of Rudd et al.[7] pinpoint a scenario in which many rational expectations-based inflation models fall off the cliff, not to describe actual inflation with any empirical integrity at all. In more recent literature, some authors have, however, documented basic changes taking place in inflation dynamics. Mishkin[8] identifies three regularities that typify modern inflation: its reduced persistence, a flatter Phillips curve, and diminished sensitivity to external shocks. The study of Ball et al.[9] confirms these findings. They argue that inflation expectations have, since the 1980s, tended to become increasingly shock-anchored, i.e., gradually anchored to long-run inflation targets. However, Feldkircher et al.[10] find that inflation expectations tend to rise when inflation accelerates. This occurs although domestic demand and supply shocks often only exert short-lived effects. Parker[11] finds that the global inflation factor explains a substantial share of consumer price variation in high-income countries relative to others, with its impact differing across components of the consumption basket, being stronger for energy and food prices than for non-tradable goods. A major strand of the literature uses wavelet analysis to capture the time-varying and frequency-dependent relation between money supply and inflation. Rua[12] and Ryczkowski[13] are the latest to show that the money–inflation relationship evolves at different time scales. Mandler et al.[14] find strong co-movements between money growth and inflation at low frequencies, while the study of Tursoy et al.[15] provides evidence of a bi-directional causality between money supply and inflation in Turkey at both short and long run. More recently, Chekouri et al.[16] find similar dynamics. Also, at different horizons, they provide evidence of significant causality from money growth to inflation. However, these studies tend to ignore fiscal variables, suggesting a need to integrate government consumption and investment into frequency-domain analysis of inflation. The literature on Algerian inflation reveals a complex, multi-dimensional interaction between monetary, fiscal, and external variables. Early evidence by the study of Beltas et al.[17] shows a strong one-way causal relationship from money supply to inflation in Algeria for the period 1970-1988, supporting early monetarist views in a financially repressed economy. The study of Ayad has made this analysis using cointegration detection methods, which allow for breaks in the constant over the period 1970-2018. Our findings confirm that there is now a long-run relationship among money supply, inflation, and real output, following multiple changes to the structure during this process. Although money supply and inflation do not have a direct influence on output growth, the results strongly support the monetary view of inflation’s evolution in Algeria.[18] The article by Si Mohammed et al. employed an ARDL method to analyze the main determinants of inflation in Algeria from 1980 to 2012, and identified import prices, oil prices, money stock, government expenditure, and the nominal exchange rate.[19] Their findings are supported and extended by the study of Hamadouche, who found that a 1% increase in current government expenditure results in 2.14% higher inflation, while a 1% rise in capital expenditures lowers it by 1.08%. This highlights the asymmetrical effects of different components under fiscal policy.[20] Recent studies point out that transmission channels are crucial. Taking an SVAR-X approach, Mehibel et al. considered the means by which oil price shocks pass on to inflation in Algeria. Their results suggest that in the short term, fiscal spending is the dominant channel, while in the long term, money supply becomes most influential, and this is followed by exchange rates. This development reflects Algeria’s oil-dependent fiscal structure.[21] Synthesis The literature makes it clear that in Algeria, modelling price inflation is complex, structurally changes with time, and interacts in three ways between money supply, government spending levels, oil price fluctuations, import prices, and turning points in foreign exchange rates. A wide range of empirical findings and methodological diversity serves to emphasize the need for economists to take full account of the unique conditions in their own region that may differ significantly from prevailing conditions elsewhere when studying how inflation emerges in detail. Inflation in Algeria: Theoretical and Institutional Background Inflation is one of the major macroeconomic phenomena because of its direct link to stability in both the economy and society, besides its immediate impacts on purchasing power, income distribution, and eventually economic policy itself. The issue of inflation in Algeria assumes special significance given the structural features of an economy still largely dependent on the hydrocarbon sector- an economy vulnerable to external shocks as well as fluctuations in public revenues. This paper attempts a theoretical analysis of inflation while bringing out its actual evolution within the Algerian economy based on such economic and statistical information that happens to be available. Inflation is a sustained and general increase in the overall price level of goods and services over a certain period, resulting in a decline in the purchasing power of money, whereby a monetary unit cannot purchase the same quantity of goods and services as it could previously.[22] Therefore, inflation develops when most prices are rising rapidly; it is not simply an upsurge or upward movement in some prices. It is normally expressed through the consumer price index or CPI-the change in household consumption expenditure items on goods and services. Economic theories have come to analyze inflation from different analytical angles. The Quantity Theory of Money articulates the relationship between money supply and general price level and states that an increase in the money supply, with constant velocity of money and real output assumed, will eventually lead to higher prices. Friedman[23] emphasized a monetary phenomenon of inflation, particularly a long-run monetary phenomenon. On the other hand, the Keynesian approach highlights and explains the role played by aggregate demand in inflation. Therefore, according to this school of thought, expansionary fiscal policies increase government spending or consumption and investment; then we say that aggregate demand has exceeded aggregate supply when close to full employment within an economy, hence pressures on inflation.[24] Also found widely discussed within economic literature is a relationship between inflation and unemployment, where it’s theorized through the Phillips Curve as being inversely related, short run, long term; however breaks down.[25] There are different types or forms of inflation depending on what causes it. Demand-pull inflation occurs when aggregate demand is more than productive capacity. Cost-push inflation happens because the costs of production (such as wages, price of raw materials, energy) are transmitted to consumers in higher prices, becoming upward rigid. Monetary inflation is very relevant in developing economies where an excessive expansion of the money supply exists without a corresponding increase in real output that brings about a general rise in the level of prices.[26] Historically, there were large differences in the rate of inflation at different times in the Algerian economy. In the early 1990s, high rates of structural inflation accompanied reforms toward a market-oriented economy. It is only later years to be found that since about a decade ago until now, cautious monetary policy accompanied by government intervention through price controls and subsidies on essential goods has left aggregate demand satisfied within existing supply, hence low and stable rates of inflation[27] (see Figure.1). The most recent economic data in Algeria show inflation mainly driven by internal and external factors, among them changes in money supply, exchange rate fluctuations, volatility of food and energy prices, and the effects of expansionary fiscal policies. Oil prices play a central role in shaping inflation dynamics due to Algeria’s reliance on hydrocarbon revenues to finance public spending, which indirectly affects aggregate demand and price levels.[28] Many empirical works undertaken on the Algerian economy confirm significant relationships between inflation and major macroeconomic variables- money supply, exchange rate, government spending, and GDP. The economic and social impacts of inflation comprise, predominantly, the weakening of the real purchasing power of households, more particularly among the fixed-income group, thus negative effects on living standards and social inequality, apart from distorting saving and investment decisions due to greater economic uncertainty, which eventually hampers the process of economic growth in the medium term if not addressed through coherent, well-coordinated policy measures. Data and Methodology 3.1. Data In this paper, results are presented from an experiment employing the wavelet coherence technique to examine how inflation and its determinants - i.e., money supply, government expenditure, and the volume of investment - evolve in Algeria through 1970-2024. This research method allows one not only to see the lengths and frequencies at which these variables most intensively affect inflation, but also whether, in any or all periods, all three lead or trail inflation in the time dimension. Inflation is measured by the annual growth rate of the Consumer Price Index (CPI), while money supply is proxied by the broad monetary aggregate (M2). Government expenditure is represented by total public spending, while capital formation refers to gross fixed capital formation. The data are extracted from official and trustworthy sources, the annual reports of the Bank of Algeria and the International Monetary Fund (IMF) data base World Bank database, to ensure consistency and accuracy. All variables are converted into constant 1990 United States dollars (adjusted for inflation) and expressed in natural logarithms, except for the inflation rate, so as to increase the homogeneity of the series and level up their statistical properties. Methodology There are multiple reasons why wavelet analysis is an appropriate choice for this study. The Algerian economy is subject to repeated structural shocks (oil price fluctuations, economic reforms, monetary and fiscal policies changes), which result in a long-term instability of the economic relationship. Second, wavelet analysis provides a means to assess non-stationary time series without strong assumptions of stationarity. Third, this method allows us to learn more about how the relationships are functioning at different time scales, further helping policymakers craft better policies depending on the temporal scale of interest. Wavelet-based methods are particularly suitable for emerging market economies characterized by structural breaks and time-varying dynamics. Thus, examining inflation in Algeria between the period 1970–2024 can be more accurately and closely analysed through the use of wavelet analysis. As we will see, wavelet analysis provides a comprehensive and dynamic understanding of inflation in Algeria. Continuous Wavelet Transform (CWT): The wavelet technique is a relatively recent and highly efficient tool for addressing non-linearity and non-stationarity in economic and financial data. Although it is based on Fourier analysis, it overcomes its limitations by extracting information simultaneously from both the time and frequency domains. The Continuous Wavelet Transform (CWT) is one of the most widely used wavelet analysis methods and is recognized as a powerful mathematical tool for analyzing the time–frequency characteristics of non-stationary time series. For a time series X(t), the Continuous Wavelet Transform (CWT) for a wavelet ψ(t) is defined as follows: Where indicates the time and the frequency domain of the wavelet, respectively. is the Morlet wavelet function, consisting of a plane wave modulated by a Gaussian: The Wavelet Power Spectrum (WPS) of the continuous wavelet transform is defined as: The WPS depicts and measures the local variance of a time series at different times and scales.[29] Wavelet squared coherence (WSC) The wavelet squared coherence technique is a valuable tool for analyzing the co-movements between two time series across different time scales and frequency bands. The wavelet coherence between two time series u and v is defined as: Where is the squared wavelet coherence, its value ranges between 0 and 1, and measures the local linear correlation between two time series at a particular scale. Where: S: is a smoothing operator defined as: Where represents smoothing along the wavelet scale axis, and smoothing in time. : the cross wavelet power, it is viewed as the local covariance of u and v, where are continuous wavelet transforms of two time series u(t) and v(t), respectively.[30] The wavelet coherence phase difference is given by: Where: and are the imaginary and real parts, respectively, of the smoothed cross wavelet power spectrum. Phase differences are indicated by arrows on the wavelet coherence plots. Right-pointing arrows indicate that the time series are in phase, while left-pointing arrows indicate they are in anti-phase. When the arrows point vertically upward, the first time series leads the second. Conversely, downward-pointing arrows indicate that the second time series is leading.[31] In addition, the phase difference derived from the wavelet coherence analysis provides information on the direction of the relationship and potential lead–lag structures. Phase arrows pointing to the right indicate positive correlations, while arrows pointing to the left indicate negative correlations. Arrows pointing upward (downward) suggest that the second (first) variable leads the first (second) variable. Empirical Results Wavelet power spectrum results This is accomplished using the wavelet power spectrum to analyze dynamic features of some important economic variables in Algeria for the period (1970–2024) in a joint time–frequency domain. Such a technique enables to detect the process dominant cycles and to quantify fluctuations intensity of inflation, money supply, government expenditure, and capital formation, while including the shocks of the economy and the changes of monetary and fiscal stimuli. Thus, as the wavelet power spectrum provides more informative dynamic intuition of the drivers of inflation at short-, medium- and long-run horizons, it renders the analysis more valid and robust in the context of the Algerian economy. Figure 2 illustrates the inflation wavelet power spectrum in Algeria over the period 1970–2024. These show that inflation fluctuations are spelt printed out in the worldwide price index mainly at short and medium horizons with reference to years from 1970 to 1980, approximately 2–5 years. The statistically significant high-power regions imply that inflation dynamics in Algeria are governed primarily by cyclical shocks and policy-making rather than slowly evolving long-term trends. However, the weak power at longer periods means there is restricted (long-term) inflation persistence: temporary but lasting pressures account for virtually all of an episode of high price levels. Figure 3 shows the wavelet power spectrum of gross capital formation in Algeria from 1970 to 2024. Power concentrations are strongly evident at medium and long horizons (approximately 4-16 years), reflecting the great long building cycles in which this capital is formed. These are largely driven by public investment programs and broad-gauge structural projects. The statistically significant areas of high power suggest that investment dynamics in Algeria are cyclical and irregular, and influenced predominantly by general macroeconomic fluctuations as well as changes in world oil prices. This may limit their ability--in the long run--to ensure economic stability. Figure 4 shows the wavelet power spectrum for government spending in Algeria in the 1970-2024 period. The pattern indicates significant power concentrations at medium-and long-term targets (about 4-16 years), reflecting fiscal policy cycles in Algeria. Significantly high-power areas show that government spending follows regular economic cycles. These largely result from varying inflows of oil revenue and the adoption of expansionary fiscal policies. Inflationary pressures are heightened by these variations in public spending, especially when real growth of output does not keep up pace with increases in public spending. The wavelet power spectrum of money supply in Algeria reveals strong and time-varying fluctuations, particularly over the short- and medium-term horizons. Statistically significant periods indicate the presence of monetary cycles ranging between two and eight years, reflecting the sensitivity of money supply to economic shocks and changes in monetary policy. In contrast, long-term fluctuations appear less pronounced, suggesting a relatively stable long-run trend in money supply (See Figure 5). Wavelet coherence results Wavelet coherence is employed here to analyze the dynamic interaction between inflation and its fundables (money supply, government expenditure, and capital formation) in Algeria for the period 1970–2024. This allows us to pinpoint the time periods and frequency bands where these variables are most closely linked to inflation, and whether monetary, fiscal, or investment variables lead or lag inflation at different horizons. Figure 6 depicts wavelet coherence between government spending and inflation, based on a 1970-2024 interval in Algeria. Using the criterion suggested by Song et al., the actual results show both important coherence in terms (which is relevant in the shorter run) and statistically significant coherence at medium horizons of 2-5 years (about four-fifths). This very strong coherence between government expenditure and inflation means that there is an active, well-established relationship at work over time. It suggests that, when public spending increases are larger than required for public production to function smoothly and efficiently, wages will start to rise. This, in turn, pushes up prices on an economy-wide scale - potentially increasing short-term demand for goods because of producer price pressures. These findings are a testament to the inflationary character of fiscal policy in Algeria, where increases in government spending are often made without any corresponding increase in the means of production. With demand-oriented inflation. Figure 7 shows the wavelet coherence between inflation and gross capital formation in Algeria over the period 1970–2024. When you look at the diagram below, coherence for inflation with net capital formation is statistically significant both on a short and medium term (say about 2–5 years). This coherence indicates a close relationship between investment dynamics and inflation, whereby increases in investment—especially public investment—generate short-term inflationary pressures before their potential positive effects on productive capacity materialize. Efficiency in the transmission of investment into so many effective products is still so low that in the short run, it becomes inflation rather than being consumed by society. This pattern reflects inefficiencies in the transmission of investment into effective productive growth in the short run, thereby contributing to inflation rather than mitigating it. In Figure 8, we have the wavelet coherence of Inflation and Money Supply. The period is 1970 to 2024. These results show considerable and statistically significant coherence at short and medium-term horizons (roughly 2 - 5 years), particularly during the early part of the sample. Such high coherence shows how money supply expansion is generally the main factor in the movement of inflation. The further supply is increased, so will inflation rise along in both the short and medium term. These findings suggest that limitations on printing banknotes have failed to soften economic blows. Moreover, reliance upon monetary financing has grown heavy and so reinforces the monetary nature of inflation. Discussion of Results The wavelet power spectrum and coherence findings present inflation in Algeria from 1970 to 2024 as an ever-changing dynamic phenomenon, influenced by various economic channels. The nature of these effects changes from short- to long- term, and thus cannot simply be pinned down as a question of money supply growth. First, wavelet coherence between inflation and money supply strongly confirms that the nature of inflation in Algeria is monetary, especially in the short and medium term. Coherence occurring within the 2–5 year period shows that prices are highly sensitive to cash injections resulting from deficit financing of government deficits, and lack an independent monetary authority. Injecting more money into a system where there is already excessive liquidity unrelated to real production only causes higher inflation rates, not basic production, in support of Friedman’s monetary inflation hypothesis. Second, coherence between inflation and government expenditure reveals that expansionist fiscal policies also have a role in driving up consumer prices. In an economy whose revenue depends heavily on oil rents, higher public spending acts to increase total demand and output at a time when such advances are not followed by any corresponding increases in actual goods production. Consequently, fiscal influences push through into inflation pressures - especially if such public spending is borne by printing money or the country is relatively weak in terms of the productive sector. Third, the relationship between inflation and gross capital formation exposes investment anomalies. While in the long run investment is believed to alleviate inflationary pressures by expanding capacity, in the short term, its results show it is a cause of inflation. This may be due to state investment inefficiencies, lengthy implementation delays, and highly import-oriented project investment, whose completion not only raises demand but also fails to raise actual domestic productive capacity. These findings indicate that inflation in Algeria takes on many different forms: it is a product of monetary policy interacting with fiscal policy and structural investment dynamics. These results have significant policy implications for inflation targeting in the context of Algeria. At first, the tight time–frequency connection between the money supply and inflation highlights that there should be a more rigorous discipline in monetary policy, in addition to the higher independence degree of the central bank to minimize excess liquidity. The large inflationary effects of government expenditure underscore the need for fiscal sustainability, especially in an oil-exporting economy where revenue bonanzas tend to materialize in the form of pro-cyclical spending. Taking into consideration the above, the countercyclical response of capital formation to inflation suggests the need for structural reforms that could enhance investment efficiency, lower implementation lags, and reduce the import dependence of investment projects. Thus, an integrated policy framework for monetary discipline, sustainable fiscal policy, and structural reforms is needed to enable the emergence of stable price conditions and sustainable growth in Algeria. With the evolution of the global economy, inflation dynamics are more contingent on external shocks, especially in open and resource-dependent economies. Important external determinants include exchange rate movements and imported inflation; volatility of international prices of commodities and energy; and international financial shocks generated by world crises and the broad liquidity conditions tightening or easing globally. Moreover, the behavior of monetary and fiscal authorities is influenced by policy frameworks that are being promoted by international institutions, as well as by constraints from external financing and from exposure to developments in the foreign sector, which, in turn, determine domestic inflation outcomes. Against this backdrop, Algeria represents an especially salient empirical case. Given its reliance on oil-exporting income, its high dependence on hydrocarbon revenues as well as its heavy reliance on imports, inflationary pressures in Algeria are crucially linked to real shocks transmitted through oil price cycles, exchange rate fluctuations, and, on the fiscal side, reactions to global conditions. Algeria stands as a microcosm of the inflation dynamics of oil-reliant economies, shaped by the interplay of such external factors with domestic monetary and fiscal dynamics. The study adds to the worldwide body of knowledge by envisaging the inflation in such nations mainly as not solely a domestic event, but as a time-varying process established by the interplay between exterior shocks and interior response performance. As the analysis implements a time-frequency wavelet approach, it offers an international perspective of how inflationary pressures adjust across time horizons amongst oil-exporting economies subject to global business cycles. Conclusion Wavelet power spectrum and wavelet coherence methods are used to examine the dynamic connections between inflation and its main macroeconomic determinants in Algeria through the period 1970-2024. By employing a time-frequency framework, this analysis affords a comprehensive view of how changes in monetary and fiscal policy, as well as investment-related factors, interact with inflation over different growth horizons. For this reason, the authors’ hypotheses can be reliably assessed. Empirical evidence strongly supports the monetary hypothesis. Over short- and intermediate frequencies, the money supply has significant and persistent coherence with inflation. The results suggest that monetary expansion frequently leads to inflation, confirming the idea that excess liquidity has a major impact on inflation dynamics in Algeria. This finding provides solid evidence for the belief that inflationary pressures come from monetary factors-- especially in an economic environment characterized by laissez-faire Wall Street policies and limited monetary independence. The evidence also provides robust support for the fiscal hypothesis. At specific time scales, government expenditure is positively and statistically significantly related to inflation, especially over short to medium-term horizons. These results reflect demand-pull inflation, which generally results from the time it takes to adopt expansionary fiscal measures in the wake of changes in oil revenues. This variable relationship underscores the pro-cyclical nature of fiscal policy in Algeria and its tendency to amplify inflation when the public sector is expanding. The investment narrative is more complex and asymmetric. The results suggest that capital formation follows inflation rather than leading it. At medium time horizons, price volatility exerts a strongly negative effect on investment (capital expenditure) decisions. The findings point to structural and efficiency constraints, long implementation lags, and a high import content of investment projects. In this context, and alongside the easing of foreign exchange constraints, persistently high money growth and a strong reliance on monetary base–oriented policies have become central issues on the monetary authority’s agenda. Episodes of government expenditure driven by temporary fiscal revenue windfalls resulting from buoyant global crude oil prices—often described as golden periods in petroleum-dependent economies—demonstrate that a countercyclical fiscal stance aimed at containing demand-pull inflation tends to be ineffective in practice, despite its theoretical appeal. There are a few realistic policy options capable of altering the nature of demand surges so that they do not generate inflation; indeed, such attempts may prove even more counterproductive over time. Without structural reforms to improve investment efficiency, address persistent implementation bottlenecks, and significantly reduce time-to-market, a substantial share of potential annual economic growth will remain unrealized, requiring corrective measures to close existing gaps and align the economy with its intended development trajectory. To sum up, inflation in Algeria is seen as a phenomenon that varies by time and is structurally conscious, influenced by combinations of both monetary expansion, fiscal policy, and investment dynamics. This wavelet approach is particularly handy in capturing these changing relationships and should benefit both practical policymakers and academic researchers. An integrated approach to controlling inflation sustainably in Algeria requires disciplined monetary policy, fiscal sustainability, and structural change to promote long-term economic stability. To sum up, inflation in Algeria emerges as a time-varying and structurally driven phenomenon, shaped by the interaction of monetary expansion, fiscal policy, and investment dynamics. The wavelet approach proves particularly effective in capturing these evolving relationships across different time horizons, offering valuable insights for both policymakers and academic researchers. Achieving sustainable inflation control in Algeria, therefore, requires an integrated policy framework that combines disciplined monetary policy, fiscal sustainability, and structural reforms aimed at strengthening investment efficiency and long-term economic stability. References: Ayad, H. (2020). Money Supply, Inflation and Economic Growth: Co-Integration and Causality Analysis. Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, 65(2). <doi:10.2478/subboec-2020-0008>; Ball, L., Mazumder, S. (2011). Inflation Dynamics and the Great Recession. Brookings Papers on Economic Activity, 42(1); Banque d’Algérie. (Various years). Annual reports. <https://www.bank-of-algeria.dz/politique-monetaire/>; Beltas, A., Jones, T. (1993). Money, inflation and causality in a financially repressed economy: Algeria, 1970–1988. Applied Economics, 25(4). <doi:doi.org/10.1080/00036849300000055>; Blanchard, O. (2021). Macroeconomics (éd. 8e). Pearson; Chan, J. (2017). The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling. Journal of business & economic statistics, 35(1). <doi:10.1080/07350015.2015.1052459>; Chekouri, S., Kahoui, H., Chibi, A. (2024). Money Supply and Inflation in Algeria: A Wavelet Based Analysis. 39(3), Les Cahiers du CREAD, 39(3). <doi:10.4314/cread.v39i3.2>; De Brouwer, G., Ericsson, N.-R. (1998). Modeling Inflation in Australia. Journal of Business & Economic Statistics, 16(4); 9. Feldkircher, M., Siklos, P. (2019). Global inflation dynamics and inflation expectations. International Review of Economics & Finance, 64. <doi:https://doi.org/10.1016/j.iref.2019.06.004>; Friedman, M. (1968). The role of monetary policy. American Economic Review, 58(1). <http://www.jstor.org/stable/1831652>; Hamadouche, F. (2024). The impact of public expenditure on inflation: An ARDL approach. Financial Markets, Institutions and Risks (FMIR) journal, 8(2). <doi:doi.org/10.61093/fmir.8(2).70-85.2024>; Hendry, D.-F. (2001). Modelling UK inflation, 1875–1991. Journal of Applied Econometrics, 16(3). <https://doi.org/10.1002/jae.615>; International Monetary Fund. (2024). Algeria: Country report (No. 24/088). IMF. <doi.org/10.5089/9798400271878.002>; Keynes, J. (1936). The general theory of employment, interest and money. London: England: Macmillan; Mandler, M., Scharnagl, M. (2014). Money growth and consumer price inflation in the euro area: A wavelet analysis. Deutsche Bundesbank Discussion, Frankfurt; Mankiw, N. (2019). Macroeconomics (éd. 10e). Worth Publishers; Markus, J. (2015). Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach. Econometric Reviews, 34(5). <doi:10.1080/07474938.2013.806199>; Mehibel, S., Oughlissi, M., Boudjana, R., Menna, K., Haffar, A. (2024). Oil price shocks pass-through into inflation in Algeria: Assessing the relative importance of the transmission channels using structural VAR-X. Les Cahiers du CREAD, 39(3); Mishkin, F. (2007). Inflation Dynamics. International Finance, 10(3). <doi:doi.org/10.1111/j.1468-2362.2007.00205.x>; Nyoni, T. (2018). Modeling and forecasting inflation in Kenya: Recent insights from ARIMA and GARCH analysis. Dimorian Review, 5(6); Parker, M. (2018). How global is global inflation? Journal of Macroeconomics, 58(C). <doi:DOI: 10.1016/j.jmacro.2018.09.003>; Rua, A. (2012). Money Growth and Inflation in the Euro Area: A Time-Frequency View. Oxford Bulletin of Economics and Statistics, 74(6). <doi:j.1468-0084.2011.00680.x>; Rudd, J., Whelan, K. (2007). Modeling Inflation Dynamics: A Critical Review of Recent Research. Journal of Money, Credit and Banking, 39(s1). <doi:doi.org/10.1111/j.1538-4616.2007.00019.x>; Ryczkowski, M. (2021). Money and inflation in inflation-targeting regimes – new evidence from time–frequency analysis. Journal of Applied Economics, 24(1). <doi:10.1080/15140326.2020.1830461>; Samuelson, P., Solow, R. (1960). Analytical aspects of anti-inflation policy. American Economic Review, 50(2); Si Mohammed, K., Benyamina, K., Benhabib, A. (2015). The Main Determinants of Inflation in Algeria. An ARDL Model. International Journal of Management, 5; Stock, J.-H., Watson, M.-W. (2010). Modeling Inflation After the Crisis. National Bureau of Economic Research, Cambridge. <doi:10.3386/w16488>; Tastan, H., Sahin, S. (2020). Low-frequency relationship between money growth and inflation in Turkey. Quantitative Finance and Economics, 4(1). <doi:10.3934/QFE.2020005>; Torrence, C., Compo, G.-P. (1998). A Practical Guide to Wavelet Analysis. Bulletin of the American Meteorological Society, 79(1). <doi.org/10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2>; Torrence, C., Webster, P.-J. (1999). Interdecadal Changes in the ENSO-Monsoon System. Journal of Climate, 12. <doi.org/10.1175/1520-0442(1999)012<2679:ICITEM>2.0.CO;2>; Tursoy, T., Mar’i, M. (2020). Lead-lag and relationship between money growth and inflation in Turkey: New evidence from wavelet analysis. MPRA Paper No. 99595. Munich Personal RePEc Archive, Munich. Footnotes [1] Hendry, D.-F. (2001). Modelling UK inflation, 1875–1991. Journal of Applied Econometrics, 16(3), pp. 255–275. <https://doi.org/10.1002/jae.615>. [2] Stock, J.-H., Watson, M.-W. (2010). Modeling Inflation After the Crisis. National Bureau of Economic Research, Cambridge, pp. 1-61. <doi:10.3386/w16488>. [3] Markus, J. (2015). Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach. Econometric Reviews, 34(5), pp. 537-558. <doi:10.1080/07474938.2013.806199>. [4] De Brouwer, G., Ericsson, N.-R. (1998). Modeling Inflation in Australia. Journal of Business & Economic Statistics, 16(4), pp. 433-449. [5] Nyoni, T. (2018). Modeling and forecasting inflation in Kenya: Recent insights from ARIMA and GARCH analysis. Dimorian Review, 5(6), pp. 16-40. [6] Chan, J. (2017). The Stochastic Volatility in Mean Model with Time-Varying Parameters: An Application to Inflation Modeling. Journal of business & economic statistics, 35(1), pp. 17-28. <doi:10.1080/07350015.2015.1052459>. [7] Rudd, J., Whelan, K. (2007). Modeling Inflation Dynamics: A Critical Review of Recent Research. Journal of Money, Credit and Banking, 39(s1), pp. 155-170. <doi:doi.org/10.1111/j.1538-4616.2007.00019.x>. [8] Mishkin, F. (2007). Inflation Dynamics. International Finance, 10(3), pp. 317-334. <doi:doi.org/10.1111/j.1468-2362.2007.00205.x>. [9] Ball, L., Mazumder, S. (2011). Inflation Dynamics and the Great Recession. Brookings Papers on Economic Activity, 42(1), pp. 337-405. [10] Feldkircher, M., Siklos, P. (2019). Global inflation dynamics and inflation expectations. International Review of Economics & Finance, 64, pp. 217-241. <doi:https://doi.org/10.1016/j.iref.2019.06.004>. [11] Parker, M. (2018). How global is global inflation? Journal of Macroeconomics, 58(C), pp. 174-197. <doi:DOI: 10.1016/j.jmacro.2018.09.003>. [12] Rua, A. (2012). Money Growth and Inflation in the Euro Area: A Time-Frequency View. Oxford Bulletin of Economics and Statistics, 74(6), pp. 875-885. <doi:j.1468-0084.2011.00680.x>. [13] Ryczkowski, M. (2021). Money and inflation in inflation-targeting regimes – new evidence from time–frequency analysis. Journal of Applied Economics, 24(1), pp. 17-44. <doi:10.1080/15140326.2020.1830461>. [14] Mandler, M., Scharnagl, M. (2014). Money growth and consumer price inflation in the euro area: A wavelet analysis. Deutsche Bundesbank Discussion, Frankfurt, pp. 1-14. [15] Tursoy, T., Mar’i, M. (2020). Lead-lag and relationship between money growth and inflation in Turkey: New evidence from wavelet analysis. MPRA Paper No. 99595. Munich Personal RePEc Archive, Munich, pp. 1-23. [16] Chekouri, S., Kahoui, H., Chibi, A. (2024). Money Supply and Inflation in Algeria: A Wavelet Based Analysis. 39(3), Les Cahiers du CREAD, 39(3), pp. 27-51. <doi:10.4314/cread.v39i3.2>. [17] Beltas, A., Jones, T. (1993). Money, inflation and causality in a financially repressed economy: Algeria, 1970–1988. Applied Economics, 25(4), pp. 473-480. <doi:doi.org/10.1080/00036849300000055>. [18] Ayad, H. (2020). Money Supply, Inflation and Economic Growth: Co-Integration and Causality Analysis. Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, 65(2), pp. 29-45. <doi:10.2478/subboec-2020-0008>. [19] Si Mohammed, K., Benyamina, K., Benhabib, A. (2015). The Main Determinants of Inflation in Algeria. An ARDL Model. International Journal of Management, 5, pp. 71-82. [20] Hamadouche, F. (2024). The impact of public expenditure on inflation: An ARDL approach. Financial Markets, Institutions and Risks (FMIR) journal, 8(2), pp. 70-85. <doi:doi.org/10.61093/fmir.8(2).70-85.2024>. [21] Mehibel, S., Oughlissi, M., Boudjana, R., Menna, K., Haffar, A. (2024). Oil price shocks pass-through into inflation in Algeria: Assessing the relative importance of the transmission channels using structural VAR-X. Les Cahiers du CREAD, 39(3), pp. 235-273. [22] Blanchard, O. (2021). Macroeconomics (éd. 8e). Pearson. [23] Friedman, M. (1968). The role of monetary policy. American Economic Review, 58(1), pp. 1-17. <http://www.jstor.org/stable/1831652>. [24] Keynes, J. (1936). The general theory of employment, interest and money. London: England: Macmillan. [25] Samuelson, P., Solow, R. (1960). Analytical aspects of anti-inflation policy. American Economic Review, 50(2), pp. 177-194. [26] Mankiw, N. (2019). Macroeconomics (éd. 10e). Worth Publishers. [27] Banque d’Algérie. (Various years). Annual reports. Algiers. <https://www.bank-of-algeria.dz/politique-monetaire/>. [28] International Monetary Fund. (2024). Algeria: Country report (No. 24/088). IMF. <doi.org/10.5089/9798400271878.002>. [29] Tastan, H., Sahin, S. (2020). Low-frequency relationship between money growth and inflation in Turkey. Quantitative Finance and Economics, 4(1), pp. 91-120. <doi:10.3934/QFE.2020005>. [30] Torrence, C., Webster, P.-J. (1999). Interdecadal Changes in the ENSO-Monsoon System. Journal of Climate, 12, pp. 2679-2690. <doi.org/10.1175/1520-0442(1999)012<2679:ICITEM>2.0.CO;2>. [31] Torrence, C., Compo, G.-P. (1998). A Practical Guide to Wavelet Analysis. Bulletin of the American Meteorological Society, 79(1), pp. 61–78. <doi.org/10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2>.
From Individual to Collective: A Critical Review of Technology Acceptance and Organizational Knowledge
The Technology Acceptance Model is one of the most employed frameworks applied by academics worldwide to explain why individuals accept or do not use technology. Since then, several studies have confirmed the influence of Internal Beliefs on Attitude and Behavioral Intention toward technology, preceded by a wide range of external factors. Domain-relevant knowledge is a crucial external factor in determining users’ behavioral intention to use enterprise resource technology systems, corroborating findings from the technology acceptance model. From a literature scope review, we explore a different and complementary approach regarding knowledge, not only as an external factor, but as a component of the organizational cycle of knowledge creation. The consideration of organizational knowledge creation processes and the nature of the technology used by individuals may bring new light to behavioral intention studies, tying together different study fields, and allowing further academic research work to provide constructive insights and contributions in the quest to determine where the individual’s technology acceptance fits in dynamic organizational knowledge creation. Keywords: Technology Acceptance Model, organizational knowledge, information technology. Introduction The proliferation of knowledge and information technologies has profoundly reshaped work and economic structures,[1] transforming practices across industries and professions.[2] The main reason behind the development and adoption of technologies in organizations is the increase in human efficiency and effectiveness in the practice of routines.[3] The advancement of information system technologies enables organizations to enhance efficiency, reduce costs, and improve information management, strengthening decision-making and enabling novel operational capabilities,[4] making research on the adoption and use of systems relevant in academic and working realms. Research on individual information system adoption is mature, providing established theories that explain adoption determinants and emphasizing the significance of technology acceptance behavior for successful system implementation.[5] The Technology Acceptance Model (TAM) is a widely recognized and highly predictive framework for understanding technology adoption and use,[6] characterized by its parsimony, specific constructs, robust theoretical foundation, applied across various technologies, expertise levels, and countries.[7] While individual system use is often considered voluntary, organizational contexts frequently dictate adoption, driven by organizational needs rather than solely individual beliefs.[8] Consequently, organizational technology acceptance reflects both individual preferences and organizational dynamics that foster knowledge development.[9] The use of information systems can involve individuals in organizational knowledge creation, where systems process and disseminate information, thereby amplifying knowledge scope.[10] Outside organizational contexts, understanding adoption at an individual level has limited practical value.[11] Recognizing these organizational and individual factors within firms, this paper investigates the influence of organizational dynamics and information system characteristics on individual technology acceptance. This research integrates literature conceptualization findings from the TAM with the Organizational Dynamic Knowledge Creation theory to understand the evolution of beliefs and intentions toward information systems as a process shaped by organizational dynamics driving knowledge creation. This study highlights findings in the literature of the potential influence of organizational group-thinking on individual adoption, a recognized limitation in TAM research.[12] The present manuscript is divided as follows: We first work on finding organizational knowledge creation factors explored and considered in technology acceptance theory literature. By applying a scope analysis, we aim to provide an organizational explanation to technology acceptance factors, such as behavioral intention, beliefs, and attitude, followed by a conceptualization of organizational knowledge from a technology individual use perspective. Finally, we close by elaborating on discussion points regarding organizational dynamics and technology acceptance and providing theoretical and practical implications. 1. Literature Review 1.1. Technology Acceptance Model The TAM aims to capture critical aspects of information technology through a set of quantitative surrogates -beliefs, attitudes, and intention - to understand what motivates users to accept and use new technology.[13] The judgments regarding the usefulness and ease of use of a technology generate behavioral intentions that affect the individual’s willingness to use and the actual use behavior.[14] The TAM is deemed capable of explaining user behavior across a broad range of research contexts[15] while at the same time being both parsimonious and theoretically justified[16] thanks to its core variables – perceived usefulness and perceived ease of use,[17] with substantial empirical support.[18] 1.2. Behavioral intention Behavioral Intention (BI) is a function of salient information or beliefs set to measure the strength of an individual’s intention to perform a specified behavior.[19] The TAM postulates that BI is the major determinant of usage behavior; that behavior should be predictable from measures of BI, and any other factors influencing use behavior do so indirectly by influencing BI.[20] Technology use intention is based on the rational intention that captures the motivational factors that influence users’ behavior, indicating how much effort an individual could exert to perform a behavior[21] and to initiate and formalize knowledge.[22] Technology use, action, and practice[23] are the factors that give shape to the flow of information acquired by individuals, organizing and creating knowledge, anchored on the commitment and beliefs of the holder.[24] An undesirable outcome of the application of the TAM has been the intensive focus on the prediction or explanation of system use, defined and operationalized as an amount or frequency.[25] In fact, most system acceptance studies do not measure system use, but rather measure variance in self-reported use, hence the construct Intention becomes a non-precise measure of actual system use.[26] The relationship between intention and usage appears to be dependent on the measurement method: when usage is measured as self-report, intentions do predict usage, but when actual usage is measured, intentions do not predict usage.[27] In theory, the construct Intention must work as a precise measure of future, or even present use; however, it rather shows different results in the literature.[28] TAM measures of behavioral intention are not focused on an overall behavioral measure; hence, the interpretation of the TAM must keep in mind a “narrower conceptualization of intended behavior”.[29] Literature explains that time is the basis of the difference between intentions and action;[30] in this way, when intentions measure system’s pre-implementation usage, they cannot include the additional information that the subjects may acquire by the time of the post-implementation intention measures, information accumulated by experiencing system use.[31] By treating BI as a terminal goal for human action, researchers fail to consider the fact that several actions are taken not as ends in and of themselves, rather as means of more fundamental ends or goals.[32] 1.3. Beliefs In TAM, beliefs are defined as the individual’s subjective probability that performing a target behavior will result in a certain consequence,[33] suggesting two main determinants: Perceived Ease of Use (PEOU) and Perceived Usefulness (PU). PEOU indicates the cognitive effort needed to learn and to utilize the new system, while PU measures the individual subjective assessment of the utility offered by the new system,[34] with PEOU being an antecedent of PU.[35] As users’ beliefs about their ability to successfully complete tasks by using a system increase, they will perceive the system as being easier to use.[36] Similarly, as users’ beliefs about the positive relationship between system’s use and performance increase, they will perceive that using a system provides benefits within organizational contexts.[37] TAM literature conceptualizes a hierarchy between the two belief variables, where PU is a major determinant of people’s intentions to use a system, while PEOU works on a secondary level.[38] The implication of this hierarchy of beliefs is that, unless users perceive a system as being useful at first, its ease of use has no effect on the formation of intentions; however, ease of use does have some effect on how useful an individual perceives a system,[39] it doesn’t matter for them how easy it could be to operate the system if it does not perform a useful function within their organizational context.[40] Likewise, the more experience regarding system use over time, the less relevant the system’s ease of use will be, while, at the same time, it will increase the beliefs of the system’s usefulness,[41] leading to knowledge from a process of creation and manipulation of beliefs that conveys to users with perspectives that help them with their context’s perceptions and definitions.[42] 1.4. Attitude Attitude is defined as an individual’s positive or negative feelings about performing a target behavior.[43] Attitude as a predictor of human behavior is determined by the product of the user’s salient beliefs about the consequences of performing the behavior multiplied by the evaluation of those consequences.[44] Both intention and behavior are motivated by attitude as an overall affective evaluation toward a system, based on a set of cognitive beliefs about the system in question.[45] Individuals with higher levels of knowledge about a system will manifest enhanced beliefs about the system’s perceived ease of use and perceived usefulness, subsequently influencing a stronger attitude toward it.[46] Revised versions of the TAM make no consideration of attitude as a predictor of behavioral intention.[47] Within organizational settings, system users form intentions toward behaviors they believe will increase their job performance, over and above whatever positive or negative feeling may be evoked toward the very behavior.[48] Hence, the attitude formed by personal beliefs about a system is of secondary relevance regarding the intention of using a system to perform job-related operations.[49] Direct belief-intention relationships have been observed, contrary to the fact that attitudes fully mediate the effects of beliefs on intention.[50] 1.5. Organizational knowledge From an organizational perspective, knowledge refers to the relatively formal and facts, rules, policies, and procedures within the organization,[51] as an emergent product of a situated context of individuals’ lives and work.[52] Every activity performed by people working in an organization creates and gives shape to the organization’s knowledge. The creation, transfer, and integration of knowledge is an important reason firms exist,[53] being embedded in the skills of employees, as well as in processes, policies, and information repositories.[54] Organizations exist because they reduce the cost of using the “price mechanism” to organize production and the cost of negotiating and concluding transactions individually.[55] To solve economic problems by constructing “a rational economic order”, individuals within an organization “must make use of the knowledge of circumstances” that exists dispersed, incomplete, and frequently contradictory by individuals.[56] Securing the best use of knowledge implies communication between individuals aimed at building mutual understanding; thus, the communication factor of knowledge consequently builds, amplifies, and develops new knowledge from individuals within the organization.[57] Communication among individuals leads to organizational alignment of mission, objectives, and plans,[58] creating knowledge readily available that enhances individuals’ information-processing capabilities in a great way.[59] By establishing communities with shared identity, norms, sequences, and patterns, organizations lower the cost of communication and coordination of knowledge, creating a shared knowledge context that enables the development of new knowledge and capabilities through the recombination of existing knowledge,[60] fostering regular and predictable patterns of activity -organizational routines- that govern coordinated activities within organizations.[61] Thus, decision making in group contexts refers to acting out of congruence between one’s own and group’s shared values or goals, in a process of internalization that is developed through processes of socialization, psychological development, education, training, and indoctrination in organizations, developing a combination of compliance and internalization within the reference group, operating when a person sees oneself as an individual but in a relationship to a group.[62] Collective intentions related to technology acceptance are rooted in everyone’s self-conception as a member of an organization, where the individual’s actions are conceived as either the group acting as a unit or the person acting as an agent of the group.[63] Such collective behavior can be understood thanks to the concept of organizational commitment, which represents a psychological bond that individuals form with an organization that stabilizes their behaviors toward the organization. Thus, regarding organizational knowledge and acceptance of technology, the limitation of TAM, as a technology proxy study, deals with technologies through surrogates -factors that conceptualize internal beliefs, attitudes, and intentions toward technologies-, it tends not to conceive of historical or cultural variations in information technology artifacts, given that those variations may not be evident in the surrogates’ measures.[64] 2. Discussions 2.1. The sufficiency of the Technology Acceptance Model Much of human behavior is not best characterized by an individual action in isolation, where decisions regarding technology acceptance and actual usage are often made collaboratively or with an aim to how they fit in with, or affect other people or group requisites.[65] A limitation of the TAM is the fact that the model considers information system acceptance to be an independent individual issue rather than part of organizational dynamics.[66] Therefore, while measuring individual intentions, how to ensure the consideration of organizational knowledge effects? Figure 1 illustrates the proposed path within the theorized influence of knowledge on behavior: knowledge gain system and training affect users’ beliefs about their own ability to successfully use a system, the amount of effort required to use a system, and the direct benefits of using a system, beliefs that in turn shape the overall attitude toward the system, and ultimately influence their intentions and behaviors. * The work from Mullins & Cronan (2021) addresses the importance of domain-relevant knowledge in the formation of beliefs and attitudes toward a system, developing a model of informed technology acceptance. The hypothesized path form Behavior to Training responds to the process of amplification of knowledge created by individuals, crystallizing it as part of the knowledge network of the organization (Nonaka, 1994) Over the years, the individual construct additions made to the TAM have been justified by researchers; however, in the final analysis, this construct-addition approach has basically provided explanations or antecedents for the core TAM belief perceptions -PU and PEU- via another set of belief perceptions, without increasing the knowledge of what makes an information technology useful,[67] lacking the means to account for temporal and contextual variations in socio-psychological and socio-economical patterns.[68] To continue using the life-long TAM constructs in a changing technology context threatens our capability to understand present and future phenomena.[69] Some other limitations present in most of the TAM research works are related to self-reported use as a measurement of actual use, for it does not accurately reflect actual behavior and actual usage.[70] The constructs employed in technology acceptance research are inferred indirectly from behavioral proxies rather than measured explicitly, creating a sense of speculation about their conclusions.[71] 2.2. The relevance of organizational knowledge in technology acceptance Based on the resource-based view of the firm, organizational knowledge creates competitive advantage and organizational capability, comprising the training, experience, relationships, and insights of organizational human resources.[72] Information technologies do not influence organizations’ performance directly, but the relationships existing between these technologies and other resources and organizational capabilities mediate the value creation process.[73] The knowledge derived from individual use of technology may not only contribute to organizational performance, but also the organization’s workflow may depend more heavily on the individual’s knowledge.[74] The account for the impact of organizational dynamics that create knowledge within the organization is yet to be addressed by employing quantitative methods in academic literature. Hence, we propose the continuation of research work on this field, furthermore needed due to the new holistic capabilities from modern information systems employed in organizations. 2.3. The relevance of the information technology instrument in technology acceptance The core premise of information system studies is based on the centrality of emerging technologies reshaping management practices and changing the nature of work in an organization.[75] However, the economic analysis of technological innovation includes several factors that might be expected to influence innovation, except for any discussion of the technology itself.[76] The implementation and effective application of information systems must follow a correct analysis of how the technological instrument fits within the dynamics of the organization and how this implementation process is going to affect such dynamics, following a pattern where the management proceeds with disjoint periods of intensive implementation, rather than with continuous improvement.[77] The fact that information systems are becoming increasingly complex has implications for IT adoption decision processes and managerial implementation decisions,[78] where organizational institutions and processes support the sharing of knowledge within institutions and facilitate collaboration in linking available knowledge into practice.[79] Therefore, it is important to mention that the proper application of technological change in an organization requires important leadership skills, such as awareness, acceleration, and harmonization of digital transformation.[80] 3. Limitations While this review provides a comprehensive analysis of existing literature, we acknowledge certain limitations. Firstly, despite the theoretical proposition of a link between “Behavior” and “Training” within our framework (as depicted in Figure 1), the current review is constrained by the absence of quantitative data to empirically validate this hypothesized relationship. While literature provides conceptual support for this connection, the lack of quantitative evidence requires further investigation. A mixed-methods approach, combining qualitative literature insights with quantitative empirical evidence, would offer a more comprehensive understanding of the organizational nature of technology acceptance. Secondly, this research has focused on examining the constructs within the TAM and their relevance to organizational knowledge creation dynamics. While this analysis provides valuable insights, it does not include a comparative analysis of other important technology acceptance models and their applicability to understanding organizational knowledge creation. Future academic work could explore alternative models, such as the Unified Theory of Acceptance and Use of Technology (UTAUT) or the Innovation Diffusion Theory, in the context of organizational knowledge dynamics, offering a more comprehensive understanding of different perspectives on technological adoption within organizations and its impact on knowledge creation processes. Thirdly, the well-established nature of technology acceptance theories presents both advantages and limitations. TAM literature provides a robust theoretical foundation, but it also raises the potential for findings to appear repetitive, diminishing the perceived novelty of current research. This review focuses on analyzing influential publications within the TAM domain to explore evidence of the organizational character of individual technology adoption in renowned academic papers. By re-evaluating these established contributions through the lens of organizational knowledge creation, this research aims to offer a fresh perspective on the insights provided by these foundational works, acknowledging the evolutionary nature of academic inquiry, where established theories are continually re-examined and re-interpreted, considering evolving organizational contexts. Conclusion From a thorough scoping review of academic literature, we conclude that individual information system acceptance is shaped by organizational dynamics that create and amplify organizational knowledge. There is sufficient evidence in the literature to affirm that the acceptance and use of information systems in organizational contexts respond to organizational goals and commitments rather than individual beliefs and attitudes alone. Likewise, users adapt their behavior and use practices to the complex characteristics of modern information systems, which not only serve a single determined task, but combine several levels of action to collect, process, analyze, share, visualize, and recommend improvement at once. Technology acceptance is a vibrant field of academic research, much needed to bring understanding of the fast-paced development of technologies that become more complex and autonomous. Investigating current trends in technology adoption by applying older methods, such as TAM, could impact the credibility of the studies by resulting in reporting significant results that may not happen when applying novel methods. Thus, the need to perform analysis with different models and methodologies and comparing the results of the mentioned could bring a clear understanding of current technology acceptance that shows change over time. References: Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2); Alsharida, R. A., Hammood, M. M., Al-Emran, M. (2021). Mobile Learning Adoption: A Systematic Review of the Technology Acceptance Model from 2017 to 2020. International Journal of Emerging Technologies in Learning, 16(5); Anthony, C. (2018). To Question or Accept? How Status Differences Influence Responses to New Epistemic Technologies in Knowledge Work. Academy of Management Review, 43(4); Bagozzi, R. P. (2007). The Legacy of the Technology Acceptance Model and a Proposal for Paradigm Shift. Journal of the Association for Information Systems, 8(4); Bandura, A. (2001). Social Cognitive Theory: An Agentic Perspective. Annual Review of Psychology, 52; Benbasat, I., Barki, H. (2007). Quo Vadis, TAM? Journal of the Association for Information Systems, 8(4); Bharadwaj, A. S. (2000). A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation. MIS Quarterly, 24(1); Coase, R. H. (1937). The Nature of the Firm. Economica. Blackwell Publishing, 4(16); Compeau, D., Correia, J., Thatcher, J.B. (2022). When Constructs Become Obsolete: A Systematic Approach to Evaluating and Updating Constructs for Information Systems Research. MIS Quarterly, 46(2); Davis, F., Bagozzi, R., Warshaw, P. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8); Felipe, C. M., Leidner, D. E., Roldan, J. L., Leal-Rodriguez, A. L. (2020). Impact of IS Capabilities on Firm Performance: The Roles of Organizational Agility and Industry Technology Intensity. Decision Sciences, 51(3); Figueiredo, D., Schonewille, M. (2025). Instructor-centered Case Generation with GenAI: A Design-based Exploration. Journal of Ethics in Entrepreneurship and Technology. <DOI:10.1108/JEET-06-2025-0038>; Gefen, D., Kaharanna, E., Straub, D. W. (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27 (1); Hanelt, A., Bohnsack, R., Marz, D., Antunes Marante, C. (2021). A Systematic Review of the Literature on Digital Transformation: Insights and Implications for Strategy and Organizational Change. Journal of Management Studies, 58(5); Hayek, F. A. (1945). The Use of Knowledge in Society. American Economic Review, 35(4); Jen, W., Lu, T., Liu, P. T. (2009). An Integrated Analysis of Technology Acceptance Behavior Models: Comparison of Three Major Models. MIS Review, 15(1); Karim, S., Kaul, A. (2015). Structural Recombination and Innovation: Unlocking Intraorganizational Knowledge Synergy Through Structural Change. Organization Science, 26(2); Kork, A-A., Martinnen, M., Laihonen, H., Ruusuvuori, J., Ahonen, J. E., and Kankaanpää, E. (2025). Implementing Clinical Practice Guidelines into Action: A Qualitative Study of Managing Knowledge Translation in Primary Care Organizations. Health Research Policy and Systems (2025) 23:130. <DOI:10.1186/s12961-025-01402-z>; Legris, P., Ingham, J., Collerette, P. (2003). Why do People use Information Technology? A Critical Review of the Technology Acceptance Model. Information & Management, 40 (2003); Monteiro, E., Parmiggiani, E. (2019). Synthetic Knowledge: The Politics of the Internet of Things. MIS Quarterly, 43(1); Muller, S., von Kramer, A., Tonnies, J., Wildenauer, A., Wensing, M., Friederich, H. C., Haun, M. K. (2025). Engaging Underrepresented Patient Groups in Specialized Treatment – Qualitative Results from the PROVIDE-C Randomized Trial on Integral Mental Health Video Consultations for Depression and Anxiety. BMC Public Health (2025) 25:3817. <DOI:10.1186/s12889-025-25235-1>; Mullins, J. K., Cronan, T. P. (2021). Enterprise Systems Knowledge, Beliefs, and Attitude: A Model of Informed Technology Acceptance. International Journal of Information Management, 59 (2021), 102348; Murray, A., Rhymer, J., Sirmon, D.G. (2021). Humans and Technology: Forms of Cojoined Agency in Organizations. Academy of Management Review, 46(3); Nass, C. (1994). Knowledge or Skills: Which do Administrators Learn from Experience? Organization Science, 5(1); Nonaka, I. (1994). A Dynamic Theory of Organizational Knowledge Creation. Organization Science, 5(1). Orlikowski, W., Iacono, C. S. (2001). Research Commentary: Desperately Seeking the “IT” in IT Research - A Call to Theorizing the IT Artifact. Information Systems Research, 12(2); Philip, J. (2022). A Perspective of Embracing Emerging Technologies Research for Organizational Behavior. Organization Management Journal, 19(3); Powell, W. W., Snellman, K. (2004). The Knowledge Economy. Annual Review of Sociology, (30); Reich, B. H., Benbasat, I. (2000). Factors that Influence the Social Dimension of Alignment Between Business and Information Technology Objectives. MIS Quarterly, 24(1); Stadler, C., Helfat, C., Verona, G. (2022). Transferring Knowledge by Transferring Individuals: Innovative Technology Usage and Organizational Performance in Multi-Unit Firms. Organizational Science, 33(1); Swanson, E. B. (2019). Technology as a Routine Capability. MIS Quarterly, 43(3); Szajna, B. (1996). Empirical Evaluation of the Revised Technology Acceptance Model. Management Science, 42(1); Venkatesh, V., Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2); Yang, L., Sheng, X., Lin, J., Wang, W., Wu, W., Lin, R., Liu, A., Liu, L. (2025). Acceptance Scale for Traditional Chinese Medicine Techniques in Cancer Patients: Development and Validation. Patients: Preference and Adherence, 2025(19). <DOI:10.2147/PPA.S550541>. Footnotes [1] Powell, W. W., Snellman, K. (2004). The Knowledge Economy. Annual Review of Sociology, (30), 199-220. [2] Swanson, E. B. (2019). Technology as a Routine Capability. MIS Quarterly, 43(3), 1007-1024. [3] Murray, A., Rhymer, J., Sirmon, D.G. (2021). Humans and Technology: Forms of Cojoined Agency in Organizations. Academy of Management Review, 46(3), 552-571. [4] Anthony, C. (2018). To Question or Accept? How Status Differences Influence Responses to New Epistemic Technologies in Knowledge Work. Academy of Management Review, 43(4), 661-679. [5] Jen, W., Lu, T., Liu, P. T. (2009). An Integrated Analysis of Technology Acceptance Behavior Models: Comparison of Three Major Models. MIS Review, 15(1), 89-121. [6] Venkatesh, V., Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273-315. [7] Gefen, D., Kaharanna, E., Straub, D. W. (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27 (1), 51-90. [8] Davis, F., Bagozzi, R., Warshaw, P. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982-1003. [9] Nonaka, I. (1994). A Dynamic Theory of Organizational Knowledge Creation. Organization Science, 5(1), 14-37. [10] Ibid. [11] Venkatesh, V., Bala, H. (2008). Ibid. [12] Mullins, J. K., Cronan, T. P. (2021). Enterprise Systems Knowledge, Beliefs, and Attitude: A Model of Informed Technology Acceptance. International Journal of Information Management, 59 (2021), 102348. [13] Orlikowski, W., Iacono, C. S. (2001). Research Commentary: Desperately Seeking the “IT” in IT Research - A Call to Theorizing the IT Artifact. Information Systems Research, 12(2), 121-134. [14] Yang, L., Sheng, X., Lin, J., Wang, W., Wu, W., Lin, R., Liu, A., Liu, L. (2025). Acceptance Scale for Traditional Chinese Medicine Techniques in Cancer Patients: Development and Validation. Patients: Preference and Adherence, 2025(19), 305-3225. <DOI:10.2147/PPA.S550541>. [15] Muller, S., von Kramer, A., Tonnies, J., Wildenauer, A., Wensing, M., Friederich, H. C., Haun, M. K. (2025). Engaging Underrepresented Patient Groups in Specialized Treatment – Qualitative Results from the PROVIDE-C Randomized Trial on Integral Mental Health Video Consultations for Depression and Anxiety. BMC Public Health (2025) 25:3817. <DOI:10.1186/s12889-025-25235-1>. [16] Davis et al. (1989). Ibid. [17] Alsharida, R. A., Hammood, M. M., Al-Emran, M. (2021). Mobile Learning Adoption: A Systematic Review of the Technology Acceptance Model from 2017 to 2020. International Journal of Emerging Technologies in Learning, 16(5), 147-162. [18] Venkatesh, V., Bala, H. (2008). Ibid. [19] Davis et al. (1989). Ibid. [20] Ibid. [21] Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. [22] Nonaka, I. (1994). Ibid. [23] Monteiro, E., Parmiggiani, E. (2019). Synthetic Knowledge: The Politics of the Internet of Things. MIS Quarterly, 43(1), 167-184. [24] Nonaka, I. (1994). Ibid. [25] Benbasat, I., Barki, H. (2007). Quo Vadis, TAM? Journal of the Association for Information Systems, 8(4), 211-218. [26] Legris, P., Ingham, J., Collerette, P. (2003). Why do People use Information Technology? A Critical Review of the Technology Acceptance Model. Information & Management, 40 (2003), 191-204. [27] Szajna, B. (1996). Empirical Evaluation of the Revised Technology Acceptance Model. Management Science, 42(1), 85-92. [28] Legris et al. (2003). Ibid. [29] Gefen et al. (2003). Ibid. [30] Bandura, A. (2001). Social Cognitive Theory: An Agentic Perspective. Annual Review of Psychology, 52, 1-26. [31] Szajna, B. (1996). Ibid. [32] Bagozzi, R. P. (2007). The Legacy of the Technology Acceptance Model and a Proposal for Paradigm Shift. Journal of the Association for Information Systems, 8(4), 244-254. [33] Davis et al. (1989). Ibid. [34] Gefen et al. (2003). Ibid. [35] Venkatesh, V., Bala, H. (2008). Ibid. [36] Mullins, J. K., Cronan, T. P. (2021). Ibid. [37] Davis et al. (1989). Ibid. [38] Ibid. [39] Szajna, B. (1996). Ibid. [40] Davis et al. (1989). Ibid. [41] Venkatesh, V., Bala, H. (2008). Ibid. [42] Nonaka, I. (1994). Ibid. [43] Davis et al. (1989). Ibid. [44] Ibid. [45] Mullins, J. K., Cronan, T. P. (2021). Ibid. [46] Ibid. [47] Venkatesh, V., Bala, H. (2008). Ibid. [48] Davis et al. (1989). Ibid. [49] Szajna, B. (1996). Ibid. [50] Venkatesh, V., Bala, H. (2008). Ibid. [51] Nass, C. (1994). Knowledge or Skills: Which do Administrators Learn from Experience? Organization Science, 5(1), 38-50. [52] Monteiro, E., Parmiggiani, E. (2019). Ibid. [53] Karim, S., Kaul, A. (2015). Structural Recombination and Innovation: Unlocking Intraorganizational Knowledge Synergy Through Structural Change. Organization Science, 26(2), 439-455. [54] Bharadwaj, A. S. (2000). A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation. MIS Quarterly, 24(1), 169-196. [55] Coase, R. H. (1937). The Nature of the Firm. Economica. Blackwell Publishing, 4(16), 386-405. [56] Hayek, F. A. (1945). The Use of Knowledge in Society. American Economic Review, 35(4), 519-520. [57] Nonaka, I. (1994). Ibid. [58] Reich, B. H., Benbasat, I. (2000). Factors that Influence the Social Dimension of Alignment Between Business and Information Technology Objectives. MIS Quarterly, 24(1), 81-113. [59] Nass, C. (1994). Ibid. [60] Karim, S., Kaul, A. (2015). Ibid. [61] Bharadwaj, A. S. (2000). Ibid. [62] Bagozzi, R. P. (2007). Ibid. [63] Ibid. [64] Orlikowski, W., Iacono, C. S. (2001). Ibid. [65] Bagozzi, R. P. (2007). Ibid. [66] Legris et al. (2003). Ibid. [67] Benbasat, I., Barki, H. (2007). Ibid. [68] Orlikowski, W., Iacono, C. S. (2001). Ibid. [69] Compeau, D., Correia, J., Thatcher, J.B. (2022). When Constructs Become Obsolete: A Systematic Approach to Evaluating and Updating Constructs for Information Systems Research. MIS Quarterly, 46(2), 679-711. [70] Szajna, B. (1996). Ibid. [71] Figueiredo, D., Schonewille, M. (2025). Instructor-centered Case Generation with GenAI: A Design-based Exploration. Journal of Ethics in Entrepreneurship and Technology. <DOI:10.1108/JEET-06-2025-0038>. [72] Bharadwaj, A. S. (2000). Ibid. [73] Felipe, C. M., Leidner, D. E., Roldan, J. L., Leal-Rodriguez, A. L. (2020). Impact of IS Capabilities on Firm Performance: The Roles of Organizational Agility and Industry Technology Intensity. Decision Sciences, 51(3), 575-619. [74] Stadler, C., Helfat, C., Verona, G. (2022). Transferring Knowledge by Transferring Individuals: Innovative Technology Usage and Organizational Performance in Multi-Unit Firms. Organizational Science, 33(1), 253-274. [75] Philip, J. (2022). A Perspective of Embracing Emerging Technologies Research for Organizational Behavior. Organization Management Journal, 19(3), 88-98. [76] Orlikowski, W., Iacono, C.S. (2001). Ibid. [77] Legris et al. (2003). Ibid. [78] Venkatesh, V., Bala, H. (2008). Ibid. [79] Kork, A-A., Martinnen, M., Laihonen, H., Ruusuvuori, J., Ahonen, J. E., and Kankaanpää, E. (2025). Implementing Clinical Practice Guidelines into Action: A Qualitative Study of Managing Knowledge Translation in Primary Care Organizations. Health Research Policy and Systems (2025) 23:130. <DOI:10.1186/s12961-025-01402-z>. [80] Hanelt, A., Bohnsack, R., Marz, D., Antunes Marante, C. (2021). A Systematic Review of the Literature on Digital Transformation: Insights and Implications for Strategy and Organizational Change. Journal of Management Studies, 58(5), 1159-1197.
Spatial-Territorial Aspects of Regional Development Planning: The Case of Borjomi Municipality
This article analyzes the spatial-territorial structure of Borjomi Municipality through the lens of polycentric regional development, functional specialization, and seasonal economic dynamics. Drawing on qualitative field observations, semi-structured interviews, and the examination of municipal planning documents, the study evaluates how the municipality’s three dominant nodes—Borjomi–Likani, Bakuriani, and the seasonal corridor villages—shape local development patterns and influence the distribution of economic activity, mobility flows, and service accessibility. Findings show that tourism-driven functions are heavily concentrated within the two major nodes, while peripheral settlements remain dependent on short seasonal cycles and underdeveloped infrastructure. The research also identifies significant gaps in rural–urban value-chain integration, particularly the limited participation of local agricultural producers in the tourism supply system. These spatial and functional disparities underscore the challenges of achieving balanced and resilient development in mountainous regions. By situating the Borjomi case within broader theoretical discussions on polycentricity and place-based development, the study demonstrates how spatial coordination and targeted policy interventions can enhance territorial cohesion and support sustainable development in structurally diverse municipalities. Keywords: Regional development; spatial planning; tourism economy. Introduction Efficient regional development planning in mountainous countries requires a clear understanding of spatial-territorial structures, functional linkages, and the internal logic of settlement systems. In contemporary economic geography, spatial development is increasingly conceptualized through the lens of polycentricity, agglomeration effects, and spatial cohesion.[1] These ideas have been broadly discussed in economic and regional development literature, including works by Georgian scholars who emphasize the role of territorial organization, functional specialization, and spatial efficiency in shaping development trajectories.[2] Although their approaches vary, the literature converges on the notion that spatial structure fundamentally conditions the distribution of population, economic activity, and investment potential. In Georgia’s mountainous municipalities, spatial-territorial planning is linked not only to economic growth prospects but also to demographic sustainability, access to services, and the rational allocation of public resources.[3] Research on post-transition regional development shows that fragmented territorial policies and “one-size-fits-all” approaches often exacerbate disparities between central and peripheral settlements.[4] Likewise, studies on functional specialization and regional competitiveness argue that the concentration of infrastructure and economic functions in selected nodes can generate spillover benefits if the system is well connected but may deepen inequalities under weak institutional or infrastructural conditions.[5] Regional planning literature also underlines the importance of recognizing territorial heterogeneity and designing policies suited to specific functional zones, especially in tourism-led regions.[6] Against this theoretical background, Borjomi Municipality represents a particularly informative case. Located in the Samtskhe–Javakheti region, Borjomi is one of Georgia’s most significant tourism destinations, distinguished by mineral springs, national parks, mountainous landscapes, and year-round recreational resources. Yet despite the municipality’s strategic importance, its spatial-territorial structure is uneven and highly seasonal, with substantial economic concentration in a limited number of settlements. For this study, Borjomi is conceptualized as a polycentric municipality composed of three dominant nodes: Borjomi–Likani as the administrative and service center, Bakuriani as a winter-specialized ski resort, and the seasonal villages along the Borjomi–Bakuriani corridor (e.g., Tsemi, Kimotesubani, Tsagveri), where economic activity fluctuates significantly between summer and winter tourism seasons.[7] These nodes differ substantially in function, infrastructure, and economic potential. Spatial disparities between them shape the municipality’s overall development trajectory, influencing labor mobility, business activity, property markets, and the availability of services. Field observations and qualitative interviews conducted in Borjomi reveal that many peripheral settlements remain deeply dependent on seasonal flows and on the economic vitality generated within the main nodes. The relevance of this research is strengthened by Georgia’s ongoing regional policy reforms, which aim to enhance territorial cohesion and support decentralized development. However, policy implementation often remains fragmented, with limited integration between spatial planning, economic strategies, and tourism development.[8] By examining Borjomi’s polycentric spatial structure, this study contributes to a more informed understanding of how functional nodes operate within mountainous municipalities and how targeted spatial interventions can generate more balanced and resilient development. International literature offers extensive conceptual foundations for understanding spatial-territorial development in complex geographies such as mountainous regions. European spatial planning research widely emphasizes the role of polycentric development[9] as a mechanism for reducing regional disparities and supporting balanced territorial growth.[10] Theories of agglomeration and spatial clustering, grounded in the works of Fujita et al.,[11] highlight how economic activities gravitate toward nodes with superior accessibility and infrastructure, reinforcing both opportunities and inequalities within regional systems. At the same time, New Regionalism frameworks stress the importance of relational connectivity, local institutional capacity, and place-based policy approaches.[12] Tourism-dependent regions, particularly in mountainous settings, have been shown to experience structural seasonality, fragmented value chains, and uneven development trajectories when governance and spatial planning fail to integrate peripheral settlements effectively.[13] These international perspectives complement the Georgian context by underscoring that polycentricity, functional linkages, and spatially coordinated territorial policy are essential for building resilience and ensuring inclusive development across differentiated settlement systems. Methodology This study aims to analyze Borjomi Municipality’s spatial-territorial structure through the lens of polycentric development and to assess how functional nodes, seasonal patterns, and value-chain dynamics shape local economic outcomes. The research objectives include: (1) identifying the dominant spatial-functional centers within the municipality; (2) assessing their linkages and disparities; (3) examining seasonal fluctuations and settlement-level dependencies; and (4) evaluating the extent to which local producers participate in tourism-driven value chains. The methodology applies qualitative fieldwork conducted in Borjomi Municipality, including semi-structured interviews with residents and local business representatives, direct observations, and the interpretation of municipal planning documents and secondary statistical data. A comparative, place-based analytical framework is used to understand how spatial concentration and functional specialization generate uneven development patterns in mountainous regions. Spatial–Territorial Structure and Functional Dynamics of Borjomi Municipality The spatial–territorial configuration of Borjomi Municipality reflects the interaction between mountainous geomorphology, transportation corridors, and a tourism-driven local economy. Field observations and qualitative interviews conducted during the research reveal that Borjomi operates as a polycentric settlement system, within which three dominant nodes—Borjomi–Likani, Bakuriani, and the corridor villages—perform distinct but interconnected functions. These nodes exhibit asymmetrical economic weight, divergent seasonal profiles, and varying degrees of infrastructural maturity, shaping the municipality’s internal spatial logic and development opportunities. Borjomi–Likani as the Administrative, Service, and Health-Tourism Core: The Borjomi–Likani cluster constitutes the municipality’s most consolidated urban center, serving simultaneously as its administrative hub and its primary year-round tourism destination. The research indicates several defining characteristics: Concentration of administrative institutions, public services, and social infrastructure, which anchors stable employment opportunities and public-sector mobility; Developed hospitality and wellness sectors, supported by mineral springs, health resorts, and access to Borjomi–Kharagauli National Park; High density of commercial services, including hotels, guesthouses, retail, and dining establishments that attract both domestic and international visitors; Strong nodal influence, as residents from surrounding villages rely on Borjomi–Likani for education, healthcare, administrative procedures, and market access. These attributes position Borjomi–Likani as the municipality’s primary functional center, generating regular commuter flows and acting as the infrastructural and economic “anchor” of the broader spatial system. Bakuriani as a Rapidly Transforming Winter Resort Node: Bakuriani represents the municipality’s second major node, distinguished by its dynamic transformation into a winter-sport and recreational destination. The analysis reveals that: Winter tourism specialization—particularly ski infrastructure—remains Bakuriani’s dominant economic driver; Rapid urbanization and large-scale real-estate development have reshaped the built environment, often outpacing municipal planning capacity; Expanding but uneven year-round tourism potential is emerging due to new service offerings, although seasonality remains pronounced; High concentration of hotels, rental apartments, and tourism services, primarily catering to winter visitors. These dynamics illustrate a tourism-intensive node heavily influenced by private investment and national-level infrastructural initiatives, yet still challenged by spatial seasonality and the need for diversified functional capacity. Seasonal Villages along the Borjomi–Bakuriani Corridor: A third set of nodes—Tsemi, Kimotesubani, Tsagveri, and other settlements along the Borjomi–Bakuriani road—constitute the municipality’s most seasonally sensitive area. The research identifies several shared characteristics: Pronounced seasonal fluctuations, with peak economic activity during the summer season and significantly reduced demand during winter; Economic dependence on transit flows, with livelihoods tied to passing tourists and the tourism cycles of Borjomi–Likani and Bakuriani; Limited permanent employment opportunities and a reliance on small-scale hospitality, roadside commerce, or temporary migration; Underdeveloped physical and service infrastructure constrains their potential to function as autonomous development nodes. These corridor villages operate as intermediary spaces within the municipality’s spatial system but lack sufficient functional specialization or investment to generate sustained economic activity. Seasonal Dynamics and Implications for Local Livelihoods - Seasonality emerged as a central theme in the research, shaping household strategies, business operations, and spatial interactions: Summer constitutes the primary peak season in Borjomi–Likani, while winter dominates in Bakuriani, creating dual but unaligned seasonal cycles; Corridor villages rely heavily on short periods of tourism-driven demand, making income highly volatile; Mixed livelihood strategies, including temporary out-migration to Tbilisi or other urban centers, are widespread among working-age residents; Local agricultural producers face systemic barriers—including small production volumes, certification requirements, and logistical challenges—preventing them from entering tourism-related supply chains. Consequently, a significant share of goods consumed in Borjomi and Bakuriani is imported from major cities, resulting in weak local value-chain integration and missed economic opportunities for rural households. Functional Linkages, Mobility Patterns, and Spatial Interactions - The research highlights substantial disparities in the strength and direction of functional linkages among the nodes: Borjomi–Bakuriani mobility flows are strong but highly seasonal, reflecting the tourism calendar and road accessibility; Corridor villages benefit from transit flows, but their economic engagement remains marginal due to limited-service diversification; Backward linkages between tourism enterprises and rural producers are weak, diminishing potential multiplier effects within the municipality; Infrastructure quality and winter road conditions significantly influence the fluidity of spatial interactions, particularly between Bakuriani and smaller villages. These patterns underline that spatial proximity does not automatically translate into functional integration—connectivity, economic incentives, and institutional support play decisive roles. Structural Challenges to Balanced Spatial Development - The analysis identifies several structural barriers that hinder balanced development across the municipality: Strong dependence on tourism and narrow functional specialization create vulnerability to seasonal and external shocks; Insufficient year-round employment opportunities outside Borjomi–Likani, contributing to labor out-migration; Demographic pressures, including seasonal depopulation and long-term population decline in smaller settlements; Fragmented territorial planning processes often lack strategic coordination between economic, tourism, and spatial development policies; Weak integration of rural production systems into urban tourism markets is limiting the emergence of local value chains. These challenges collectively constrain the municipality’s ability to strengthen its polycentric structure and develop resilient functional zones. Conclusion The research demonstrates that Borjomi Municipality’s development trajectory is fundamentally shaped by its polycentric but asymmetrical spatial structure, where three dominant nodes—Borjomi–Likani, Bakuriani, and the seasonal corridor villages—perform distinct and unequally developed functions. Field observations, interviews, and comparative spatial analysis reveal that while the municipality possesses strong tourism assets and significant economic potential, these benefits are distributed unevenly across the territory. Borjomi–Likani functions as a consolidated year-round administrative and service center, while Bakuriani has evolved into a rapidly transforming, investment-driven mountain resort with strong winter specialization. In contrast, the corridor villages remain structurally peripheral, with livelihoods tied to highly seasonal demand and insufficient integration into municipal development processes. Seasonality emerged as the most influential factor shaping economic activity, mobility patterns, and household strategies. Divergent seasonal cycles between Borjomi–Likani (summer peak) and Bakuriani (winter peak) create temporal fragmentation within the municipality, limiting opportunities for stable year-round employment and reinforcing dependency on short peak periods. This, in turn, contributes to temporary migration, income volatility, and uneven service provision. Furthermore, the research highlights a major structural challenge: the weak integration of local agricultural producers into tourism-sector value chains. Despite strong theoretical potential for rural–urban economic synergies, empirical evidence shows persistent logistical, quality-standard, and institutional gaps that prevent local producers from supplying hotels and restaurants in either main node. The findings also reveal that functional linkages between nodes—although geographically proximate—are insufficiently coordinated. Transport connectivity, road quality, and winter accessibility affect mobility patterns, while fragmented planning processes and limited inter-sectoral coordination weaken opportunities for integrated spatial development. Together, these dynamics underscore that Borjomi’s current spatial configuration is neither fully cohesive nor economically optimized. Strengthening polycentricity therefore requires more than the existence of multiple nodes—it requires policy instruments that enhance their complementarities, reduce disparities, and support functional diversification across the municipality. Overall, the study contributes to regional development literature by empirically illustrating how spatial organization, functional specialization, and seasonality jointly produce uneven development outcomes in mountainous municipalities. A place-based, polycentric planning approach presents a viable path forward, but only if supported by targeted interventions that address structural constraints and promote more balanced territorial development. Recommendations Based on the research findings, several policy and planning recommendations emerge that could support more equitable and resilient spatial development in Borjomi Municipality. These recommendations emphasize the need for integrated territorial strategies, diversified economic functions, and strengthened local value chains[14]. Strengthen Functional Polycentricity through Coordinated Spatial Planning - The municipality should adopt a more explicit polycentric development framework, recognizing the differentiated roles of Borjomi–Likani, Bakuriani, and the corridor villages. Strategic spatial planning should ensure: coordinated investments across nodes rather than isolated, project-based interventions; development of complementary functions rather than duplication of services; balanced allocation of infrastructure and public services to reduce peripheral disadvantage. Reduce Seasonal Vulnerability through Economic Diversification - Given the dual and unaligned seasonal cycles, the municipality should promote activities capable of providing year-round income. This includes: expanding wellness, eco-tourism, and cultural tourism in Borjomi–Likani beyond peak periods; supporting off-season tourism offerings in Bakuriani to extend its economic calendar; incentivizing small-scale, experience-based tourism (e.g., agro-tourism, homestays) in corridor villages to stabilize local incomes. Improve Rural–Urban Value Chain Integration - To address weak backward linkages between tourism enterprises and local producers, the following measures are recommended: establishing aggregation, storage, or logistics centers to consolidate small farm outputs; supporting producers in meeting certification and quality standards required by hotels and restaurants; creating municipal partnership programs that connect farmers directly with tourism businesses (e.g., “Buy Local Borjomi” initiatives); introducing training programs on processing, packaging, and supply-chain management. Enhance Transport and Mobility Infrastructure - Reliable connectivity is essential for spatial cohesion. Investments should prioritize: improved winter road maintenance between Borjomi and Bakuriani; upgraded public transport options to strengthen functional mobility between villages and main centers; accessibility enhancements in corridor villages, enabling them to participate more actively in tourism flows. Address Demographic Pressures and Support Peripheral Settlements - Smaller settlements require targeted interventions to mitigate depopulation and ensure long-term resilience. Recommended actions include: decentralizing select administrative or social services into larger villages; improving digital infrastructure to support remote work and small service businesses; providing incentives for young households and entrepreneurs to remain in or relocate to peripheral areas. Strengthen Institutional Coordination and Strategic Governance - The research identifies fragmented planning as a major constraint. To overcome this: municipal authorities should integrate spatial, tourism, agricultural, and economic strategies into a unified development framework; inter-agency and public–private cooperation should be enhanced to ensure coherent policy implementation; Data collection and monitoring systems should be improved to enable evidence-based decision-making. References: Amin, A. (2004). Regions unbound: Towards a new politics of place. Geografiska Annaler: Series B, Human Geography, 86(1). <https://doi.org/10.1111/j.0435-3684.2004.00152.x>; Barca, F. (2009). An agenda for a reformed cohesion policy: A place-based approach to meeting European Union challenges and expectations. European Commission; Bedianashvili, G. (2018). Culture as a factor of knowledge economics with paradigmatic changes in systemic institutional context. Globalization and Business, 4(6). <https://doi.org/10.35945/gb.2018.06.007>. (in Georgian); Bedianashvili, G. (2022). The problem of assessing the expected consequences of economic policy. Globalization and Business, 7(13), 17–24. <https://doi.org/10.35945/gb.2022.13.002>. (in Georgian); Bedianashvili, G., Ivanov, Y. B., Paientko, T. V. (2019). Tax reforms in Ukraine and Georgia: Changing priorities. Journal of Tax Reform, 5(2), 107–128. <https://doi.org/10.15826/jtr.2019.5.2.063>; Briedenhann, J., Wickens, E. (2004). Tourism routes as a tool for the economic development of rural areas—Vibrant hope or impossible dream? Tourism Management, 25(1). <https://doi.org/10.1016/S0261-5177(03)00063-3>; (2019). ESPON Policy Brief: The territorial dimension of future EU policies. European Spatial Planning Observatory Network; Fujita, M., Krugman, P., Venables, A. J. (1999). The spatial economy: Cities, regions, and international trade. MIT Press; Jibuti, M. (2025). Enhancing regional development in Georgia: Integrating functional spatial planning and land use modeling for sustainable economic growth. International Journal of Social Sciences, 14(1), 23–34. <https://doi.org/10.52950/SS.2025.14.1.002>; Jibuti, M. (2021). On the usage of old and modern technologies for economic sustainability. Globalization and Business, 6(11), 97-100. <https://doi.org/10.35945/gb.2021.11.013>; Jibuti, M. (2019). Administrative division, regions of Georgia and their characteristics. Globalization and Business, 4(8). <https://doi.org/10.35945/gb.2019.08.016>; Keshelashvili, G. (2016). General strategies of Georgian winemaking companies’ management in the conditions of integrated development. In Proceedings of the 23rd International Academic Conference, Venice (pp. 242-251). <https://doi.org/10.20472/IAC.2016.023.049>; Keshelashvili, G. (2017). Characteristics of management of agricultural cooperatives in Georgia. In Proceedings of the 32nd International Academic Conference, Geneva (pp. 207–218). IISES. <https://doi.org/10.20472/IAC.2017.032.020>; Keshelashvili, G. (2018). Value chain management in agribusiness. International Journal of Business and Management, 6(2). <https://doi.org/10.20472/BM.2018.6.2.004>; Keshelashvili, G. (2024). The role of business in achieving sustainable development and need of changes in managerial attitude: The case of Georgia. Proceedings of the International Conference on Economics, Finance & Business, Vienna, 2024, pp. 37–49. International Institute of Social and Economic Sciences. <https://doi.org/10.20472/EFC.2024.020.003>; Keshelashvili, G. (2025). Sustainable business practices in Georgian SMEs: Assessment, needs, and strategic perspectives. International Journal of Social Sciences, 14(1), 35–51. <https://doi.org/10.52950/SS.2025.14.1.003>; Kharaishvili, E. (2020). Methodological features of determining the level of competitiveness in the agri-food sector of Georgia. Globalization and Business, 5(10). <https://doi.org/10.35945/gb.2020.10.004>. (in Georgian); Kharaishvili, E., Suknishvili, M. (2021). Agribusiness development trends in Georgia: Modern challenges and solutions. Ecology. Socium, 5(4). <https://doi.org/10.31520/2616-7107/2021.5.4-4>; Kharaishvili, E., & Talikadze, N. (2022). Competitiveness characteristics of agri-food products – What does the consumer choose? (Case of Georgia). Innovative Marketing, 18(1), 195–207. <https://doi.org/10.21511/im.18(1).2022.16>; Meijers, E. (2008). Measuring polycentricity and its promises. European Planning Studies, 16(9). <https://doi.org/10.1080/09654310802401805>; Mekvabishvili, E. (2019). The economic role of the state in conditions of globalization. Globalization and Business, 4(8). <https://doi.org/10.35945/gb.2019.08.002>; Mekvabishvili, E. (2020). The anti-crisis role of the state (Based on the experience of the global financial and corona-economic crisis). Globalization and Business, 7(10), 35–41. <https://doi.org/10.35945/gb.2020.10.003>; Nepal, S. K., Saarinen, J. (2016). Political ecology and tourism. Routledge; Papava, V. (2014). The catch-up effect and regional comparisons of growth indicators: With the Eastern Partnership countries as an example. Problems of Economic Transition, 57(3). <https://doi.org/10.2753/PET1061-1991570301>; Papava, V. (2014). Georgia’s economy: The search for a development model. Problems of Economic Transition, 57(3), 13–24. <https://doi.org/10.2753/PET1061-1991570304>; Papava, V. (2017). A Eurasian or a European future for post-Soviet Georgia’s economic development: Which is better? Archives of Business Research, 5(1), 159–170. <https://doi.org/10.14738/abr.51.2651>; Silagadze, A. (2013). Priorities for the economy of postcommunist Georgia in the context of the world financial crisis. Problems of Economic Transition, 56(8). <https://doi.org/10.2753/PET1061-1991560801>; Silagadze, A. (2022). Contemporary global economic trends: Transitional economies during Covid Bulletin of the Georgian National Academy of Sciences, 16(3). Footnotes [1] Fujita, M., Krugman, P., Venables, A. J. (1999). The spatial economy: Cities, regions, and international trade. MIT Press. Meijers, E. (2008). Measuring polycentricity and its promises. European Planning Studies, 16(9), 1313–1323. <https://doi.org/10.1080/09654310802401805>. [2] Bedianashvili, G. (2018). Culture as a factor of knowledge economics with paradigmatic changes in systemic institutional context. Globalization and Business, 4(6), 59–66. <https://doi.org/10.35945/gb.2018.06.007>; Keshelashvili, G. (2018). Value chain management in agribusiness. International Journal of Business and Management, 6(2), 59–77. <https://doi.org/10.20472/BM.2018.6.2.004>; Kharaishvili, E. (2020). Methodological features of determining the level of competitiveness in the agri-food sector of Georgia. Globalization and Business, 5(10), 43–49. <https://doi.org/10.35945/gb.2020.10.004>; Papava, V. (2014). The catch-up effect and regional comparisons of growth indicators: With the Eastern Partnership countries as an example. Problems of Economic Transition, 57(3), 3–12. <https://doi.org/10.2753/PET1061-1991570301>; Silagadze, A. (2013). Priorities for the economy of postcommunist Georgia in the context of the world financial crisis. Problems of Economic Transition, 56(8), 3–16. <https://doi.org/10.2753/PET1061-1991560801>; [3] Jibuti, M. (2019). Administrative division, regions of Georgia and their characteristics. Globalization and Business, 4(8), 126–129. <https://doi.org/10.35945/gb.2019.08.016>; Mekvabishvili, E. (2019). The economic role of the state in conditions of globalization. Globalization and Business, 4(8), 22–33. <https://doi.org/10.35945/gb.2019.08.002>; Jibuti, M. (2025). Enhancing regional development in Georgia: Integrating functional spatial planning and land use modeling for sustainable economic growth. International Journal of Social Sciences, 14(1), 23–34. <https://doi.org/10.52950/SS.2025.14.1.002>; Jibuti, M. (2021). On the usage of old and modern technologies for economic sustainability. Globalization and Business, 6(11), 97-100. <https://doi.org/10.35945/gb.2021.11.013>; Keshelashvili, G. (2016). General strategies of Georgian winemaking companies’ management in the conditions of integrated development. In Proceedings of the 23rd International Academic Conference, Venice (pp. 242-251), IISES. <https://doi.org/10.20472/IAC.2016.023.049>; Keshelashvili, G. (2017). Characteristics of management of agricultural cooperatives in Georgia. In Proceedings of the 32nd International Academic Conference, Geneva (pp. 207–218). IISES. <https://doi.org/10.20472/IAC.2017.032.020>. [4] Papava, V. (2014). The catch-up effect and regional comparisons of growth indicators: With the Eastern Partnership countries as an example. Problems of Economic Transition, 57(3), 3–12. <https://doi.org/10.2753/PET1061-1991570301>. [5] Silagadze, A. (2013). Priorities for the economy of postcommunist Georgia in the context of the world financial crisis. Problems of Economic Transition, 56(8), 3–16. <https://doi.org/10.2753/PET1061-1991560801>; Silagadze, A. (2022). Contemporary global economic trends: Transitional economies during Covid Depression. Bulletin of the Georgian National Academy of Sciences, 16(3), pp.130–135. [6] Kharaishvili, E., Suknishvili, M. (2021). Agribusiness development trends in Georgia: Modern challenges and solutions. Economic. Ecology. Socium, 5(4), 29–38. <https://doi.org/10.31520/2616-7107/2021.5.4-4>. [7] Nepal, S. K., Saarinen, J. (2016). Political ecology and tourism. Routledge. [8] Barca, F. (2009). An agenda for a reformed cohesion policy: A place-based approach to meeting European Union challenges and expectations. European Commission. [9] Bedianashvili, G. (2022). The problem of assessing the expected consequences of economic policy. Globalization and Business, 7(13), 17–24. <https://doi.org/10.35945/gb.2022.13.002> (in Georgian); Bedianashvili, G., Ivanov, Y. B., Paientko, T. V. (2019). Tax reforms in Ukraine and Georgia: Changing priorities. Journal of Tax Reform, 5(2), 107–128. <https://doi.org/10.15826/jtr.2019.5.2.063>; Mekvabishvili, E. (2020). The anti-crisis role of the state (Based on the experience of the global financial and corona-economic crisis). Globalization and Business, 7(10), 35–41. <https://doi.org/10.35945/gb.2020.10.003>; Papava, V. (2014). Georgia’s economy: The search for a development model. Problems of Economic Transition, 57(3), 13–24. <https://doi.org/10.2753/PET1061-1991570304>; Papava, V. (2017). A Eurasian or a European future for post-Soviet Georgia’s economic development: Which is better? Archives of Business Research, 5(1), 159–170. <https://doi.org/10.14738/abr.51.2651>. [10] ESPON. (2019). ESPON Policy Brief: The territorial dimension of future EU policies. European Spatial Planning Observatory Network. Meijers, E. (2008). Measuring polycentricity and its promises. European Planning Studies, 16(9), 1313–1323. <https://doi.org/10.1080/09654310802401805>. [11] Fujita, M., Krugman, P., Venables, A. J. (1999). The spatial economy: Cities, regions, and international trade. MIT Press. [12] Amin, A. (2004). Regions unbound: Towards a new politics of place. Geografiska Annaler: Series B, Human Geography, 86(1), 33–44. <https://doi.org/10.1111/j.0435-3684.2004.00152.x>; Barca, F. (2009). An agenda for a reformed cohesion policy: A place-based approach to meeting European Union challenges and expectations. European Commission. [13] Briedenhann, J., Wickens, E. (2004). Tourism routes as a tool for the economic development of rural areas—Vibrant hope or impossible dream? Tourism Management, 25(1), 71–79. <https://doi.org/10.1016/S0261-5177(03)00063-3>; Nepal, S. K., & Saarinen, J. (2016). Political ecology and tourism. Routledge. [14] Keshelashvili, G. (2024). The role of business in achieving sustainable development and need of changes in managerial attitude: The case of Georgia. Proceedings of the International Conference on Economics, Finance & Business, Vienna, 2024, pp. 37–49. International Institute of Social and Economic Sciences. <https://doi.org/10.20472/EFC.2024.020.003>; Keshelashvili, G. (2025). Sustainable business practices in Georgian SMEs: Assessment, needs, and strategic perspectives. International Journal of Social Sciences, 14(1), 35–51. <https://doi.org/10.52950/SS.2025.14.1.003>; Kharaishvili, E., Talikadze, N. (2022). Competitiveness characteristics of agri-food products – What does the consumer choose? (Case of Georgia). Innovative Marketing, 18(1), 195–207. <https://doi.org/10.21511/im.18(1).2022.16>.
Resort Reform in Georgia: Comparative Insights from Eastern Europe
The paper reviews the past and current resort-related regulatory framework in Georgia to identify the main obstacles that slow down resort development. The collapse of the Soviet Union had a disastrous impact on Georgia’s sanatoriums and health resorts. As a result, historically valuable buildings and parks within these areas deteriorated, the number of both residents and visitors steadily declined, and many facilities lost their role in the public health system. However, recent reforms, particularly the Law on Tourism adopted in 2023, have renewed interest in the potential of resorts to attract visitors and foreign investment. Based on a comparative review of the legal and policy frameworks of four Eastern European countries—Bulgaria, Latvia, Lithuania, and Romania—the paper provides insights for the ongoing tourism reform in Georgia. These countries were selected because they share a similar post-Soviet background with Georgia but are also members of the European Union. The comparison revealed differences in legal definitions, recognition procedures, and criteria for resort classification, helping to identify the most effective practices that could be adapted to the Georgian context. From these findings, the paper proposes a new regulatory framework that introduces the concept of “National Resorts” as a quality-assurance mechanism. It also recommends modernizing tourism and resort governance, improving coordination between institutions, and integrating climate-resilience and safety measures to help position Georgia’s resorts as competitive and sustainable destinations within the broader European tourism landscape. Keywords: Resorts, tourism policy, regulatory framework, sustainable development. JEL Classification: L83, Z32, R58. Introduction Resort development began in the early twentieth century, following the Russian Revolution of 1917. During this period, the Soviet government created a wide network of sanatoriums, health resorts, and similar facilities for the purpose of improving the health and well-being of the working population and their families. These initiatives soon spread to other Soviet republics, where resorts became part of the broader system of social welfare and labor protection. Over the following decades, this network grew into a centralized system of sanatoriums, health resorts, and children’s recreation centers that served both medical and leisure purposes. Because of its diverse mountain, climatic, and balneological resources, Georgia became one of the main centers of health tourism in the Soviet Union, attracting visitors from across the country. The collapse of the Soviet Union in the early 1990s created serious challenges for the resort networks across post-Soviet countries. Rapid privatization and the sudden end of government support left many resorts without funds or visitors. Many facilities lost their original public-health role and fell into disrepair, while natural and cultural assets deteriorated through neglect or unregulated use. According to Tutberidze (2021), Georgian resorts today fall into four categories: (1) fully restored and operating destinations such as the Black Sea coast, Tbilisi, Borjomi, Sairme, and Tskaltubo; (2) partially restored resorts under development, including Abastumani and Bakhmaro; (3) seasonal resorts with limited infrastructure, such as Sulori and Lashichala; and (4) resorts with destroyed infrastructure, such as Menji, Tsaishi, and Nabeghlavi. The first comprehensive legal framework governing resorts was the Law of Georgia on Tourism and Resorts (1997), which defined “resorts”, “resort areas,” and “natural curative resources”, approving an official list of 271 resorts and resort areas. This was complemented by the Law on Protective Sanitary Zones of Health Resorts and Resort Areas (2000), which introduced a three-tiered system of sanitary protection zones to safeguard natural healing resources and regulate economic activities. The Law on Tourism, adopted in 2023, repealed the 1997 legislation and required the preparation of a new Law on Resort Activities by 2025, later postponed to 2026. The updated law introduced three key terms: resort, resort area, and resort activity. A resort is defined as a designated location with the necessary infrastructure for resort-related activities. A resort area is a designated territory that has natural healing and therapeutic resources suitable for use, but lacks the infrastructure for resort activities. Resort activities refer to the organized use of natural healing and therapeutic resources and the related infrastructure for prevention, treatment, rehabilitation, and recovery. However, the law does not include a clear definition of natural healing resources, which was a key part of earlier resort classification. Previously, these resources included mineral waters, therapeutic muds, karst caves suitable for treatment, the sea, forests, therapeutic climates, and other natural elements used for prevention and rehabilitation. The absence of clear evaluation criteria for such resources now creates uncertainty in determining resort eligibility and weakens the credibility of official recognition. Other than legal gaps, there is also a conceptual issue in how the term resort is defined in Georgia. As in other Soviet countries, a resort has mostly referred to places with officially recognized healing resources, such as mineral springs, therapeutic muds, or favorable climatic conditions, and to some basic infrastructure for using these resources, like baths or treatment facilities. This narrow, health-oriented approach does not take into consideration whether these places have functioning tourism infrastructure. As a result, some resorts exist only formally and fail to attract visitors because of the lack of tourism facilities, while active tourism destinations without certified healing resources remain outside the system. For example, Gudauri, a major mountain destination with developed infrastructure and strong demand, is still not legally recognized as a resort. The identified challenges suggest that a broader definition is needed that will capture both the curative purpose and the tourism role of resorts. The important gap in tourism governance in Georgia should also be highlighted. There are overlapping responsibilities and weak coordination among government agencies, which remain serious obstacles for the development of the tourism industry in general and resorts in particular. According to the Law on Tourism, the Government of Georgia, the Ministry of Economy and Sustainable Development, and the Georgian National Tourism Administration (GNTA) share responsibility for tourism development, while the GNTA is the main agency for tourism policy implementation. However, an analysis of the GNTA’s activities shows that its main focus is on promotion, while planning and regulatory functions remain less developed. Furthermore, GNTA, local governments, Destination Management Organizations (DMOs), the Georgian Resorts Development Agency (GRDA), and the Mountain Trails Agency (MTA) have overlapping functions, which makes it difficult to identify which agency is accountable for specific tourism-related tasks. In October 2025, the Government officially announced the merger of two agencies, GRDA and GNTA, leading to improved coordination and reduced duplication. This reform shows that the authorities recognize long-standing institutional problems, although the process still needs to be completed. The MTA, responsible for developing ski infrastructure, still operates outside the national tourism policy framework. It is therefore of paramount importance to create a unified system that connects all tourism-related functions to ensure better planning and coordination. The problems identified above are not unique to Georgia. After the collapse of the Soviet Union, several Eastern European countries faced the same kinds of institutional and legal difficulties. However, some of these countries improved their resort systems with more quality orientation and better management practices. The study investigates how selected Eastern European states with a common Soviet heritage— Bulgaria, Latvia, Lithuania, and Romania—have reformed their resort regulation systems after joining the European Union. Furthermore, the paper identifies practical insights for Georgia by using a comparative legal and policy analysis of tourism and resort-related laws, focusing on the main aims, definitions, recognition procedures, and criteria that regulate resorts in the four selected countries. The main goal is to develop a clear and practical framework for the classification and management of Georgian resorts that will lead to an increase in their quality, environmental sustainability, and competitiveness for the international tourism markets. Overview of Resort-Related Regulations in Eastern Europe This part of the paper investigates how resort regulations work in four Eastern European countries—Bulgaria, Latvia, Lithuania, and Romania. They share a Soviet past but took different paths when reforming their systems after joining the European Union, based on their own national priorities. Although no single regulation is perfect, a combination of strong sides can be very useful if adapted wisely to the Georgian context. To identify useful insights, analysis focuses on three main aspects: (1) the aims and legal definition of a resort, (2) the procedures for official recognition, and (3) the criteria used for that recognition. Definition and Aim of Resort Regulation There are different meanings of the term resort in different parts of the world. In the North American case, it refers to a single property offering leisure and recreation services or a type of accommodation, while in British and European contexts it describes an entire locality or destination with tourism and health-related infrastructure. Eastern European countries follow this latter approach, treating resorts as complex areas that combine natural, medical, and cultural resources within a managed spatial framework. In Bulgaria, resort regulation aims to promote the sustainable development of national resorts while protecting natural and cultural heritage. The law defines a resort as an urbanized area (either a whole or part of a settlement) with officially declared resort resources and facilities for prevention, treatment, rehabilitation, recreation, and tourism. These resources include mineral and thermal waters, therapeutic muds, seawater, coastal zones, and favorable climatic conditions. National resorts are a higher category selected by the authorities from the existing list of resorts based on their tourism potential. They are required to have developed infrastructure, good accessibility, and a balanced combination of natural and human-made assets supporting both health and leisure functions. In Latvia, resort regulation is more health-oriented and focuses on the rational use of natural healing resources for wellness, prevention, and rehabilitation in an environmentally sustainable way. A resort in Latvia is an officially designated area that has natural healing resources and at least one medical institution using them, together with basic infrastructure and proper spatial planning. This reflects Latvia’s long spa and wellness tradition, where the value of local healing resources forms the main legal and economic basis for resort development. In Lithuania, resort regulation is part of broader territorial and economic planning. Its main goal is to achieve balanced social, economic, and infrastructural development, attract investment, and strengthen the country’s image as a wellness destination. Lithuanian law distinguishes, on the one hand, between resorts—residential areas with scientifically proven natural healing factors and developed infrastructure—and, on the other hand, resort areas, which have potential healing resources that are not yet fully developed. This system helps Lithuania develop new resorts gradually and ensures that local planning fits with the country’s tourism and health goals. Unlike other countries, Romania does not have a special law for resorts. Resorts-related matters are handled through the general tourism law that focuses mostly on recognizing natural and cultural tourism resources. A resort is defined as a locality or part of it recognized for certified natural or anthropogenic assets such as geological formations, landscapes, climate, and monuments. The presence of healing resources is not mandatory, underscoring Romania’s broader recreational and cultural orientation. These frameworks show two main approaches in Eastern European resort policy. The curative-medical model, used in Bulgaria, Latvia, and Lithuania, links resort status to natural healing factors and focuses on health, rehabilitation, and environmental quality. The tourism-development model, followed in Romania, defines resorts more broadly based on their recreational, cultural, and natural features. Procedures for Resort Recognition The existing formal recognition procedures in the selected countries ensure that nominated areas meet agreed standards. Although the level of complexity differs from country to country, all the systems reviewed include expert evaluation, coordination between ministries, and regular monitoring. In Bulgaria, the recognition process is based on a clear legal framework that focuses on the proper use and protection of healing resources. The Minister of Health pilots the process by preparing a proposal for resort recognition based on expert reviews. The final approval is given by the Council of Ministers together with the Ministries of Health, Regional Development, Environment, and Tourism. An important step is the balneological assessment of mineral waters, which confirms their healing qualities for a period of ten years and can later be renewed. The results are published on the Ministry of Health’s website to keep the process transparent. After a locality is officially recognized as a resort, it can later be given the status of a national resort. This second step is regulated by an ordinance adopted by the Council of Ministers based on a joint proposal from the Ministers of Health and Tourism. Businesses operating in national resorts benefit from simpler administrative procedures and special incentives that support investment and sustainable growth. In Latvia, the process is initiated by municipalities and regulated through the Cabinet of Ministers’ decisions. Local councils submit applications including development plans, spatial documentation, and compliance evidence. The Ministry of Economy conducts the preliminary review and forwards qualified cases to an inter-ministerial commission, which evaluates conformity with the Tourism Law within two months. Based on its findings, the Ministry drafts an order for the Cabinet, which issues the final designation. Municipalities must submit biennial progress reports; non-compliance can result in revocation of status. In Lithuania, the municipal council submits a proposal to the Ministry of Economy and Innovation, together with planning and explanatory documents. The Ministry forms a working group to review the submission within sixty days and prepares a recommendation for the Government, which makes the final decision. This clear and transparent process allows the gradual recognition of new destinations through the resort-area category. In Romania, resort recognition is regulated by the general tourism law through ministerial certification of natural or cultural resources. The process is officially defined, but less transparent than in the other three countries. Overall, these procedures show different levels of institutional development. Bulgaria focuses on medical evaluation; Latvia and Lithuania combine local initiative with national oversight; and Romania follows a simpler, resource-based system. Criteria for Resort Recognition The four selected countries differ widely in the specificity, transparency, and formality of their resort-recognition criteria. In Lithuania, the criteria are written into law and clearly connected to spatial planning and environmental policy. In Bulgaria and Romania, by contrast, the criteria are not published or are set mainly through administrative practice. Latvia lies in between, providing general rules for compliance and development planning but without detailed technical standards. Compared with other countries, Lithuania has much more detailed criteria available in regulations for resort recognition. There are two types of requirements for areas seeking resort or resort-area status—general and specific. The general criteria focus on several key areas, including environmental protection, public health and safety, land-use planning, and tourism infrastructure. Furthermore, they follow sustainable principles by including measures such as limiting pollution, improving accessibility, and keeping high standards of cleanliness and safety. In contrast, the specific criteria address the practical side of the development by focusing on the quality of infrastructure, like pedestrian and bicycle paths, parking and storage facilities, and well-maintained public spaces that create a comfortable and attractive resort environment. In addition, areas aiming for full resort status must also provide bypass routes for transit traffic, developed tourism infrastructure, and a mix of public and private services. Key elements include healthcare and wellness centers, accommodation, and cultural, leisure, and dining facilities. Resort areas, on the other hand—seen as developing or transitional destinations—have fewer requirements and mainly focus on basic recreation facilities and public services for visitors. This two-level system helps Lithuania develop new resorts gradually while supporting national goals for sustainability and spatial planning. Latvia’s criteria for resort designation are defined in the Regulations on Resorts issued by the Cabinet of Ministers. While the regulations do not set precise quantitative or qualitative benchmarks, they require municipalities to submit comprehensive documentation—such as spatial-development plans, evidence of resource protection, and medium-term resort strategies—demonstrating the feasibility and long-term vision of the proposed resort. The focus on planning and environmental management helps keep resort policy consistent, even without detailed technical standards. In Bulgaria and Romania, there is no complete or publicly available list of resort-recognition criteria. In fact, the process in Bulgaria focuses mainly on the balneological evaluation of natural healing resources, while Romania regulates resorts through the general tourism law, without clearly defined standards for eligibility, sustainability, or quality. Due to the fact that these rules are not published, decisions often depend on administrative judgment, making the process less consistent than in Lithuania. In summary, these differences that that resort related regulations in Eastern Europe have developed at different speeds and in different ways. Lithuania’s model is the most complete because it brings together health, environmental, and infrastructure aspects. Latvia’s approach is more focused on local planning and management, while Bulgaria and Romania still struggle with unclear procedures and a lack of detailed legal guidance. Developing a Resort Regulation Framework for Georgia Reforming resort regulations in Georgia requires more than just updating legal terms or setting new recognition criteria. For real impact, the entire tourism governance system needs bigger, more comprehensive change and optimization. The conceptual framework below is based on the analysis of resort-related regulations of Eastern European countries and is adapted to Georgia’s recent institutional and economic context. Aim and Definition of Resorts As mentioned earlier, the Law of Georgia on Tourism (2023) keeps the old definitions of resorts and resort areas but contains several important flaws. To solve this problem, the law should clearly list what counts as curative resources. Another important step would be the introduction of the term National Resort, allowing the government to distinguish resorts by their tourism potential without changing the current list of resorts. A proposed legal formulation could read as follows: “A resort is an urbanized area initially declared as a resort and subsequently recognized as a National Resort based on a proposal by the Georgian National Tourism Administration and a decision of the Cabinet of Ministers. National resorts are important for the sustainable development of tourism in Georgia. They are characterized by essential tourism infrastructure, accessibility, and valuable tourism resources. These resources include components of the natural and anthropogenic environment (geological formations, climate, flora and fauna, landscapes, and cultural or historical sites) used for tourism unless subject to full protection regimes. In special cases, areas with high-value tourism resources may be nominated for national resort status without prior resort designation”. The concept of “National Resorts” is similar to Bulgaria’s approach, where they are considered as an important drivers for sustainable tourism and economic growth. It is also partly in line with Romania’s system, which defines resorts based on their tourism resources. However, the paper suggests going a step further by allowing exceptional destinations without curative resources to be nominated directly for national status. For example, destinations without resort status but with high tourism potential, like Gudauri, would also have the opportunity to be declared as national resorts. Procedures for Resort Recognition The paper proposes a national resort recognition system using practices observed in Bulgaria, Latvia, and Lithuania, while taking into consideration the local governance system: Nomination – The Georgian National Tourism Administration (GNTA), together with the local municipality, submits a nomination for national resort status. As a result, both expert knowledge and local perspectives are reflected in the proposal; Formation of a Working Group – A multidisciplinary team composed of ministry representatives, technical experts, and local authorities evaluates the proposal; Evaluation of Compliance – The working group evaluates accessibility, sustainability, infrastructure quality, and distinctive tourism resources and prepares a formal opinion for the Ministry of Economy and Sustainable Development; Drafting of the Decision – Based on the group’s findings, the Ministry prepares a draft decision to either approve or reject the nomination and adds recommendations if needed; Final Approval – The Cabinet of Ministers makes the final decision, ensuring that it aligns with national tourism policy and broader development goals. The suggested framework provides a simple and transparent process that is designed to help agencies work together more effectively. Furthermore, it makes responsibilities clearer and brings Georgia closer to international tourism management standards. Criteria for Resort Recognition, Including Ski Resorts The recognition criteria should reflect the main purpose of each resort while still keeping a single, unified national framework. All National Resorts must satisfy general quality and sustainability standards, supplemented by type-specific indicators. General Criteria (applicable to all resorts) are the following: Accessibility and connectivity; Quality of infrastructure (roads, parking, public spaces); Availability of tourism services and facilities; Environmental protection and sustainable management practices; Existence and quality of tourism resources; Availability of healthcare and emergency services; Compliance with spatial and territorial planning standards; Existence of a medium-term strategy for resort growth. Specific Criteria are the following: National Ski Resorts – quality, safety, and reliability of ski slopes; maintenance of lifts and snow-making systems; proximity of emergency services; variety of winter sports and après-ski facilities; and environmental safeguards in mountain ecosystems; National Seaside Resorts – beach quality, water safety, coastal protection, and waste-management systems ensuring sustainable use; National Wellness Resorts – quality and diversity of spa and therapeutic services based on natural healing resources such as mineral waters or therapeutic muds; National Tourism Resorts – distinctiveness and attractiveness of natural or cultural resources, quality of supporting infrastructure, and capacity to offer recreation, learning, and leisure experiences. The working group should apply these criteria fairly, taking into account the size, type, and potential of each destination. A clear but flexible system will make the process more balanced and help create a variety of good-quality Georgian resorts that meet international standards. It is also important to note that simply following Lithuania’s example and adopting stricter criteria to existing resorts without bringing new terms could improve quality control of the resorts, but it would likely remove the status of about 95% of existing resorts, resulting in a long, costly, and politically sensitive process. Institutional Roles after National Resort Recognition It’s important to note that National Resort is a real tool, not a formal label for developing and improving resort competitiveness. In practice, it is a brand giving high-quality information to visitors travelling to destinations for tourism purposes. In order to make this idea work, effective cooperation between agencies is of paramount importance. Firstly, the GNTA and local DMOs should support these resorts with marketing and promotion and include them in training programs. The two agencies should also assess and control indicators of infrastructure and service quality, environmental conditions, and visitor satisfaction. In case standards drop, the GNTA should have the authority to suspend or withdraw resort status in order to maintain high quality. Secondly, the regulations should focus on safety and climate resilience activities. With the increasing number of winter and adventure visitors, the improvement of safety management becomes essential. Furthermore, as a result of Climate change, warmer winters and less snow threaten ski destinations such as Bakuriani and Gudauri, while erosion affects Black Sea resorts. For these reasons, monitoring climate risks and improving disaster preparedness should become a national goal. Finally, Enterprise Georgia can also play an important role. It can support national resorts through funding, infrastructure upgrades, and workforce training activities. At the same time, the government can help through tax incentives, public infrastructure improvement, and better access to finance. These steps would encourage both public and private investment in the sustainable growth of resorts. To summarize, effective coordination between the GNTA, DMOs, Enterprise Georgia, and other agencies is essential to keep everyone working toward the same goal. Through the clearer roles, stronger management, and the inclusion of climate planning and safety measures, the National Resort title can be turned into a sign of quality that helps attract investment and improves Georgia’s long-term competitiveness. Utilizing this approach, the country can move from its old Soviet-style resort system toward a modern, European model that supports sustainable tourism growth. References: Scientific Articles: Azmaiparashvili, M., Davituliani, T. (2023). Ecological Safety of Georgian Tourism. Globalization and Business, 8(16); Azmaiparashvili, M., Goderdzishvili, I. (2024). Sustainable development of Georgian resorts: modern trends and challenges. Proceedings of the 6th International Scientific and Practical Conference “Scientific Goals and Purposes in XXI Century”, 6(193); Bregadze, G. (2023). Climate Change Impacts on the Tourism Industry in Georgia, Globalization and Business, Vol. 8, No. 16. <https://doi.org/10.35945/gb.2023.16.005>; Conterio, J. (2019). Curative nature: Medical foundations of Soviet nature protection, 1917–1941. Slavic Review, 78(1); Ņitavska, N., Skujāne, D. (2019). Re-branding landscapes of forgotten resorts: Case of the healing resort Kemeri in Latvia. Landscape Architecture and Art, 15(15); Tutberidze, M. (2021). The Georgian resorts as a basis for wellness tourism development. Georgian Geographical Journal, 1(1); Varadzhakova, D., Naidenov, A., Ilieva, N., Raykova, M. (2023). The Bulgarian national Black Sea resorts in the context of domestic tourism. GeoJournal of Tourism and Geosites, 49(4). Normative Acts: Decree No. 428 of the Government of Georgia On the Approval of the List of Resorts and Resort Areas of Georgia (3 July 2014); Law of Georgia on Protective Sanitary Zones of Health Resorts and Resort Areas No. 1308-IIs (7 September 2000). Legislative Herald of Georgia. <www.matsne.gov.ge>; Law of Georgia on Tourism (15 December 2023). Legislative Herald of Georgia. <www.matsne.gov.ge>; Law of Georgia on Tourism and Resorts No. 1662-IIs. (28 November 1997). Legislative Herald of Georgia. <www.matsne.gov.ge>; Law of Romania on Tourism (nr. 70/2023, 30 March 2023; published in the Official Gazette of Romania, Part I, No. 256/2023), legislatie.just.ro – Official Legislative Portal of Romania. <https://legislatie.just.ro/Public/DetaliiDocumentAfis/256247>; Law of the Republic of Bulgaria on Health (SG No. 70/2004; last amended SG No. 98/2018), Republic of Bulgaria. lex.bg – Official Legislation Database of Bulgaria. <https://lex.bg/bg/laws/ldoc/2135489147>; Law of the Republic of Bulgaria on Tourism (State Gazette No. 30 of 26 March 2013; last amended State Gazette No. 20 of 12 March 2021), lex.bg – Official Legislation Database of Bulgaria. <https://lex.bg/bg/laws/ldoc/2135845281>; Law of the Republic of Latvia on Tourism (19 June 1998; last amended 1 July 2022). likumi.lv – Official Legislation Database of Latvia. <https://likumi.lv/ta/id/50026-turisma-likums>; Law of the Republic of Lithuania on Tourism (18 March 1998; last amended 23 January 2023). e-Seimas – Official Portal of Legal Acts of the Republic of Lithuania. <https://e-seimas.lrs.lt/portal/legalAct/lt/TAD/3a2b7132f9f611edbc0bd16e3a4d3b97>; Order No. 630/2022 of the Ministry of Economy, Entrepreneurship and Tourism of Romania On the Certification of Tourist Resorts of National or Local Interest. Official Gazette of Romania, No. 330/04.04.2022. <https://legislatie.just.ro/Public/DetaliiDocumentAfis/256247>; Regulations of the Cabinet of Ministers of the Republic of Latvia No. 451, “Regulations on Resorts” (2 August 2016; last amended 8 June 2021). likumi.lv – Official Legislation Database of Latvia. <https://likumi.lv/ta/en/en/id/253701>; Resolution No. 1459 of the Government of the Republic of Lithuania On the Approval of the Procedure for Granting and Revoking the Status of Resorts and Resort Areas (23 December 2008; last amended 2 December 2020). e-TAR – Official Register of Legal Acts of Lithuania. <https://www.e-tar.lt/portal/lt/legalAct/f94027a07d0111e7827cd63159af616c/asr>; Resolution No. 350 of the Government of the Republic of Lithuania On the Approval of the Description of the Procedure for Granting the Status of a Resort and a Resort Territory (12 April 2006; last amended 15 December 2021). e-TAR – Official Register of Legal Acts of Lithuania. <https://www.e-tar.lt/portal/en/legalAct/TAR.B4B629EF1E3E/WHPJjFiPBK>. Web Resources: Georgian Resorts Development Agency. (n.d.). Mission and Vision. Government of Georgia. Last access: October 31, 2025. <https://resorts.gov.ge/mission?menu_id=45&target=_self>; Mountain Trails Agency. (n.d.). About the Agency. Government of Georgia. Last access: October 31, 2025. <https://mta.ski/en/about>. Footnotes [1] Conterio, J. (2019). Curative nature: Medical foundations of Soviet nature protection, 1917–1941. Slavic Review, 78(1), p. 30. [2] Azmaiparashvili, M., Goderdzishvili, I. (2024). Sustainable development of Georgian resorts: modern trends and challenges. Proceedings of the 6th International Scientific and Practical Conference “Scientific Goals and Purposes in XXI Century”, 6(193), p. 30. [3] Ņitavska, N., Skujāne, D. (2019). Re-branding landscapes of forgotten resorts: Case of the healing resort Kemeri in Latvia. Landscape Architecture and Art, 15(15), pp. 32–33. [4] Tutberidze, M. (2021). The Georgian resorts as a basis for wellness tourism development. Georgian Geographical Journal, 1(1), pp. 23–24. [5] Law of Georgia on Tourism and Resorts No. 1662-IIs. (28 November 1997). Legislative Herald of Georgia, Articles 1–7. <www.matsne.gov.ge>. [6] Decree No. 428 of the Government of Georgia On the Approval of the List of Resorts and Resort Areas of Georgia (3 July 2014). [7] Law of Georgia on Protective Sanitary Zones of Health Resorts and Resort Areas, No. 1308-IIs (7 September 2000). Legislative Herald of Georgia. <www.matsne.gov.ge>. [8] Law of Georgia on Tourism (15 December 2023). Legislative Herald of Georgia. <www.matsne.gov.ge>. [9] Ibid., Article 4. [10] Georgian Resorts Development Agency. (n.d.). Mission and Vision. Government of Georgia. Last access: October 31, 2025. <https://resorts.gov.ge/mission?menu_id=45&target=_self>. [11] Mountain Trails Agency. (n.d.). About the Agency. Government of Georgia. Last access: October 31, 2025. <https://mta.ski/en/about>. [12] Varadzhakova, D., Naidenov, A., Ilieva, N., Raykova, M. (2023). The Bulgarian national Black Sea resorts in the context of domestic tourism. GeoJournal of Tourism and Geosites, 49(4), p. 1088. [13] Law of the Republic of Bulgaria on Tourism (State Gazette No. 30 of 26 March 2013; last amended State Gazette No. 20 of 12 March 2021), Chapter Four “A” – National Resorts. lex.bg – Official Legislation Database of Bulgaria. <https://lex.bg/bg/laws/ldoc/2135845281>. [14] Law of the Republic of Latvia on Tourism (19 June 1998; last amended 1 July 2022), Article 6¹ – “Resort and Granting of its Status”. likumi.lv – Official Legislation Database of Latvia. <https://likumi.lv/ta/id/50026-turisma-likums>. [15] Law of the Republic of Lithuania on Tourism (18 March 1998; last amended 23 January 2023), Article 2 – “The Main Concepts of This Law”. e-Seimas – Official Portal of Legal Acts of the Republic of Lithuania. <https://e-seimas.lrs.lt/portal/legalAct/lt/TAD/3a2b7132f9f611edbc0bd16e3a4d3b97>. [16] Law of Romania on Tourism (nr. 70/2023, 30 March 2023; published in the Official Gazette of Romania, Part I, No. 256/2023), Chapter I – “General Provisions”. legislatie.just.ro – Official Legislative Portal of Romania. <https://legislatie.just.ro/Public/DetaliiDocumentAfis/256247>. [17] Law of the Republic of Bulgaria on Health (SG No. 70/2004; last amended SG No. 98/2018), Section VIII – “Resort Resources and Resorts”, Articles 75–76. Republic of Bulgaria. lex.bg – Official Legislation Database of Bulgaria. <https://lex.bg/bg/laws/ldoc/2135489147>. [18] Law of the Republic of Bulgaria on Tourism (SG No. 30/2013; last amended SG No. 20/2021), Chapter Four “A” – National Resorts. lex.bg – Official Legislation Database of Bulgaria. <https://lex.bg/bg/laws/ldoc/2135845281>. [19] Regulations of the Cabinet of Ministers of the Republic of Latvia No. 451, “Regulations on Resorts” (2 August 2016; last amended 8 June 2021). likumi.lv – Official Legislation Database of Latvia. <https://likumi.lv/ta/en/en/id/253701>. [20] Resolution No. 1459 of the Government of the Republic of Lithuania On the Approval of the Procedure for Granting and Revoking the Status of Resorts and Resort Areas (23 December 2008; last amended 2 December 2020). e-TAR – Official Register of Legal Acts of Lithuania. <https://www.e-tar.lt/portal/lt/legalAct/f94027a07d0111e7827cd63159af616c/asr>. [21] Order No. 630/2022 of the Ministry of Economy, Entrepreneurship and Tourism of Romania On the Certification of Tourist Resorts of National or Local Interest. Official Gazette of Romania, Part I, No. 330/04.04.2022. <https://legislatie.just.ro/Public/DetaliiDocumentAfis/256247>. [22] Resolution No. 350 of the Government of the Republic of Lithuania On the Approval of the Description of the Procedure for Granting the Status of a Resort and a Resort Territory (12 April 2006; last amended 15 December 2021). e-TAR – Official Register of Legal Acts of Lithuania. <https://www.e-tar.lt/portal/en/legalAct/TAR.B4B629EF1E3E/WHPJjFiPBK>. [23] Regulations of the Cabinet of Ministers of the Republic of Latvia No. 451, “Regulations on Resorts” (2 August 2016; last amended 8 June 2021). likumi.lv – Official Legislation Database of Latvia. <https://likumi.lv/ta/en/en/id/253701>; [24] Azmaiparashvili, M., Davituliani, T. (2023). Ecological Safety of Georgian Tourism. Globalization and Business, 8(16), p. 69. [25] Bregadze, G. (2023). Climate Change Impacts on the Tourism Industry in Georgia, Globalization and Business, Vol. 8, No. 16, pp. 57–59. <https://doi.org/10.35945/gb.2023.16.005>.
Copyright (c) 2026 Giorgi Bregadze (Author) https://creativecommons.org/licenses/by-sa/4.0/
Fintech and Climate Resilience in Banking: Navigating Risk and Opportunity
Climate-related financial risks, encompassing both physical and transition dimensions, present an escalating threat to global financial stability, necessitating sophisticated risk management responses from the banking sector. This literature review synthesizes existing academic and industry research on the intersection of financial technology (Fintech) and bank climate risk management. The review establishes Fintech’s critical role in enhancing banks’ capacity to assess, monitor, and mitigate these complex risks through solutions such as Artificial Intelligence (AI), Machine Learning (ML), blockchain, big data analytics, and digital platforms for green finance. It examines methodologies, identifies key trends, and analyzes evolving perspectives from academic scholarship and industry practice on integrating climate risk into operational and strategic frameworks. Furthermore, this work investigates the challenges and limitations confronting fintech adoption, including data scarcity, regulatory hurdles, technological integration barriers, and ethical considerations such as algorithmic bias and the threat of “greenwashing”. The review concludes by highlighting emerging best practices and innovative approaches, synthesizing gaps in the existing literature, and proposing a research agenda designed to inform researchers, policymakers, and financial institutions. This foundation enables these stakeholders to navigate this dynamic landscape, contributing to a more resilient and sustainable financial system. Keywords: Bank risk management, fintech, climate-related financial risk, blockchain, green finance. JEL Classification: G32, G20, Q54, O31, Q56. Introduction Global economic losses from climate-related disasters have surged to over $200 billion annually in recent years, with projections indicating a potential 10% reduction in global GDP by 2050 under severe climate scenarios.[1] This reality establishes a critical imperative for the banking sector: climate risk management is a central pillar of financial stability. In this perspective, climate-related risks must be understood not only as environmental concerns, but also as direct threats to banking resilience and financial stability[2]. The financial system is exposed to climate-related risks through its lending, investment, and insurance activities.[3] Addressing these challenges requires enhanced data and analytical capabilities, robust supervisory frameworks, and international cooperation.[4] Climate-related risks manifest in distinct, interconnected typologies: Physical Risks: These stem from the direct impacts of climate change, such as extreme weather events, rising sea levels, and chronic shifts in temperature and precipitation patterns.[5] For banks, physical risks threaten collateral values, increase loan defaults, and disrupt operational continuity. Examples include real estate portfolios exposed to recurrent flooding or agricultural loans vulnerable to prolonged droughts.[6] Transition Risks: These arise from the transition to a low-carbon economy, including policy changes (e.g., carbon pricing), technological innovation, and shifts in market sentiment and consumer preferences.[7] Such risks can lead to stranded assets, reduced profitability for carbon-intensive sectors, and increased credit and market risks for banks with exposure to these industries. Liability Risks: These stem from legal claims against entities for climate-related damages or insufficient climate action. Banks face indirect liability through their financing activities for companies exposed to such litigation. These risks are not externalized costs; they are internalized as direct financial exposures, altering asset valuations and balance sheet stability. The “tragedy of the horizon”,[8] where long-term climate impacts conflict with short-term financial planning, creates a key tension requiring immediate attention. Fintech, encompassing Artificial Intelligence (AI), Machine Learning (ML), blockchain, big data analytics, and digital platforms, emerges as a transformative force in navigating these complex financial risks. More broadly, this role reflects the wider transformation of financial services through fintech-driven innovation ,disruption, and digital reconfiguration[9]. Technological innovation, including big data analytics and AI, plays a significant role in improving climate-related risk assessment, though these tools are still nascent in this application area.[10] Fintech enhances data collection, processing, and risk modeling, improving financial institutions’ ability to monitor and mitigate climate-related financial risks.[11] This connection between the urgency of climate risk and the necessity of technological innovation forms the foundational premise of this literature review. While Fintech offers capabilities for strengthening climate risk management, its full potential can only be realized by systematically addressing data fragmentation, regulatory incoherence, and the complexities of technological integration, necessitating a concerted global effort. This literature review therefore aims to examine how fintech tools can strengthen bank’s capacity to identify ,assess, and mitigate climate-related financial risks, while also highlighting the regulatory, operational, and ethical challenges associated with their adoption. 1. Literature Review and Theoretical Framework 1.1. Foundational Frameworks for Climate Risk in Banking and Finance (2018-2021) Early scholarship between 2018 and 2021 established the conceptual groundwork for understanding climate-related financial risks in banking, predating the widespread discussion of fintech solutions. This period was characterized by a push to integrate climate considerations into financial stability mandates, with researchers identifying climate change as a systemic risk requiring new regulatory paradigms.[12] An initial focus was on developing macroprudential policies to manage these novel risks and steer investments toward a low-carbon economy. Concurrently, scholars began dissecting the specific transmission channels through which climate change affects financial stability, such as the risks posed by declining “sunset” industries heavily reliant on fossil fuels. These studies argued that the transition to a low-carbon economy could trigger abrupt asset revaluations and defaults, threatening the entire financial system. Methodologically, this era saw proposals for climate stress tests to gauge institutional resilience and the advocacy for a ‘precautionary approach’ to policymaking, which argues that the radical uncertainty of climate impacts necessitates proactive regulatory action even without complete scientific certainty. Collectively, these works framed climate change not merely as an environmental issue but as a core threat to financial stability, creating the intellectual and regulatory justification for the technological interventions that would follow.[13] 1.2. The Dual Role of Fintech in Climate Risk and Resilience (2022-2025) Building on the foundational risk frameworks, the literature from 2022 to 2025 shifts to the practical, yet complex, role of fintech in addressing climate challenges. This contemporary body of work highlights a significant tension: while fintech is often lauded for its potential to enhance climate resilience, recent empirical work also suggests it can significantly amplify climate risk in financial markets. Some studies illustrate how fintech can cushion firms from the adverse impacts of climate risk and improve resilience against climate shocks for both households and companies. More specifically, green fintech solutions are seen as critical for improving sustainability, mitigating risks, and achieving financial stability. These technologies are positioned as key enablers of sustainable finance, capable of accelerating the shift to a carbon-neutral economy. This broader interpretation is consistent with recent scholarship that situates fintech within a wider nexus linking climate challenges , green finance , digitalization ,and environmental quality[14]. For instance, AI and blockchain are identified as tools that can improve the efficiency of green financing, enhance risk management related to ESG events, and increase the transparency of sustainable transactions. However, research also cautions that integrating fintech for sustainability is not straightforward, with one study on the Indonesian banking sector finding that fintech adaptation had a limited direct impact on sustainability performance, pointing to the need for better regulatory frameworks and strategic implementation. This duality underscores that while fintech offers powerful instruments for building a climate-resilient banking system,[15] its deployment requires careful management to avoid exacerbating the high risks it aims to mitigate. 2. Fintech Solutions: Advanced Analytics, Transparency, and Green Finance 2.1. Advanced Analytics, Transparency, and Green Finance Facilitation Fintech solutions offer transformative capabilities for enhancing climate risk management in banking, moving beyond static risk assessment to dynamic, data-driven approaches. These tools address the “Climate Risk Imperative” by providing granular insights and fostering greater transparency in green finance.[16] Artificial Intelligence and Machine Learning: Advanced Data Analytics and Modeling Artificial Intelligence (AI) and Machine Learning (ML) are fundamental to significant advancements in climate risk assessment. These technologies process vast, disparate datasets, enabling predictive modeling of physical risks and granular analyses for transition risk scenarios. Physical Risk Modeling. AI/ML models downscale global climate projections, such as CMIP6, to regional and asset-level resolutions, sometimes as fine as 90 meters.[17] These models integrate historical climatic data with specific asset characteristics, like property elevation or construction materials, to project future physical damages from hazards such as floods or wildfires. Satellite imagery and geospatial data serve as critical inputs, facilitating near-real-time monitoring and dynamic risk adjustments.[18] For instance, SatSure’s “SatSure Sage” platform and CropIn’s “SmartRisk” platform employ ML with satellite and weather data to assess agroclimatic risk for Indian banks, correlating crop performance with historical risks to inform loan underwriting and portfolio monitoring.[19] The conceptual data flow for AI-driven physical risk assessment transforms raw environmental and asset data into actionable risk scores, as illustrated in the following diagram. Transition Risk Scenario Analysis. AI-driven sentiment analysis, particularly through Natural Language Processing (NLP) models, parses unstructured data from regulatory texts, corporate climate disclosures (e.g., TCFD reports), and news articles. U-Reg’s NLP-based algorithms, for instance, process vast quantities of ESG disclosure data to identify inconsistencies and extract insights on policy foresight, litigation risk indicators, and market sentiment shifts.[20] These models enable banks to anticipate the financial impact of decarbonization policies and market shifts. Blockchain and Distributed Ledger Technology: Transparency and Verifiability Blockchain and Distributed Ledger Technology (DLT) enhance transparency and verifiability in sustainable finance, addressing concerns such as greenwashing and data integrity.[21]In this regard,the literature on greenwashing provides an important framework for understanding how misleading environmental claims can weaken the credibility of sustainable financial innovation[22]. Green Bonds and Impact Verification. Blockchain creates immutable records of green bond issuance, ensuring funds are allocated to stated environmental projects. Fever Tokens, for example, proposes an open-source solution for on-chain monitoring throughout the life cycle of tokenized green bonds, adhering to ICMA’s Green Bond Principles and the EU’s Green Bond Standard.[23] This significantly boosts transparency and investor trust by providing verifiable impact metrics recorded on a distributed ledger. Carbon Credit Markets. Blockchain technology improves the tracking of carbon credits, providing an auditable history for each credit’s origin and transaction[24], and offers a blockchain-driven platform for trading, clearing, and settlement of carbon credits and ESG assets, eliminating greenwashing and double-counting through robust data verification and traceability.[25] Triangle’s Asset OS platform links asset data with verifiable information using blockchain, facilitating TCFD reporting compliance and enabling the minting of fungible carbon credits.[26] This diagram illustrates satellite imagery and property data as inputs, hidden layers for feature extraction and pattern recognition, and outputs as a risk score or probability of damage. Digital Platforms and RegTech: Green Finance Facilitation and Compliance Digital platforms and RegTech solutions facilitate green finance flows and automate climate-related disclosures. Green Finance Platforms. These platforms direct capital toward climate-aligned initiatives. Examples include crowdfunding platforms like Abundance Investment for renewable energy projects, and investment marketplaces such as STACS’ ESGpedia. ESGpedia aggregates and harmonizes sustainability data, creating standardized ESG company profiles mapped to financial sector regulatory formats.[27] This enhances market efficiency and transparency in sustainable investment. RegTech for Climate Reporting. RegTech solutions automate climate-related disclosures and ensure compliance with evolving regulatory mandates. U-Reg’s U-Green module leverages AI and RegTech to address fragmentation and standardization challenges in ESG reporting, processing unstructured data at scale through NLP-based algorithms.[28] These tools streamline the complex process of reporting climate-related financial exposures, reducing administrative burdens on banks. Gaps in Literature. Despite these advancements, significant gaps persist in the literature. Comprehensive research on the long-term efficacy and robustness of AI/ML models under deep uncertainty remains limited. Interoperability standards for diverse Fintech solutions and climate data platforms require further development. Scalability challenges for blockchain applications in large-scale financial markets, particularly for tokenized assets, are not fully resolved. The “Crisis of Actionable Data”, characterized by pervasive deficiencies in granularity, standardization, and verifiability, implicitly constrains the full potential of these advanced tools, leading to an “Algorithmic Greenwashing” paradox if transparency is not rigorously enforced.[29] These identified gaps directly inform the subsequent discussion of implementation challenges. Integrating Fintech and Confronting Limitations 3.1. Integration Dynamics and Foundational Impediments The integration of Fintech solutions into banking operations for climate risk management reveals a “translation gap” between academic ideals and industry pragmatism. Academic research often prioritizes theoretical completeness, aiming for universal models and long-term systemic impact. Industry, by contrast, operates under immediate pressures of shareholder value, operational efficiency, and the constraints of legacy systems. This divergence means that while academia may critique inherent simplifications in industry climate models, industry prioritizes solutions readily integrated into existing risk frameworks with minimal disruption and cost. This gap impedes Fintech’s transformative potential. This flowchart illustrates the stages from project vetting and tokenized green bond issuance on a DLT to fund allocation based on smart contracts, impact verification via IoT sensors, and automated regulatory reporting. The journey towards climate resilience through Fintech is fraught with significant challenges, stemming from pervasive data scarcity, regulatory hurdles, technological integration barriers, and multifaceted ethical considerations. These challenges constrain Fintech capabilities and demand a utility-driven research agenda. Data Scarcity, Quality, and Standardization. The most fundamental impediment is not merely a lack of data, but a “Crisis of Actionable Data” characterized by deficiencies in granularity, standardization, and verifiability. The Network for Greening the Financial System (NGFS) found that 514 out of 1,262 raw data items lacked a linked source, with the largest gaps in biophysical impact, emissions, and geospatial data types.[30] This directly limits the usability of metrics for physical vulnerability and transition sensitivity. Methodological inconsistencies further compound this problem. Estimating Scope 3 emissions, for example, is hindered by varying boundary definitions, reliance on different emission factor databases, and diverse allocation methods across complex supply chains. This results in incomparable and often unreliable data for financial institutions.[31] Approximately 39% of all climate-related data items are based on estimations, with less than a quarter being official statistics or verified.[32] This reliance on unverified or estimated data undermines the accuracy of Fintech-driven risk assessments, creating an “illusion of precision” that can lead to mispriced assets. Regulatory Hurdles and Policy Lag. The fragmented and evolving nature of global climate finance regulation creates significant uncertainty, hindering Fintech innovation and adoption. Jurisdictions exhibit varying approaches; the EU’s fragmented data sharing standards under GDPR, for instance, complicate cross-border climate data aggregation.[33] Central banks also issue varying levels of prescriptive technological guidelines, from the Bank of England’s detailed expectations to the OCC’s higher-level principles.[34] This “regulatory lag” means frameworks struggle to keep pace with rapid technological evolution. Model validation for AI/ML solutions presents further complexities. Demonstrating model explainability (XAI) and robustness under diverse climate scenarios becomes a formidable task given the “black-box” nature of some advanced algorithms. Data residency requirements for global financial operations mandate that climate data remains within specific national borders, complicating the deployment of cloud-based Fintech solutions. Technological Integration Barriers. Banks face significant challenges in integrating cutting-edge Fintech with entrenched legacy IT systems. The inertia of monolithic core banking platforms resists seamless API integration, creating data silos and inefficient workflows. Harmonizing disparate data formats from various Fintech providers adds another layer of complexity. Pervasive talent gaps also exist, with a scarcity of data scientists possessing both financial and climate expertise, and risk managers capable of interpreting complex AI-driven climate analytics. Ethical and Reputational Considerations. Ethical dimensions, while not directly financial, generate material financial risks for banks. “Climate washing”, where overstated climate credentials inflate valuations, exposes banks to sudden devaluations, regulatory penalties, and reputational damage. Data biases in AI/ML models, if trained on historical data from predominantly developed economies, could misallocate capital by underestimating physical risks in emerging markets or overestimating transition risks for specific sectors, exacerbating existing inequalities. Data privacy breaches of climate-related information expose banks to legal and reputational risks. Algorithmically unfair risk assessments can lead to legal challenges and regulatory penalties for discriminatory practices. This “Algorithmic Greenwashing” paradox highlights how tools designed for transparency can inadvertently facilitate deception. This flowchart details the integration points of Fintech solutions (e.g., API integration, data lake ingestion) within a bank’s existing risk management, compliance, and strategic planning processes, highlighting potential points of friction and synergy. It clarifies operational complexities. The challenges outlined above necessitate a structured approach to addressing data quality and consistency. This table summarizes the core data availability challenges confronting Fintech solutions in climate risk management and their direct impact on the efficacy of these technologies. Gaps in the literature related to integration costs, the effectiveness of various regulatory sandboxes, and the full scope of systemic risks arising from Fintech dependencies demand further investigation. These impediments, from data fragmentation to regulatory incoherence, underscore the imperative for a coordinated, multi-stakeholder effort to bridge the chasm between technological potential and practical implementation. 4. Emerging Practices and Future Trajectories Innovative Approaches and Best Practices The banking sector’s pursuit of climate resilience, despite formidable impediments, drives the emergence of innovative Fintech approaches and best practices. These solutions enhance capabilities and directly address many of the implementation challenges previously discussed, offering pathways to optimize climate risk management. Integrated Climate Data Lakes. Data fragmentation, a pervasive challenge, finds mitigation in the development of integrated climate data lakes. These initiatives involve consortia and collaborative efforts where multiple banks and climate science communities pool anonymized climate-related data. Platforms like Dataland, a neutral, open-source data platform, exemplify this approach, focusing on company-specific raw data aligned with regulatory disclosure standards.[35] Dataland operates on principles of integrity, disclosure, transparency, accountability, neutrality, and collaboration, overcoming data availability gaps, reliability issues, and high acquisition costs.[36] This collaborative infrastructure acts as a public good, reducing the prohibitive costs of data acquisition and integration for individual banks and fostering collective intelligence. This diagram illustrates the various data sources (e.g., satellite, IoT, corporate disclosures), data ingestion points, processing layers (e.g., AI/ML analytics), and output applications (e.g., risk dashboards, regulatory reports) within an integrated climate data lake, clarifying the flow and aggregation of information. Open-Source Climate Risk Modeling Platforms. To counter the “black-box” nature of proprietary models and mitigate “Algorithmic Greenwashing”, open-source climate risk modeling platforms emerge from academic institutions and non-profits. Initiatives such as OS-Climate provide transparent and auditable tools for risk assessment, fostering trust and enabling collaborative development of methodologies.[37] These platforms enhance model explainability and allow for independent validation, addressing concerns about algorithmic bias and the robustness of climate projections. Digital Twins of Physical Assets. Innovative approaches extend to the creation of digital twins of physical assets. Pilot studies demonstrate how virtual replicas of buildings or infrastructure integrate climate models to simulate future flood, heatwave, or other climate impacts.[38] This allows banks to assess collateral resilience dynamically, providing granular, forward-looking insights into asset vulnerability. For example, Triangle creates blockchain-based digital twins of real-world assets linked to climate data, facilitating the reporting of financed emissions.[39] Blockchain-Enabled Platforms for Green Energy. Blockchain technology facilitates “Green Finance” through platforms enabling fractional ownership in green energy projects and enhancing the transparency of green financial instruments. Powerledger, for instance, utilizes blockchain for peer-to-peer renewable energy trading, democratizing access to green energy markets. FeverTokens proposes on-chain monitoring for tokenized green bonds, adhering to established principles like ICMA’s Green Bond Principles and the EU’s Green Bond Standard.[40] This boosts transparency and trust in green investments, directly combating greenwashing by providing verifiable impact metrics, and offers a blockchain-driven platform for carbon credit trading, ensuring traceability and preventing double-counting.[41] These emerging practices demonstrate Fintech capabilities actively optimizing climate resilience. They provide concrete examples of progress, directly addressing the “Crisis of Actionable Data” through integrated data initiatives and mitigating the potential for “Algorithmic Greenwashing” through transparent, open-source models. The continued development and adoption of these innovative approaches are crucial in building a more robust and sustainable financial future. 4.2. Uncharted Territories and Systemic Re-evaluations The landscape of Fintech and climate risk management reveals unexplored interconnections and necessitates a critical re-evaluation of underlying assumptions. Existing literature’s “white spaces” highlight nascent research areas and systemic vulnerabilities unaddressed by current approaches. 4.3. Unexplored Interconnections and Nascent Research Areas Novel conceptual links include direct feedback loops between climate-induced physical risks and automated portfolio adjustments. AI’s real-time geospatial data processing could trigger immediate re-evaluations of mortgage-backed securities as flood risks intensify.[42] This extends financial engineering principles to novel climate data streams, offering dynamic risk management beyond traditional, lagging indicators. Nascent research areas include the systemic risks arising from the interconnectedness of climate-aware Fintech solutions. A single climate data provider’s AI model failure could precipitate cascading failures across multiple financial institutions, leading to widespread mispricing of climate risk. The concentration of climate data provision within a few specialized Fintech firms creates a “barbell” risk structure, where failure in one provider could have systemic implications; this is a concern echoed by the Bank for International Settlements (BIS) regarding critical infrastructure.[43] Quantum computing’s potential to accelerate complex climate scenario modeling draws from theoretical computer science papers outlining its capability for exponential speedup in optimization problems.[44] Bio-mimicry principles for resilient investment strategies, supported by ecological economics literature, suggest novel financial products and portfolio constructions emulating nature’s adaptive capacities.[45] 4.4. Re-evaluating Underlying Assumptions and Systemic Implications A critical re-evaluation of underlying assumptions in climate models is necessary. The “assumption of linear climate impact models” is challenged by research highlighting non-linear tipping points and feedback loops within the climate system.[46] These non-linear dynamics render linear projections inadequate. The “sufficiency of historical data” for predicting future climate risks is challenged by palaeoclimate studies and extreme event attribution science, which demonstrate unprecedented climate shifts.[47] Implicit biases in model training data, particularly when AI models are trained on incomplete or geographically skewed climate data, can misrepresent risks for underrepresented regions. This leads to mispriced assets and potential financial instability.[48] The “assumption of universal data availability” is challenged by the NGFS report, which quantifies significant data gaps, identifying 514 out of 1,262 raw data items as unlinked to a source.[49] The systemic implications of Fintech adoption include a significant shift in the competitive landscape. The BIS notes a potential “barbell” market structure, where large, technologically advanced players dominate climate risk analytics, potentially marginalizing smaller banks that lack the necessary investment capacity.[50] This concentration could create new systemic vulnerabilities should these dominant providers experience disruptions, thereby impacting regulatory oversight. A critical re-evaluation of underlying assumptions in climate models is summarized in the table below. This table summarizes the essential re-evaluation of underlying assumptions in climate models, contrasting traditional views with challenges and implications for financial risk assessment. These “Gaps in Literature” and “Unexplored Interconnections” necessitate future research, justifying a “Utility-Driven Research Agenda”. Current understanding and technological application remain insufficient for navigating the complex future of climate resilience in banking. The financial sector’s pursuit of climate resilience, while relying heavily on Fintech innovation, navigates a landscape marked by significant data gaps, fragmented regulatory environments, and the inherent inertia of legacy systems. While Fintech solutions offer granular risk assessment and enhanced transparency in green finance, their widespread adoption encounters fundamental limitations.[55] This necessitates a radical rethinking of data governance, cross-border supervisory cooperation, and a re-evaluation of the implicit assumptions guiding current climate models. The optimal future state involves a symbiotic ecosystem where financial institutions, Fintech innovators, and regulators collaboratively establish standardized, interoperable, and ethically sound frameworks, moving beyond isolated solutions to build a robust and anticipatory climate-resilient financial architecture. Conclusion The escalating threat of climate-related financial risks has emerged as a pivotal concern for global financial stability. This literature review has synthesized a comprehensive body of research concerning the intersection of financial technology (Fintech) and climate risk management within the banking sector. The findings underscore the critical role that Fintech can play in enhancing the banking industry’s capacity to assess, monitor, and mitigate the multifaceted risks posed by climate change. Through the deployment of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), blockchain, big data analytics, and digital platforms for green finance, banks can navigate the complexities of climate risk more effectively. Fintech’s integration into climate risk management represents a transformative shift in how banks can operate in an increasingly volatile environment. The literature indicates that AI and ML can significantly improve risk assessment processes by enabling more accurate modeling of climate-related financial risks. These technologies facilitate the analysis of vast datasets, allowing banks to identify patterns and predict potential impacts of climate change on their portfolios. Furthermore, big data analytics can enhance monitoring capabilities, providing real-time insights into environmental changes and their potential financial implications. Blockchain technology also offers promising solutions for transparency and traceability in green finance initiatives. By creating immutable records of transactions, blockchain can help mitigate concerns related to greenwashing—the practice of presenting an organization as more environmentally friendly than it truly is. This transparency is essential for building trust among stakeholders and ensuring that investments genuinely contribute to sustainability goals. Despite the promising potential of fintech in addressing climate-related financial risks, several challenges and limitations persist. One of the most significant barriers is data scarcity. The availability of high-quality, granular data on climate impacts remains limited, particularly in developing regions. This scarcity complicates risk assessment and modeling efforts, hindering banks’ ability to make informed decisions. Regulatory hurdles also pose a considerable challenge to fintech adoption in climate risk management. The rapidly evolving regulatory landscape surrounding climate-related disclosures and sustainability reporting can create uncertainty for financial institutions. Banks must navigate these complexities while ensuring compliance, which can be resource-intensive and may stifle innovation. Technological integration barriers further complicate the adoption of fintech solutions. Many banks operate on legacy systems that may not be compatible with new technologies. This mismatch can hinder the seamless implementation of advanced analytics and AI, limiting the potential benefits that these technologies can offer. Ethical considerations, particularly concerning algorithmic bias and the risk of greenwashing, must also be addressed. The deployment of AI and ML in climate risk management necessitates a careful examination of the underlying algorithms to ensure they do not inadvertently perpetuate biases or misrepresent environmental impacts. As banks increasingly rely on these technologies, establishing robust ethical guidelines and accountability mechanisms will be essential to maintain credibility and public trust. Considering these challenges, the literature review has illuminated several emerging best practices and innovative approaches that can guide banks in their climate risk management efforts. Collaboration between financial institutions, technology providers, and regulatory bodies is paramount. By fostering partnerships, stakeholders can share expertise, resources, and data, ultimately enhancing the efficacy of fintech solutions in addressing climate risks. Furthermore, the establishment of industry standards for climate risk assessment and reporting can facilitate greater consistency and comparability across financial institutions. Such standards would not only aid banks in aligning their practices with regulatory expectations but also enhance transparency for investors and stakeholders. The promotion of green finance initiatives through digital platforms represents another innovative approach. By leveraging fintech solutions, banks can facilitate access to sustainable investment opportunities, thereby driving capital towards environmentally friendly projects. This approach not only supports climate goals but also aligns with the growing demand from investors for responsible investment options. While this review has synthesized a wealth of existing research, it has also identified several gaps that warrant further exploration. Notably, there is a need for more empirical studies that assess the real-world impact of fintech solutions on climate risk management within banks. Longitudinal studies that track the effectiveness of these technologies over time would provide valuable insights into their sustainability and scalability. Additionally, research exploring the intersection of fintech and climate risk in emerging markets is limited. Given that many developing regions are disproportionately affected by climate change, understanding how fintech can be leveraged in these contexts is crucial. Future studies should investigate the unique challenges and opportunities that these markets present, particularly concerning data availability and regulatory frameworks. Moreover, the ethical implications of using AI and ML in climate risk management require deeper examination. Research focused on establishing best practices for algorithmic transparency and accountability will be vital in ensuring that fintech solutions contribute positively to sustainability goals without exacerbating existing inequalities. The integration of fintech into climate risk management represents a significant opportunity for banks to enhance their resilience in the face of growing climate-related financial risks. The literature review has established that while challenges remain, the potential benefits of leveraging advanced technologies are substantial. By adopting innovative approaches, fostering collaboration, and addressing ethical considerations, banks can navigate the complexities of climate risk more effectively. As stakeholders in the financial ecosystem—researchers, policymakers, and institutions—continue to explore this dynamic landscape, the insights gained from this review can inform strategies that contribute to a more resilient and sustainable financial system. 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Journal of Business Economics and Management (JBEM), ISSN 2029-4433, Vilnius Gediminas Technical University, Vilnius, Vol. 21, Iss. 5, pp. 1486-1507. <https://doi.org/10.3846/jbem.2020.1322>. [1] International Monetary Fund. (2024, April). Navigating Climate Transitions: The Role of Financial Policies. Global Financial Stability Report, Chapter 2. Washington, DC: International Monetary Fund. [2] Nieto, M. J. (2019). Banks, Climate Risk and Financial Stability. Journal of Financial Regulation and Compliance, 27, no. 2: 243–262. <https://doi.org/10.1108/JFRC-03-2018-0043>. [3] International Monetary Fund. (2024). Fintech and Climate Risk Management in Banking. IMF Working Paper, 24/8. Washington, DC: International Monetary Fund, p. 4. [4] Ibid. [5] Arner, D., Barberis, J., Buckley, R. P. (2020). Fintech, Bigtech, and the interoperability of digital financial infrastructure. Journal of Financial Regulation, 6(2), pp. 211-244. <https://www.bis.org/publ/bppdf/bispap117.pdf>. [6] International Monetary Fund. (2024, April). Navigating Climate Transitions: The Role of Financial Policies. Global Financial Stability Report, Chapter 2. Washington, DC: International Monetary Fund. [7] International Monetary Fund. (2024). Fintech and Climate Risk Management in Banking. IMF Working Paper, 24/8. Washington, DC: International Monetary Fund, p. 5. [8] International Monetary Fund. (2024, April). Navigating Climate Transitions: The Role of Financial Policies. Global Financial Stability Report, Chapter 2. Washington, DC: International Monetary Fund. [9] Gomber, P., Kauffman, R. J., Parker, C., Weber, B. W. (2018). On the fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems, 35(1), pp. 220-265. <https://doi.org/10.1080/07421222.2018.1440766>. [10] International Monetary Fund. (2024). Fintech and Climate Risk Management in Banking. IMF Working Paper, 24/8. Washington, DC: International Monetary Fund, p. 17. [11] Ibid., p. 1. [12] Wu, Q. (2024). From bits to emissions: how FinTech benefits climate resilience? Empirical Economics. <https://doi.org/10.1007/s00181-024-02609-9>. [13] Singhvi, S., Dadhich, M. (2023). FinTech Revolution and Future of Sustainable Banking: Opportunities and Risks Analysis. International Journal of Management and Development Studies, vol. 12, no. 04, pp. 12-21. <DOI:10.53983/ijmds.v12n04.003>. [14] Cen .Y and J. Yin. (2024). Navigating Climate Challenges: Focusing on the Effectiveness of Natural Resource Rents, Fintech, Green Finance, Environmental Quality, and Digitalisation. Resources Policy 95: 105102. <https://doi.org/10.1016/j.resourpol.2024.105102>. [15] Mhlanga, D. (2022). The role of financial inclusion and FinTech in addressing climate-related challenges in the industry 4.0: Lessons for sustainable development goals. Front. Clim. 4:949178. <DOI:10.3389/fclim.2022.949178>. [16] Bank for International Settlements (BIS) Innovation Hub, Central Bank of the United Arab Emirates (CBUAE), Emirates Institute of Finance (EIF). (2023). Scaling climate action: Unleashing innovative technologies in sustainable finance. <https://www.bis.org/innovation_hub/projects/2023_cop28_techsprint.pdf>. [17] The International Finance Corporation (IFC). (2023). Mapping of Digital Solutions to Support Financial Services Providers in Assessing Climate Impact on Agricultural Portfolios. <https://www.ifc.org/content/dam/ifc/doc/2024/mapping-of-digital-solutions-to-support-financial-services-providers-in-assessing-climate-impact-on-agricultural-portfolios-ifc-2023.pdf>. [18] Ibid., Executive Summary, p. 4. [19] Kouhizadeh, M., Sarkis, J. (2020). Blockchain Practices, Potentials, and Perspectives in Greening Supply Chains. <https://iaeme.com/MasterAdmin/Journal_uploads/IJRCAIT/VOLUME_7_ISSUE_2/IJRCAIT_07_02_017.pdf>. [20] Bank for International Settlements (BIS) Innovation Hub, Central Bank of the United Arab Emirates (CBUAE), Emirates Institute of Finance (EIF). (2023). Scaling climate action: Unleashing innovative technologies in sustainable finance, Part 2, Finalist showcase - U-Reg Technology. <https://www.bis.org/innovation_hub/projects/2023_cop28_techsprint.pdf>. [21] Ibid., p. 2. [22] Yang, Z., Nguyen T. T. H., Nguyen H. N., Nguyen T. T. N., Cao T. T. (2020). Greenwashing behaviours: Causes, taxonomy and consequences based on a systematic literature review. Journal of Business Economics and Management (JBEM), ISSN 2029-4433, Vilnius Gediminas Technical University, Vilnius, Vol. 21, Iss. 5, pp. 1486-1507. <https://doi.org/10.3846/jbem.2020.1322>. [23] Babu, R. (2024). Blockchain-Enabled Carbon Credit Trading: Revolutionizing Sustainability Efforts. International Journal of Research. Computer Applications and Information Technology (IJRCAIT), 7(2), pp. 228-238. [24] Bartlett, R., Morse, A., Stanton, R., Wallace, N. (2019). Consumer-lending discrimination in the FinTech era. National Bureau of Economic Research. <https://faculty.haas.berkeley.edu/morse/research/papers/discrim.pdf>. [25] Bank for International Settlements (BIS) Innovation Hub, Central Bank of the United Arab Emirates (CBUAE), Emirates Institute of Finance (EIF). (2023). Scaling climate action: Unleashing innovative technologies in sustainable finance, Part 2, Finalist showcase - ZERO13, p. 27. <https://www.bis.org/innovation_hub/projects/2023_cop28_techsprint.pdf>. [26] Ibid. Finalist showcase - Triangle Solution proposed, p. 25. <https://www.bis.org/innovation_hub/projects/2023_cop28_techsprint.pdf>. [27] Ibid., Finalist showcase -STACS Solution proposed, p. 20. <https://www.bis.org/innovation_hub/projects/2023_cop28_techsprint.pdf>. [28] Ibid., Finalist showcase - U-Reg Technology, p. 21. [29] Ibid., p. 2. [30] Network for Greening the Financial System (NGFS). (2022). Final report on bridging data gaps. Section 3.2.1. <https://www.ngfs.net/sites/default/files/medias/documents/final\_report\_on\_bridging\_data\_gaps.pdf>. [31] Ibid., Section 3.2.2. [32] Ibid., Section 3.1. [33] Office of the Comptroller of the Currency (OCC). (2023). Semiannual Risk Perspective. Part IV, E. <https://www.occ.gov/publications-and-resources/publications/semiannual-risk-perspective/files/pub-semiannual-risk-perspective-fall-2023.pdf>. [34] Ibid. [35] United Nations Environment Programme Finance Initiative (UNEP FI). (2024). The Climate Data Challenge: The Critical Role of Open-Source and Neutral Data Platforms. Technical Supplement to the 2024 Climate Risk Landscape Report. <https://www.unepfi.org/wordpress/wp-content/uploads/2024/05/Dataland-Final-Report-The-Climate-Data-Challenge-1.pdf>. [36] Ibid., Section 3.2.2. [37] Ibid., p. 5. [38] The International Finance Corporation (IFC). (2023). Mapping of Digital Solutions to Support Financial Services Providers in Assessing Climate Impact on Agricultural Portfolios. <https://www.ifc.org/content/dam/ifc/doc/2024/mapping-of-digital-solutions-to-support-financial-services-providers-in-assessing-climate-impact-on-agricultural-portfolios-ifc-2023.pdf>. [39] Bank for International Settlements (BIS) Innovation Hub, Central Bank of the United Arab Emirates (CBUAE), Emirates Institute of Finance (EIF). (2023). Scaling climate action: Unleashing innovative technologies in sustainable finance, Part 2, Finalist showcase - Triangle Solution proposed, p. 25. <https://www.bis.org/innovation\_hub/projects/2023\_cop28\_techsprint.pdf>. [40] Ibid., p. 24. [41] Ibid., Part 2, Finalist showcase - ZERO13, p. 27. [42] The International Finance Corporation (IFC). (2023). Mapping of Digital Solutions to Support Financial Services Providers in Assessing Climate Impact on Agricultural Portfolios. <https://www.ifc.org/content/dam/ifc/doc/2024/mapping-of-digital-solutions-to-support-financial-services-providers-in-assessing-climate-impact-on-agricultural-portfolios-ifc-2023.pdf>. [43] Feyen, E., Frost, J., Gambacorta, L., Natarajan, H., Saal, M. (2021). Fintech and the digital transformation of financial services: implications for market structure and public policy. BIS Papers No 117. Bank for International Settlements and the World Bank Group. <https://www.bis.org/publ/bppdf/bispap117.pdf>. [44] Bolton, P., Despres, M., Pereira da Silva, L. A., Samama, F., Svartzman, R. (2020). The green swan: Central banking and financial stability in the age of climate change. Bank for International Settlements. Abstract, Executive Summary, Chapter 1 (pp. 1-10), Chapter 3 (pp. 23-46), Chapter 4 (pp. 47-64), Chapter 5 (pp. 65-67), Annex 2 (pp. 72-78). <https://www.bis.org/publ/othp31.pdf>. [45] Ibid., Chapter 4.5, p. 63. [46] Gosling, T. (2024). Universal Owners and Climate Change, Journal of Financial Regulation, Vol. 00, No. 00, pp. 1–40. <https://lbsresearch.london.edu/id/eprint/3972/1/fjae010.pdf>. [47] Ibid., p.15. [48] Basel Committee on Banking Supervision. (2021). Climate-related financial risks – measurement methodologies. Basel, Switzerland: Bank for International Settlements. Sections 2.2, 3.2, 4.1.2, 4.2.1, and Executive Summary. <https://www.bis.org/bcbs/publ/d518.pdf>. [49] Network for Greening the Financial System (NGFS). (2022). Final report on bridging data gaps. Section 3.2.1. <https://www.ngfs.net/sites/default/files/medias/documents/final\_report\_on\_bridging\_data\_gaps.pdf>. [50] Feyen, E., Frost, J., Gambacorta, L., Natarajan, H., Saal, M. (2021). Fintech and the digital transformation of financial services: implications for market structure and public policy. BIS Papers No 117. Bank for International Settlements and the World Bank Group. <https://www.bis.org/publ/bppdf/bispap117.pdf>. [51] United Nations Environment Programme Finance Initiative (UNEP FI). (2024). The Climate Data Challenge: The Critical Role of Open-Source and Neutral Data Platforms. Technical Supplement to the 2024 Climate Risk Landscape Report. <https://www.unepfi.org/wordpress/wp-content/uploads/2024/05/Dataland-Final-Report-The-Climate-Data-Challenge-1.pdf>. [52] Office of the Comptroller of the Currency (OCC). (2023). Semiannual Risk Perspective, Part IV, E. <https://www.occ.gov/publications-and-resources/publications/semiannual-risk-perspective/files/pub-semiannual-risk-perspective-fall-2023.pdf>. [53] Bolton, P., Despres, M., Pereira da Silva, L. A., Samama, F., Svartzman, R. (2020). The green swan: Central banking and financial stability in the age of climate change. Bank for International Settlements. Abstract, Executive Summary, Chapter 1 (pp. 1-10), Chapter 3 (pp. 23-46), Chapter 4 (pp.47-64), Chapter 5 (pp. 65-67), Annex 2 (pp. 72-78). <https://www.bis.org/publ/othp31.pdf>. [54] Ibid., Chapter 4.5, p. 63. [55] Dunbar, K., Sarkis, J., Treku, D. N. (2024). Fintech for environmental sustainability: promises and pitfalls. One Earth, 7(1), pp. 23-30. <https://doi.org/10.1016/j.oneear.2023.12.012>.
Copyright (c) 2026 Rym Bouchelit, Abdelkader Belarbi (Author) https://creativecommons.org/licenses/by-sa/4.0/
International Commodity Price Shocks and the Inflation, Consumption, and Investment Effects in Africa
African countries’ participation in the global value chain and trade has evolved steadily. Amidst the recent spike in commodity prices, this trend has important implications for the propagation of trade-price shocks in African economies. This study examines how commodity price shocks shape inflation, consumption, and investment in Africa. We find that the effects of commodity price shocks on inflation, consumption, and investment exhibit significant heterogeneity and qualitative commonalities across countries. We tested the possibility that different commodities may have a disparate bearing on a country’s economic development. The analysis shows that price increases in all commodity types - energy, non-energy, and food commodities–produce similar influences qualitatively, but not in magnitude. Interestingly, non-energy commodities exert greater quantitative effects than energy commodities. Our results indicate that, in most instances, disruptions in the international commodity market may reflect global economic uncertainty, with attendant effects on consumption, investment, and policy decisions in the domestic economy. Keywords: Commodity prices, inflation, investment, consumption, Africa, local projections. JEL classification: C22, E21, E22, E31, F62, Q02. Introduction The global economy has increasingly been characterized by internationally fragmented production processes. The globalization of production processes has given rise to global value chains (GVCs) with many suppliers located in several countries. This trend has important implications for the transmission of trade shocks across countries. Recently, the crisis-plagued world has faced three parallel shocks: energy, fertilizer, and food price shocks. These overlapping crises have renewed interest in the impact of commodity market dynamics on the economy. African countries have made little but growing strides in GVCs.[1] Siba estimates that Africa’s performance in global value chain trade averaged 8% of GDP over the period 2000-2015. Africa’s participation in GVCs is concentrated in a few resource-based and light-manufacturing sectors. Agricultural products, transport services, and mining and related sectors (e.g., petroleum and minerals) were among the leading GVC participation sectors in all African regions in 2015.[2] Africa’s limited integration into global value chains (GVCs) is consistent with the continent’s trade patterns. According to ElGanainy et al.,[3] Africa’s recorded cross-border trade has grown relatively modestly in recent decades, with limited growth in merchandise trade, whereas the continent’s exports to the rest of the world are commodity-dominated. Africa’s involvement in global trade and GVCs has important implications for the region’s vulnerability to external shocks, including commodity-price shocks. The globalization of production processes naturally births the analysis of the international propagation of adverse external shocks. This includes policy-oriented studies on the effects of globalization.[4] In recent years, an increasing number of studies have investigated the role of GVCs in the international transmission of business cycle shocks.[5] According to Kim, Lee, and Park;[6] Athukorala and Kohpaiboon;[7] and Pula and Peltonen,[8] East Asia has become more vulnerable to business cycle movements in the EU and the U.S. as the region has become increasingly integrated in GVCs. The large trade collapse during the Great Recession of 2008–2009 was attributed to the growing role of GVCs in international trade.[9] Other global trade-related studies have analyzed the propagation of trade shocks to the domestic economy. Kilian[10] observes that energy price shocks may have immediate and large effects on the U.S. economy, despite recent observations that the impacts of energy price shocks may have weakened since the second half of the 1980s. Wei[11] demonstrates the effects of oil prices on the stock market, whereas Polgreen and Silos[12] study the propagation of oil price shocks to labour market outcomes. Parra and Wodon[13] argued that while the issue of oil prices remains important, recent attention has focused on food prices. Parra and Wodon reported that oil prices may have larger multiplier effects than food prices, whereas food prices tend to have a larger direct impact on consumers. These findings have important implications for the macroeconomic impact of recent commodity-price crises. Testament to the nature of globalization, the food, energy, and fertilizer crises are not just overlapping but also reinforcing. Energy and fertilizers are notable inputs in industrial food production and supply. At the same time, fertilizer production relies heavily on energy.[14] Thus, the energy crisis has exacerbated the fertilizer crisis. The much costlier fertilizers, together with the fuel crisis, add to the mounting pressure on the global food supply chains. The unfolding triple crisis highlights the central role of global commodity price shocks in driving domestic production, consumption, and economic progress. In addition, commodity exports are major revenue sources for most commodity-dependent African countries, and the dynamics in international commodity markets have important implications for public finances and fiscal measures that can affect private consumption and investments. These caveats are important because they provide anecdotal evidence to support the supply and demand channels through which global commodity price shocks are expected to exert major impacts on the domestic economy. This current contribution addresses the question of the vulnerability of price takers to external shocks and adds to the debate on commodity dependence syndrome. In contrast to previous studies, we provide a comparative analysis of the dynamic impacts of energy, non-energy, and food price shocks on consumer and producer prices. This study relates to previous analyses that highlight how the dynamics of international commodity prices affect domestic prices and the challenges posed to price stabilization policies. However, we advance the discussion and examine whether different commodities exert disparate effects on domestic inflation. Kilian indicates that while recent literature has yielded many insights, there is still more to be learned about how energy price shocks are transmitted through the economy. Against this backdrop, this study provides an in-depth analysis of the quantitative importance of the effects of international commodity prices on domestic consumption and investment. This analysis is important because changes in commodity prices affect the domestic economy through their effects on consumption and investment decisions. Meanwhile, the consumption and investment effects of commodity market dynamics have received little attention. Our contribution covers both private and public consumption and investments, and includes whether various commodities affect consumption and investment decisions differently in different countries. Our empirical analysis employs the local projection method and reveals highly heterogeneous and common impacts of international commodity price shocks on inflation, consumption, and investment. We find no general pass-through of these shocks to headline CPI inflation, with inflationary effects primarily observed in The Gambia, a net-importer. This reflects potential monetary policy responses and exchange rate appreciation, which may directly reduce imported inflation and overall CPI. Producer price inflation responses varied, being largely negative for most countries but positive for South Africa, though nearly all eventually showed some upward pressure. Crucially, both household and government consumption, as well as public and private investment, exhibited significant cross-country variations in their responses. These diverse findings underscore the critical importance of country-specific macroeconomic structures and policy frameworks in mediating external shocks. Practically, this implies that policy architecture in these commodity-dependent African economies must be highly tailored, recognizing that a ‘one-size-fits-all’ approach is ineffective. Understanding these specific transmission channels is crucial for designing targeted interventions that can effectively manage inflation, stabilize consumption, and foster investment in the face of volatile global commodity markets. The remainder of this paper is organized as follows. In Section 2, we discuss the related literature. In Section 3, we present our measures of prices, consumption, and investment, and then present some stylized facts. In Section 4, we introduce the econometric methods. Section 5 presents our empirical results and discussion. Section 6 concludes the paper. Related literature: Macroeconomic Impacts of Commodity Price Shocks Commodity market disruptions tend to have large and far-reaching real effects. Energy is an essential input for all industrial production processes. In addition, energy and food account for a considerable portion of consumption baskets: approximately 25% in advanced economies (AEs), 50% in Low-Income and Developing Economies (LIDE), and almost 40% in Emerging Market Economies (EMEs). According to Avalos et al.,[15] two economic features underscore the variations in the macroeconomic impact of trade price shocks. The first is reliance on imports: for net importing countries, high prices represent a loss of real purchasing power. For net exporting countries, although consumers also face higher prices, real income increases for the entire country. Industrial structure is another dimension of differential impact; energy-intensive sectors, such as manufacturing, may experience more severe impacts than other sectors. Although most African countries are particularly vulnerable to the first count, the prospect of spillover effects of energy price shocks on industrial applications is high. Kilian explains that the traditional view of trade price shocks is that they act as technological or aggregate-supply shocks. Despite important advances, the nature of this supply channel of transmission and its quantitative importance remain unexhausted. An alternative proposition is that trade price shocks affect the economy primarily through their effects on producer and consumer expenditures. From this alternative view, higher energy prices cause both a shift in expenditure and a reduction in aggregate demand. This causes firms to adjust their production plans, with attendant ripple effects throughout the economy. The demand channel of transmission is consistent with anecdotal evidence that oil price shocks are typically perceived as adverse demand shocks at the industry level. Hamilton[16] posited that energy price shocks are transmitted not only through adjustments in consumer expenditures but through similar shifts in firms’ investment expenditures. Energy price shocks may affect non-residential investments via two main channels. First, the cost channel through which an increase in the price of energy raises the marginal cost of production. This channel depends on the energy share of the cost structure. The second channel is the demand channel. Through this channel, a fall in consumer expenditure leads to a decline in the demand for firm output. The literature on the macroeconomic effects of commodity price variability in developing countries has primarily focused on two aspects of variability: ex ante uncertainty about future prices and discrete ex post price shocks.[17] These two manifestations of variability affect investment decisions. Collier and Gunning[18] show that commodity price shocks strongly impact investment. Similarly, Dixit and Pindyck[19] find evidence supporting the view that investment decisions may be very sensitive to the uncertainty generated by commodity market dynamics. Empirically, few studies have sought to ascertain the impact of commodity price shocks on investment decisions. In his work, Dehn showed that the positive effects of commodity price shocks on private investment rates in low-income developing countries are conditional on commodity price levels. On the other hand, Collier and Gunning argue that both the quantity and quality of investment are reduced during shocks due to a combination of factors, including excessive and misdirected public expenditures. In this study, we examine the dynamic impact of commodity price shocks on both public and private investments and ascertain whether different commodities exert disparate influences. Our study builds on the literature regarding the macroeconomic effects of energy price shocks. Park et al.[20] employed a structural vector autoregressive model to examine the impact of oil price variations on Korean macroeconomic indicators and discovered a negative reaction to industrial output and prices. In related studies, He and Lee;[21] and Greenwood-Nimmo et al.[22] concluded that the real economy and financial markets are extremely sensitive to fluctuations in oil prices in South Korea. In their study of the US, Kilian and Zhou[23] found no evidence that gasoline price shocks caused persistent inflationary effects or moved long-run household inflation expectations. Roch[24] determined that macroeconomic volatility and business cycle fluctuations are influenced by commodity price shocks while Qian, Zhang and Li[25] demonstrated that the impact of international commodity price shocks on macro fundamentals in the US and China exhibits temporal variation. Data and Stylized Facts Data sources The data for the analysis include world commodity prices in real terms (all commodities, energy, non-energy, and food), consumer and producer prices, household consumption, government consumption, private investment, and public investment. The dataset is yearly and runs over the period 1960-2022. The data were sourced from the World Bank database (World Development Indicators and the World Bank Commodity Price Data). The analysis included a sample of six (6) countries, selected solely based on data availability. These countries included Ethiopia (ETH), Ghana (GHA), The Gambia (GMB), Senegal (SEN), Mauritius (MUS), and South Africa (ZAR). We proxy consumer and producer prices using consumer (CPI) and producer (PPI) inflation, gauge household and government consumption using household final and government consumption expenditures, respectively, and private and public investment using fixed capital formations. Evolution of trade[26] in major African economies African countries have had divergent experiences in global trade. The wide disparity in the trade experiences of individual countries reflects the fragmented trade policy landscape in Africa and an overall trade environment that has limited greater trade integration both within the continent and with the rest of the world. Trade is highest in Mauritius, with trade as a percentage of GDP remaining above 100 percent in the last six decades (see Figure 1). In contrast, Ethiopia has experienced very limited trade openness, with trade accounting for less than 40 percent of GDP in the last 60 years. Trade in Ghana has almost doubled over the last two decades, largely because of the emergence of crude oil exports. In sharp contrast, trade has declined considerably in Gambia, from an average of about 87 percent to 49 percent in the last 22 years. Trade in the six countries has expanded only modestly, reflecting the modest growth in trade in Africa as a whole in recent decades.[27] Energy, Food, and fertilizer markets developments Energy and food prices have historically co-moved (See Figure 2). Nonetheless, the recent surges in energy and food market prices differ from recent historical precedents in several respects. Notably, prices have increased further. The World Bank’s real food price index stood at 130 in 2022, an increase of 36.7% from 2020, and the highest value since 1975. Energy prices rose more than twice, while non-energy prices rose 31 percent above their troughs in 2020, dwarfing all previous episodes except for the price surges between 1972 and 1981 (Figure 2). But for the 1972-1981 episode of commodity price rise, energy prices experienced the most increases. Econometric Methodology The question of the economic impact of trade price shocks may be an empirical one. Thus, this research seeks a data-driven answer to the question. The empirical analysis considers that commodity market development depends on global macroeconomic aggregates such as global real economic activity and interest rates. Thus, the correlation between macroeconomic outcomes and energy, fertilizer, and food prices does not imply causation. One solution is to extract the exogenous components of trade prices via appropriate statistical transformations[28] and quantify the dynamic impacts of commodity price shocks using impulse responses. Our framework uses Jordà’s[29] local projection method to estimate the impulse responses. Jordà’s local projection approach requires estimating a series of regressions for each horizon, h, for each variable. For h = 0,…,H, we estimated the following linear model: where E is the economic aggregate of interest for country j, and Com is the commodity price. The local projection model directly forecasts E using covariates on the right-hand side of Equation (1). Hence, all estimated coefficients are indexed by h, which is the horizon considered when estimating Equation (1). The coefficient captures the response of E at time t + h to a shock to commodity prices at time t. Thus, we can construct the impulse response function as a sequence of the coefficients , which are estimated in a series of single regressions for each horizon. In contrast, the standard vector auto-regressions (VAR) method provides the parameters for horizon 0 and then uses them to iterate forward to construct the impulse response functions. The local projection method has the advantage of being relatively robust to misspecification of the structural vector auto-regression (SVAR) and does not constrain the shape of the impulse response function. Thus, local projections (LP) do not require any restrictions on VAR systems and are less sensitive to lag length misspecifications. Second, LP does not require all variables to enter all equations, allowing for a more parsimonious specification. Finally, the left-hand side variables do not have to be in the same form as those on the right-hand side. Ramey and Zubairy;[30] and Montiel Olea and Plagborg-Møller[31] provide a more comprehensive comparison of VAR and LP impulse responses. We follow Ramey and Zubairy; and Castelnuovo[32] use Newey and West’s[33] correction for our standard errors as a remedy for the serial correlation in the error terms because of the successive leading of the dependent variable. Finally, we set H = 6 so that the maximum horizon considered for our impulse responses was six years. The variables are expressed as annual growth rates (log-differences). Thus, the impulse responses represent the impact of a 1 percentage point change in commodity price growth on the annual growth rate of the respective macroeconomic variable (CPI, PPI, consumption, or investment). This transformation is standard practice for macroeconomic time series and allows for a clear interpretation of impulse responses as percentage point changes in growth rates. Empirical Results and Discussions In our framework, the commodity price shock is treated as an exogenous variable. This is particularly appropriate for small open economies, where the findings of Arezki et al.[34] underline the role of international commodity prices as external drivers rather than outcomes of domestic macroeconomic variables. This approach is consistent with Jordà and Taylor,[35] who argue that the exogeneity of such shocks ensures the consistency of estimates, even in a two-variable system. This is because omitted macroeconomic or financial factors do not bias the coefficients since they do not predict the shock. While we also experimented with treating the shock as endogenous, it did not significantly alter the impulse responses. This robustness aligns with findings in the literature on local projection (LP) models, which are known to be resilient to misspecification. Several studies, including Montiel Olea and Plagborg-Møller; Møntiel Olea et al.;[36] Li et al.,[37] and Plagborg-Møller et al.,[38] have found no evidence of systematic changes in impulse response estimates when control variables are added. As Jordà emphasizes, LP models often include lags of variables as controls to account for autocorrelation and dynamic effects, ensuring that residuals are white noise. However, these controls are primarily for robustness and efficiency and do not fundamentally change the impulse response itself. Following the methodology of Montiel Olea and Plagborg-Møller, we include up to four lags of the variables as controls to ensure robustness and account for autocorrelation. Impact on consumption The relationship between international commodity prices and government expenditure is profoundly significant for commodity-exporting African countries. These economies heavily rely on commodity exports as a primary source of fiscal revenue, implying that positive price shocks directly translate into increased government income and expanded fiscal space for public spending, including consumption and investment. However, this dependence often leads to pro-cyclical fiscal policies, where spending surges during booms but faces abrupt cuts during busts, contributing to macroeconomic instability and increased debt burdens, as seen in countries like Ethiopia and Ghana. Furthermore, windfall revenues can sometimes fuel discretionary spending driven by political cycles. Understanding this direct channel through which commodity-price shocks influence domestic public finances and aggregate demand is therefore crucial for assessing fiscal sustainability, designing effective fiscal rules, and implementing counter-cyclical policies to mitigate volatility and foster stable economic development. The impulse response plots for government consumption are shown in Figure 3. The magnitude of commodity price shock diffusion on government consumption is negative for most countries, except for Ethiopia and Mauritius. In 2 years after 1 percent increase in commodity prices, government consumption decreased by 0.2 percentage points for The Gambia, 0.12 percentage points for Senegal, 0.4 percentage points for Ghana, and 0.07 percentage points for South Africa. For Ethiopia and Mauritius, government consumption increased by 0.2 and 0.08 percentage points, respectively. We examine whether the impact of commodity price shocks differs according to commodity type. The impulse response plots (Appendix – Figures A1, A2, and A3) show that the impact of energy, non-energy, and food commodity price shocks on government consumption are qualitatively indistinguishable. In terms of size, non-energy commodities have a greater impact on government consumption than energy commodities. Furthermore, we test the propagation of commodity price shocks on household consumption; the impulse responses are shown in Figure 4. For Senegal, we observed a delayed but negative and significant response. In Senegal, household consumption slumped by 0.09 percentage points, 3 years after a 1 percent unanticipated increase in commodity prices, before returning to pre-shock levels 5 years after the shock. However, for Ghana and Mauritius, household consumption increased in reaction to a positive commodity price shock, reaching a peak of about 0.1 percentage points 3 years after the shock. In Ethiopia, The Gambia, and South Africa, household consumption declines initially on impact but increases in the second to fourth years after the commodity price shock. This response pattern may suggest that, in the short run, commodity price increases directly decrease consumer expenditures, but in the second-round effect, there is an increase in consumption given the relatively inelastic demand for energy and food commodities. Disaggregating commodities into energy, non-energy, and food commodities exerts similar impacts in shape (Appendix – Figures A4, A5, and A6). However, in terms of size, price increases for non-energy commodities, including food, exert a greater impact than energy commodities. Kilian explains that higher energy prices are expected to shift consumption expenditures by reducing discretionary income, as consumers have less money to spend after paying their energy bills. However, the less elastic the demand for energy, the larger this discretionary income effect will be, all else being equal. The quantitative effect of energy price changes is bounded by the energy share in consumption, even with a perfectly inelastic energy demand. For commodity-dependent countries like Ghana, the fall in government consumption from a surge in commodity prices is surprising. However, it is noteworthy that for Ghana, after the initial fall, government consumption increased between the third and fifth years, reaching a peak of about 0.2 percentage points. This response pattern may suggest that the reaction of government consumption is conditional on the level of commodity price surges. Income, cost, and uncertainty effects are manifested in the response of government and household consumption to commodity price shocks among African countries. High commodity prices may translate into improved real income and cause a northward movement in consumption expenditures. Through the cost-effect, increased commodity prices would raise the cost of imported energy and non-energy goods and lead to higher consumption expenditure. However, this is dependent on the availability of substitutes and the elasticity of demand for the affected goods. Changing commodity prices may heighten economic uncertainty, causing consumers and governments to consolidate and increase precautionary savings. This is consistent with the submissions by Bernanke,[39] Pindyck, and Solimano[40] that prompted by heightened uncertainties from commodity price dynamics, consumers may postpone irreversible purchases of consumer durables. Impact on investment Figure 5 shows the results of public investment responses to commodity price hikes. The responses are positive for Ethiopia, The Gambia, and Mauritius, and negative for Senegal, Ghana, and South Africa, though not statistically significant. When we examine the effects of different commodities separately, we find that the pattern of responses to energy commodity price shocks is very similar to that obtained for all commodity price shocks (the impulse responses are shown in Appendix Figures A7, A8, and A9). We observe that non-energy community price shocks have a greater impact on public investment than unanticipated hikes in energy commodities for all countries, except for The Gambia and Mauritius. In contrast to energy commodities, the impact of non-energy commodity price increases on public investment in Ethiopia is delayed and negative. In Ghana, public investment increased at some points in reaction to upsurges in non-energy commodity prices, in contrast to the influence of energy price increases. We examine the impact of commodity price hikes on industrial investment. As illustrated in Figure 6, commodity price shocks negatively impacted industrial production in most of the sample countries. In contrast, private investment in The Gambia has been positively impacted. Our results are consistent with those of Inoue, Okimoto,[41] and Kim.[42] Kim discovered that an oil price increase has led to a decline in both the level of industrial output and the price level of goods, and demonstrated that a rise in oil prices had a negative effect on industrial production activities by slowing demand. The respective effects of energy and non-energy commodity price shocks on private investment are almost the same quantitatively and qualitatively (see the impulse response plots in Appendix -Figures A10, A11, and A12). However, food price shocks exerted initial positive effects in Ethiopia and Ghana and a delayed but positive impact in Mauritius. For most commodity-exporting countries, the a priori expectation is that the bulk of the transitory gains from high commodity prices is saved and invested; therefore, investment should increase. Therefore, the observed fall in investment rates during shocks, which occur when prices are high, may be surprising. Instructively, commodity price hikes have increased investment at some point for all the sampled countries except Ghana. This pattern may suggest that a commodity price shock has both growth-enhancing and growth-declining effects on the economy. On the one hand, an unanticipated expansion of the business cycle in global commodity markets may stimulate investment and growth via improved global demand, real income, and savings. However, it raises the cost of energy and non-energy goods, creates uncertainty, and thereby slows investment and growth. Our findings indicate that even resource-rich countries are subject to the volatility of commodity prices, which may undermine investments and growth. The evidence from our analysis is in line with the findings of Gubler and Hertweck[43] and shows that fluctuations in the international commodities market are necessary signals of impending economic downturns and significantly drive consumption and investment decisions. Consistent with Dehn and other studies, we find that commodity prices have a strong effect on investment. Our results show that, contrary to Dehn’s observations, commodity price uncertainty matters for investment decisions in developing countries. Impact on inflation Figure 7 shows a plot of the responses of headline CPI inflation among the sampled African countries. The magnitude of the commodity price shock diffusion on headline CPI inflation is negative for most countries, except for The Gambia. A one percent increase in commodity prices raises the headline CPI inflation by 0.14 percentage points for The Gambia. For other African countries, Ghana responds the most (-0.75 percentage point), followed by Mauritius (-0.21 percentage point), Senegal (-0.19 percentage point), Ethiopia (-0.14 percentage point), and South Africa (-0.03 percentage point). We also examine the responses of headline CPI inflation to different commodity price shocks. The responses of headline CPI inflation to the energy commodity price shock (Appendix – Figure A13), non-energy commodity price shock (Appendix – Figure A14), and food price shock (Appendix - Figure A15) resemble those of the all-commodity price shock qualitatively. In terms of magnitude, non-energy and food price shocks generate larger effects for all countries except for Ghana. This may suggest that energy products exert a relatively great pressure on CPI inflation in Ghana. We investigate the responses of PPI inflation, as shown in Figure 8. We observe negative and significant responses for all the countries, except for South Africa. Except for The Gambia, the rest of the countries with negative responses exhibit a positive response at some point within the five years after the shock. Non-energy commodities wielded greater quantitative effects on PPI inflation than energy commodities in all the countries. The impulse response plots for the effects of energy, non-energy, and food commodity price hikes on PPI inflation are shown in the Appendix, Figures A14, A15, and A16, respectively. Our empirical estimates are consistent with theory and other results in the literature. Kilian and Zhou[44] estimated that the energy price shocks were not primarily responsible for the 2021 and 2022 inflationary pressures in the US. In Korea, Greenwood-Nimmo et al.[45] found that oil price shocks have had a minor effect on inflation. Sekine and Tsuruga[46] observed that the effect of commodity price shocks on inflation varies across country groups and is transitory, suggesting a low risk of a persistent second-round effect on inflation. Despite popular opinion and expectations, there was no general evidence of a pass-through of commodity prices, including energy and food price shocks to inflation. Conventionally, an increase in commodity prices, especially energy, is expected to feed into domestic inflation through increased production costs (for PPI) and higher consumer prices (for CPI). The evidence from our analysis shows that international commodity price surges would, in most instances, not be likely to create persistent inflation. For commodity-exporting countries like Ghana, Senegal, or South Africa, a positive commodity price shock can lead to an appreciation of the domestic currency, backed by increased foreign exchange inflows. A stronger currency makes imported goods cheaper, which directly reduces imported inflation and overall CPI, especially in economies heavily reliant on imports. This supply-side disinflationary effect could outweigh demand-side inflationary pressures. Do our estimates suggest any role for policy in moderating the dynamic impacts of commodity price changes on the macroeconomy? One possible explanation for our results is that policy tightening in response to the expected inflationary pressures and the uncertainty generated by the commodity market turmoil may have kept inflationary impulses muted. While this is confirmed by the fiscal consolidation in reaction to unanticipated commodity price surges, the case for monetary policy would have to be tested. Besides, governments in commodity-rich countries might use increased revenues from commodity booms to subsidise essential goods, including fuel and food, thereby dampening inflationary pressures on consumers and producers. This is a common policy response aimed at mitigating the cost of living. Notwithstanding, our results show that external drivers, including international commodity dynamics, play a considerable role in the inflation transformation in The Gambia. The results confirm the findings of Nachega et al.[47] that there is a strong co-movement between global food inflation and CPI inflation in The Gambia, which can be explained by the fact that The Gambia is a net importer of essential foods and energy, and the weight of food items and non-alcoholic beverages in The Gambia’s CPI basket is around 50 percent. In South Africa, the cost channel appears to be important, making the prospect of spillover effects of commodity price shocks on industrial applications high. However, it appears the shifts in producer prices are not passed on to consumers. These results have important implications for policymakers. The sensitivity of the domestic economy to international commodity dynamics may not be entirely dependent on the integration into GVCs and global trade per se. But more importantly, it is the fact that international commodity markets’ dynamics reflect global economic uncertainty and demand, with the attendant reactions in the domestic economy. The results suggest that a combination of the policy stance at the time of the shock and policy changes made in response to the shock is critical in maintaining economic stability and mitigating any adverse effects from the international commodity markets’ dynamics. Conclusions The sharp rise in energy and food prices in recent years has renewed interest in the question of how much higher commodity prices affect economic development. Our analysis allows us to assess the overall effects of such a price increase on CPI and PPI inflation, household and government consumption, and public and private investments. First, we find no evidence of a general pass-through of commodity prices, including energy and food price shocks to inflation. Indeed, the inflationary impacts of commodity price shocks on headline CPI inflation are confirmed for only one country, The Gambia, a net-importer of essential foods and energy. Concerning the PPIs, the responses are negative and significant for all the sampled countries except South Africa. For South Africa, the PPI inflation responded positively to commodity price hikes. Even for the countries with negative responses, only The Gambia has not exhibited a positive response at some point within the five years following an unanticipated increase in commodity prices. This implies that the surge of commodity prices has generated some inflationary pressure on a country’s PPI. Secondly, we find cross-country differences in the response of household and government consumption to commodity price shocks. On impact, government consumption initially increased in Ethiopia and Mauritius after a positive shock to commodity prices. For Ghana, The Gambia, Senegal, and South Africa, the response of government consumption was negative. Similarly, the response of household consumption to increases in commodity prices shows considerable cross-country variations. The initial response of household consumption was negative for Senegal, Ethiopia, The Gambia, and South Africa. For Ghana and Mauritius, the response was positive. Lastly, we investigate the impact of a commodity price hike on investment. For public investment, the responses are significantly positive for Ethiopia, The Gambia, and Mauritius, and negative for Senegal, Ghana, and South Africa. Private investment, on the other hand, responded negatively in all countries except in The Gambia. Our analysis includes separating energy and non-energy commodities and evaluating their dynamic impacts. While energy, non-energy, and food commodities exert similar effects qualitatively, non-energy commodities have wielded greater quantitative impacts than energy commodities do. This is quite instructive given that the literature has generally focused on the effects of energy commodities. While energy products have important applications in the economy and are therefore the subject of concern, our empirical estimates show that the dynamics of non-energy commodities have equal prospects in affecting the domestic economy. The overriding conclusion from the analysis is that propagation of commodity price shocks is dominantly through the uncertainty channel, and their ripple effect on the domestic economy is via adjustments in consumer and firm expenditures. This uncertainty has implications for both supply-side and demand-side accounts of the transmission of commodity price shocks. Specifically, consumption expenditures may shift as consumers increase their precautionary savings, while firms may scale back investment in response to uncertainty about demand, cost, and the general economic environment. Thus, when commodity prices rise, the uncertainty effect will reinforce the decline in firms’ investment expenditures due to reduced consumer demand and higher costs. Given the profound structural reliance of many African economies on commodity exports, the fluctuations in commodity prices directly affect fiscal revenues, affect government consumption and investments, influence exchange rate dynamics, and alter household incomes, thereby posing substantial challenges to economic management. Practically, our findings reflect the need for robust fiscal frameworks, including stabilisation funds and debt management strategies, to manage commodity revenue volatility and avoid pro-cyclical spending. The analysis re-establishes the importance of economic diversification and strengthening non-commodity sectors to reduce vulnerability to commodity price fluctuations. The inherent vulnerability of commodity-dependent economic structures means that international commodity price movements are not merely minor disturbances but represent a fundamental driver of business cycle fluctuations and broader macroeconomic instability. This underscores the critical policy relevance of the current research, moving beyond a general statement of importance to highlight the deep-seated structural challenges faced by these nations. In the future, it is worth examining the importance of endogenous policy responses in the macroeconomic implications of commodity price shocks. Thus, we need to understand how the configuration and the response of key policy instruments, especially monetary policy, moderate the macroeconomic dynamics caused by commodity price shocks. The bivariate approach provides the total effect of commodity price shocks, which may implicitly capture omitted channels. Notwithstanding, future empirical work that incorporates a more comprehensive set of control variables within a multivariate LP framework or a Structural Vector Autoregression (SVAR) model is also likely to be promising. This would allow for a more nuanced understanding of the shock transmission mechanisms and address potential endogeneity concerns. References Allard, C., Kriljenko, M. J. I. C., Gonzalez-Garcia, M. J. R., Kitsios, E., Trevino, M. J. P., Chen, M. W. (2016). Trade integration and global value chains in sub-Saharan Africa: In pursuit of the missing link. International Monetary Fund; Arezki, R., Imam, P. A., Kpodar, K., Le-Van, D. (2025). Shocks and shields: Macroeconomic institutions during commodity price swings (Working Paper No. 25/15). 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Value chains in Africa: What role for regional trade? OECD Development Matters; Wei, C. (2003). Energy, the stock market, and the putty–clay investment model. American Economic Review, 93(1). <https://doi.org/10.1257/000282803321455223>. Footnotes [1] Allard, C., Kriljenko, M. J. I. C., Gonzalez-Garcia, M. J. R., Kitsios, E., Trevino, M. J. P., Chen, M. W. (2016). Trade integration and global value chains in sub-Saharan Africa: In pursuit of the missing link. International Monetary Fund. [2] Siba, E. (2022). Value chains in Africa: What role for regional trade? OECD Development Matters. [3] El Ganainy, A., Hakobyan, S., Liu, F., Weisfeld, H., Allard, C., Balima, H. W., Bteish, C., Giri, R., Kanda, D. S., Meleshchuk, S., Ramirez, G. (2023). Trade integration in Africa: Unleashing the continent’s potential in a changing world (IMF Departmental Paper No. 2023/003). International Monetary Fund. [4] See for example, Saito, M., Ruta, M., Turunen, J. (2013). Trade interconnectedness: The world with global value chains (Policy Paper). International Monetary Fund. [5] For example, Gangnes, B., Ma, A. C., Van Assche, A. (2012). Global value chains and the transmission of business cycle shocks (Economics Working Paper Series No. 29). Asian Development Bank. [6] Kim, S., Lee, J. W., Park, C. Y. (2011). Emerging Asia: Decoupling or recoupling. World Economy, 34(1), 23–53. <https://doi.org/10.1111/j.1467-9701.2010.01320.x>. [7] Athukorala, P. C., Kohpaiboon, A. (2011). East Asia in world trade: The decoupling fallacy, crisis, and policy challenges (FIW Working Paper No. 52). Research Centre International Economics. [8] Pula, G., Peltonen, T. A. (2011). Has emerging Asia decoupled? In The evolving role of Asia in global finance (pp. 255–286). Emerald Group Publishing. [9] Bems, R., Johnson, R. C., Yi, K. M. (2010). Demand spillovers and the collapse of trade in the global recession. IMF Economic Review, 58(2), 295–326. <https://doi.org/10.1057/imfer.2010.16>. [10] Kilian, L. (2008). The economic effects of energy price shocks. Journal of Economic Literature, 46(4), 871–909. <https://doi.org/10.1257/jel.46.4.871>. [11] Wei, C. (2003). Energy, the stock market, and the putty–clay investment model. American Economic Review, 93(1), 311–323. <https://doi.org/10.1257/000282803321455223>. [12] Polgreen, L., Silos, P. (2006). Crude substitution: The cyclical dynamics of oil prices and the college premium (FRB Atlanta Working Paper No. 2006–14). Federal Reserve Bank of Atlanta. [13] Parra, J. C., Wodon, Q. (2008). Comparing the impact of food and energy price shocks on consumers: A social accounting matrix analysis for Ghana (World Bank Policy Research Working Paper No. 4741). World Bank. [14] Nitrogen fertilizers require a large amount of natural gas/fossil fuels for production. [15] Avalos, F., Cap, A., Igan, D., Kharroubi, E., Nodari, G. (2022). Energy markets: Shock, economic fallout and policy response (BIS Quarterly Review No. 64). Bank for International Settlements. [16] Hamilton, J. D. (2013). Historical oil shocks. In R. Whaples R. E. Parker (Eds.), Routledge handbook of major events in economic history (pp. 239–265). Routledge. [17] Dehn, J. (2000). Private investment in developing countries: The effects of commodity shocks and uncertainty (Working Paper No. 2000-11). Centre for the Study of African Economies, University of Oxford. [18] Collier, P., Gunning, J. W. (1999). Trade shocks in developing countries. Oxford University Press. [19] Dixit, A. K., Pindyck, R. S. (1994). Investment under uncertainty. Princeton University Press. [20] Park, C., Chung, M., Lee, S. (2011). The effects of oil price on regional economies with different production structures: Evidence from Korea using a SVAR model. Energy Policy, 39(12), 8185–8195. <https://doi.org/10.1016/j.enpol.2011.09.041>. [21] He, Y., Lee, M. (2022). Macroeconomic effects of energy price: New insights from Korea. Mathematics, 10(15), 2653. <https://doi.org/10.3390/math10152653>. [22] Greenwood-Nimmo, M., Nguyen, V. H., Shin, Y. (2012). Probabilistic forecasting of output growth, inflation and the balance of trade in a GVAR framework. Journal of Applied Econometrics, 27(4), 554–573. <https://doi.org/10.1002/jae.1230>. [23] Kilian, L., Zhou, X. (2022). The impact of rising oil prices on U.S. inflation and inflation expectations in 2020–2023. Energy Economics, 113, 106228. <https://doi.org/10.1016/j.eneco.2022.106228>. [24] Roch, F. (2019). The adjustment to commodity price shocks. Journal of Applied Economics, 22(1), 437–467. <https://doi.org/10.1080/15140326.2019.1665316>; [25] Qian, C., Zhang, T., Li, J. (2023). The impact of international commodity price shocks on macroeconomic fundamentals: Evidence from the U.S. and China. Resources Policy, 85, 103904. <https://doi.org/10.1016/j.resourpol.2023.103904>. [26] Trade is measured as the sum of exports and imports as a share of GDP. [27] Trade in Africa as a whole has expanded from 49 percent of GDP in 2000 to 53 percent by 2019 (El Ganainy et al., 2023). [28] Kilian, L. (2008). The economic effects of energy price shocks. Journal of Economic Literature, 46(4), 871–909. [29] Jordà, Ò. (2005). Estimation and inference of impulse responses by local projections. American Economic Review, 95(1), 161–182. <https://doi.org/10.1257/0002828053828518>. [30] Ramey, V. A., Zubairy, S. (2018). Government spending multipliers in good times and in bad: Evidence from U.S. historical data. Journal of Political Economy, 126(2), 850–901. <https://doi.org/10.1086/696277>. [31] Montiel Olea, J. L., Plagborg-Møller, M. (2021). Local projection inference is simpler and more robust than you think. Econometrica, 89(4), 1789–1823. <https://doi.org/10.3982/ECTA18756>. [32] Castelnuovo, E. (2019). Yield curve and financial uncertainty: Evidence based on U.S. data. Australian Economic Review, 52(3), 323–335. <https://doi.org/10.1111/1467-8462.12324>. [33] Newey, W. K., West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3), 703–708. <https://doi.org/10.2307/1913610>. [34] Arezki, R., Imam, P. A., Kpodar, K., Le-Van, D. (2025). Shocks and shields: Macroeconomic institutions during commodity price swings (Working Paper No. 25/15). International Monetary Fund. <https://www.imf.org/en/Publications/WP/Issues/2025/01/24/Shocks-and-Shields-Macroeconomic-Institutions-During-Commodity-Price-Swings-560031>. [35] Jordà, Ò., Taylor, A. M. (2025). Local projections. Journal of Economic Literature, 63(1), 59–110. <https://doi.org/10.1257/jel.20241521>. [36] Montiel Olea, J. L., Plagborg-Møller, M., Qian, E., Wolf, C. K. (2024). Double robustness of local projections and some unpleasant VARithmetic. NBER Working Paper Series, No. 32463. National Bureau of Economic Research. <https://doi.org/10.3386/w32463>. [37] Li, D., Plagborg-Møller, M., Wolf, C. K. (2024). Local projections vs. VARs: Lessons from thousands of DGPs. Journal of Econometrics, 244(2), Article 105650. <https://doi.org/10.1016/j.jeconom.2023.105650>. [38] Montiel Olea, J. L., Plagborg-Møller, M., Qian, E., Wolf, C. K. (2025). Local projections or VARs? A primer for macroeconomists. NBER Macroeconomics Annual 2025, 40. <https://doi.org/10.48550/arXiv.2503.17144>. [39] Bernanke, B. S. (1983). Irreversibility, uncertainty, and cyclical investment. Quarterly Journal of Economics, 98(1), 85–106. <https://doi.org/10.2307/1885568>. [40] Pindyck, R. S., Solimano, A. (1993). Economic instability and aggregate investment. NBER Macroeconomics Annual, 8, 259–303. [41] Inoue, T., Okimoto, T. (2017). Measuring the effects of commodity price shocks on Asian economies (ADBI Working Paper No. 693). Asian Development Bank Institute. [42] Kim, Y. (2005). The impact of oil price change on the Korean manufacturing sector. Environmental and Resource Economics Review, 14(2), 291–336. [43] Gubler, M., Hertweck, M. S. (2013). Commodity price shocks and the business cycle: Structural evidence for the U.S. Journal of International Money and Finance, 37, 324–352. <https://doi.org/10.1016/j.jimonfin.2013.06.005>. [44] Kilian, L., Zhou, X. (2022). The impact of rising oil prices on U.S. inflation and inflation expectations in 2020–2023. Energy Economics, 113, 106228. [45] Greenwood-Nimmo, M., Nguyen, V. H., Shin, Y. (2012). Probabilistic forecasting of output growth, inflation and the balance of trade in a GVAR framework. Journal of Applied Econometrics, 27(4), 554–573. [46] Sekine, A., Tsuruga, T. (2018). Effects of commodity price shocks on inflation: A cross-country analysis. Oxford Economic Papers, 70(4), 1108–1135. <https://doi.org/10.1093/oep/gpy025>. [47] Nachega, J. C., Kwende, G., Barroeta, F. A. M., Kemoe, L. (2024). Domestic and external drivers of inflation: The Gambia (IMF Selected Issues Paper No. 2024/004). International Monetary Fund.
Copyright (c) 2026 Johnson Worlanyo Ahiadorme (Author) https://creativecommons.org/licenses/by-sa/4.0/
Forecasting the Economic Impacts of Renewable Energy Transition in Hydrocarbon-Exporting MENA Economies
This study examines the macroeconomic implications of accelerating the renewable energy transition in hydrocarbon-exporting Middle East and North Africa (MENA) economies. Drawing on annual data from 2000 to 2024 for Saudi Arabia, the United Arab Emirates, Qatar, Kuwait, Algeria, and Oman, we estimate a panel structural vector autoregression (SVAR) that treats oil prices, global demand, and national renewable policy efforts as exogenous shocks. The model captures the dynamic interplay among non-oil GDP, government revenue, labor‑market outcomes, and renewable‑energy penetration. Impulse‑response analysis reveals that a positive renewable‑energy shock leads to sustained increases in non-oil GDP and modest reductions in unemployment, while fiscal dependence on hydrocarbons declines slightly. Scenario-based forecasts to 2035 show that countries with more ambitious renewable‑energy policies, such as the United Arab Emirates and Saudi Arabia, enjoy the largest absolute gains in non-oil GDP, whereas smaller economies still achieve meaningful proportional improvements. These findings underscore the potential of renewable investments to accelerate economic diversification and mitigate fiscal vulnerabilities. By incorporating a domestic policy index and forecasting alternative adoption paths, the study fills a gap in exporter-specific research and provides practical insights for policymakers seeking to balance growth with the energy transition. Keywords: Renewable energy transition, hydrocarbon-exporting MENA, structural VAR, scenario forecasting, economic diversification. Introduction The energy transition is reshaping macroeconomic prospects for fossil‑fuel exporters amid record global deployment of renewables and tightening climate goals. In 2024, renewable power capacity expanded by about 585 GW to reach roughly 4,448 GW worldwide, a 15% annual increase.[1] Despite this surge, current trajectories still fall short of the 2030 tripling target set in international fora, underscoring the urgency of accelerated action. Within this global picture, the Middle East added about 5 GW of new renewable capacity in 2023, signaling momentum but from a comparatively low base.[2] For hydrocarbon-exporting economies, multilateral analysis stresses mounting uncertainty over long-run fossil demand and associated fiscal and external risks, elevating the importance of diversification and resilience. Saudi Arabia remains highly exposed to hydrocarbon cycles; oil rents measured about 24% of GDP in 2021, yet it has accelerated tenders and set ambitions toward large-scale renewables by 2030.[3] The United Arab Emirates exhibits a large non-oil base (non-oil GDP near 77% in 2025 forecasts) while its flagship firm, Masdar, targets 100 GW of wind and solar by 2030,[4] positioning the country as a regional renewables leader. Qatar’s fiscal and external surpluses narrowed with lower hydrocarbon prices in 2023, yet LNG expansion underpins a still‑positive medium-term outlook.[5] Kuwait’s hydrocarbons account for roughly 70% of government revenue and about 80% of exports, reflecting deep fiscal sensitivity to oil prices.[6] Algeria’s hydrocarbons have supplied about two-thirds of budget revenue since 2020,[7] while Oman remains heavily reliant on 85% of public income from oil and gas, prompting tax reform to broaden the base (Maashani et al., 2025).[8] Existing empirical Kahia et al. (2019),[9] Mebrek et al. (2024),[10] Michailidis et al. (2025),[11] Satari Yuzbashkandi et al. (2024)[12] work on MENA often employs panel VARs linking renewable energy, growth, and emissions, but typically centers on net oil importers or broader regional samples with limited exporter-specific analysis. Parallel strands assess oil‑price shocks and macro-outcomes, or fiscal multipliers, yet seldom incorporate explicit renewable penetration metrics within a structural identification for exporters. Cross-country studies suggest renewables can hedge growth against oil‑price volatility, but country‑and‑policy-specific mechanisms remain underexplored for hydrocarbon-exporting MENA economies. Moreover, forward-looking, scenario-consistent forecasts to the mid-2030s are scarce for this subset, particularly those integrating exogenous oil shocks and domestic policy trajectories. Evidence, therefore, reveals a gap at the intersection of renewable adoption, fiscal vulnerability, and macro‑forecasting in exporter contexts. This study addresses the gap by estimating a panel structural VAR with exogenous oil‑price and global‑demand shocks and an explicit domestic renewable‑policy index, enabling causal interpretation and scenario-based projections. The framework recovers impulse responses and variance decompositions while producing conditional forecasts under alternative renewable‑adoption paths. Hypothesis 1 posits that increases in renewable investment and penetration exert a positive and statistically significant effect on long-run GDP growth in hydrocarbon-exporting MENA economies. Hypothesis 2 posits that higher renewable shares reduce fiscal vulnerability to oil‑price volatility, observable as lower revenue elasticity and variance to oil shocks. The empirical assessment covers Saudi Arabia, the United Arab Emirates, Qatar, Kuwait, Algeria, and Oman from 2000-2024 with projections to 2035. The study is important for macroeconomic planning in hydrocarbon-dependent economies facing structural energy market shifts and demanding fiscal agendas. The objective is to quantify the growth and fiscal consequences of renewable deployment using structural identification rather than simple correlations. Scenario‑consistent forecasts aim to inform budgeting, debt sustainability, and diversification strategies under heterogeneous policy and price paths. Additional goals include benchmarking country-specific outcomes across the six exporters and gauging the magnitude of fiscal‑risk mitigation attributable to renewables. The resulting evidence seeks to support credible transition pathways aligned with national strategies and international commitments. The model includes non-oil GDP, revenue ratios, labor metrics, and renewable share, with oil prices, world GDP, and policy index as exogenous. Data (2000–2024) come from the World Bank, IMF, IRENA, and OPEC, with standard transformations. Sign restrictions identify oil and renewable shocks; lag length is data-driven. Forecasts run to 2035 under scenarios; robustness uses local projections and policy index tests (IRENA). The paper sets context, reviews literature, defines data and methodology, and then estimates a panel SVAR. It ends with results, policy implications, and future research directions. Literature Review Over the past few decades, the global energy landscape has undergone a fundamental transformation, driven by escalating environmental challenges and the economic vulnerabilities associated with fossil fuel dependence.[13] This transition has prompted a growing body of academic research aimed at examining the dynamic relationship between energy consumption, particularly renewable energy sources, and economic growth. Special attention has been devoted to resource-abundant regions such as the Middle East and North Africa (MENA), where the imperative to diversify energy portfolios intersects with broader sustainability and development goals. Poudineh et al. (2018)[14] argue that investing in renewable energy is a “no‑regret” strategy for hydrocarbon-exporting MENA economies. They highlight that reforms such as removing fossil‑fuel subsidies and establishing stable regulatory frameworks are crucial for promoting renewables. The study emphasizes electricity market design, robust institutions, and risk‑mitigation measures to attract investment. While not quantitative, the analysis situates renewable‑energy policies within broader energy‑sector reforms and underscores the importance of aligning policies with national development strategies. Kahia et al. (2019)[15] used second-generation panel data techniques on the ten countries with the highest renewable‑energy consumption, addressing cross-sectional dependence and heterogeneity. After confirming unit roots and cointegration via CADF and Westerlund tests, the authors employ Common Correlated Effects (CCE) and Augmented Mean Group (AMG) estimators. They find that renewable‑energy consumption has a positive and significant long-run effect on economic growth, while fossil‑fuel consumption also positively influences growth; however, primary renewable‑energy production exhibits a negative effect, suggesting technological inefficiencies. The study underscores the need for aligning energy policies with sustainability objectives. Kouyakhi (2022)[16] analyses six Arab countries using a Panel ARDL framework with Mean Group (MG) and Pooled Mean Group (PMG) estimators. The analysis confirms a long-run cointegrated equilibrium among renewable‑energy consumption, real GDP, and CO₂ emissions. Long-run MG estimates indicate that renewable‑energy consumption significantly reduces CO₂ emissions (coefficient ≈ −0.13), while economic growth increases emissions (coefficient ≈ 0.84). Short-run coefficients are mostly insignificant, and a Hausman test favors the MG estimator, implying heterogeneity across countries. The authors conclude that policymakers should accelerate the adoption of green technologies to mitigate emissions and decouple growth from environmental degradation. Using panel data for Algeria, Egypt, Iraq, the UAE, Qatar, and Saudi Arabia, Dırır (2023)[17] employs a Panel ARDL model and Dumitrescu-Hurlin causality tests to identify factors influencing renewable‑energy consumption. The model relates renewable consumption to energy imports, national income, inflation, government spending, economic growth, trade, and manufacturing value‑added. Long-run estimates show that energy imports and national income reduce renewable‑energy use, whereas inflation, government expenditure, economic growth, and industrial performance increase it. Causality tests reveal unidirectional causality from energy imports, national income, economic growth, trade and industrial performance to renewable‑energy consumption, but not vice‑versa. Alofaysan (2024)[18] examines eight MENA countries using a non-parametric panel quantile ARDL (Q‑ARDL) and PMG‑ARDL approach. It finds that increases in green innovation and renewable‑energy consumption reduce the carbon footprint at different quantiles and that these effects strengthen over time. PMG‑ARDL results confirm that renewable energy and green innovation protect ecological quality in the long run, whereas economic growth tends to increase environmental degradation; short-run effects are weaker. Policy recommendations stress the importance of supportive regulatory frameworks, R&D investment, and workforce training to harness long-term benefits. Matallah (2024)[19] discusses how AI can enhance forecasting, optimize storage, and support smart grid operations in MENA. Citing recent studies, it notes that AI-based forecasting methods can reduce prediction errors in solar and wind output by up to 30%, improving grid balancing. The MENA AI‑in‑energy market was valued at roughly US$54.48 million in 2024 with a projected CAGR of 22.24% through 2033. The article argues that successful AI deployment could reduce dependence on oil revenues, attract clean‑technology investment, and bolster energy security, but challenges such as data scarcity, regulatory gaps, and potential inequalities must be addressed. Policy pathways include pilot AI projects, investment in data infrastructure, “green AI” strategies, regulatory reforms, and regional cooperation. Unlike earlier research, our study estimates a panel SVAR-X model for six hydrocarbon exporters, incorporating exogenous oil shocks and a newly constructed domestic renewable policy index. This enables causal interpretation of renewable energy’s impact on diversification and fiscal vulnerability. By offering scenario-based forecasts to 2035 under varying policy ambitions, our study fills a critical gap and provides actionable insights for exporter-specific transition strategies. Methodology The panel SVAR framework models each country’s macroeconomic variables as functions of their own lags, the lags of other countries, and exogenous shocks. Identification uses sign restrictions consistent with theory: a positive oil‑price shock is assumed to raise government revenue on impact, while a positive renewable‑energy shock increases the renewable share without contemporaneously affecting oil prices. This approach avoids some of the identification problems inherent in traditional simultaneous equation models by focusing on shocks. Lag lengths are chosen using information criteria, with cross-sectional dependence tests ensuring robustness. Outputs include impulse‑response functions, forecast‑error variance decompositions, and scenario-based forecasts to 2035, validated through 2015–2024 back‑testing. 3.1. Data and variables Annual data for 2000–2024 are compiled for Saudi Arabia, the UAE, Qatar, Kuwait, Algeria, and Oman. Sources include the World Bank’s World Development Indicators (WDI), IMF Government Finance Statistics (GFS) and World Economic Outlook (WEO), IRENA/IEA renewables statistics, OPEC/EIA oil‑price data, and national policy documents. Variables and their characteristics are summarized in Table 1. The choice of real non-oil GDP reflects the need to measure economic activity beyond the hydrocarbon sector and assess whether renewable investments stimulate broader growth. Government revenue as a share of GDP is included because oil revenues accrue mainly to governments, and fiscal policy choices in oil-centered economies significantly influence macroeconomic performance. A labor‑market indicator captures employment and social impacts of the transition, acknowledging that macroeconomic shocks affect labor outcomes. Renewable penetration (share of electricity generation or capacity) is the key policy variable, indicating the progress of the energy transition; higher renewable shares may hedge growth against oil‑price volatility. Brent oil prices enter exogenously as the principal external shock affecting hydrocarbon exporters, while world GDP growth proxies global demand conditions. Finally, a domestic renewable‑policy index constructed from the timing and stringency of renewable targets, auctions, and incentives captures national policy efforts to drive the transition. Results and Discussion Descriptive statistics and trends The non-oil GDP averages $163.4 billion but varies significantly across countries (std. dev. ≈ 131.5), reflecting differences in economic size and diversification. Government revenue ratios range between 24% and 65%, indicating varying degrees of dependence on hydrocarbon income. Unemployment rates span from 2% to 12%, while renewable energy shares range from 0% to 19.76%, and policy indices from 0 to 7.57—highlighting stark differences in labor market dynamics, energy transition progress, and policy ambition, as shown in Table 2. According to the comparative forecast data in Table 3, Saudi Arabia and the UAE exhibit the most substantial non-oil economic scales, both averaging near $325 billion, while Oman’s output remains modest at around $33 billion. Kuwait maintains the highest fiscal reliance on hydrocarbons, with government revenues constituting 60% of GDP, in stark contrast to Qatar’s 29.8%. The UAE demonstrates clear leadership in renewable energy adoption, reaching a 10.5% share, while Kuwait trails significantly. Similarly, the UAE’s top position on the policy index reflects its structured and aggressive commitment to the energy transition. The non-oil GDP of all six hydrocarbon exporters has risen substantially since 2000. The United Arab Emirates and Saudi Arabia show the most pronounced growth, ending 2024 above US$490 bn and US$450 bn, respectively. Qatar climbs steadily from about US$22 bn to around US$200 bn, while Kuwait, Algeria, and Oman remain smaller but trend upward. Renewable‑energy penetration has increased markedly across the six countries, though starting near zero in 2000. The United Arab Emirates leads with penetration exceeding 20 % by 2024, thanks to an ambitious policy and large projects. Saudi Arabia and Qatar follow, reaching roughly 10 % and 8 %, while Algeria and Oman climb toward 7–8 % and Kuwait lags at about 5–6 %. Across all exporters, government revenue as a share of GDP has declined, signaling reduced dependence on hydrocarbon income. Kuwait remains the highest, dropping from around 65 % to just under 55 %, while Saudi Arabia and the UAE fall from around 45 % and 40 % to roughly 35 % and 30 % respectively. Qatar moves from the low 30s to about 25 %, and Algeria and Oman drift from about 50 % toward the mid-40s. The scatter plot shows a clear positive relationship between renewable‑energy penetration and non-oil GDP levels. Countries and years with higher renewable shares tend to exhibit larger non-oil GDP, as evidenced by the upward-sloping fitted line. While there is dispersion in the data indicating that other factors also drive growth, the overall trend supports the idea that clean‑energy adoption complements economic diversification. The heatmap reveals a strong positive correlation between renewable energy share and non-oil GDP (ρ ≈ 0.79), suggesting that clean energy adoption supports economic diversification. Similarly, the renewable policy index strongly correlates with both renewable share (ρ ≈ 0.81) and non-oil GDP (ρ ≈ 0.54). In contrast, government revenue and unemployment exhibit negative relationships with both diversification and policy indicators. This figure plots the response of each variable to a one‑standard deviation increase in the renewable‑energy share. Non-oil GDP (blue) rises quickly, peaking around year 3 and remaining elevated over the horizon, indicating that renewable adoption stimulates broader economic activity. Government revenue (orange) dips slightly—reflecting reduced reliance on hydrocarbon revenues—then stabilizes near zero, suggesting minimal long-term fiscal drag. Unemployment (green) falls by up to 0.12 percentage points and stays below its baseline, consistent with job creation in clean‑energy sectors. The renewable share (red) itself experiences a large initial jump that decays but remains above zero, reflecting partial persistence of policy or investment shocks. This network diagram visualizes the lagged relationships estimated in the VAR (1) model. Nodes represent the four endogenous variables (NonOil GDP, Government Revenue, Unemployment Rate, and Renewable Share). Directed edges show how a lagged change in one variable affects another; edge labels report the coefficient and significance (*** p < 0.01, ** p < 0.05, * p < 0.10). The strongest relationships are the autoregressive links (loops omitted for clarity): Non-oil GDP depends heavily on its own past, and Government Revenue strongly on its own past. Notably, lagged Non‑oil GDP positively influences the renewable share (0.04***), implying that economic expansion encourages renewable adoption, while lagged Government Revenue has little effect on renewables. Negative edges from renewable share to Government Revenue and to Unemployment Rate (coefficients –0.12 and –0.07) capture the slight fiscal and labor‑market improvements following renewable investment. Figure 8 plots the IRFs for non-oil GDP, government revenue, and unemployment in Saudi Arabia, the UAE, and Algeria following both renewable policy shocks and oil price shocks. We observe that renewable policy shocks generally yield moderate positive effects on growth and employment, while reducing fiscal dependence slightly. In contrast, oil shocks produce weak or insignificant effects, suggesting that domestic renewable efforts may offer more stable macroeconomic benefits. Forecast scenario analysis This section explores forward-looking scenarios for non-oil GDP under baseline and accelerated renewable energy adoption paths across six hydrocarbon-exporting MENA economies. Using structural forecast techniques from the panel SVAR model, we compare economic outcomes in 2035 under two distinct trajectories: continuation of current trends versus an enhanced renewable deployment strategy. These projections not only quantify potential gains from energy transition but also reflect the interplay between policy ambition and macroeconomic responsiveness. Figure 9 compares the 2035 non-oil GDP under baseline vs accelerated renewables across six hydrocarbon-exporting MENA countries. UAE and Saudi Arabia record the largest absolute gains (exceeding US$150 billion), while Qatar and Kuwait also rise from lower baselines. Algeria and Oman post notable proportional gains, highlighting country-specific potential tied to renewable ambition and capacity. Stronger policy and infrastructure (e.g., UAE) amplify outcomes; weaker frameworks mute them, underscoring renewables as an economic diversification and macro‑development opportunity. This bubble chart maps each country’s baseline non-oil GDP (x‑axis) against the additional growth under the accelerated scenario (y‑axis); bubble size reflects the strength of each country’s renewable‑energy policy index. Countries in the upper‑right quadrant (e.g., United Arab Emirates and Saudi Arabia) combine large economies with substantial extra growth, highlighting their capacity to capitalize on renewable investments. Qatar shows a strong opportunity relative to its size, whereas Kuwait and Algeria have moderate gains with smaller bubbles, signaling less ambitious policy support. Oman sits lower and to the left, indicating both a smaller economy and more modest gains. This chart visually ranks opportunities and underscores how policy ambition interacts with baseline size. 4.3. Sensitivity and model implications This figure illustrates how macroeconomic variables respond to rising renewable policy ambition across six MENA hydrocarbon exporters. As the Renewable Policy Index increases, non-oil GDP grows across all countries, confirming that proactive renewable strategies align with economic diversification. Unemployment rates decline modestly, reflecting job creation potential in clean energy and associated sectors. Government revenue as a share of GDP decreases slightly, consistent with reduced fiscal reliance on hydrocarbons. Countries like the UAE and Saudi Arabia exhibit the strongest sensitivity due to their ambitious renewable targets and investments. These trends collectively support the hypothesis that renewable adoption enhances resilience and reduces macroeconomic volatility in oil-dependent economies. Conclusion This study demonstrates that accelerating renewable‐energy adoption in hydrocarbon-exporting MENA economies markedly enhances economic diversification: non-oil GDP rises across all countries, unemployment declines, and fiscal reliance on hydrocarbon revenues diminishes. By employing a panel SVAR with exogenous oil‑price and global‑demand shocks and a domestic policy index, the research provides novel, causal insights into how renewable shocks propagate through different macroeconomic channels. Scenario-based forecasts indicate that the United Arab Emirates and Saudi Arabia obtain the largest absolute gains from accelerated adoption, while smaller economies like Oman enjoy proportionally significant improvements. The findings underscore the importance of sustained investment in renewables, supportive policy frameworks, and proactive fiscal planning to ensure resilience during the transition. Collectively, the study adds value by filling a gap in exporter-specific analysis and by offering a replicable framework for scenario forecasting in resource-rich economies. Recommendations Governments should design stable regulatory environments that encourage private investment in renewable projects, including clear bidding procedures, feed-in tariffs, and long-term procurement schedules. Removing fossil‑fuel subsidies and reinvesting windfall revenues into renewable infrastructure and human capital will accelerate the transition while safeguarding fiscal sustainability. The six exporters can benefit from joint renewable projects, cross-border grid integration, and shared financing mechanisms, such as regional green bonds and climate funds. Developing collaborative platforms for technology transfer and knowledge sharing—especially in storage, grid management, and AI-enabled forecasting—will amplify gains and reduce the costs of transition across the region. Future work should extend the model to sectoral and microeconomic levels, examining employment effects within specific industries and incorporating household welfare and income distribution. Researchers could also integrate climate risk metrics, financial development indicators, and firm-level data to capture the interactions between renewable adoption, capital markets, and private investment flows. References: Alofaysan, H. (2024). The effect of environmental smart technology and renewable energy on carbon footprint: a sustainability perspective from the MENA region. Energies, 17(11). <doi.org/10.3390/en17112624>; Dirir, S. A. (2023). Identifying the factors that drive renewable energy consumption in the MENA region. Business Economics and Management Research Journal, 6(2). <doi.org/10.58308/bemarej.1230694>; Kahia, M., Ben Jebli, M., Belloumi, M. (2019). Analysis of the impact of renewable energy consumption and economic growth on carbon dioxide emissions in 12 MENA countries. Clean Technologies and Environmental Policy, 21(4). <doi.org/10.1007/s10098-019-01676-2>; Kahia, M., Ben Jebli, M., Belloumi, M. (2019). Analysis of the impact of renewable energy consumption and economic growth on carbon dioxide emissions in 12 MENA countries. Clean Technologies and Environmental Policy, 21(4). <doi.org/10.1007/s10098-019-01676-2>; Kouyakhi, N. R. (2022). CO₂ emissions in the Middle East: Decoupling and decomposition analysis of carbon emissions, and projection of its future trajectory. Science of the Total Environment (845), 157182. <doi.org/10.1016/j.scitotenv.2022.157182>; Kularatne, C., Miyajima, K., Muir, D. (2024). Estimating the growth impact of economic transformation in Qatar. Review of Middle East Economics and Finance, 20(3). <doi.org/10.1515/rmeef-2024-0011>; Lou, Q., Iqbal, N., Alraey, Y. (2024). Sensitivity to changes in oil prices, tax returns and the cross-section of stock returns: The present situation for net-oil exporting economies. Heliyon, 10(13). <doi.org/10.1016/j.heliyon.2024.e33119>; Maashani, S. S. S., Gamal, A. A. M., Shaarani, A. Z., Rambeli, N., Zulkifli, N. (2025). The role of specific macroeconomic factors on tax revenue policy in an oil-dependent economy: Evidence from Oman. Review of Economics and Political Science. <doi.org/10.1108/reps-06-2024-0017>; Magrassi, G. C., Lanza, A., Travisani, V. (2021). Saudi Arabia in transition: Opportunities for Italian-Saudi cooperation in the age of renewable energy (Thesis); Matallah, S. (2024). MENA oil exporters need a renewable energy transition before the oil wells run dry: A special focus on innovation, financial development, and governance. Geological Journal, 59(3). <doi.org/10.1002/gj.4894>; Mebrek, N., Louail, B., Riache, S. (2024). Do trade openness and foreign direct investment affect CO₂ emissions in the MENA region? New evidence from a panel ARDL regression. Economics and Environment. <doi.org/10.34659/eis.2024.91.4.972>; Michailidis, M., Zafeiriou, E., Kantartzis, A., Galatsidas, S., Arabatzis, G. (2025). Governance, energy policy, and sustainable development: Renewable energy infrastructure transition in developing MENA countries. Energies, 18(11). <doi.org/10.3390/en18112759> ; Miyake, S., Rispler, J., Teske, S. (2025). Solar and wind energy potentials in Australia: A GIS-based assessment for Australia’s ability to transition to net-zero emissions by 2050. Environmental Research Communications, 7(9), 095002. <doi.org/10.1088/2515-7620/adfc30>; Mouffok, M. A., Mouffok, O., Bouabdallah, W., Souar, Y. (2025). Asymmetric Effect of Monetary and Fiscal Policy Uncertainty on the Energy Transition: Evidence from the United States. Globalization and Business, 10(19), pp. 23-40.‏ <doi.org/10.35945/gb.2025.19.002>; Poudineh, R., Sen, A., Fattouh, B. (2018). Advancing renewable energy in resource-rich economies of the MENA. Renewable Energy (123). <doi.org/10.1016/j.renene.2018.02.015>; Satari Yuzbashkandi, S., Mehrjo, A., Eskandari Nasab, M. H. (2024). Exploring the dynamic nexus between urbanization, energy efficiency, renewable energies, economic growth, with ecological footprint: A panel cross-sectional autoregressive distributed lag evidence along Middle East and North Africa countries. Energy & Environment, 35(8). <doi.org/10.1177/0958305X231181672>; Sharif Zadeh, A. (2024). Road to Net-Zero: Impact of economic development in the United Arab Emirates on greenhouse gas emissions as a result of substitution of conventional energy with renewable and clean energy sources. Doctoral thesis, RMIT University; Shenavar, R. (2025). Transition to renewable energy in the Middle East: Challenges, opportunities, and the path to sustainability; Zemrı, B. E. (2024). Forecasting the role of renewable energy on Algeria’s economic stability: ARIMAX model. International Journal of Business and Economic Studies, 6(2). <doi.org/10.54821/uiecd.1474631>. Footnotes [1] Miyake, S., Rispler, J., Teske, S. (2025). Solar and wind energy potentials in Australia: A GIS-based assessment for Australia’s ability to transition to net-zero emissions by 2050. Environmental Research Communications, 7(9), 095002, p. 2. <doi.org/10.1088/2515-7620/adfc30>. [2] Shenavar, R. (2025). Transition to renewable energy in the Middle East: Challenges, opportunities, and the path to sustainability, p.18. [3] Magrassi, G. C., Lanza, A., Travisani, V. (2021). Saudi Arabia in transition: Opportunities for Italian-Saudi cooperation in the age of renewable energy (Thesis), p. 10. [4] Sharif Zadeh, A. (2024). Road to Net-Zero: Impact of economic development in the United Arab Emirates on greenhouse gas emissions as a result of substitution of conventional energy with renewable and clean energy sources. Doctoral thesis, RMIT University, p. 29. [5] Kularatne, C., Miyajima, K., Muir, D. (2024). Estimating the growth impact of economic transformation in Qatar. Review of Middle East Economics and Finance, 20(3), p. 241. <doi.org/10.1515/rmeef-2024-0011>. [6] Lou, Q., Iqbal, N., Alraey, Y. (2024). Sensitivity to changes in oil prices, tax returns and the cross-section of stock returns: The present situation for net-oil exporting economies. Heliyon, 10(13). <doi.org/10.1016/j.heliyon.2024.e33119>. [7] Zemrı, B. E. (2024). Forecasting the role of renewable energy on Algeria’s economic stability: ARIMAX model. International Journal of Business and Economic Studies, 6(2), p. 92. <doi.org/10.54821/uiecd.1474631>. [8] Maashani, S. S. S., Gamal, A. A. M., Shaarani, A. Z., Rambeli, N., Zulkifli, N. (2025). The role of specific macroeconomic factors on tax revenue policy in an oil-dependent economy: Evidence from Oman. Review of Economics and Political Science, p. 6. <doi.org/10.1108/reps-06-2024-0017>. [9] Kahia, M., Ben Jebli, M., Belloumi, M. (2019). Analysis of the impact of renewable energy consumption and economic growth on carbon dioxide emissions in 12 MENA countries. Clean Technologies and Environmental Policy, 21(4), pp. 871-885. <doi.org/10.1007/s10098-019-01676-2>. [10] Mebrek, N., Louail, B., Riache, S. (2024). Do trade openness and foreign direct investment affect CO₂ emissions in the MENA region? New evidence from a panel ARDL regression. Economics and Environment. <doi.org/10.34659/eis.2024.91.4.972>. [11] Michailidis, M., Zafeiriou, E., Kantartzis, A., Galatsidas, S., Arabatzis, G. (2025). Governance, energy policy, and sustainable development: Renewable energy infrastructure transition in developing MENA countries. Energies, 18(11), p. 2759. <doi.org/10.3390/en18112759>. [12] Satari Yuzbashkandi, S., Mehrjo, A., Eskandari Nasab, M. H. (2024). Exploring the dynamic nexus between urbanization, energy efficiency, renewable energies, economic growth, with ecological footprint: A panel cross-sectional autoregressive distributed lag evidence along Middle East and North Africa countries. Energy & Environment, 35(8), pp. 4386-4407. <doi.org/10.1177/0958305X231181672>. [13] Mouffok, M. A., Mouffok, O., Bouabdallah, W., Souar, Y. (2025). Asymmetric Effect of Monetary and Fiscal Policy Uncertainty on the Energy Transition: Evidence from the United States. Globalization and Business, 10(19), pp. 23-40.‏ <doi.org/10.35945/gb.2025.19.002>. [14] Poudineh, R., Sen, A., Fattouh, B. (2018). Advancing renewable energy in resource-rich economies of the MENA. Renewable Energy (123), pp. 135-149. <doi.org/10.1016/j.renene.2018.02.015>. [15] Kahia, M., Ben Jebli, M., Belloumi, M. (2019). Analysis of the impact of renewable energy consumption and economic growth on carbon dioxide emissions in 12 MENA countries. Clean Technologies and Environmental Policy, 21(4), pp. 871-885. <doi.org/10.1007/s10098-019-01676-2>. [16] Kouyakhi, N. R. (2022). CO₂ emissions in the Middle East: Decoupling and decomposition analysis of carbon emissions, and projection of its future trajectory. Science of the Total Environment (845), 157182. <doi.org/10.1016/j.scitotenv.2022.157182>. [17] Dirir, S. A. (2023). Identifying the factors that drive renewable energy consumption in the MENA region. Business Economics and Management Research Journal, 6(2), pp. 170-185. <doi.org/10.58308/bemarej.1230694>. [18] Alofaysan, H. (2024). The effect of environmental smart technology and renewable energy on carbon footprint: a sustainability perspective from the MENA region. Energies, 17(11), p. 2624. <doi.org/10.3390/en17112624>. [19] Matallah, S. (2024). MENA oil exporters need a renewable energy transition before the oil wells run dry: A special focus on innovation, financial development, and governance. Geological Journal, 59(3), pp. 838–853. <doi.org/10.1002/gj.4894>.
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Exploring the Positive Impact of Remote Work on Job Satisfaction: The Mediating Roles of Career Plateau, Autonomy, and Trust
Based on survey responses from public‑sector workers and the IT contractors who work with them (N = 196 for analyses), we explore how remote work is related to satisfaction through autonomy, career plateau, and trust, and the degree to which remote work serves to buffer the negative link between plateau and satisfaction. Results reveal a positive direct effect of remote work on job satisfaction (b=0.114, p=.011), with autonomy mediating a beneficial indirect path (b=0.025, p<.05) and career plateau exacerbating a negative indirect path (b=−0.087, p<.05). Trust does not emerge as a significant mediator, but remote work moderates the negative association between career plateau and satisfaction (b=0.173, p=.010), suggesting a buffering effect. The parallel-mediation model explains 39.7% of the variance in job satisfaction, highlighting the complex interplay between flexibility and career stagnation. These findings combine the work‑design and career‑plateau perspectives: remote working recrafts resources (autonomy) and constraints (plateau) together. Implications entail balancing schedule/location freedom with explicit development trajectories and visibility cues for those who are remote. Our findings contribute to theory by delineating when remote work acts as a resource or constraint, while offering practical insights for organizations navigating hybrid work models. Keywords: Remote work, autonomy, career plateau, job satisfaction, public sector, hybrid work. Introduction Remote Work, Career Plateau, Autonomy, Trust, and Job Satisfaction Remote work has now firmly entered the modern workplace. The COVID‑19 pandemic greatly sped up adoption, but its staying power builds on more fundamental changes in work design, managerial control systems, and employee preferences. Research shows potential benefits that endure (e.g., increased autonomy, better work–life balance, and, in some, increased productivity) but also continuing risks (e.g., boundary control, professional isolation, or career restrictions.[1] But for all these dramatic changes, theory has yet to catch up to practice. What is less well understood is how remote work interacts with employees’ experiences at a career plateau, or how autonomy and trust interact to mediate the effects of remote arrangements on job satisfaction. On its face, the net effect of remote work on employee attitudes looks simple: Remote work expands autonomy, and it saves people from dealing with the commuting time losses, both of which make people happier. There is meta-analytic evidence that Remote work is positively associated with perceived autonomy and work-family outcomes.[2] Field studies also show that in certain organizational contexts, working remotely can increase productivity without affecting its quality.[3] However, there is equally compelling evidence for countervailing dynamics. Randomized and quasi‑experimental studies indicate that workers working at a distance may be promoted less, even though their performance exceeds that of workers in the office, consistent with an inferior visibility or managerial bias hypothesis.[4] On a large‑scale institutional level, these communications report intensification, after‑hours reachability norms (Right to disconnect), and on the one hand, risks to mental health within a weak governance system. [5] Theoretically, it is crucial to clarify these contradicting mechanisms. We propose career plateau—structural (limited promotion) as the missing link. Career plateau is a powerful predictor of reduced motivation, commitment, and job satisfaction.[6],[7] The “classic” interventions to address the plateau (job rotation, mentoring, sponsorship, and developmental assignment) implicitly rely on physical proximity and supervisor‑initiated support. Under remote or hybrid models, these levers may not be applied with any degree of consistency; in fact, remote contexts can either deny plateaued workers the visibility necessary for restarting advancement or, when properly managed and well designed, can mitigate the side effects of plateau.[8] Hence, whether working remotely mitigates or accelerates the plateau has broad, and yet unanswered, theoretical implications, as well as practical implications given the growing trend in remote working. Our research builds on work-design theory[9] and career-plateau literature[10] to propose a parallel-mediation model. We hypothesize that first, remote work enhances job satisfaction by increasing autonomy, second, satisfaction is diminished by amplifying career plateau perceptions, and third, trust moderates these relationships. Additionally, we test whether remote work buffers the negative impact of career plateau on satisfaction, a mechanism that is not overlooked in prior studies. We theorize that the consequences of remote work for job satisfaction flow through two canonical yet under‑integrated mechanisms: autonomy and trust. Autonomy—the degree of decision latitude and control over one’s tasks and timing—is a central driver of positive work attitudes.[11] The study’s contributions are as follows: First, to explain remote work’s dual effects, it integrates theoretical perspectives—autonomy as a job resource and career plateau as a demand. Second, it extends the applicability of these frameworks to public-sector contexts, where institutional factors shape work-design outcomes differently than in private organizations.[12] Work-design and HRM levers translate into outcomes. For example, in Kuwait, HRM becomes ‘a vehicle for diversity management’,[13] and large-sample evidence shows knowledge utilization mediates performance effects.[14] Empirically, we examine public‑sector employees because they commonly face strong procedural constraints, formalized evaluation systems, and hierarchical authority structures that are slow to adapt to virtual collaboration. These features render plateau salient and make the interplay of autonomy and trust particularly consequential for job satisfaction.[15],[16] The setting thus provides a conservative test of our theorized mechanisms and generates insights with broader relevance to organizations attempting to sustain engagement under hybrid or fully remote regimes. Empirical evidence supports our hypotheses. Autonomy mediates a positive indirect path (b=0.025), while career plateau mediates a negative one (b=−0.087). Trust does not significantly mediate the relationship, but remote work weakens the plateau-satisfaction link (b=0.173), highlighting its buffering role. These findings align with recent work on hybrid models.[17],[18] The remainder of this paper is organized as follows: Section 2 reviews theoretical foundations and develops hypotheses. Section 3 details the methodology, including sampling and analytical procedures. Section 4 presents results, and Section 5 discusses implications for theory and practice. The conclusion synthesizes key findings and outlines future research directions. Literature Review The relationship between remote work and job satisfaction has been extensively examined through the lens of work-design theories, particularly the Job Demands-Resources (JD-R) model.[19] This framework posits that job resources, such as autonomy, enhance satisfaction by facilitating goal achievement, whereas job demands, like career stagnation, deplete motivation. Remote work uniquely intersects both pathways, acting as a resource through flexibility while potentially introducing demands via reduced career visibility.[20] Trust, -lateral (collegial)—is foundational to coordination under conditions of information asymmetry and reduced direct supervision; yet empirical research during the pandemic offers mixed findings on whether remote work strengthens trust (by signaling organizational support) or erodes it (by amplifying monitoring frictions, reduced visibility, and uncertainty).[21] We posit that autonomy and trust operate as linked pathways that can either buffer or amplify the negative effects of plateau on satisfaction in remote settings. Although prior research on trust has been mainly conducted in traditional office settings, it is believed that the remote nature of work may change individuals’ patterns in evaluating trust.[22] The quality of communication in remote teams often depends on the level of trust. A recent study found that when employees felt isolated during the pandemic, communication quality declined, and low information-sharing in turn reduced trust levels.[23] In other words, the isolation loop in turn led to lowering trust levels. However, when teams intentionally maintained high-quality communication, they preserved trust and thus prevented work-related isolation.[24] This means that a lack of information is less frustrating for employees with high levels of trust in their peers, as the need for extra information is inversely related to trust levels.[25] Conceptually, we view remote work as a contextual resource that can expand decision latitude and task control (autonomy) but may simultaneously attenuate informal visibility, thereby undermining advancement prospects and trust. Career plateau captures constraints on perceived future movement. When autonomy is high and trust is strong, plateaued employees can reconfigure work around meaningful task variety and schedule control, improving satisfaction despite limited formal advancement opportunities. When autonomy is low or trust is weak, remote work can intensify plateau’s negative effects by isolating employees from information flows and support networks. Autonomy emerges as a central mechanism linking remote work to satisfaction. The Conservation of Resources (COR) theory further explains this relationship, suggesting that autonomy preserves psychological resources by minimizing role conflict.[26] However, autonomy’s benefits may be context-dependent. Public-sector employees, for instance, often face rigid accountability structures that constrain the positive effects.[27] Autonomy Pathway. Remote work affords greater control over the timing and location of tasks, which should increase intrinsic motivation. We therefore expect remote work to exert a positive indirect effect on job satisfaction via autonomy, particularly for employees who perceive a plateau but retain latitude to redesign tasks.[28] Cross‑national heterogeneity in the feasibility of working from home further conditions predicted effects: in economies with limited digital infrastructure or high task‑in‑presence occupations, the autonomy pathway may be weaker while trust frictions are stronger.[29],[30],[31] These considerations motivate testing our model in a public‑sector context within a developing economy. Boundary conditions matter. Institutional frameworks that regulate working time, data security, and the right to disconnect shape managerial discretion and employees’ ability to maintain boundaries.[32] Occupational stratification in flexibility access can also create two‑tier systems in which higher‑status roles reap the benefits of location independence while lower‑status roles are excluded.[33] Cross‑national research shows that the feasibility of working from home varies widely across economies due to industrial structure and digital infrastructure.[34] These contingencies underscore the need to test theory outside of Western, high‑infrastructure corporate contexts—particularly in public sector organizations and developing‑economy settings where hierarchical control norms and resource constraints are salient.[35] Taken together, the literature suggests a precise research problem: remote work introduces countervailing forces that can either mitigate or intensify career plateau. On one hand, remote work can elevate autonomy, reduce interruptions, and enable deep work, thereby enhancing satisfaction; it can also widen internal labor markets by decoupling assignments from physical location. On the other hand, remote work can reduce face‑to‑face interactions, limit informal learning, and trigger managerial skepticism about commitment, producing promotion penalties and trust erosion.[36],[37],[38] The unresolved theoretical question is how these mechanisms jointly determine job satisfaction among plateaued employees—and under what organizational and institutional conditions one mechanism dominates the other. Accordingly, we ask three interrelated research questions: RQ1: How does remote work relate to employee job satisfaction when considering the existence of a career plateau? RQ2: Do autonomy and trust mediate the relationship between remote work and job satisfaction, net of plateau effects? RQ3: Under what boundary conditions (e.g., managerial practices, institutional safeguards, housing issues) do the autonomy and trust pathways offset—or fail to offset—the adverse attitudinal consequences of plateau? In sum, our study makes three contributions to management theory. First, we extend the career plateau literature by analyzing plateau not only as a static constraint but as a contingent state whose attitudinal consequences depend on work design and governance in virtual contexts.[39],[40] Second, we integrate Remote work research with classic work design theory by specifying autonomy and trust as “joint” mechanisms that transmit the effects of remote work to satisfaction. This integrative model clarifies why the same remote arrangement can yield opposite outcomes across organizations. The main objective is to advance theory by clarifying when and why remote work alleviates—or intensifies—the attitudinal consequences of career plateau. By modeling autonomy and trust as joint mediators and specifying institutional and managerial boundary conditions, we integrate work design and Remote work literatures and illuminate practical levers for organizations seeking to retain and motivate plateaued employees in remote settings. The next sections describe the empirical context and measures, and report analyses that adjudicate among competing mechanisms. Methodology This section outlines the research design, data collection methods, sample characteristics, and analytical techniques used to examine the relationship between career plateau, remote work, job autonomy, and job satisfaction. Research Design The study follows a quantitative research design, utilizing a cross-sectional survey method to collect data from employees across various industries. The quantitative approach allows for the empirical testing of the proposed hypotheses and the examination of relationships between the variables of interest. The use of survey data enables the collection of self-reported measures on career plateau, job satisfaction, and remote work experiences. Population and Sample The target population for this study consists of full-time employees working in both remote and non-remote settings. The sample includes individuals from both public and private sector organizations to ensure diversity in work environments and career progression opportunities. The sample was selected based on the following criteria: Recruitment was conducted via social media and via email. Due to gatekeeper constraints, the HR unit did not authorize outreach via official work email; therefore, we employed nonprobability convenience–purposive sampling (criterion targeting of agency staff and affiliated personnel). We directly invited approximately 400 unique individuals (Public Service Agency employees and affiliated IT contractors). Of these, 196 completed the survey (≈50% completion). Because some invitations were issued via group posts, the denominator for broadcast reach is approximate; we therefore report completion counts and an indicative response rate. The sample size was determined using Cohen’s power analysis, targeting a medium effect size (0.40) with 80% statistical power, resulting in a target sample size of approximately 200 respondents. A priori, with N=196 at α=.05, the design affords ~80% power to detect small–medium effects (e.g., r=.20; d=.40; R2=06), whereas very small effects and weak interactions may be underpowered. Power Analysis (Cohen‑style; α = .05, target power = .80; N = 196). With N = 196, the study is powered to detect the following minimum detectable effects (MDE). Values are approximate and suitable for reporting; tailored computations may vary slightly with exact model specifications and predictor counts. sampling method: Nonprobability, convenience–purposive sampling (criterion-targeted). method was used to ensure representation of the employee in public sector of Georgia. Results We tested a parallel-mediation model (PROCESS Model 4; 5,000 bootstrap samples; two-tailed 95% CIs) with remote work as the predictor, job satisfaction as the outcome, and three mediators—trust in the organization, career plateau, and job autonomy—using complete cases (N = 196). All coefficients reported below are unstandardized; p values are two-tailed. Model Fit and Diagnostics Variance inflation factors (VIFs) for all predictors ranged from 1.12 to 1.87, well below the conventional threshold of 5, confirming the absence of multicollinearity. Residual diagnostics revealed normally distributed errors (Shapiro-Wilk W=0.986, p=.214), supporting the validity of parametric tests. The model’s explanatory power (R2=.397) substantially exceeds typical values in job satisfaction research (median R2=.25 in comparable studies,[41] likely due to the simultaneous inclusion of both resource and demand pathways. direct path: Remote work exhibited a positive direct effect on job satisfaction (b=0.114, SE=0.044, t=2.57, p=.011), with a 95% confidence interval excluding zero [0.027, 0.201]. This suggests that, independent of mediation pathways, increased remote work frequency and positive attitudes toward remote work enhance satisfaction—a finding consistent with meta-analytic evidence on flexibility benefits.[42] However, the modest effect size indicates that unmediated relationships alone cannot fully explain satisfaction dynamics, necessitating examination of indirect paths. Mediation. The omnibus model for job satisfaction was significant (R² = .397, F(4, 191) = 31.41, p < .001). The direct effect of remote work on job satisfaction was positive (b = 0.114, SE = 0.044, t = 2.57, p = .011; 95% CI [0.027, 0.201]). Among the mediators, trust (b = 0.357, SE = 0.048, p < .001) and autonomy (b = 0.182, SE = 0.054, p = .001) were positively related to satisfaction, whereas career plateau was negatively related (b = −0.189, SE = 0.045, p < .001). On the a-paths from remote work to the mediators, remote work significantly increased career plateau (b = 0.458, SE = 0.064, p < .001) and autonomy (b = 0.139, SE = 0.052, p = .008) but did not significantly affect trust (b = −0.063, SE = 0.059, p = .284). This aligns with prior research emphasizing the dual nature of remote work’s impact (Fritsch et al., 2025), though our public-sector context introduces unique institutional constraints not fully captured in private-sector studies (Pedro & Bolívar, n.d.). Mediator Relationships The total indirect effect of remote work on satisfaction was not statistically significant (b = −0.084; BootSE = 0.046; 95% CI [−0.175, 0.006]). Decomposed by mediator, the specific indirect effects were via career plateau, negative and significant (b = −0.087; BootSE = 0.026; 95% CI [−0.140, −0.039]) corroborating its status as a psychological demand (Abele et al., 2012). via autonomy, positive and significant (b = 0.025; BootSE = 0.014; 95% CI [0.002, 0.056]); supporting its role as a critical job resource[43] and via trust, nonsignificant (b = −0.023; BootSE = 0.025; 95% CI [−0.074, 0.027]). Thus, remote work appears to operate through countervailing mechanisms: increasing autonomy (beneficial) and increasing career plateau (harmful), which offset in aggregate while the direct association remains positive. aligning with mixed findings about its centrality in remote contexts. [44] The differential strengths of these relationships suggest that autonomy and plateau may operate as primary mechanisms, while trust functions as a boundary condition—a possibility explored in subsequent moderation analyses. Notably, the mediators’ effect sizes remained stable when controlling for tenure, age, and sector, indicating robust relationships across demographic subgroups. Comparative Insights The dominance of autonomy and plateau effects over trust contrasts with earlier findings emphasizing interpersonal factors in remote work satisfaction.[45] This could indicate that trust becomes salient only when mediated through autonomy—a possibility warranting future research. The parallel mediation framework advances beyond traditional single-mediator models by quantifying how remote work simultaneously activates opposing psychological processes. As shown in subsequent subsections, this approach reveals nuanced trade-offs that inform both theory and practice regarding hybrid work implementation. Moderation Analysis: Remote Work × Career Plateau In a separate regression, we tested whether remote work attenuates the negative association between career plateau and satisfaction. The interaction was positive and significant (b = 0.173, SE = 0.067, t = 2.60, p = .010; model R² = .251). The main effect of plateau was negative (b = −0.930, SE = 0.231, p < .001); the main effect of remote work was not significant (b = −0.263, SE = 0.239, p = .274). The positive interaction indicates a buffering pattern—the detrimental association between plateau and satisfaction is weaker at higher levels of remote work. Sample-size differences relative to the full survey (199 completes) reflect listwise deletion in these models (N = 196). Discussion Interpretation of Findings This study examined how remote work relates to job satisfaction through three theoretically grounded pathways—autonomy, career plateau, and trust—and whether the remote-work context changes how strongly plateau depresses satisfaction. Across analyses, remote work showed a positive direct association with job satisfaction; autonomy partially transmitted this benefit; perceived career plateau transmitted a countervailing negative path; generalized trust did not carry the effect; and remote work attenuated the negative association between plateau and satisfaction. Taken together, the pattern clarifies why remote arrangements elevate average satisfaction while some employees simultaneously worry about stalled growth: the same arrangement delivers a valued day-to-day job resource while exposing or amplifying a career constraint. We interpret these results through Job Demands–Resources (JD–R) and Conservation of Resources (COR) perspectives. Remote work reconfigures the resource–demand balance: it increases decision latitude and boundary control (a job resource) but can weaken informal exposure to sponsorship, mentoring, and serendipitous opportunities (a career demand). In JD–R terms, autonomy functions as a resource that uplifts attitude,[46] whereas plateau perceptions operate as a demand that depresses them. From a COR lens, remote work supplies resources (time sovereignty, reduced commuting, control of boundaries) that can be invested to offset losses associated with the plateau.[47] The positive direct effect of remote work is consistent with prior evidence that flexible arrangements, on average, increase job satisfaction through improved autonomy, reduced role stressors, and better work–life fit.[48] Our mediation results sharpen this account by locating autonomy as a proximal job characteristic that carries a measurable portion of the effect. At the same time, the negative mediation via plateau echoes the career literature that links perceived stagnation to lower attitudes and well-being.[49],[50],[51] Remote work, therefore, is not an unalloyed good: it is a design choice that redistributes resources and demands in ways that are beneficial on average but uneven across individuals. The non-significant mediation via trust suggests that—in our setting—trust is less a direct attitudinal conduit and more an upstream condition for autonomy. Once autonomy is explicitly modeled, generalized trust adds little incremental explanatory power for job satisfaction, aligning with work-design perspectives that prioritize proximal task characteristics.[52] Finally, the moderating role of remote work on the plateau–satisfaction link indicates a buffering process: when employees have more latitude and temporal control, the psychological costs of stalled advancement are less damaging to their immediate job attitudes. This helps reconcile the empirical coexistence of high average satisfaction among remote workers with persistent concerns about career progress. In short, flexibility can coexist with stagnation, and the former can soften the attitudinal penalty of the latter. Direct Effect: Why Remote Work Elevates Satisfaction Remote work consolidates several micro-resources—quiet time for task focus, discretion over scheduling, and control over interruptions—that map directly onto increased experienced autonomy and reduced hindrance stressors. Meta-analytic evidence indicates small-to-moderate average gains in satisfaction, particularly when telework intensity is moderate and choice is present.[53] Our estimates are consistent with this magnitude and pattern. Buffering: Remote Work and the Plateau–Satisfaction Link The moderation indicates that flexible conditions reduce the marginal disutility of feeling plateaued. Mechanistically, boundary control and time sovereignty may allow employees to reallocate effort toward meaningful side projects, skills development, or nonwork roles, thereby preserving affective evaluations even when formal advancement is slow. We label this pattern buffered plateauing: the career constraint is not eliminated, but its attitudinal consequences are attenuated by context-supplied resources. Theoretical Implications First, we bridge work design and career dynamics by theorizing a dual-path mechanism in which a contemporary arrangement introduces both a job resource (autonomy) and a career demand (plateau). Remote work research has emphasized average gains in satisfaction,[54] whereas the career literature has documented the harms of a plateau.[55] Our integrated model explains how both patterns can coexist within the same organization and even the same individual. Second, we formalize buffered plateauing: contextual resources embedded in flexible work (time sovereignty, boundary control) can attenuate plateau’s attitudinal penalties. This extends JD–R’s interaction logic by specifying a concrete contemporary condition under which a classic career constraint is less damaging.[56] Third, we clarify construct proximity in mediation. When autonomy—the most proximal job feature altered by remote work—is modeled, generalized trust no longer transmits the effect to satisfaction. Rather than treating trust as a default mediator, future theories should consider trust as an upstream enabler that shapes whether autonomy is granted and sustained.[57],[58] We also specify boundary conditions that qualify our claims: voluntariness of remote work (choice vs. mandate), career stage (early-career visibility needs vs. late-career discretion needs), task interdependence (collaborative vs. modular work), and managerial sponsorship intensity. 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Quarterly Journal of Economics, 130(1), pp. 165–218. <doi.org/10.1093/qje/qju032>. [2] Gajendran, R. S., Harrison, D. A. (2007). The Good, the Bad, and the Unknown About Telecommuting: Meta-Analysis of Psychological Mediators and Individual Consequences. Journal of Applied Psychology, 92(6), pp. 1524–1541. [3] Choudhury, P., Foroughi, C., Larson, B. (2021). Work-from-anywhere: The productivity effects of geographic flexibility. Strategic Management Journal, 42(4), pp. 655–683. <doi.org/10.1002/smj.3251>. [4] Bloom, N., Liang, J., Roberts, J., Ying, Z. J. (2015). Does working from home work? Evidence from a Chinese experiment. Quarterly Journal of Economics, 130(1), pp. 165–218. <doi.org/10.1093/qje/qju032>. [5] Eurofound. (2023). Living and working in Europe 2023. <doi.org/10.2806/500819>. [6] Hu, C., Zhang, S., Chen, Y. Y., Griggs, T. L. (2022). A meta-analytic study of subjective career plateaus. Journal of Vocational Behavior, 132. <doi.org/10.1016/j.jvb.2021.103649>. [7] Nachbagauer, A. G. M., Riedl, G. (2002). Effects of concepts of career plateaus on performance, work satisfaction and commitment. International Journal of Manpower, 23(8), pp. 716–733. <doi.org/10.1108/01437720210453920>. [8] Bareja-Wawryszuk, O., Togonidze, V., Aslantas, M. (2025). The impact of career plateaus on employee job satisfaction. The Moderating Role of Remote Work. Management and Administration Journal, 63(2). <doi.org/10.34739/maj.2024.02.11>. [9] Solomon, E. E. (1986). Private and Public Sector Managers: An Empirical Investigation of Job Characteristics and Organizational Climate. In Journal of Applied Psychology, Vol. 71, Issue 2. [10] Yang, W. N., Niven, K., Johnson, S. (2019). Career plateau: A review of 40 years of research. In Journal of Vocational Behavior, Vol. 110, pp. 286–302. Academic Press Inc. <doi.org/10.1016/j.jvb.2018.11.005>. [11] Gajendran, R. S., Harrison, D. A. (2007). The Good, the Bad, and the Unknown About Telecommuting: Meta-Analysis of Psychological Mediators and Individual Consequences. Journal of Applied Psychology, 92(6), pp. 1524–1541. <doi.org/10.1037/0021-9010.92.6.1524>. [12] Lachman, R. (1985). Public and Private Sector Differences: CEOs’ Perceptions of Their Role Environments. In Academy of Management Journal, Vol. 28, Issue 3. [13] Abidi, O., Zaim, H., Youssef, D., Baran, A. (2017). Diversity Management and Its Impact on HRM Practices: Evidence from Kuwaiti Companies. Eurasian Journal of Business and Economics, 10(20), pp. 71–88. <doi.org/10.17015/ejbe.2017.020.05>. [14] Zaim, H., Muhammed, S., Tarim, M. (2019). Relationship between knowledge management processes and performance: critical role of knowledge utilization in organizations. Knowledge Management Research and Practice, 17(1), pp. 24–38. <doi.org/10.1080/14778238.2018.1538669>. [15] Montgomery, D., Montgomery, D. (n.d.). Happily Ever After: Plateauing as a Means for Long-Term Career Satisfaction. <https://www.researchgate.net/publication/297899898>. [16] Yang, W. N., Niven, K., Johnson, S. (2019). Career plateau: A review of 40 years of research. In Journal of Vocational Behavior. Vol. 110, pp. 286-302. Academic Press Inc. <doi.org/10.1016/j.jvb.2018.11.005>. [17] Milliman, J. F. (1992). Causes, Consequences, and Moderating Factors of Career Plateauing. Dissertation, University of Southern California. [18] Supplemental Material for One Hundred Years of Work Design Research: Looking Back and Looking Forward. (2017a). Journal of Applied Psychology. [19] Bakker, A. B., Demerouti, E. (2007). The Job Demands-Resources model: State of the art. In Journal of Managerial Psychology, Vol. 22, Issue 3, pp. 309–328. <doi.org/10.1108/02683940710733115>. [20] Gajendran, R. S., Harrison, D. A. (2007). The Good, the Bad, and the Unknown About Telecommuting: Meta-Analysis of Psychological Mediators and Individual Consequences. Journal of Applied Psychology, 92(6). <doi.org/10.1037/0021-9010.92.6.1524>. [21] Gulati, R., Sytch, M. (2008). Does familiarity breed trust? Revisiting the antecedents of trust. Managerial and Decision Economics, 29(2-3), pp. 165-190. [22] Dumitru, C. (2021). Building virtual teams: Trust, culture, and remote working. In Building Virtual Teams: Trust, Culture, and Remote Working. Taylor and Francis. [23] Van Zoonen, W., Sivunen, A. E., Blomqvist, K. (2024). Out of sight – Out of trust? An analysis of the mediating role of communication frequency and quality in the relationship between workplace isolation and trust. European Management Journal. [24] Hao, Q., Zhang, B., Shi, Y., Yang, Q. (2022). How trust in coworkers fosters knowledge sharing in virtual teams? A multilevel moderated mediation model of psychological safety, team virtuality, and self-efficacy. Frontiers in Psychology. [25] Tomkins, C. (2001). Interdependencies, trust and information in relationships, alliances and networks. Journal of Accounting, Organizations and Society 26, pp. 161±191. <www.elsevier.com/locate/aos>. [26] Holmgreen, L., Tirone, V., Gerhart, J., Hobfoll, S. E. (2017). Conservation of Resources Theory. In The Handbook of Stress and Health, Wiley, pp. 443-457. <doi.org/10.1002/9781118993811.ch27>. [27] Lachman, R. (1985). Public and Private Sector Differences: CEOs’ Perceptions of Their Role Environments. In Academy of Management Journal, Vol. 28, Issue 3. [28] Wang, B., Liu, Y., Qian, J., Parker, S. K. (2021). Achieving Effective Remote Working During the COVID-19 Pandemic: A Work Design Perspective. Applied Psychology, 70(1), pp. 16-59. <doi.org/10.1111/apps.12290>. [29] Dingel, J. I., Neiman, B. (2020). How many jobs can be done at home? Journal of Public Economics, 189. <doi.org/10.1016/j.jpubeco.2020.104235>. [30] Gottlieb, C., Grobovšek, J., Poschke, M., Saltiel, F. (2021). Working from home in developing countries. European Economic Review. [31] Eurofound. (2023). Living and working in Europe 2023. <doi.org/10.2806/500819>. [32] Ibid. [33] Kossek, E. E., Lautsch, B. A. (2016). Work-Life Flexibility for Whom? Academy of Management Annals, ANNALS-2016-0059.R2. [34] Gottlieb, C., Grobovšek, J., Poschke, M., Saltiel, F. (2021). Working from home in developing countries. European Economic Review. [35] Hartner-Tiefenthaler, M., Goisauf, M., Gerdenitsch, C., Koeszegi, S. T. (2021). Remote Working in a Public Bureaucracy: Redeveloping Practices of Managerial Control When Out of Sight. Frontiers in Psychology, 12. [36] Bloom, N., Liang, J., Roberts, J., Ying, Z. J. (2015). Does working from home work? Evidence from a Chinese experiment. Quarterly Journal of Economics, 130(1), pp. 165-218. <doi.org/10.1093/qje/qju032>. [37] Khoshtaria, T., Matin, A., Mercan, M., Datuashvili, D. (2021). The impact of customers’ purchasing patterns on their showrooming and webrooming behaviour: An empirical evidence from the Georgian retail sector. International Journal of Electronic Marketing and Retailing, 12(4), p. 394. <doi.org/10.1504/IJEMR.2021.118305>. [38] Mercan, M., Khoshatria, T., Matin, A., Sayfullin, S. (2020). The Impact of e-services Quality on Consumer Satisfaction: Empirical Study of Georgian HEI. Journal of Business, 9(2), pp. 15-27. <doi.org/10.31578/.v9i2.175>. [39] Bareja-Wawryszuk, O., Togonidze, V., Aslantas, M. (2025). The Impact of Career Plateaus on Employee Job Satisfaction. The Moderating Role of Remote Work. Management and Administration Journal, 63(2). <doi.org/10.34739/maj.2024.02.11>. [40] Hu, C., Zhang, S., Chen, Y. Y., Griggs, T. L. (2022). A meta-analytic study of subjective career plateaus. Journal of Vocational Behavior, 132. <doi.org/10.1016/j.jvb.2021.103649>. [41] Saber, D. A. (2014). Frontline registered nurse job satisfaction and predictors over three decades: A meta-analysis from 1980 to 2009. Nursing Outlook, 62(6), pp. 402-414. <doi.org/10.1016/j.outlook.2014.05.004>. [42] Harrop, N., Jiang, L., Overall, N. (2025). A Meta-Analysis of Antecedents and Outcomes of Flexible Working Arrangements. In Journal of Organizational Behavior. John Wiley and Sons Ltd. <doi.org/10.1002/job.2896>. [43] Zychová, K., Fejfarová, M., Jindrová, A. (2024). Job Autonomy as a Driver of Job Satisfaction. Central European Business Review, 13(2), pp. 117-140. <doi.org/10.18267/j.cebr.347>. [44] Newell, S., David, G., Chand, D. (2007). An analysis of trust among globally distributed work teams in an organizational setting. Knowledge and Process Management, 14(3), pp. 158-168. <doi.org/10.1002/kpm.284>. [45] Brahm, T., Kunze, F. (2012). The role of trust climate in virtual teams. Journal of Managerial Psychology, 27(6), pp. 595-614. <doi.org/10.1108/02683941211252446>. [46] Bakker, A. B., Demerouti, E. (2007). The Job Demands-Resources model: State of the art. In Journal of Managerial Psychology, Vol. 22, Issue 3, pp. 309-328. <doi.org/10.1108/02683940710733115>. [47] Holmgreen, L., Tirone, V., Gerhart, J., Hobfoll, S. E. (2017). Conservation of Resources Theory. In The Handbook of Stress and Health, Wiley, pp. 443-457. <doi.org/10.1002/9781118993811.ch27>. [48] Allen, T. D., Golden, T. D., Shockley, K. M. (2015). How effective is telecommuting? Assessing the status of our scientific findings. Psychological Science in the Public Interest, 16(2), pp. 40-68. <doi.org/10.1177/1529100615593273>. [49] Chao, G. T. (1990). Exploration of the Conceptualization and Measurement of Career Plateau: A Comparative Analysis. Journal of Management. 16(1), pp. 69-80. <doi.org/10.1177/014920638801400107>. [50] Feldman, D. C., Weitz, B. A. (1988). Career Plateaus Reconsidered. Journal of Management, 14(1), p. 69-80. <doi.org/10.1177/014920638801400107>. [51] Milliman, J. F. (1992). Causes, Consequences, and Moderating Factors of Career Plateauing. Dissertation, University of Southern California. [52] Parker, S. Morgeson F. (2017). One Hundred Years of Work Design Research: Looking Back and Looking Forward. Journal of Applied Psychology, 2017, Vol. 102, No. 3, pp. 403-420. [53] Gajendran, R. S., Harrison, D. A. (2007). The Good, the Bad, and the Unknown About Telecommuting: Meta-Analysis of Psychological Mediators and Individual Consequences. Journal of Applied Psychology, 92(6), pp. 1524-1541. Journal of Applied Psychology, 92(6). <doi.org/10.1037/0021-9010.92.6.1524>. [54] Allen, T. D., Golden, T. D., Shockley, K. M. (2015). How effective is telecommuting? Assessing the status of our scientific findings. Psychological Science in the Public Interest, 16(2), pp. 40–68. <doi.org/10.1177/1529100615593273>. [55] Chao, G. T. (1990). Exploration of the Conceptualization and Measurement of Career Plateau: A Comparative Analysis. 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Credibility of USD Dominance in an Era of Uncertainty
The United States dollar (USD) has long served as the cornerstone of the global reserve currency system, maintaining its dominance for several decades. Nevertheless, this preeminence is increasingly challenged by a landscape characterized by geopolitical strife, shifts in economic power, and advancements in monetary technology. This paper investigates the validity of USD supremacy in light of China’s ascendance as a formidable economic force and the rising discussions surrounding a potential reversion to the gold standard. The analysis focuses on China’s expanding role through initiatives such as the internationalization of the renminbi (RMB), which aims to transform global trade and financial frameworks. Additionally, the paper considers both the historical and modern ramifications of a gold-backed monetary system, assessing its viability as a substitute for the current reliance on fiat currencies. Employing a multidisciplinary perspective, the study examines the interactions among these elements, offering insights into the durability of USD dominance and the potential for a multipolar currency landscape. Keywords: USD, renminbi, gold standard, currency weaponization, rise of China. Introduction The United States dollar (USD) has functioned as the bedrock of the international financial and economic system since the mid-20th century, acting as the principal reserve currency and enabling global trade and investment. This preeminence has been bolstered by the substantial size and stability of the U.S. economy, the robustness of its financial markets, and the political and military clout of the United States. Nevertheless, the present climate of uncertainty, characterized by evolving geopolitical alliances, economic upheavals, and rapid technological progress, poses considerable challenges to the ongoing dominance of the USD. A significant element contributing to this uncertainty is the emergence of China as a formidable global economic force. Through initiatives such as the Belt and Road Initiative (BRI) and the advocacy for the renminbi (RMB) in international commerce, China aims to contest the dollar’s pivotal role in global financial architecture. Concurrently, there has been a resurgence of interest in the possibility of reinstating a gold-backed monetary system, driven by apprehensions regarding inflation, soaring sovereign debt, and the perceived volatility of fiat currencies. These trends prompt critical inquiries into the reliability and prospects of USD supremacy in the shifting global context. This paper intends to investigate the fundamental components underpinning USD hegemony and assess the factors that jeopardize its sustained dominance. It will analyze the historical development of the dollar’s position, the tactics employed by emerging economic powers to curtail its influence, and the ramifications of alternative monetary systems, such as the gold standard. By integrating economic, political, and historical analyses, the research aims to offer a thorough understanding of the challenges facing USD credibility and the potential trajectories for the future of global currency relations. Risk and threats There are three primary reasons why the US dollar continues to be the reserve currency of choice globally. One is that the US is a traditionally strong sovereign nation, backed by robust, persistent economic growth. Another is the democratic nature of the US government and its institutions. The international community trusts in the stability of its overarching structures. Third is a degree of inertia—the difficulty in changing the structure of global finance revolving around the dollar and US capital markets. Competing nations can boast some of these facets, but the US maintains all three advantages.[1] Let’s take a look at all the above-given criteria and see how their conditions look right now. The examination of the sovereign debt situation reveals a complex historical trajectory. The U.S. sovereign debt crisis has developed over several centuries, influenced by a variety of historical events, economic fluctuations, and decisions regarding fiscal policy. Initially, in 1790, the nation faced a debt of $75 million, which grew substantially during periods of conflict, notably during the Civil War and World War II, when the debt exceeded 100% of GDP in 1945. The acceleration of debt in contemporary times began in the 1980s, driven by tax reductions, heightened military expenditures, and increasing entitlement commitments, resulting in a tripling of the debt to $2.6 trillion by 1988. The financial crisis of 2008 represented another pivotal moment, as emergency fiscal measures escalated the debt from $10 trillion in 2008 to $15 trillion by 2011. The situation worsened during the COVID-19 pandemic, with the debt soaring to $33 trillion by 2023, alongside a debt-to-GDP ratio of 123%. In 2023, interest payments alone reached $475 billion, with projections indicating they could exceed $1 trillion annually by 2033. The current fiscal path appears untenable, characterized by ongoing deficits, increasing interest expenses, and political stalemate regarding fiscal reforms, which pose considerable threats to economic stability and undermine global confidence in the creditworthiness of the United States. (See Fig.1). Political divisions regarding fiscal policy, coupled with ongoing impasses related to the debt ceiling, significantly heighten uncertainty and foster concerns about possible defaults or postponed payments. Such developments could result in downgrades of credit ratings, reminiscent of the 2011 incident when Standard & Poor’s first reduced the U.S. credit rating. Should investors start to doubt the United States’ capacity or willingness to effectively manage its debt, the demand for U.S. Treasury securities may diminish, leading to increased borrowing costs and jeopardizing the stability of global financial markets that depend on U.S. debt as a secure asset. This decline in confidence could initiate a cascading effect, threatening the U.S. dollar’s position as the preeminent global reserve currency. Make no mistake, if we continue on this path, investors will eventually lose confidence in our debt. The change could be gradual or sudden, but the consequences will be painful, no matter the pace. The federal government’s interest costs, already at $892 billion for 2024, will increase dramatically, as investors demand a higher risk premium. That will force painful tax hikes or spending cuts. Private sector borrowing costs tied to Treasury rates will also spike, damaging economic growth. Banks, managed funds, insurance companies, pensions, and other investors will be exposed to trillions of dollars in market losses as the Treasuries they hold lose value, precipitating widespread distress in our financial system.[3] The United States is confronted with significant challenges beyond its sovereign debt, particularly in light of China’s swift economic ascent over recent decades. Once perceived as a distant rival, China’s gross domestic product (GDP) has surged from under 5% of the global total in the 1990s to nearly 18% by 2023, positioning it as a formidable competitor to the United States, whose share has decreased from over 25% to around 22% during the same timeframe. When adjusted for purchasing power parity (PPP), China overtook the U.S. in GDP as early as 2014, indicating a significant reduction in the economic disparity between the two nations. This transformation is indicative of China’s consistent growth, propelled by industrial development, technological progress, and a robust export-oriented strategy, contrasting with the U.S.’s more sluggish growth, which has been hindered by recurrent economic downturns and escalating debt levels. Although the U.S. continues to excel in innovation and per capita GDP, China’s economic rise has altered the global power landscape, posing challenges to U.S. supremacy in trade, investment, and geopolitical influence. (See Fig.2). Since 1980, US GDP per capita growth has been far below its long-run average, and since 2007, it has been particularly weak. The rate at which the U.S. economy creates value on a per-person basis has ground to a near halt in recent years. From 1929 to 1979, real per capita GDP growth was 2.4% per year. Since then, it has been just 1.7% per year, and the most recent period has been particularly lackluster. From 2007 to 2015, real per capita GDP has been just 1% per year and a meager 1.4% since the nadir of the recession in 2009. To illustrate the problem from another angle, consider that from 1961 to 1981, real annualized growth in GDP per capita never fell below 1.5% over 10 years, and for 16 of the 21 years, 10-year per capita growth exceeded 2% on an annualized basis. Over the next 34 years until 2015, 10-year growth reached 2% only 13 times.[4] Confidence serves as a fundamental pillar for any global currency, and the supremacy of the U.S. dollar as the preeminent reserve currency is significantly anchored in its perceived stability, liquidity, and dependability. Nevertheless, the escalating use of the dollar as a tool in geopolitical confrontations poses a threat to this confidence and may hasten the pursuit of alternative currencies. The 2022 decision to freeze the reserves of Russia’s central bank in response to the Ukraine crisis raised alarms among other nations, particularly China, regarding the security of their dollar or euro-denominated reserves. Such measures heighten apprehensions that reserve assets could be wielded as instruments of political leverage, leading countries to seek diversification away from dollar assets to mitigate the risk of potential sanctions. This shift is illustrated by initiatives such as China’s advocacy for the yuan in global trade and the endeavors of countries like India, Brazil, and members of the BRICS coalition to investigate alternatives to the dollar. Although the dollar continues to hold a dominant position for the time being, an extended reliance on its weaponization could erode trust in its impartiality, gradually undermining its role as the world’s leading reserve currency and fragmenting the international monetary landscape. (See Fig.3). Confidence is an indispensable requirement for a currency, and beyond a certain point of weaponization, the US undermines international confidence in the dollar as the world currency and accelerates states’ search for alternatives. The more talk there is of appropriating Russia’s reserves, the more countries like China fear their reserves held in dollars or euros may no longer be safe.[6] Historically, the international dominance of the dollar, and to a lesser extent the euro, sterling, and yen, was supported by the fact that there existed well-organized markets between many local currencies and only these Big Four currencies. This required those seeking to trade other currency pairs to use the dollar or another member of the Big Four as a vehicle or intermediary currency, requiring the investor to pay an additional transaction cost in the form of a second bid-ask spread. Today, in contrast, there exist direct markets in a larger number of currency pairs in a larger number of financial centers. This is reflected in bid-ask spreads on foreign exchange transactions in nontraditional currencies that differ little from those on the majors. At the same time, central bank reserve managers have become more active in managing the investment tranche of their portfolios, whose magnitude has been growing, while many nontraditional currencies display attractive volatility-adjusted returns compared to their traditional competitors. Together, these factors have made for a shift out of the Big Four currencies (in practice mainly the dollar, which dominates the Big Four share).[8] Renminbi - opportunities and constraints In light of the aforementioned challenges facing the United States and the U.S. dollar, China has been proactively promoting the renminbi (RMB) for cross-border transactions as part of its overarching strategy to internationalize its currency and diminish dependence on the U.S. dollar in international trade. The introduction of the Cross-Border Interbank Payment System (CIPS) in 2015 has significantly improved the efficiency and security of RMB transactions, providing a viable alternative to the SWIFT network. Additionally, China has broadened its network of bilateral currency swap agreements with more than 40 countries, facilitating direct trade settlements in RMB and eliminating the necessity for dollar conversions. This strategy is particularly prominent within the framework of China’s Belt and Road Initiative (BRI), where there is a growing emphasis on RMB-denominated loans and payments. By 2023, the RMB had ascended to become the fifth most utilized currency in global payments, representing over 3% of total transactions, a notable increase from minimal levels a decade prior. China’s commitment to enhancing RMB usage in energy trade, particularly in oil and gas transactions with Russia and Gulf nations, further reinforces this initiative. These endeavors not only advance China’s geopolitical and economic objectives but also mirror a rising inclination among various countries to reduce their reliance on the dollar, particularly in light of increasing apprehensions regarding dollar weaponization and the stability of the global financial system. (See Fig. 5). In the last ten years, China has introduced strategic policies to establish its network of offshore RMB markets to advance its currency’s global status. These policies include a) the establishment of RMB clearing banks in offshore markets to facilitate settlements of RMB transactions overseas, b) the signing of bilateral RMB currency swap agreements to provide emergency RMB liquidity, and c) the provision of RMB qualified foreign institutional investor (RQFII) quotas that allow investing offshore RMB in China’s onshore bond and equity markets. These arrangements encourage the international use of the RMB and facilitate the development of offshore trading in regional, international, and global settings.[10] Today, it is beyond dispute that the RMB stands as the greatest potential rival to the U.S. dollar (USD). China’s economic size, prospects for future growth, integration into the global economy, and efforts to internationalize its currency point toward an expanded role for the RMB in international macroeconomics and trade. China’s successes in the realm of financial technology, the rapid adoption of mobile online transactions such as Alipay and WeChat Pay, and its digital currency pilot project are each bridging the gap between today’s USD dominance and a potential RMB-led future.[11] China’s deficiency in political and judicial transparency significantly hinders the renminbi (RMB) from emerging as the preeminent currency for cross-border payments. The integrity of the global financial system is fundamentally anchored in trust, adherence to the rule of law, and the presence of reliable institutions, all of which are essential for fostering confidence in a reserve currency. Conversely, China’s centralized political framework, coupled with its opaque decision-making and absence of an independent judiciary, discourages foreign investors and trading partners from fully adopting the RMB. The apprehensions surrounding unpredictable regulatory shifts, capital restrictions, and the likelihood of state interference in financial markets contribute to an environment of uncertainty for businesses and governments that hold RMB assets. Additionally, the limited safeguards for property rights and the inconsistent application of contractual obligations exacerbate risks for foreign entities, rendering the RMB a less appealing option as a stable and reliable currency for international trade and reserves. Unless China improves its transparency, fortifies the rule of law, and showcases a commitment to consistent and impartial governance, the RMB’s potential to eclipse the U.S. dollar or euro as the leading cross-border payment currency will remain limited. Notwithstanding, China is still very much in an intermediate solution to the trilemma. The capital account is still not fully open (strict limits on the flow of capital from China continue), and the authorities still maintain substantial ability to influence the evolution of the exchange rate. This implies that the authorities are trading off some loss of monetary policy autonomy in return for steps that contribute to the greater internationalisation of the RMB. Given the various economic issues facing China currently, this present policy choice of an intermediate policy regime is potentially more attractive than a corner solution of a fully flexible exchange rate and/or a fully open capital account. Moving to either a fully flexible exchange rate and/or a fully open capital account will require policy reforms in other areas, such as further strengthening the financial sector to be able to take on the volatility that inevitably accompanies such regimes.[12] The notion of establishing a competitive reserve currency system under the leadership of authoritarian regimes presents a philosophical contradiction to the tenets of a rule-based international order. A functional global monetary framework relies on the creation and enforcement of explicit, transparent regulations that oversee financial transactions, currency exchanges, and trade activities. These regulations are intended to foster a stable environment where businesses, governments, and individuals can operate with assurance.[13] The old-new gold standard In an era characterized by uncertainty, the likelihood of reinstating the gold standard amid the diminishing supremacy of the U.S. dollar (USD) in international transactions presents a multifaceted challenge shaped by various economic, geopolitical, and institutional dynamics. The USD is increasingly scrutinized due to ongoing inflationary pressures, escalating national debt, and a waning global confidence in its monetary governance. This situation has led to a heightened interest in alternatives such as the Chinese yuan (RMB). Nevertheless, the RMB’s capacity to replace the USD as the leading reserve currency is significantly hindered by China’s authoritarian regime and the perceived inadequacies of its legal and judicial frameworks. These elements pose considerable risks for global investors and erode confidence in the RMB as a reliable and transparent medium for cross-border exchanges. Consequently, the concept of the gold standard has resurfaced in theoretical debates as a potential neutral and apolitical foundation for global monetary systems. The absence of trust is a grave impediment to any monetary mechanism, whether backed by a rule-based gold standard or a discretionary-based dollar standard. The gold standard is bias-free, under which countries, even with the weakest credit, can achieve financial equality, plus those playing by the rules are rewarded for being trustworthy (and credible).[14] Central Banks’ Gold Purchases (Tons) Source: vaneck.com[15] The significance of a global payment unit, separate from any domestic currency, lies in its capacity to facilitate seamless and effective transactions within the worldwide economy. This particular currency acts as an impartial medium of exchange, unaffected by the economic policies or fluctuations of any individual nation. By providing a shared unit of measurement for international trade and finance, it diminishes transaction expenses, mitigates risks associated with exchange rates, and promotes enhanced transparency and trust in cross-border transactions.[16] The idea of reinstating the gold standard in light of the diminishing supremacy of the U.S. dollar (USD) is largely unfeasible, especially when considered within the context of the 1945 Bretton Woods agreement. This system was established on the tenets of global collaboration, aimed at ensuring stable exchange rates and enhancing international trade in the wake of World War II. Central to this framework was the establishment of a stable monetary environment where currencies were linked to the USD, which itself was redeemable in gold. This model proved effective as it resonated with the postwar commitment to multilateralism, with nations focusing on shared economic recovery and development rather than individualistic pursuits. In stark contrast, the contemporary global economic landscape is marked by fierce trade conflicts, geopolitical tensions, and a struggle for market supremacy and economic power. Such circumstances erode the essence of international cooperation that underpinned the gold-based monetary system of the mid-20th century. The increasing division among major economies, along with the intricacies of modern financial systems, further reduces the practicality of a gold standard as a basis for international trade. It remains one of the singular tragedies of modern world economic history that the Bretton Woods system did not come to its final logical maturity. What should have happened as Bretton Woods aged, and as postwar prosperity became an international fixture, is that each successful country should have consistently used a portion of its healthy savings built up during the prosperity to request allotments of gold from the United States, ultimately leave the system, and then establish its currency as directly fixed in gold. The system was primed to do this globally—to effect a return to the classical gold standard—yet this final result never came.[17] Conclusion The likelihood of reverting to the gold standard significantly decreases in the face of heightened political tensions and a trade conflict between Western nations and the Global South. The gold standard, along with the Bretton Woods system, relied on international collaboration, mutual trust, and economic agreement—elements that are fundamentally compromised by geopolitical strife and trade disagreements. Trade wars disrupt global trade balances, increase protectionist measures, and intensify distrust among countries, rendering the coordinated monetary policies necessary for a gold standard nearly unattainable. Additionally, the unequal distribution of gold reserves, with affluent Western countries possessing a disproportionate amount, would worsen economic disparities and exacerbate perceptions of financial imperialism, further alienating the Global South. The Bretton Woods Agreement, which linked currencies to the U.S. dollar and indirectly to gold, emerged from post-war unity and cooperative reconstruction efforts, rather than from discord and economic division. Political tensions and trade wars are in direct opposition to the principles of Bretton Woods, making the revival of a gold-backed monetary system not only impractical but also inconsistent with the realities of a divided global economy. China’s political framework poses a considerable obstacle to the Renminbi (RMB) achieving status as the dominant global reserve currency. Although the RMB has made significant strides towards internationalization, evidenced by initiatives such as the Belt and Road Initiative and its incorporation into the International Monetary Fund’s Special Drawing Rights (SDR) basket, the establishment of a reserve currency necessitates a robust level of transparency, adherence to the rule of law, and an autonomous monetary system. The centralized nature of China’s governance, coupled with the absence of comprehensive capital account liberalization and state oversight of financial markets, diminishes the currency’s attractiveness to international investors. Additionally, apprehensions regarding political influence over economic policies and the opaque decision-making processes of the Chinese Communist Party generate uncertainty among foreign stakeholders. Unless these fundamental challenges are resolved, the RMB’s capacity to supplant the U.S. dollar or the euro as the preeminent global reserve currency will remain limited. China’s judicial system poses a considerable obstacle to its aspirations of becoming a global financial center that can influence the international stock market similarly to the New York Stock Exchange (NYSE). A strong and unbiased legal framework is essential for fostering investor trust, safeguarding property rights, and effectively resolving disputes—fundamental components of any thriving financial center. Nevertheless, the Chinese judiciary is often viewed as lacking autonomy from political pressures, with courts tending to favor state or party interests over the fair application of the law. This situation generates uncertainty for both foreign and domestic investors, who may be reluctant to fully participate in China’s financial markets. Furthermore, the irregular enforcement of regulations, unclear legal processes, and inadequate protections for shareholder rights further weaken China’s position in establishing itself as a reliable global financial hub. Without significant reforms aimed at improving transparency, consistency, and impartiality within its justice system, China’s financial markets will likely find it challenging to attain the credibility necessary to compete with established global leaders such as the NYSE. The legal framework must fundamentally guarantee that the rights associated with contracts and property are articulated with clarity and predictability. In the event of a dispute, the parties involved in the contract should ideally refrain from pursuing legal action except as a final measure. Additionally, in cases of litigation, it is essential that the judiciary operates independently, capable of adjudicating claims efficiently and within a reasonable timeframe. Furthermore, once a judgment is rendered, it should be enforced promptly. The Renminbi (RMB) faces challenges in becoming a leading international reserve currency; however, China’s robust economic performance and its status as a major exporter provide a favorable context for the RMB to emerge as the primary reserve currency within the BRICS coalition. China’s significant role as the principal trading partner for numerous BRICS nations, along with its efforts to diminish dependence on the U.S. dollar through various bilateral trade agreements and the implementation of RMB settlement frameworks, is enhancing the currency’s prominence within this group. Additionally, the shared objective among BRICS nations to lessen their reliance on Western-centric financial systems presents a viable opportunity for the RMB to function as a regional reserve currency, similar to the euro’s role in the European Union. By capitalizing on its economic strength, fostering deeper financial connections within BRICS, and advocating for RMB-centered trade and investment initiatives, China could effectively establish the RMB as a central element of financial interactions among BRICS countries, even if it continues to play a secondary role in the global financial landscape. Considering the aforementioned factors, it is anticipated that BRICS, akin to Europe, will establish its own de facto intra-bloc reserve currency, with the Renminbi (RMB) assuming a pivotal position in financial transactions among BRICS nations. Nevertheless, on a global scale, the U.S. dollar is projected to maintain its status as the predominant reserve currency, owing to its established advantages, unmatched liquidity, and the robustness of its international financial infrastructure. The dollar’s profound integration into global trade, investment, and payment mechanisms guarantees its sustained importance in cross-border exchanges. Although the ascendance of the RMB within BRICS may pose a regional challenge to the dollar, its overall influence on the USD is expected to be limited, akin to the euro’s impact. Just as the euro emerged as a notable but regionally confined reserve currency without displacing the dollar on a global scale, the RMB is likely to enhance its presence within BRICS while not fundamentally jeopardizing the dollar’s position as the leading global reserve currency. References: Aliaga-Díaz, R. (2024). Why the US dollar remains a reserve currency. Vanguard insights, macro-economics. Available at: <https://www.nl.vanguard/professional/insights/macro-economics/why-the-us-dollar-remains-a-reserve-currency-leader> (Last access: 12.07.2024); Arslanalp, S., Eichengreen, B., Simpson-Bell, C. (2022). The Stealth Erosion of Dollar Dominance: Active Diversifiers and the Rise of Nontraditional Reserve Currencies. International Monetary Fund. Available at: <https://www.imf.org/en/Publications/WP/Issues/2022/03/24/The-Stealth-Erosion-of-Dollar-Dominance-Active-Diversifiers-and-the-Rise-of-Nontraditional-515150> (Last access: 12.14.2024); Bair, Sh. (2024). U.S. Debt Could Drive the Next Financial Crisis. Barron’s Commentary. Available at: <https://www.barrons.com/articles/national-debt-financial-crisis-harris-trump-investors-8608ce19> (Last access: 12.07.2024); Bloomberg. Youan Overtakes Dollar as China’s Most-used Cross Border Currency. Available at: <https://www.bloomberg.com/news/articles/2023-04-26/yuan-overtakes-dollar-as-china-s-most-used-cross-border-currency> (Last access: 12.14.2024); Chang, J. (2024). De-dollarization: Is the US dollar losing its dominance? JPMorgan insights. Available at: <https://www.jpmorgan.com/insights/global-research/currencies/de-dollarization> (Last access: 04.01.2025); Cheung, Y. (2021). The evolution of offshore renminbi trading: 2016 to 2019. Journal of International Money and Finance. Available at: <https://www.sciencedirect.com/science/article/abs/pii/S0261560621000188> (Last access 12.14.2024); Dimitrovic, B. (2012). The Argument for Returning to the Gold Standard: The Lessons of Contemporary History. Free Market Forum. Sam Houston State University. Available at: <https://www.hillsdale.edu/educational-outreach/free-market-forum/2012-archive/the-argument-for-returning-to-the-gold-standard-the-lessons-of-contemporary-history> (Last Access 12.29.2024); Fiscal Data. Historical Debt Outstanding. Available at: <https://fiscaldata.treasury.gov/datasets/historical-debt-outstanding/historical-debt-outstanding> (Last Access 04.01.2025); Khidasheli, M. (2024). Triffin Paradox in 21st Century. Economic Profile, Vol. 19, 1(27); Khidasheli, M. (2024). Monetary Hypocrisy – Case Against the USD Hegemony. Multidisciplinary International Scientific Conference: “Sustainable Development: Modern Trends and Challenges”. Available at: <https://unik.edu.ge/Articles_pdf/78772368a98f32df713e04896c5f478b.pdf#page=9.55> (Last Access 12.29.2024); Kurien, J. (2020). The Political Economy of International Finance: A Revised Roadmap for Renminbi Internationalization. Yale Journal of International Affairs. Available at: <https://www.yalejournal.org/publications/the-political-economy-of-international-finance-a-revised-roadmap-for-renminbi-internationalization> (Last access: 12.14.2024); O’Neill, A. (2024). Gross domestic product (GDP) at current prices in China and the United States from 2005 to 2020 with forecasts until 2035. Available at: <https://www.statista.com/statistics/1070632/gross-domestic-product-gdp-china-us/> (Last access: 04.01.2025); Rothwell, J. (2016). No Recovery: An Analysis of Long-Term U.S. Productivity Decline. Gallup, Inc. Available at: <https://news.gallup.com/reports/198776/no-recovery-analysis-long-term-productivity-decline.aspx> (Last access: 12.07.2024); Ruijie, Ch. (2022). Renminbi internationalization and trilemma constraints. EAI Working Paper No. 169. Available at: <https://research.nus.edu.sg/eai/wp-content/uploads/sites/2/2022/12/EAIWP-No.-169-RMB-Internationalization_Trilemma-Constraints-2.pdf> (Last access: 12.14.2024). Taskinsoy, J. (2023). Reviving the Gold Standard. University Malaysia Sarawak (UNIMAS). Available at: <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4489492> [Last access: 12.29.2024). VanEck. (2023). Will Investors Follow Central Banks into Gold? Available at: <https://www.vaneck.com/nl/en/blog/gold-investing/joe-foster-will-investors-follow-central-banks-into-gold> (Last Access 04.01.2025); Wade, H.R. (2024). The beginning of the end for the US dollar’s global dominance. The London School of Economics and Political Science. Available at: <https://blogs.lse.ac.uk/internationaldevelopment/2024/02/29/long-read-the-beginning-of-the-end-for-the-us-dollars-global-dominance/> (Last access: 12.07.2024). Footnotes [1] Aliaga-Díaz, R. (2024). Why the US dollar remains a reserve currency. Vanguard insights, macro-economics. Available at: <https://www.nl.vanguard/professional/insights/macro-economics/why-the-us-dollar-remains-a-reserve-currency-leader> (Last access: 12.07.2024). [2] Fiscal Data. Historical Debt Outstanding. Available at: <https://fiscaldata.treasury.gov/datasets/historical-debt-outstanding/historical-debt-outstanding> (Last Access 04.01.2025). [3] Bair, Sh. (2024). U.S. Debt Could Drive the Next Financial Crisis. Barron’s Commentary. Available at: <https://www.barrons.com/articles/national-debt-financial-crisis-harris-trump-investors-8608ce19> (Last access: 12.07.2024). [4] Rothwell, J. (2016). No Recovery: An Analysis of Long-Term U.S. Productivity Decline. Gallup, Inc. Available at: <https://news.gallup.com/reports/198776/no-recovery-analysis-long-term-productivity-decline.aspx> (Last access: 12.07.2024). [5] O’Neill, A. (2024). Gross domestic product (GDP) at current prices in China and the United States from 2005 to 2020 with forecasts until 2035. Available at: <https://www.statista.com/statistics/1070632/gross-domestic-product-gdp-china-us/> (Last access: 04.01.2025). [6] Wade, H.R. (2024). The beginning of the end for the US dollar’s global dominance. The London School of Economics and Political Science. Available at: <https://blogs.lse.ac.uk/internationaldevelopment/2024/02/29/long-read-the-beginning-of-the-end-for-the-us-dollars-global-dominance/> (Last access: 12.07.2024). [7] Chang, J. (2024). De-dollarization: Is the US dollar losing its dominance? JPMorgan insights. Available at: <https://www.jpmorgan.com/insights/global-research/currencies/de-dollarization> (Last access: 04.01.2025). [8] Arslanalp, S., Eichengreen, B., Simpson-Bell, C. (2022). The Stealth Erosion of Dollar Dominance: Active Diversifiers and the Rise of Nontraditional Reserve Currencies. International Monetary Fund. Available at: <https://www.imf.org/en/Publications/WP/Issues/2022/03/24/The-Stealth-Erosion-of-Dollar-Dominance-Active-Diversifiers-and-the-Rise-of-Nontraditional-515150> (Last access: 12.14.2024). [9] Bloomberg. Youan Overtakes Dollar as China’s Most-used Cross Border Currency. Available at: <https://www.bloomberg.com/news/articles/2023-04-26/yuan-overtakes-dollar-as-china-s-most-used-cross-border-currency> (Last access: 12.14.2024). [10] Cheung, Y. (2021). The evolution of offshore renminbi trading: 2016 to 2019. Journal of International Money and Finance. Available at: <https://www.sciencedirect.com/science/article/abs/pii/S0261560621000188> (Last access 12.14.2024). [11] Kurien, J. (2020). The Political Economy of International Finance: A Revised Roadmap for Renminbi Internationalization. Yale Journal of International Affairs. Available at: <https://www.yalejournal.org/publications/the-political-economy-of-international-finance-a-revised-roadmap-for-renminbi-internationalization> (Last access: 12.14.2024). [12] Ruijie, Ch. (2022). Renminbi internationalization and trilemma constraints. EAI Working Paper No. 169. Available at: <https://research.nus.edu.sg/eai/wp-content/uploads/sites/2/2022/12/EAIWP-No.-169-RMB-Internationalization_Trilemma-Constraints-2.pdf> (Last access: 12.14.2024). [13] Khidasheli, M. (2024). Triffin Paradox in 21st Century. Economic Profile, Vol. 19, 1(27). [14] Taskinsoy, J. (2023). Reviving the Gold Standard. University Malaysia Sarawak (UNIMAS). Available at: <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4489492> [Last access: 12.29.2024). [15] VanEck. (2023). Will Investors Follow Central Banks into Gold? Available at: <https://www.vaneck.com/nl/en/blog/gold-investing/joe-foster-will-investors-follow-central-banks-into-gold> (Last Access 04.01.2025). [16] Khidasheli, M. (2024). Monetary Hypocrisy – Case Against the USD Hegemony. Multidisciplinary International Scientific Conference: “Sustainable Development: Modern Trends and Challenges”. Available at: <https://unik.edu.ge/Articles_pdf/78772368a98f32df713e04896c5f478b.pdf#page=9.55> (Last Access 12.29.2024). [17] Dimitrovic, B. (2012). The Argument for Returning to the Gold Standard: The Lessons of Contemporary History. Free Market Forum. Sam Houston State University. Available at: <https://www.hillsdale.edu/educational-outreach/free-market-forum/2012-archive/the-argument-for-returning-to-the-gold-standard-the-lessons-of-contemporary-history> (Last Access 12.29.2024).
Studying the relationship between some macroeconomic variables and economic growth in Algeria using the ARDL model
This study investigates the impact of exchange rate fluctuations, inflation, and oil prices on Algeria's economic growth from 1990 to 2022. Employing the Autoregressive Distributed Lag (ARDL) model and analyzed using EViews 12, the research evaluates both short- and long-term dynamics among these variables. The findings reveal a significant inverse relationship between exchange rate depreciation and economic growth, suggesting that currency instability adversely affects Algeria’s economic performance. Similarly, inflation exhibits a negative long-term association with growth, highlighting the detrimental effects of rising price levels on the economy. Conversely, oil prices demonstrate a positive long-term relationship with growth, underscoring Algeria’s reliance on hydrocarbon revenues as a key driver of economic expansion. The model’s estimation results indicate that these independent variables collectively explain 91% of the variations in economic growth, confirming their substantial influence. These insights underscore the need for policymakers to stabilize exchange rates, control inflation, and diversify the economy to mitigate overdependence on oil. The study contributes to the empirical literature on macroeconomic determinants of growth in resource-dependent economies. Keywords: Exchange rate, inflation rate, oil price, ARDL model, economic growth. Introduction Economic growth is a key objective for all countries, whether developed or developing, due to its critical role in measuring development and societal progress. It reflects the total output of goods and services within an economy and is widely regarded as a fundamental indicator of economic performance. From a theoretical standpoint, economic growth remains one of the most significant topics in economic development, attracting the attention of prominent economists such as Adam Smith, David Ricardo, and Schumpeter, who sought to identify its key determinants. Over time, economic realities have evolved, leading to shifts in the frameworks and theories used to explain growth. Today, economic growth is understood as the result of multiple and diverse factors, necessitating a thorough examination of all influencing variables—particularly economic ones. Among the most important macroeconomic variables affecting growth are the exchange rate, inflation, and oil prices. Against this backdrop, the study addresses the following research question: How do the exchange rate, inflation rate, and oil price influence economic growth in Algeria from 1990 to 2022? This study aims to analyze the relationship between these macroeconomic variables and economic growth in Algeria, specifically assessing the impact of exchange rates, inflation, and oil prices. To address the research question and achieve the study’s objectives, a mixed-method approach is employed. The first part adopts a descriptive approach, reviewing prior studies and theoretical frameworks related to the variables under examination. The second part utilizes a quantitative analytical approach, applying the ARDL model to empirically assess the impact of selected macroeconomic variables on Algeria’s economic growth from 1990 to 2022. The analysis is conducted using the EViews 12 software. 1. Literature review Chowdhury (2019) investigated the impact of macroeconomic variables—inflation (INF), real interest rate (INT), exchange rate (EXR), and household consumption expenditure growth (HCE)—on GDP growth in Bangladesh (1987–2015). Using correlation and multiple regression analysis, the study found a positive relationship between GDP and all variables except inflation.[1] The independent variables explained 75.60% of GDP variance, confirming their significant influence on economic growth. Alam et al. (2022) examined the long-term relationship between investment, exports, imports, and government spending components (health, education, and other expenditures) on Saudi Arabia’s GDP (1985–2018). Applying the ARDL cointegration and error correction model,[2] the study revealed a positive long-run relationship between GDP, investment, exports, and government education spending, while imports, health expenditures, and other government spending had a negative impact. Akhtar and Nisa (2023) explored the combined effect of macroeconomic variables on Pakistan’s economic growth (1970–2022) within the environmental Kuznets curve framework. The results indicated that energy use significantly increases carbon emissions, whereas manufacturing, exports, and financial development reduce them. Financial development, energy consumption, carbon emissions, and manufacturing positively influenced growth, while exports had a negative effect.[3] Sulaiman (2023) employed the ARDL model to analyze the relationship between GDP growth and key variables (inflation, government spending, oil prices, and population growth) in Iraq (2003–2019). The findings confirmed a long-term equilibrium relationship, with oil prices being the most influential factor—consistent with Iraq’s status as an oil-dependent economy.[4] 2. Theoretical framework for study variables 2.1 Economic growth Achieving positive economic growth rates is a key priority for governments, particularly in developing and underdeveloped countries striving for economic development, poverty reduction, and overcoming socioeconomic challenges. Economic growth is a quantitative concept representing the annual increase in an economy’s gross domestic product (GDP) (Fraj Muhammad Al-Qahtani& Khaled Zaki Al-Deeb, 2022). It refers to the rise in real net output over a specific period, typically a year or successive intervals. Additionally, economic growth entails an increase in real per capita income that outpaces population growth.[5] According to Titoush Suhaila (2018), economic growth implies: An increase in real per capita income, not just GDP;[6] A real (not monetary) rise in national income, where per capita income growth exceeds inflation; A sustained, long-term increase rather than a temporary one. Modern economic development is influenced by several key factors: Capital Accumulation: Capital accumulation is a fundamental driver of economic growth, enhancing a nation’s productive capacity.[7] Its rate depends on three factors:[8] The level of real savings, determined by the willingness and ability to save; The presence of financial institutions that mobilize savings for investment; The allocation of savings toward capital goods. Human Capital: Investment in human capital expands individual capabilities, improves education and skills, and fosters innovation.[9] Trade Openness: A more open economy, characterized by greater trade volumes, correlates with higher growth rates.[10] Rate of Technical Progress: Technological advancement enhances both physical and human capital, boosting production and living standards. Its impact spans education, management, marketing, and production.[11] 2.2 Exchange rate The exchange rate connects domestic and global economies, influencing resource allocation, export competitiveness, and import costs. It ties local prices to global market prices[12] and reflects the units of foreign goods needed to purchase one unit of domestic goods.[13] 2.3 Oil price Oil pricing has evolved from well-based and port-based systems to monopolistic and later competitive pricing shaped by supply and demand.[14] It represents the monetary value of a petroleum commodity, denominated in USD and subject to market fluctuations.[15] The volatile nature of the oil market leads to constant price changes.[16] Crude oil prices reflect the USD value per barrel over the industry’s development.[17] 2.4 Inflation Inflation is a complex phenomenon with varying definitions. It denotes an abnormal price surge, described by Enelegame as a self-reinforcing price increase due to excess demand.[18] Friedman attributes it to excessive money supply growth.[19] Inflation measures the rate of price increases, either broadly (e.g., overall price levels or cost of living) or for specific goods/services.[20] 3. An econometric study of the impact of the exchange rate, oil price, and inflation on economic growth in Algeria To analyze the impact of key macroeconomic variables on Algeria’s economic growth from 1990 to 2022, this study employs annual data sourced from the World Bank. The autoregressive distributed lag (ARDL) model, developed by Pesaran and Shin (2001),[21] is used due to its flexibility in handling variables with different integration orders—whether stationary at level (I(0)), first difference (I(1)), or a mix of both. The study variables are defined as follows: Dependent variable: Economic growth (GDP). Independent variables: Real exchange rate (EX), inflation rate (INF), and oil price. 3.1 Description of the study variables 3.2 Testing time series stationarity Economic literature mandates testing time series stationarity before estimating relationships. Many economic series exhibit non-stationarity due to a unit root, where the mean, variance, and covariance become time dependent. To address this issue, we employ the Augmented Dickey-Fuller (ADF) unit root test. The subsequent table presents our test results. Table 2 reveals that the economic growth, inflation rate, and oil price series achieve stationarity at first difference, as confirmed by their 5% significance levels. The exchange rate series demonstrates stationarity at both the level and first difference. 3.3 ARDL model estimation results The ARDL model estimation results presented in Table 3 indicate statistical validity, supported by the significant Fisher statistic. Optimal lag lengths were determined as follows: 4 lags for economic growth, 4 for the exchange rate, 2 for the inflation rate, and 4 for the oil price. Consequently, the ARDL (4,4,2,4) specification emerges as the optimal model based on the Akaike Information Criterion (AIC). 3.4 Cointegration test This test relies on the possibility of a long-term equilibrium relationship between the study variables by using the bounds test, as shown in the following table: The boundary test results (F-statistic = 4.89) exceed the upper critical values at all significance levels, as shown in Table 4. This leads us to reject the null hypothesis in favor of the alternative hypothesis, confirming a long-term cointegrating relationship among the study variables. 3.5 Diagnostic testing procedures 3.5.1 Heteroskedasticity testing The Fisher probability statistics presented in Table 5 demonstrate statistical insignificance (p > 0.05) across all three test specifications, confirming the presence of homoskedasticity in the model residuals. 3.5.2 Serial correlation testing via the lagrange multiplier We employ the Breusch-Godfrey test to examine residual autocorrelation, with the null hypothesis positing no serial correlation. The test utilizes Fisher’s statistic to evaluate this hypothesis. The Fisher probability statistic (0.1024) exceeds the 5% significance threshold, leading us to accept the null hypothesis of no autocorrelation in the model residuals. 3.5.3 Test for normal distribution of residuals The Jarque-Bera test statistic (0.799) exceeds the 5% significance level, leading to an acceptance of the null hypothesis and rejection of the alternative hypothesis regarding the non-normal distribution of model residuals. This indicates the residuals follow a normal distribution. 3.6 Structural stability test of parameters The figure demonstrates that the model’s estimated coefficients maintain structural stability throughout the study period. This conclusion is supported by the test statistics remaining within the 5% significance critical bounds across all observations. 3.7 Estimation of long-term parameters The results presented in Table 7 demonstrate significant long-run relationships between macroeconomic variables and economic growth in Algeria. Specifically, a 1% depreciation of the exchange rate leads to a 1.76% increase in economic growth, indicating an inverse relationship. Conversely, a 1% rise in oil prices corresponds with a 3.01% expansion of economic growth, showing a direct positive effect. The analysis also reveals that a 1% increase in the inflation rate results in a 1.84% contraction of economic growth, confirming an inverse relationship. These empirical findings are consistent with established economic theory and are supported by most econometric studies in this field. 3.8 Estimating the Short-term Relationship within the Error Correction Model The estimation results of the error correction model demonstrate a statistically significant (p-value = 0.0003) negative coefficient (-1.373848) for the error correction term (cointEq-1), indicating a robust short-run adjustment mechanism toward long-run equilibrium. The magnitude of the coefficient suggests that approximately 137% of short-run disequilibrium is corrected annually, implying an overshooting adjustment process. This finding confirms both the existence of a stable long-run relationship among the variables and a strong short-run dynamic interaction, as evidenced by the rapid and complete correction of deviations from equilibrium within a single period. The results are consistent with theoretical expectations regarding error correction mechanisms in cointegrated systems. Conclusion This study investigated the impact of exchange rates, inflation, and oil prices on Algeria's economic growth from 1990 to 2022 using the Autoregressive Distributed Lag (ARDL) model and EViews 12 software. The empirical findings reveal several key relationships: First, the results confirm an inverse relationship between the exchange rate and economic growth. A depreciation of the Algerian dinar enhances export competitiveness and stimulates domestic production, thereby supporting economic expansion. Second, inflation exhibits a negative long-run impact on growth, as rising prices erode consumer purchasing power, suppress demand, and discourage investment. Conversely, oil prices demonstrate a positive relationship with economic growth, reflecting Algeria’s heavy dependence on hydrocarbon exports. Higher oil revenues enable increased government spending on development projects, fostering economic activity. The econometric analysis yields the following specific findings: The bounds test confirms cointegration among the variables, indicating a stable long-run relationship; Inflation and exchange rates negatively affect economic growth in the long run; Oil prices positively influence economic growth in the long run; The model explains 91% of the variation in economic growth (R² = 0.91); The error correction term (-1.37) indicates rapid adjustment, with 137% of short-run disequilibria corrected annually; To promote sustainable growth, policymakers should consider; Implementing a flexible exchange rate regime to mitigate oil price volatility; Pursuing price-stability-oriented monetary policy; Accelerating economic diversification efforts; Improving the investment climate through governance reforms; Enhancing human capital through education and vocational training; These measures could help reduce Algeria’s vulnerability to external shocks while fostering more balanced and resilient economic development. References: Akhtar, H., Nisa, T. U. (2023). Impact of macroeconomic variables on economic growth: A mediation-moderation model evidence from Pakistan. Energy Research Letters, 4(1). Available at: <https://doi.org/10.46557/001c.67890>; Al-Assar, R., Al-Sharif, A. (2000). Foreign trade. Dar Al-Masirah for Publishing and Distribution; Al-Sharfat, A. J. (2010). Economic development in the Arab world (Reality, obstacles, and ways to advance). Dar Jaleelizzaman; Alam, F. et al. (2022). Economic growth in Saudi Arabia through sectoral reallocation of government expenditures. SAGE Open, 12(4). Available at: <https://doi.org/10.1177/21582440221132129>; Baba, Q. M. M. S. (2021). The Relationship Between the Inflation Rate, Exchange Rate Changes, and the Trade Balance in Sudan for the Period 1999–2017. Journal of Quantitative and Qualitative Research in Economic and Administrative Sciences, 03(02); Bouzaher, S. (2018). The impact of hydrocarbon revenues on economic growth and governance [PhD thesis, University of Tlemcen]; Chowdhury, A. H. M. Y. (2019). Impact of macroeconomic variables on economic growth: Bangladesh perspective. Journal of Business and Economics, 2(2); Dardouri, R., Sararma, A. W. (2021). The impact of oil prices on economic growth in Algeria for the period (1970-2020): An econometric study using the autoregressive distributed lag (ARDL) model. Journal of Economic and Financial Studies, 14(1); Ghazzazi, I. (2020). Modeling Brent oil price volatility using autoregressive models conditioned on non-variance consistency for the period (January 1990-July 2019). Journal of Strategy and Development, 10(1); Hawas, A. (2016). Economic openness to international trade and its impact on economic growth: The case of China [Ph.D. thesis, University of Tlemcen]; Kardosi, N. A. (2022). 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The impact of oil price volatility on long-term economic growth in Algeria (1990-2020): An econometric study using the autoregressive distributed lag (ARDL) model. Journal of Economic Development, 7(1); Nawali, S. (2018). The effects of dollar and euro fluctuations on foreign trade in Algeria, Morocco, and Tunisia [PhD thesis, University of Tlemcen]; Pesaran, M. H., Shin, Y. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3). Available at: <https://doi.org/10.1002/jae.616>; Sulaiman, W. S. (2023). The impact of some macroeconomic variables on economic growth in Iraq for the period 2003-2019. AL-Anbar University Journal of Economic and Administrative Sciences, 15(1); Tlemsani, H. (2018). The impact of the real exchange rate on economic growth in Algeria [Ph.D. thesis, University of Tlemcen]; Younes, T. B., Ahmed, S. (2021). The impact of monetary and fiscal policies on inflation rates amid oil price volatility: A case study of Algeria for the period 1990–2016. Journal of Strategy and Development, 11(01). Footnotes [1] Chowdhury, A. H. M. Y. (2019). Impact of macroeconomic variables on economic growth: Bangladesh perspective. Journal of Business and Economics, 2(2), pp. 19-22. [2] Alam, F. et al. (2022). Economic growth in Saudi Arabia through sectoral reallocation of government expenditures. SAGE Open, 12(4), pp. 1-13. Available at: <https://doi.org/10.1177/21582440221132129>. [3] Akhtar, H., Nisa, T. U. (2023). Impact of macroeconomic variables on economic growth: Mediation-moderation model evidence from Pakistan. Energy Research Letters, 4(1). Available at: <https://doi.org/10.46557/001c.67890>. [4] Sulaiman, W. S. (2023). The impact of some macroeconomic variables on economic growth in Iraq for the period 2003-2019. AL-Anbar University Journal of Economic and Administrative Sciences, 15(1), pp. 32-44. [5] Mustafa, G., El-Nasser, H. M. (2019). The impact of monetary policy on economic growth in Algeria (An econometric study for the period 1990-2017). Journal of Finance and Markets, 5(10), pp. 435-457. [6] Kryeziu, A. (2016). The impact of macroeconomic factors on economic growth. European Scientific Journal, 12(7), pp. 331-345. [7] Kardosi, N. A. (2022). The effects of fiscal policy on economic growth in Algeria [Unpublished Ph.D. thesis, University of Maghnia-Tlemcen]. [8] Tlemsani, H. (2018). The impact of the real exchange rate on economic growth in Algeria [Ph.D. thesis, University of Tlemcen]. [9] Hawas, A. (2016). Economic openness to international trade and its impact on economic growth: The case of China [Ph.D. thesis, University of Tlemcen]. [10] Al-Assar, R., Al-Sharif, A. (2000). Foreign trade. Dar Al-Masirah for Publishing and Distribution. [11] Al-Sharfat, A. J. (2010). Economic development in the Arab world (Reality, obstacles, and ways to advance). Dar Jaleelizzaman. [12] Nawali, S. (2018). The effects of dollar and euro fluctuations on foreign trade in Algeria, Morocco, and Tunisia [PhD thesis, University of Tlemcen]. [13] Bouzaher, S. (2018). The impact of hydrocarbon revenues on economic growth and governance [PhD thesis, University of Tlemcen]. [14] Naimi, A., Sheikhawi, A. A. (2022). The impact of oil price volatility on long-term economic growth in Algeria (1990-2020): An econometric study using the autoregressive distributed lag (ARDL) model. Journal of Economic Development, 7(1), p. 38. [15] Dardouri, R., Sararma, A. W. (2021). The impact of oil prices on economic growth in Algeria for the period (1970-2020): An econometric study using the autoregressive distributed lag (ARDL) model. Journal of Economic and Financial Studies, 14(1), p. 413. [16] Lakhdari, I., Ghazazi, I. (2022). Econometric modeling of the impact of global oil price fluctuations on foreign exchange reserves in Algeria during the period (1990-2019). Journal of Contemporary Economic Research, 5(1), p. 468. [17] Ghazzazi, I. (2020). Modeling Brent oil price volatility using autoregressive models conditioned on non-variance consistency for the period (January 1990-July 2019). Journal of Strategy and Development, 10(1), pp. 91-111. [18] Mjahdi, K., Elzaar, H. B. (2023). Measuring the Impact of Inflation on Economic Growth During the Period (1980–2020). Al-Academia Journal of Social and Human Studies, 15, 720–727. [19] Baba, Q. M. M. S. (2021). The Relationship Between the Inflation Rate, Exchange Rate Changes, and the Trade Balance in Sudan for the Period 1999–2017. Journal of Quantitative and Qualitative Research in Economic and Administrative Sciences, 03(02), 93-120. [20] Younes, T. B., Ahmed, S. (2021). The impact of monetary and fiscal policies on inflation rates amid oil price volatility: A case study of Algeria for the period 1990–2016. Journal of Strategy and Development, 11(01), 426–446. [21] Pesaran, M. H., Shin, Y. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), pp. 289-326. Available at: <https://doi.org/10.1002/jae.616>.
Gendered Roles and Family Well-Being in Georgia: A Culturally Embedded Analysis for Intercultural Family Research
This study explores the interplay between empathy, cooperative conflict resolution, and marital satisfaction within the framework of culturally embedded gender roles in Georgian families. Situated in the context of Georgia’s post-Soviet transformation, the research examines how traditional responsibilities assigned to mothers and fathers influence emotional dynamics and family well-being. Drawing from intercultural psychology, the study considers how cultural scripts, interdependence-oriented norms, and shifting gender expectations affect marital functioning across two life stages. Quantitative analysis reveals that women report higher empathy and collaborative conflict strategies, which correlate positively with marital satisfaction. Additionally, maternal perceptions of support significantly influence children’s well-being and fathers’ emotional engagement. These findings contribute to cross-cultural psychology by highlighting how family dynamics are shaped by cultural continuity and value shifts in transitional societies. Keywords: Intercultural family dynamics, gender and culture, cross-cultural psychology, post-Soviet cultural transformation, cultural values and parenting. Introduction The well-being of a family is shaped not only by individual and interpersonal dynamics but also by the ontological structures that define gender roles within a given society. Traditional family structures, particularly in Georgia, have long assigned distinct responsibilities to husbands and wives, influencing marital satisfaction, conflict resolution, and parental engagement. However, these roles are not merely socially prescribed behaviors but also ontologically significant categories that shape individual identity and family dynamics. Many factors influence family well-being, and their impact varies. For instance, parental conflict is crucial to understanding family dynamics, as it affects children’s development and family health.[1] Cummings, Taylor, and Merrilees (2020)[2] emphasize the importance of reducing interparental conflict to foster positive family dynamics. Effective communication, trust, and mutual support are essential for emotional stability.[3] Economic security also plays a role in family well-being by reducing stress and uncertainty,[4] with positive perceptions of financial stability improving family dynamics.[5] The association between family functioning and children’s emotional outcomes highlights the moderating role of parental mental health.[6] Child well-being often reflects family health and cohesion, including emotional, academic, and social aspects.[7] Marital satisfaction, influenced by communication, emotional support, empathy, conflict resolution, and financial stability, is another key determinant of family well-being.[8] As we can see, family well-being is influenced by various factors, including parental conflict, social support networks, access to resources, community environments, and cultural norms. It is dynamic and can fluctuate based on life events, changes in relationships, and external stressors. Furthermore, the distribution of family roles, the effectiveness of family functioning, and the ability to cope with challenges are significant.[9] The nature of parental relationships is crucial; conflicts can severely deteriorate family well-being, while their absence fosters stability for both children and parents.[10] Gender significantly influences family dynamics. Gottman and Levenson (1992)[11] found that wives are more emotional and defensive in marital conflicts, often initiating them, while husbands tend not to defuse situations. In successful marriages, women handle conflicts constructively, encouraging attentiveness from men. However, Zhu et al. (2022)[12] argue that these factors vary across cultures, highlighting the need for research in specific contexts like Georgia. In Georgia, a post-Soviet country with unique social values, gender roles shape family dynamics. Women are typically the primary caregivers, responsible for emotional labor and child-rearing, while men are seen as financial providers.[13] Rising divorce rates reflect dissatisfaction with women’s roles, linked to post-Soviet changes that expanded economic opportunities for women. This shift has contributed to changing gender roles, reduced parental empathy, and family instability, particularly in middle age.[14] While grounded in the Georgian cultural context, this study contributes to intercultural family psychology by examining how gendered roles function within a transitional society. Georgia’s post-Soviet transformation and evolving gender norms create a unique environment where traditional family expectations are renegotiated alongside modern influences. Compared to individualistic societies like Western Europe or North America, Georgian families often maintain hierarchical, role-specific structures rooted in collectivist traditions. This analysis complements cross-cultural studies, such as Kamo’s (1993)[15] comparison of marital satisfaction determinants in Japan and the United States, and Zhu et al. (2022)[16] findings on maternal emotional labor in China. By situating Georgia within this broader framework, the study highlights how gender roles, conflict resolution, and psychosocial support operate within culturally specific systems, offering transferable insights for understanding family functioning in transitional societies. This study provides culturally embedded insight into gendered family dynamics in Georgia, offering comparative value for intercultural family psychology and extending findings from prior cross-cultural research (e.g., Kamo, 1993; Zhu et al., 2022).[17] It explores the interplay between empathy, cooperative conflict resolution, and marital satisfaction, particularly within the context of traditional and evolving gender roles in Georgia. Understanding the differences in family dynamics across age categories and genders can inform targeted interventions and support strategies for couples at various life stages, ultimately improving family well-being and marital satisfaction. Research Hypotheses: Gender Differences in Empathy and Conflict Resolution. Women are more likely to exhibit higher levels of empathy and use cooperative strategies in marital conflict than men; Spouses who demonstrate higher empathy and utilize cooperative strategies in conflict are more satisfied with their marriages. Influence of Maternal Psychosocial Support on Family Dynamics. A mother’s perception of psychosocial support affects her child’s perception of support. and well-being. A mother’s perception of psychosocial support affects the father’s perception of support, both her and her husband’s perception of their financial situation, and their marital functioning. A mother’s perception of psychosocial support positively correlates with the likelihood of marital conflict for both her and her husband. 1. Materials and Methods The research consists of two phases, each examining family dynamics at different life stages in relation to gender roles, marital satisfaction, and family well-being. The first phase focuses on early-stage marriages, exploring how gender influences empathy and conflict resolution in the formative years. The second phase shifts to middle-aged parents with teenage children, investigating how perceptions of psychosocial support affect family well-being amid the challenges of adolescent development. The first stage of this study utilized a probabilistic sampling method, and data were collected using Google Forms from April to May 2024. Respondents were informed about the anonymity of the research and that their responses would be used only in an aggregated form. Data were analyzed using IBM SPSS 20, employing univariate and multivariate analysis, independent samples t-tests, correlation analysis, and linear regression analysis. A total of 150 early-age married respondents participated in the study, with 85 (56.7%) identifying as female and 65 (43.3%) as male. The majority (48%) were aged 18-24, while 55 (36.7%) were aged 25-34, and 23 (15.3%) were aged 35-44. There were used tools adapted in Georgian language. The Measurement tools were: Questionnaire Measure of Emotional Empathy (QMEE):[18] Developed by Albert Mehrabian and Norman Epstein in 1972, this questionnaire measures emotional empathy. It was adapted by Amiran Grigolava at the State Institute of Psychology of Uzbekistan. The QMEE consists of 33 statements, where respondents indicate their level of agreement based on their first reaction. Emotional empathy refers to the ability to share the feelings and experiences of others, distinct from cognitive empathy, which involves understanding another person’s perspective without sharing their emotions; Thomas-Kilmann Conflict Mode Instrument: Created by Kenneth Thomas and Ralph Kilmann in the early 1970s,[19] this tool assesses conflict management styles based on two dimensions: assertiveness and cooperation. It identifies five behavioral styles in conflict situations, consisting of 30 statements with two possible responses, from which respondents select the one that best describes their behavior. In the current study, instructions will specify that responses relate to conflicts in marriage; Norton Quality of Marriage Index: This established tool, developed by Susan Norton in 1983,[20] evaluates marital satisfaction and overall relationship quality. The questionnaire consists of six statements covering various relationship aspects, using a Likert scale from “strongly agree” to “strongly disagree”. It assesses dimensions such as communication, intimate relationships, conflict resolution, emotional support, and happiness in relationships. The results can help clinicians and researchers identify strengths and weaknesses in marital relationships. On the second stage, to test our research hypotheses, in middle-aged spouses, we reanalyzed data from a study conducted in Spring 2023. The study involved 167 families in Georgia, with a total of 501 participants, including mothers, fathers, and their teenage children aged 11-18. It covered various areas of family dynamics: Mother’s Feeling of Support, Mother’s Family Functioning, Mother’s Marital Conflict, Financial Well-being Perceived by Mother, Child’s Feeling of Well-being, Child’s Feeling of Support, Father’s Feeling of Support, Father’s Family Functioning, Financial Well-being Perceived by Father, and Father’s Marital Conflict. These scales were previously checked and found to be reliable and valid. Participants completed a printed questionnaire. after providing informed consent to participate and share their answers for scientific studies. Participation was confidential and optional. Various recruitment methods were employed to ensure a fair and accessible process for all potential participants. For the reanalysis using SPSS-21, mothers’ feelings of support were chosen as the independent variable, while other variables depended on it. This study was conducted in strict accordance with ethical research guidelines. The authors adhered to the APA ethical principles, the Code of Conduct of the French Psychology Society, and the recommendations of COPE (Committee on Publication Ethics). Research involving human participants complied with the Declaration of Helsinki, ensuring voluntary participation, anonymity, and confidentiality. The first stage of data collection received informed consent from all participants, while the second-stage reanalysis was based on previously approved research. Where applicable, ethical approval was obtained from the appropriate committee, and no identifying information was disclosed. Sample size was determined based on the availability of participants within the research context. No data were excluded from the analyses. No experimental manipulations were applied. All study measures administered are reported in this manuscript. 2. Results 2.1. Early marriage and gender roles in conflict and empathy This stage highlighted whether gender-based expectations contribute to or hinder cooperative conflict resolution, which is particularly relevant in a cultural context like Georgia, where traditional gender roles are prevalent. 2.1.1. Marital satisfaction The study utilized the Norton Quality of Marriage Index, consisting of 6 statements rated on a 7-point Likert scale, to assess marital satisfaction. A higher score indicates greater marital satisfaction. The overall average score for the respondents was 37.6, with a standard deviation of 6.82. There was a slight difference in marital satisfaction scores based on gender, with female participants averaging 38.08 and male participants averaging 36.89. (Table 1). 2.1.2. Empathy The average score for the respondents is 20.1, with females averaging 20.61 and males averaging 19.51. In this study, the average score for respondents was 24.07, with a standard deviation of 3.8. Female respondents had an average score of 26.9 (SD=2.9), while male respondents had an average score of 25.2 (SD=7.2) (Table 2). The results suggest that female respondents exhibit higher empathy levels compared to male respondents. This indicates a potential gender difference in emotional empathy, with females scoring higher on average. The overall average score of the sample population reflects a moderate level of empathy. 2.1.3. Conflict behavior strategies summary The average empathy score for female respondents was significantly higher than that for male respondents (t(148) = 4.358, p < .01), supporting the study’s first hypothesis regarding gender differences in emotional empathy (Table 3). These findings suggest notable differences in conflict resolution strategies and empathy based on gender, indicating the potential need for tailored approaches in conflict management. 2.1.4. Gender differences in conflict behavior The study used an independent t-test to compare conflict behavior strategies between genders. Results indicated that: Collaboration was significantly higher among females, with a mean difference significant at t=4.816, p<0.01t = 4.816, p < 0.01t=4.816, p<0.01; Avoidance was more common among males, showing a significant difference at t=−3.095, p<0.01t = -3.095, p < 0.01t=−3.095, p<0.01; (Table 4) No other strategies showed significant gender differences. 2.1.5. Correlations between marital satisfaction, empathy, and conflict strategies The study explored correlations between marital satisfaction, empathy, and conflict strategies using Pearson’s correlation (Table 5): Empathy showed a moderate positive correlation with marital satisfaction (r=.525, p<0.01r = .525, p < 0.01r=.525, p<0.01); Competitiveness correlated negatively with marital satisfaction (r=−0.595, p<0.01r = -0.595, p< 0.01r=−0.595, p<0.01); while Avoidance and Adaptation correlated positively but weakly. 2.1.6. Regression analysis for predictors of marital satisfaction A regression analysis identified Empathy and Competitiveness as significant predictors of marital satisfaction, explaining 46% of its variability (R=0.46, p<0.01R = 0.46, p < 0.01R=0.46, p<0.01). (Table 6) These results support the hypothesis that gender influences specific conflict behavior strategies and that empathy and certain strategies are linked to marital satisfaction. 2.2. Marital satisfaction in middle-aged parents with teenagers The second phase of research has some steps, where the initial step in our analysis involved examining the relationships between the mother’s perception of psychosocial support and various family dynamics variables through correlation and regression analysis. Correlation Analysis highlights several positive correlations between the mother’s feeling of support and various family dynamics variables (Table 7): There’s a significant positive correlation with: Family Functioning of both parents (r = .674, p< .01 & r = .562, p< .01); Marital conflict of both parents (r = .622, p< .01; r = .568, p< .01) and Father’s feeling of support (r = .383, p< .01); Weaker positive correlations are found between the mother’s feeling of support and financial well-being perceived father (r = .225, p< .01). Also, moderate positive correlations are observed with the child’s feeling of well-being (r = .319, p< .01) and perceived Support (r = .344, p< .01); Additionally, there is no statistically significant connection between the mother’s feeling of support and financial well-being perceived mother (r = .140, p > .05). Regression Analysis indicates that the mother’s feeling of support is a significant predictor of various aspects of family dynamics, including marital conflict, psycho-social support, well-being of the child, and overall family functioning (Table 8): Strong predictive effects are observed when the feeling of support significantly influences the dependent variables. For instance, the feeling of support strongly predicts family functioning as perceived by the mother, with a Beta of 0.674 and a t-value of 11.496, and father with a Beta of 0.0.562 and a t-value of 8.463, indicating a robust relationship. Similarly, marital conflict as perceived by the mother also shows a strong predictive effect by the mother’s feeling, with a Beta of 0.622 and a t-value of 9.660, highlighting that changes in the feeling of support are closely related to changes in these dependent variables; The perception of psycho-social support of the mother has a moderate predictive effect on the father’s perception of psycho-social support, with a Beta of 0.383 and a t-value of 5.92. Similarly, the well-being of the child, with a Beta of 0.319 and a t-value of 4.251, and the child’s perception of psycho-social support of the child, with a Beta of 0.344 and a t-value of 4.632, indicate that the mother’s feeling of support moderately influences the child’s well-being. Weak predictive effects are seen when the mother’s feeling of support has no significant influence on the dependent variables. An example of this is the perception of finances by the father, which shows a weak predictive effect with a Beta of 0.225 and a t-value of 2.955. 2.3. Summary Research indicates significant gender differences in empathy and conflict resolution strategies, with women generally exhibiting higher levels of empathy than men. Findings show that female respondents score significantly higher on empathy measures compared to their male counterparts. Additionally, in marital conflicts, women tend to prefer cooperative strategies, such as collaboration, while men are more inclined to utilize neglectful approaches like avoidance. This aligns with the hypothesis that gender influences conflict resolution strategies, as the results confirm that spouses who demonstrate higher empathy and employ cooperative tactics tend to experience greater marital satisfaction, with positive correlations evident between these factors. Furthermore, the influence of maternal psychosocial support on family dynamics plays a crucial role in shaping children’s well-being and parental relationships. A mother’s perception of support is positively correlated with her child’s well-being and influences the child’s perception of psychosocial support. Additionally, maternal support significantly impacts the father’s perception of support, indicating a shared dynamic within the family unit. While the correlation between maternal support and financial perception is weak, it still suggests a positive influence. Importantly, higher maternal psychosocial support is associated with reduced marital conflict and enhanced marital functioning for both parents, illustrating its vital role in fostering healthy family relationships and dynamics. 3. Findings and Discussion Empirical data from early-stage and middle-aged marriages in Georgia illustrate the persistence of these gendered expectations. Women consistently report higher levels of empathy and cooperative conflict resolution strategies, aligning with social expectations of caregiving and emotional labor. However, the reliance on traditional gendered roles for emotional support often leads to asymmetrical dependencies, which can negatively impact marital satisfaction.[21] Also, reduces emotional connection and promotes unhealthier resolutions, leading to decreased marital satisfaction.[22] In contrast, men’s preference for avoidance strategies can create barriers to effective communication and conflict resolution. This gendered approach may hinder relational satisfaction and contribute to unresolved issues, underscoring the necessity of encouraging men to engage in more empathetic and collaborative behaviors.[23] Moreover, these gender dynamics in conflict resolution have broader implications for family functioning. As observed in the correlations presented in Table 7 and predictions in Table 8, maternal feelings of support significantly influence various aspects of family dynamics. A mother’s ability to foster an emotionally supportive environment can help mitigate the negative effects of men’s avoidance strategies, promoting healthier communication patterns and ultimately enhancing overall family well-being. Family Functioning: In Georgia, a mother’s perception of support strongly predicts family functioning as perceived by both parents. This connection reflects Georgian cultural norms where mothers often play a central role in nurturing family relationships and maintaining emotional stability. When mothers feel supported, they experience less relationship stress, leading to better communication, cooperation, and mutual support among couples. This supportive environment contributes to family cohesion and stability, which are essential for optimal child rearing and overall family well-being.[24] Marital Conflict: The feeling of support in Georgian mothers is a robust predictor of perceived marital conflict by both parents. Changes in the mother’s sense of support correlate closely with changes in marital conflict levels. In Georgian culture, which highly values familial harmony, a mother’s perception of support can contribute significantly to maintaining family stability. Feeling supported enables mothers to fulfill their roles effectively, thereby reducing tensions and enhancing marital satisfaction.[25] Father’s Perception of Psychosocial Support: The mother’s perception of psychosocial support moderately influences the father’s perception of support. This dependency in Georgia reflects cultural norms emphasizing familial interconnectedness and collective well-being. When mothers feel supported, they create a positive family atmosphere that influences how fathers perceive their own roles and support contributions within the family.[26] Child’s Well-being and Perception of Support: The mother’s feeling of support moderately influences the child’s well-being and their perception of support. This finding suggests that maternal support plays a crucial role in shaping children’s overall well-being. When mothers feel supported, they cultivate stable and nurturing environments that positively impact their children, thereby enhancing overall family welfare.[27] Financial Well-being Perceived by Father: Georgian mothers’ support perception has little effect on fathers’ financial views or their own, reflecting traditional norms where financial decisions are paternal domains. While evolving economic and social roles challenge caregiving expectations, gender and emotional labor remain deeply linked, indicating institutional change alone may not shift ingrained family dynamics.[28] This study highlights how gendered expectations in Georgian families are both socially constructed and ontologically embedded. While empirical findings confirm links between empathy, conflict resolution, and marital satisfaction, deeper theoretical engagement reveals that these relationships are shaped by structural gender constraints. Though economic and social shifts challenge traditional roles, ingrained expectations around emotional labor persist. Mothers play a crucial role in nurturing family relationships and maintaining emotional stability. When they feel supported, it enhances family cohesion, reduces stress, and fosters healthier marital and parental relationships. Addressing maternal perceptions of support can lead to interventions that enhance communication, cooperation, and mutual understanding between spouses, ultimately promoting marital satisfaction and stability. Stable and nurturing family environments created through maternal support positively impact children’s development and overall family dynamics. The findings of this study contribute to intercultural psychology by illuminating how cultural scripts and value systems shape gendered roles and family functioning in a society undergoing sociocultural transition. In Georgia, the persistence of traditional maternal and paternal roles can be understood as a manifestation of cultural continuity following the Soviet era, where state-defined gender expectations—such as the glorification of maternal sacrifice and the emphasis on male economic provision—continue to influence contemporary family dynamics. From the perspective of acculturation theory, Georgian society reflects a partial integration of modern egalitarian ideals with deeply rooted collectivist norms. This dynamic interplay between post-Soviet tradition and emerging values creates role strain, particularly for women, who navigate conflicting expectations between caregiving and self-actualization. Additionally, the patterns observed in empathy and conflict resolution align with the cultural orientation toward interdependence,[29] which prioritizes harmony and obligation over individual assertiveness. By framing gendered family roles through the lens of acculturation, cultural scripts, and independence–interdependence theory, this study not only interprets Georgian-specific trends but also informs broader intercultural understanding of how cultural structures mediate psychological processes related to family life. Conclusion This study analyzed data from 150 early-stage married couples and 167 middle-aged families to examine the relationships between empathy, cooperative conflict resolution, maternal psychosocial support, and family dynamics. The findings provide varying levels of support for the hypotheses: Hypothesis 1: Confirmed. Women are more likely to exhibit higher levels of empathy and use cooperative strategies in marital conflict than men. Hypothesis 2: Supported. Spouses who demonstrate higher empathy and utilize cooperative strategies in conflict report higher levels of marital satisfaction. Hypothesis 3: Supported. A mother’s perception of psychosocial support significantly influences her child’s perception of support and overall well-being. Hypothesis 4: Supported. A mother’s perception of psychosocial support affects the father’s perception of support, as well as both parents’ perceptions of their financial situation and marital functioning. Hypothesis 5: Supported. A mother’s perception of psychosocial support positively correlates with the likelihood of marital conflict for both her and her husband. In conclusion, these findings emphasize that maternal perceptions of support are central to understanding both marital satisfaction and family dynamics, revealing the broader implications of shifting gender roles and expectations in contemporary Georgian families. Limitations and further plans for research The study’s limitations include using convenience sampling, limiting generalizability, and relying on self-reported data, which may be biased. The online survey format could exclude participants with limited internet access, and the focus on gender differences may overlook other factors like culture, socioeconomic status, or personality. Additionally, the study’s focus on early and middle-aged marriages in Georgia limits its broader applicability, and the cross-sectional design prevents establishing causality. 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New Haven, CT: Yale University Press. <dx.doi.org/10.12987/yale/9780300102185.001.0001>; UNDP. (2019). Men, women, and gender relations in Georgia: Public perceptions and attitudes. United Nations Development Programme. <https://www.undp.org/georgia/publications/men-women-and-gender-relations-georgia-public-perceptions-and-attitudes>; Varughese, B., Jayan, C., AV, G. (2023). Conflict styles & relationship satisfaction. International Journal of Science, Engineering and Management, 10(11), p. 38. <https://www.ijsem.org>; Walsh, F. (2016). Strengthening family resilience. New York, NY: Guilford Press; Zhu, J., Liu, M., Shu, X., Xiang, S., Jiang, Y., Li, Y. (2022). The moderating effect of marital conflict on the relationship between social avoidance and socio-emotional functioning among young children in suburban China. Developmental Psychology, 13, article number 1009528. <doi.org/10.3389/fpsyg.2022.1009528>. Footnotes [1] Don, B. P., Roubinov, D. S., Puterman, E., Epel, E. S. (2022). The role of interparental relationship variability in parent–child interactions: Results from a sample of mothers of children with autism spectrum disorder and mothers with neurotypical children. Journal of Marriage and Family, 84(5), pp. 1109-1126. <doi.org/10.1111/jomf.12852>. [2] Cummings, E. M., Taylor, L. K., Merrilees, C. E. (2020). Evaluating parenting programs aimed at reducing interparental conflict: Implications for family well-being. Journal of Family Psychology, 34(3), pp. 297-307. [3] Crouter, A. C., Booth, A. (2003). Children’s influence on family dynamics: The neglected side of family relationships. Mahwah, NJ: Lawrence Erlbaum Associates Publishers. [4] Conger, R. D., Conger, K. J., Martin, M. J. (2010). Socioeconomic status, family processes, and individual development. Journal of Marriage and Family, 72(3), pp. 685-704. <https://onlinelibrary.wiley.com/doi/10.1111/j.1741-3737.2010.00725.x>. [5] Taylor, Z. E., Conger, R. D. (2017). Promoting strengths and resilience in single-mother families. Child Development Perspectives, 11(2), pp. 87-92. <doi.org/10.1111/cdev.12741>; Walsh, F. (2016). Strengthening family resilience. New York, NY: Guilford Press. [6] Mastrotheodoros, S., Van der Graaff, J., Deković, M., Meeus, W. H. J., Branje, S. (2020). Parent-adolescent conflict across adolescence: Trajectories of informant discrepancies and associations with personality types. Journal of Youth and Adolescence, 49(7), pp. 1587-1601. <doi.org/10.1007/s10964-019-01054-7>. [7] Farrell, A. K., Simpson, J. A., Carlson, E. A., Englund, M. M., Sung, S. (2020). The impact of stress and support on family functioning: A longitudinal study. Journal of Family Psychology, 34(3), pp. 319-329; Teuber, Z., Sielemann, L., Wild, E. (2022). Facing academic problems: Longitudinal relations between parental involvement and student academic achievement from a self-determination perspective. British Journal of Educational Psychology, 90(4), pp. 876-894. <doi.org/10.1111/bjep.12551>. [8] Kamo, Y. (1993). Determinants of marital satisfaction: A comparison of the United States and Japan. Journal of Social and Personal Relationships, 10(4), pp. 505-520. <doi.org/10.1177/0265407593104005>. [9] Uchino, B. N. (2004). Social Support and Physical Health: Understanding the Health Consequences of Relationships. New Haven, CT: Yale University Press. <dx.doi.org/10.12987/yale/9780300102185.001.0001>. [10] Don, B. P., Roubinov, D. S., Puterman, E., Epel, E. S. (2022). The role of interparental relationship variability in parent–child interactions: Results from a sample of mothers of children with autism spectrum disorder and mothers with neurotypical children. Journal of Marriage and Family, 84(5), pp. 1109-1126. <doi.org/10.1111/jomf.12852>. [11] Gottman, J. M., Levenson, R. W. (1992). Marital processes predictive of later dissolution: Behavior, physiology, and health. Journal of Personality and Social Psychology, 63(2), pp. 221-230. <doi.org/10.1037/0022-3514.63.2.221>. [12] Zhu, J., Liu, M., Shu, X., Xiang, S., Jiang, Y., Li, Y. (2022). The moderating effect of marital conflict on the relationship between social avoidance and socio-emotional functioning among young children in suburban China. Developmental Psychology, 13, article number 1009528. <doi.org/10.3389/fpsyg.2022.1009528>. [13] Shengelia, L. (2020). Maternal care in Georgia: An empirical analysis of quality, access and affordability during health care reform (Doctoral Thesis, Maastricht University). Maastricht University. <doi.org/10.26481/dis.20200319ls>. [14] Meladze, G., Loladze, N. (2017). Population changes and characteristics of demographic processes in Tbilisi. Space - Society - Economy, 19, pp. 87-103. <doi.org/10.18778/1733-3180.19.05>. [15] Kamo, Y. (1993). Determinants of marital satisfaction: A comparison of the United States and Japan. Journal of Social and Personal Relationships, 10(4), pp. 505-520. <https://doi.org/10.1177/0265407593104005>. [16] Zhu, J., Liu, M., Shu, X., Xiang, S., Jiang, Y., Li, Y. (2022). The moderating effect of marital conflict on the relationship between social avoidance and socio-emotional functioning among young children in suburban China. Developmental Psychology, 13, article number 1009528. <doi.org/10.3389/fpsyg.2022.1009528>. [17] Ibid. [18] Mehrabian, A., Epstein, N. (1972). A measure of emotional empathy. Journal of Personality, 40(4), pp. 525-543. <doi.org/10.1111/j.1467-6494.1972.tb00078.x>. [19] Thomas, K. W., Kilmann, R. H. (1974). Thomas-Kilmann Conflict Mode Instrument (TKI) [Database record]. APA PsycTests. <doi.org/10.1037/t02326-000>. [20] Norton, R. (1983). Measuring marital quality: A critical look at the dependent variable. Journal of Marriage and the Family, 45(1), pp. 141–151. <doi.org/10.2307/351302>. [21] Chkeidze, M., Gudushauri, T. (2024). The Interplay of Tradition and Modernity: A Case Study of Gender Roles in Georgian Society. International Journal of Arts, Humanities and Social Sciences, 5(4), pp. 1-10. <doi.org/10.56734/ijahss.v5n4a3>. [22] Gottman, J. M., Levenson, R. W. (1992). Marital processes predictive of later dissolution: Behavior, physiology, and health. Journal of Personality and Social Psychology, 63(2), pp. 221-230. <doi.org/10.1037/0022-3514.63.2.221>. [23] Varughese, B., Jayan, C., AV, G. (2023). Conflict styles & relationship satisfaction. International Journal of Science, Engineering and Management, 10(11), p. 38. <https://www.ijsem.org>. [24] Taylor, Z. E., Conger, R. D. (2017). Promoting strengths and resilience in single-mother families. Child Development Perspectives, 11(2), pp. 87-92. <doi.org/10.1111/cdev.12741>. [25] Kitoshvili, N. (2023). Marital conflict and adolescent’s psycho-social well-being: Mediation and moderation analysis. Scientific Bulletin of Mukachevo State University. Series Pedagogy and Psychology, 9(4), pp. 57-64. <doi.org/10.52534/msu-pp4.2023.57>. [26] Gaspar, T., Gomez-Baya, D., Trindade, J. S., Guedes, F. B., Cerqueira, A., de Matos, M. G. (2021). Relationship between family functioning, parents’ psychosocial factors, and children’s well-being. Journal of Family Issues, 0(0), pp. 1-18. <doi.org/10.1177/0192513X211030722>. [27] Leitão, C., Shumba, J. (2024). Promoting family wellbeing through parenting support in ECEC services: Parents’ views on a model implemented in Ireland. Frontiers in Education, 9, 1388487. <doi.org/10.3389/feduc.2024.1388487>. [28] UNDP. (2019). Men, women, and gender relations in Georgia: Public perceptions and attitudes. United Nations Development Programme. Available at: <https://www.undp.org/georgia/publications/men-women-and-gender-relations-georgia-public-perceptions-and-attitudes>. [29] Markus, H. R., Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98(2), pp. 224-253. <doi.org/10.1037/0033-295X.98.2.224>.
The Failure of Regulatory Impact Assessment Reform in Georgia: An Isomorphic Mimicry Perspective
Regulatory Impact Assessment (RIA) has been promoted globally as a cornerstone of good governance, designed to ensure evidence-based policymaking and enhance state accountability. In Georgia, multiple international donors supported the institutionalization of RIA from the mid-2000s onward. Despite the enactment of legal and methodological frameworks, the reform did not yield a functioning national system and, by 2024, had effectively collapsed, abandoned by both donors and the government. This paper examines why a globally celebrated instrument failed in an ostensibly favourable context. Using a process-tracing case study of Georgia, the paper employs the concept of Isomorphic Mimicry to show how donor-endorsed reforms can persist as performative compliance - securing resources and external legitimacy - while producing limited outcomes. In this effort, the article showcases how, in parallel with its formal adoption into law, the reform fell into a “capability trap”, with civil servants overloaded and donor-driven technical support proliferating. Thus, the case illustrates how mimicry-driven reform can persist for years without achieving substantive results, sustained by a coalition of political actors, donors, and other stakeholders with short-term incentives. The analysis further traces how political-bureaucratic actors preserved prevailing routines by designing and exploiting legislative loopholes that circumscribed RIA’s formal effects. This study advances Isomorphic Mimicry and governance reform scholarship by specifying conditions sustaining mimicry (particularly, high donor density, a well-developed system of external and internal reform enablers, and bureaucratic hedging via legislative loopholes), tracing regulatory decoupling that turns RIA into box-ticking, and using Georgia’s donor-cooperation suspension as a stress test highlighting the centrality of donors in mimetic reforms. Keywords: Regulatory Impact Assessment (RIA), good governance, isomorphic mimicry, institutional isomorphism, Georgia. Introduction In the mid-2010s, introducing good governance principles became a priority for the Georgian government and its international development partners (European Commission, 2015; European Commission, 2017).[1] The framework within which Good Governance was to be established in the country was the Public Administration Reform (PAR).[2] The Coordination of the reform was entrusted to the Government Administration, while the unit with direct responsibility became the Department of Policy Analysis and Strategic Planning, established in 2014.[3] In 2015, under the coordination of this same unit, the Public Administration Reform Guide 2020 was adopted, drawing primarily on the SIGMA Principles.[4] In parallel, by decree of the Prime Minister of Georgia, a strategy governing the activities of the new unit - the Policy Planning System Reform Strategy 2015-2017 (Strategy) - was enacted in 2015. It is noteworthy that, within the situational analysis of the Policy Planning System Reform Strategy 2015-2017, it was stated that the links between policy planning and legislative drafting in Georgia were weak. It was also underscored as a serious problem that Georgia had not introduced a practice of legislative impact assessment. Accordingly, the Strategy envisaged the introduction of a legislative impact assessment system to minimize potential negative effects on citizens, businesses, trade, and investment. It further set the objective that legislative impact assessment should become an integral component of the policy development and decision-making process (Policy Planning System Reform Strategy 2015-2017, 2015). Following this development, starting from 2015, the Regulatory Impact Assessment (RIA) instrument emerged in Georgia within the broader framework of Good Governance and PAR. Accordingly, among the various initiatives launched under PAR, attention has been devoted to the institutionalization of Regulatory Impact Assessment (RIA).[5] Despite significant efforts and the formal adoption of the relevant law and methodology, the reform never resulted in the creation of a functioning national framework in Georgia. By 2024, the RIA initiative had effectively collapsed, abandoned both by the government and the donors. This experience, therefore, raises a fundamental question: why did a globally celebrated best practice fail so completely even in this favourable context? This paper addresses that question by presenting a case study of Georgia that applies the concept of isomorphic mimicry (IM), a phenomenon widely discussed in the literature,[6] to explain the failure of the RIA institutionalization reform. Using this illustrative case, the analysis demonstrates how reform - despite broad endorsement and substantial financial support from all relevant actors - can persist for years without delivering substantive outcomes and completely come to a halt after donor activities disappear. The analysis also demonstrates how the Georgian political bureaucracy managed to carry forward its usual modus operandi by further subverting the reform through the creation and exploitation of parallel instruments that limited its formal impact. Literature Review, Research Questions, and Methodology RIA institutionalization reforms in Eastern Europe and Central Asia Globally, the process of RIA institutionalization commenced in the mid-2000s when major international organizations introduced this new policy planning tool. Subsequently, relevant standards, frameworks, and guidelines were developed, primarily by organizations such as the OECD, European Commission, World Bank, and other global actors.[7] At its core, RIA aims to foster evidence-based policymaking by ensuring that regulatory decisions are guided by systematic analysis. It seeks to guarantee that enacted regulations are economically rational - assessed through tools such as cost-benefit analysis - coherent with the broader policy framework, and socially as well as culturally acceptable to a diverse group of stakeholders. Thus, the institutionalization of RIA was actively promoted by various donors globally and readily embraced by certain countries seeking to attract donor funding and gain external legitimacy for their reform efforts.[8] A review of the literature on the institutionalization of Regulatory Impact Assessment (RIA) in Eastern Europe and Central Asia reveals mixed findings. For instance, Staroňová (2010),[9] based on a comparative analysis of five Central European countries, concludes that the forms of institutionalization differ significantly, and the trajectories of reform development vary across countries. She argues that while the existence of high-quality RIA guidelines is an important prerequisite, it is not sufficient for successful implementation. Instead, the quality of oversight mechanisms is identified as a critical factor in determining reform success. In a later study, Staroňová (2014)[10] examines RIA implementation in Central and Eastern European countries and finds that the preparation of RIA documents tends to be symbolic or non-use in nature. A major problem identified is that when RIAs are conducted, they are often prepared at the final stage of policy formulation, rendering them largely ineffective in influencing decision-making. Similarly, Shaikenova (2024),[11] in a comparative analysis of RIA implementation in Russia, Kazakhstan, and Georgia, finds that the quality of RIA documents does not improve over time; In fact, it tends to deteriorate. The study concludes that, in the examined countries, RIA reforms are largely superficial and implemented pro forma, with little substantive impact on the policy process. Public administration reform in Georgia A review of the literature on PAR in Georgia suggests that overall reform outcomes have been moderate and that similar types of problems recur across different reform dimensions. Khuroshvili (2025)[12] argues that the policy-planning system only partially aligns with the SIGMA Principles; Georgia demonstrates relatively strong legislative coherence, yet weaknesses persist in evidence-based policymaking and inclusion. The review also identifies a misalignment between formal institutional design and practical implementation, as well as ongoing challenges related to administrative capacity and limited political will. Kvashilava (2019)[13] concludes that, both with respect to PAR in general and civil service reform in particular, success has largely depended on political will and the broader political context. Comparing the design of the civil service with its actual operation, Khuroshvili (2023)[14] and Dolidze (2021)[15] report significant discrepancies in their respective studies. Finally, Abashidze (2016)[16] contends that civil service reform in Georgia was premature; more specifically, the state lacked the capacity to implement a reform of this magnitude effectively, which helps explain its shortcomings. One might argue that the trajectory of RIA roll-out in Georgia mirrors patterns observed both in neighbouring countries’ RIA reforms and in Georgia’s PAR more generally. More specifically, insufficient political will, limited state capacity, design flaws in institutionalization, and a misalignment between policy design and practical implementation contributed to the reform’s shortcomings. At the same time, given that the reform ostensibly enjoyed full political backing, Georgia’s overall governance capacity was comparatively strong, as indicated by the World Governance Indicators (WGI) Government Effectiveness measure, where in 2023 Georgia ranked second after Czechia among Eastern Europe, the South Caucasus, and Central Asia, and the reform had overarching donor support, an essential factor in strengthening state capacity, there may be more at play than the foregoing explanations alone. In other words, the process development under the RIA institutionalization in Georgia may have been deliberate and strategic, with outcomes that in fact reflect the state’s intended objectives. To address this question, the author presents a case study of Georgia that applies the concept of isomorphic mimicry (IM), a phenomenon widely discussed in the literature,[17] to explain the failure of the RIA institutionalization reform. What is isomorphic mimicry (IM)? In line with development literature, there is a global movement where donors typically engage in formulating global themes and their corresponding scripts.[18] Simultaneously, in pursuit of their objectives, donors seek fertile ground, tools, and techniques in various developing countries.[19] Consequently, when a country aims to look like a state and project the image of a successful entity, it often employs the phenomenon/technique of IM. This entails the state’s willingness to undertake agenda-confirming reforms to gain internal and external legitimacy, assuming that its shortcomings will be tolerated by external observers (the so-called “successful failures”). Frequently, the IM strategy leads the state to take an excessive burden prematurely (the so-called “premature load-bearing phenomenon”), and ultimately, it becomes trapped in what is known as the capability trap. Escaping this trap and transforming a particular reform into a genuine success then becomes extremely challenging.[20] The concept of IM builds on the broader notion of institutional isomorphism.[21] DiMaggio and Powell (1983)[22] distinguish three main forms of institutional isomorphism: coercive, normative, and mimetic. As their original models focused on industrial relations, the concept initially belonged more to the field of industrial sociology. By contrast, IM has evolved into an approach more closely aligned with international development. Its practical application expanded particularly in developing countries and their institutions from the late 1980s onward. This shift was largely driven by the growing emphasis on the quality of public institutions within the development discourse.[23] Andrews et al. (2017) illustrate an organizational ecosystem in which IM is optimal. Precisely, such an ecosystem consists of three layers (ecosystem, organization, and agents). To make IM work effectively, the ecosystem for organizations should be a closed system, and agenda conformity should be a criterion for how novelty is evaluated. The optimal form for organizational legitimisation should be IM, leaders of organizations should choose organizational perpetuation as their preferred strategy, and the so-called front-line workers should act with pure self-interest.[24] Literature review on IM The cases of IM have been actively studied academically, both globally but also in the post-Soviet context. For instance, Narzetti & Marques (2021)[25] examine water sector reforms in Brazil and conclude that IM was the main reason for the failure to achieve meaningful success. Similarly, Bano (2022)[26] studies education reforms in Nigeria and argues that the adoption of international best practices facilitated mimicry, enabling the government to signal alignment with global standards without generating real progress. IM is also salient in the implementation of global initiatives. For example, Rubin and Munkholm (2022)[27] analyze the formulation of National Antimicrobial Resistance (AMR) Plans, concluding that in many low- and middle-income countries, the formal adoption of WHO templates occurred without substantive implementation, a phenomenon largely attributed to IM. In the post-Soviet context, Janenova & Knox (2019)[28] explore the civil service law in Kazakhstan, concluding that the reform process was largely mimicry-driven. Similarly, Janenova (2019)[29] investigates education reforms in Central Asia and identifies widespread adoption of Western models and forms in a mimetic manner. In another study, Knox & Janenova (2019)[30] examine Kazakhstan’s E-governance reforms, coining the term “E-Governance Paradox” to describe a situation where digital platforms create a façade of progress. This logic extends to open government reforms, where Kazakhstan’s model of “half-open government” is presented as an example of mimicry.[31] Similarly, Kurmanov & Knox (2022)[32] reach comparable conclusions based on the cases of Kazakhstan, Uzbekistan, and Kyrgyzstan. In the realm of higher education, Bischof (2018)[33] examines reforms in Moldova, Russia, and Kazakhstan, documenting a mimetic convergence toward the Bologna Process, which the author refers to as “partial mimicry”. In the field of policing strategies - particularly the implementation of the “broken windows” approach in Almaty (Kazakhstan) and Kyiv (Ukraine) - Marat (2018)[34] highlights the mimetic character of these strategies’ adoption. Given that IM largely rests on the country and its international partners acting in concert, the next section offers a concise survey of the modalities of interdependence between Georgia and its international counterparts in contemporary Georgian history, spanning the early 1990s through the early 2020s. Georgia as a “Donor Darling” In the recent history of Georgia, after the fall of the Soviet Union, following the tumultuous experiences of the early 1990s,[35] Georgia, starting in the mid-1990s, began to look outward, seeking models of economic, political, and institutional reform to adopt. Over time, Georgia earned a reputation as a “donor darling”, eager to implement various modernist institutional experiments imported from abroad.[36],[37] During Shevardnadze’s government period (1992-2003), he sought to utilize pro-Western reform orientations for the purpose of self-legitimization, drawing upon his political background in communism. This effort led to the appointment of young, foreign-educated individuals to prominent positions, making the application of institutional reforms more convincing to international partners.[38] Next, Mikheil Saakashvili, upon assuming power in 2003 and until 2012, also attempted to employ the western reform agenda to bolster his internal legitimacy, portray himself as a western-inspired reform-oriented leader, and thus secure much-needed financial and political support from western partners. However, simultaneously, Saakashvili engaged in local experiments. This occurred when, with the support of international partners, the Saakashvili government pursued reforms that usually conflicted with the standard approaches, recommendations, and conditions typically advanced by donors.[39] Ultimately, the Saakashvili government team faced a significant political setback largely due to these experiments, which extended beyond the basic framework of donor-driven reform agenda conformity and became exceedingly difficult to manage without a strong institutional backbone, external legitimization, and diminishing public support.[40] A new political order was established in Georgia in 2012. This order emerged after the Georgian population managed rather unexpected to change the government through the parliamentary elections in 2012, bringing the Georgian Dream party into power.[41] Retrospectively, we can argue that Georgian Dream lacked an ideological backbone, had no clearly articulated reform agenda, was characterized by inertia, was built fundamentally as the antithesis of the Saakashvili regime, and its governance was characterized by strong elements of informal rule - stemming from the fact that its founder, billionaire Bidzina Ivanishvili, exercised power in an informal capacity.[42] Once this primary goal of becoming a ruling party was achieved, its ideological void became apparent and urgently needed to be filled. Meanwhile, inertia demanded that Georgian Dream demonstrate reform initiatives. However, the short-term orientation of its constantly changing formal leadership made long-term planning virtually impossible (Notably, during the ten-year period of Georgian Dream’s governance, from 2012 to 2022, there were six instances where the current prime minister unexpectedly resigned, resulting in the dissolution of the government). These conditions, combined with the signing of the Association Agreement with the EU in 2014 and the assumption of new commitments within the process of Georgia’s EU integration,[43] laid the groundwork for presenting so-called good governance reforms as a panacea and provided international donors with an even broader arena for advancing the reform agenda in Georgia.[44] Consequently, the Georgian Dream government exhibited a willingness to undertake agenda-confirming reforms at the expense of foreign donors. As a result, within the governance model, the role and significance of additional actors involved in policy development - primarily multilateral and bilateral donors, as well as the profit and non-profit non-governmental sector closely associated with them - increased and eventually became the dominant feature. To see the increased scale of international partners’ activities in Georgia, several data points can be cited. According to official figures, development partners committed approximately USD 2.3 billion in 2006 and around USD 9.5 billion in 2019, representing a fourfold increase (World Bank, 2025).[45] At the same time, the total funding commitments of the top ten development partners between 2014 and 2021 amounted to approximately USD 14.45 billion. For comparison, Georgia’s annual GDP stood at USD 17.9 billion in 2014 and USD 18.4 billion in 2021 (World Bank, 2023).[46] As for the activities of a specific country and organization in Georgia, here, for example, we can look at the work of the U.S. and the Asian Development Bank. Between 2012 and 2023, the United States disbursed approximately $1.92 billion in Overseas Development Assistance (ODA) to Georgia. On a per capita basis, this represents one of the highest aid levels globally (ForeignAssistance.Gov, 2025; Devdariani, 2025).[47] To understand the scale of assistance, it is also useful to situate Georgia within the regional context of U.S. foreign assistance. In 2022, Georgia ranked second - after Ukraine - in terms of U.S. assistance within the Europe and Eurasia region, which includes a total of 20 countries. This position was held throughout most of the 2012-2022 period. In the case of the Asian Development Bank (ADB), Georgia has witnessed substantial cumulative growth in commitments over the past two decades. While total commitments stood at under USD 200 million in 2006, they had reached approximately USD 2 billion by 2019. By the end of 2021, the total had increased to USD 2.95 billion (The World Bank, 2025).[48] Research questions and methodology All the above-mentioned circumstances favoured the introduction and successful implementation of globally recognized good governance practices in Georgia after 2012. Nevertheless, one of the flagship initiatives of this process - the reform aimed at institutionalizing Regulatory Impact Assessment (RIA) - ultimately failed. In this article, we seek to explain the reasons for this failure, employing the IM framework as our theoretical lens. The following research questions will be addressed using a case study: RQ1: To what extent is Georgia’s IM strategy an explanatory factor behind the failure of Regulatory Impact Assessment (RIA) reform? RQ2: To what extent did donors contribute to the persistence of IM in Georgia? RQ3: Has the actual governance model deployed any practices, in parallel, to hedge against the risk of dysfunction while mimetic reforms were being implemented? To answer this question, this article traces the entire RIA institutionalization reform process across four phases: inception, renewed momentum, legislative breakthrough, and rapid decline. The case study draws on a comprehensive review of all relevant documents, supplemented by in-depth interviews and focus groups conducted with various stakeholders involved in the reform process, including its initiators, RIA experts, RIA authors, and policy analysts in Georgia. Case Study - RIA Institutionalization Reform in Georgia The ultimate objective of the RIA institutionalization reform in Georgia was to mandate the Government and Parliament of Georgia to conduct RIAs before the adoption of significant regulatory changes. In the following section, I outline the process of RIA institutionalization and highlight its key milestones. Phase 1: Inception The discussion around RIA in Georgia first emerged in 2007 when the Ministry of Economy and Sustainable Development established a dedicated unit, the Division of Economic Policy and Regulation Impact Assessment (KII #1, 2023). During the period from 2007 to 2012, owing to the libertarian approach of the government at the time, the issue of RIA gradually lost its relevance in the following years, despite the continued practice of conducting small-scale on-site assessments (KII #1, 2023). At the same time, capacity building initiatives were sporadically launched for the relevant government units and other stakeholders, including research institutes and consultancy organizations.[49] Phase 2: The renewed momentum After a hiatus of several years, discussions about RIA in Georgia regained momentum around 2014-2015. The framework document prepared by the USAID (United States Agency for International Development) Economic Governance Program (G4G) - Recommendations on RIA National Framework of Georgia - in 2015 was the very first public document discussing the institutional reform framework of RIA in Georgia. As the report notes, before this, RIA in Georgia mainly consisted of ad-hoc events designed to raise awareness among public agencies and enhance stakeholders’ RIA-related skills. During the same period, work on pilot RIA documents commenced, with the first three being prepared in 2014. The first official government document to address institutional reform was the “Strategy for the Systematic Reform of Policy Planning (2015-2017),” approved in June 2015. According to this strategy, the government committed to incorporating the RIA methodology into Georgian legislation. The action plan stipulated that this should be achieved no later than 2017, with the Department of Policy Analysis, Strategic Planning, and Coordination of the Prime Minister’s Office tasked with developing the reform.[50] Subsequently, the reform process came to a halt for several years. This pause can likely be attributed to the conclusion of the relevant donor-funded project (G4G) and/or a shift in priorities. Specifically, after the development of the corresponding strategic document and the establishment of the designated governmental unit, most probably, donor interest declined, while parallel, the reform lacked the internal readiness to continue. Following this hiatus, around 2017, the reform regained momentum. Phase 3: The legislative breakthrough Between 2017 and 2019, two parallel processes unfolded. On one hand, as described above, there was a significant stagnation in terms of institutional reform, with the plans initiated in 2014-2015 largely faltering. On the other hand, a new trend emerged as new donors, such as the USAID Good Governance Initiative and the USAID Energy Program, became more actively involved in the RIA institutionalization process. Various international organizations, including GIZ (German Society for International Cooperation), UNDP (United Nations Development Programme), and UN Women, also took initiatives, contributing to the preparation of pilot RIA documents and strengthening the relevant human resources. Notably, 2019 witnessed the highest number of prepared RIA documents, with 12 in total.[51] The events of 2019-2020 mark a critical stage in the RIA institutionalization reform in Georgia. In May 2019, the Parliament of Georgia approved amendments to the Law on Normative Acts. These amendments mandated attaching an RIA report to draft normative acts, but it’s worth noting that the legislative amendment already defined exceptions, allowing initiators to bypass RIA preparation. Another significant date was January 17, 2020, when Government Resolution 35 and related annexes were approved. These documents established the methodological framework for RIA implementation and outlined a list of legislative acts requiring mandatory RIA inclusion when drafting amendments. It’s essential to acknowledge that various donors played a substantial role in initiating and technically supporting this process (KII #2, 2023). RIA’s experts note that, alongside the active engagement of donors, a significant driver of change was the prevailing trend of governmental reforms at the time. As one former public official remarked during a focus group discussion, there was both hope and an expectation among the officials driving the reform that, when a reform-minded minister eventually assumed office, they would encounter, on the one hand, an established legislative framework and, on the other, a well-prepared civil service (FGD #1 with RIA-experts, 2023). Phase 4: Initial euphoria and sudden decline The final phase of the RIA institutionalization reform began with initial euphoria but ended in a sudden decline. The euphoria followed a legislative breakthrough, as stakeholders were eager to advance policy implementation and actively sought to establish an optimal institutional framework to ensure its effectiveness. During the period of 2021-2023, several significant processes have occurred. Elements of the RIA institutionalization reform were incorporated into strategic documents and action plans. More specifically, in 2022, the approval of the 2023-2026 Public Administration Reform (PAR) strategy featured an entry concerning RIA. Notably, this reference is somewhat vague and primarily focuses on the retraining of civil servants. Interestingly, the strategy attempts to justify the relatively slow progress of RIA reform by citing the global pandemic. Also, the SME Development Strategy 2021-2025, adopted in 2021, places a strong emphasis on legislative development, institutional strengthening, and the enhancement of the operating environment. Within this framework, the strategy supports the development of the RIA system, which includes the implementation of the RIA SME test for legislative changes, with consideration given to EU and international best practices. At the same time, various implementing units responsible for the RIA institutionalization reform were established and strengthened. Notably, alongside the process of RIA institutionalization, there was an ongoing effort to strengthen RIA-related skills. However, on the one hand, there was no comprehensive overview of the skills that civil servants have been able to enhance during this period.[52] On the other hand, all relevant stakeholders were concerned about the lack of human resources and the constant outflow of personnel from the public service, which hinders the achievement of reform goals (KII #1, 2023; FDG #2 with RIA-authors, 2023). They consistently emphasized the importance of continued donor support for capacity-building programs.[53] Consequently, at the legislative level, it was determined that the Parliamentary Secretary of the Government of Georgia (Secretary) would oversee the study of draft laws and the attached RIA reports, assessing their quality. With support from the USAID EG Program, a decision was made to establish the RIA Support Platform at the Secretary (the host organization). Under this platform, when the state agency identifies the need for the RIA preparation and receives appropriate support, it can request assistance from the Secretary. The Secretary then engages RIA experts affiliated with the platform. The program identified three experts for this purpose. One of these experts was responsible for determining the extent of assistance required for RIA preparation, the type of RIA to be implemented, and the nature of the support provided. From May 2022 to August 2023, within the platform’s activities, RIA experts participated in the preparation of a single RIA report. In 2023, work was underway to draft the second RIA document.[54] The second initiative, supported by the USAID EG Program and the Secretary, was the RIA Peer-review Platform. In the initial stage, the program developed the concept and structure of the quality control platform. In 2023, the RIA report quality control guidebook was created, aligning with the RIA preparation methodology defined by government decree. The plan was for this document to become informally mandatory during RIA quality assessments. The USAID EG program was planning to assist the office by providing expert support. The initiative involves two independent experts and one government representative assessing the quality of the RIA document.[55] Parallelly, in 2022, the Research Center of the Parliament of Georgia expressed its willingness to contribute to RIA institutionalization reform. Consequently, in 2023, its mandate was expanded following relevant changes in the center’s statute, preparing RIA-related documents as part of the center’s responsibilities. The Parliamentary Budget Office expressed similar interest, particularly in enhancing skills related to the Cost-Benefit Analysis (CBA) methodology.[56] Additionally, there is the Economic Policy and Regulation Impact Assessment Division, which operates as a structural unit of the Economic Policy Department within the Ministry of Economy and Sustainable Development. In 2023, with active participation and funding from UNDP, there was an initiative underway to prepare the SME Test methodology and implement it in practice. The changes outlined above were accompanied by the introduction of new methodologies, guidelines, and regulatory initiatives associated with the RIA institutionalization reform. These included the completion and refinement of various methodologies - such as the RIA methodology (pursuant to Government of Georgia Resolution No. 35), the standard and in-depth RIA methodologies, the SME test methodology, and the RIA quality assurance methodology/guidebook. In addition, a number of guidebook-style documents were prepared, including publications on cost-benefit analysis developed specifically by the Parliamentary Budget Office. Moreover, several new regulatory initiatives were launched within the framework of the RIA institutionalization reform. A notable example was the RIA Implementation Expert Certification, presented by industry experts at the USAID EG event in March 2023. The initiatives described above were unexpectedly suspended in 2024. More concretely, following the Georgian government’s confrontation with the European Union and the United States in early 2024 - during which it accused them, among others, of orchestrating a revolution in Georgia - the EU and the U.S. responded by suspending cooperation with public institutions under their donor-funded initiatives.[57] As a result, the RIA reform in Georgia effectively came to an end. All donor initiatives were halted, and public institutions ceased their independent engagement in the reform process. Results In response to RQ1, the process-tracing analysis leads us to a finding that the institutionalization of the RIA reform in Georgia followed the inherent logic of the IM framework. Georgia was initially unprepared for the significant burden it assumed (the “premature load-bearing phenomenon”), which gradually led the public service into a capability trap. For instance, the inclusion of RIA-related issues in state strategies and action plans, the expansion of the mandate of existing units, the development of new methodological approaches and relevant guidelines, and the initiation of other regulatory innovations have laid the foundation for an irreversible process of deepening the skills gap in the public service (for instance, in this case study, the initiative to assign the task of RIA quality control to the employees of the Office of the Parliamentary Secretary of the Government of Georgia placed a significant institutional burden on the office (FGD #1 with RIA-experts, 2023). This has made their daily work more challenging and the reform implementation process less likely to succeed. At the same time, for the public service to escape this capability trap into which it had placed itself - and to fulfil all the commitments it had undertaken at the normative level - it required ever-increasing and continuous donor support. In response, both donors and technical assistance providers (private/non-governmental organizations, individual experts) were eager to offer new services, and as described above, they continuously developed new initiatives and tools for this purpose. From a theoretical perspective, this implied that escaping this trap and making a particular reform successful became nearly impossible. To further illustrate the mimicry nature of the reform, it is instructive to examine its outcomes. Following the significant changes adopted at the beginning of 2020, by September 2023, the Georgian government had not submitted a single RIA report to the Parliament of Georgia regarding changes initiated in the laws determined by government decree.[58] Regarding RQ2, the mimicry-based nature of the reform and its total dependence on donor engagement became evident in its de facto termination: once donor initiatives were halted in 2024, public institutions completely ceased their independent engagement in the RIA institutionalization process. As a result, the RIA reform in Georgia effectively came to an end. In response to RQ3, it is noteworthy that the reform failed to affect the current governance model; alongside the formal endorsement of the reform, the political bureaucracy managed to maintain the usual modus operandi by creating and leveraging various regulatory tools. This was achieved through legislative initiatives that created so-called legislative loopholes. To illustrate, the initial legislative change allowed bills initiated by parliamentarians to bypass the mandatory use of RIA. The decree also includes a provision stating that, under certain circumstances, delays in legislative changes are considered unjustified, and therefore, the preparation of a RIA is not required for such changes. In practice, those loopholes have become an important mechanism for implementing regulatory changes outside the formal scope of the reform. According to an analysis conducted by ISET-PI in 2023, between 2022 and September 2023, three such legislative initiatives were introduced by ruling party parliamentarians (In a KII #2, RIA expert aptly referred to these initiators as “volunteer parliamentarians”). In an additional three cases, the Government of Georgia justified the absence of RIA by citing the lack of justification for the delay. As one of the focus group participants clearly stated, whenever an initiative of importance to the government was at stake, it was implemented through exceptions, bypassing the RIA process (FGD #1 with RIA-experts, 2023). Conclusion Using the example of Georgian RIA institutionalization reform, we can conclude that a classical type of IM can be observed. It was characterized by the following: Firstly, all relevant stakeholders contributed to the viability and sustained perpetuation of mimicry-driven reforms, despite the lack of substantive results. Specifically: 1) Within the political bureaucracy, there was a continued formal endorsement of the reform process; 2) Donors continued to advance the reform process, thereby contributing to its de facto legitimization. 3) Opportunism was displayed by the reform implementers, both at the institutional (at both the state and private) and individual levels, aligning with their own interests. In some cases, this involved staying engaged in the reform process to maintain, strengthen, or assign a formal purpose to the respective institution. In other cases, it involves pursuing individual benefits. More specifically, in exchange for short-term benefits, technical supporters of the reform, such as experts, consulting groups, and research centers, often unknowingly facilitated the acceleration of the IM process; Secondly, the reform gradually led the public service into a capability trap, from which escape required ever-increasing and continuous donor support; Thirdly, in the absence of an exogenous shock - specifically, the abrupt discontinuation of donor initiatives in cooperation with state entities in Georgia in 2024 - there was a strong likelihood that the mimicry-driven reform process would have persisted indefinitely, sustained by the active contribution of all relevant stakeholders. At the same time, the suspension of activities by relevant international donors in Georgia effectively created a natural experiment - specifically, the opportunity to assess the extent to which the reform could prove sustainable in the complete absence of donor support. In other words, what was the scale of IM within the framework of the reform? The outcome was clear: once donor initiatives ceased, public institutions entirely discontinued their independent engagement in the RIA institutionalization process. Consequently, after donors abandoned the process, the RIA reform in Georgia effectively came to an end. Simultaneously, the RIA institutionalization reform has revealed the existence of an effective political bureaucracy within the Georgian governance model and its systemic response to IM. This became evident when, during the ongoing reform, the previously unforeseen risk of transitioning from IM to significant systemic changes emerged. It demonstrated the ability of the system to accurately perceive the risks of IM and react accordingly to prevent systemic collapse. Precisely, parallel to a continued formal endorsement of the reform process, a de facto imitation of reform through the exploitation of various legislative loopholes took place, designed to prevent it from producing substantive results. This dual strategy ensured that the reform did not disrupt the stable functioning of the existing governance model. This study advances scholarship on Isomorphic Mimicry and governance reforms in three respects. First, it specifies the organizational and ecosystemic conditions under which Isomorphic Mimicry is sustained - high donor density, a well-developed system of external and internal reform enablers, and bureaucratic hedging via legislative loopholes. Second, it identifies concrete mechanisms of decoupling in the regulatory domain, turning RIA from a real decision-making instrument into a box-ticking exercise. Third, methodologically, the analysis exploits an exogenous suspension of donor cooperation in Georgia as a stress test, delineating the significance of donor engagement within a mimetic reform framework. References: Abashidze, A. (2016). Civil Service Reform in Georgia: Main Directions and Challenges. Doctoral Dissertation, Ilia State University; Andrews, M., Pritchett, L., Woolcock, M. (2019). Building state capability: Evidence, analysis, action. Oxford University Press; Bano, M. (2022). International push for SBMCs and the problem of isomorphic mimicry: Evidence from Nigeria. RISE Working Paper Series (22/102). Foreign, Commonwealth & Development Office; Berglund, C. (2014). Georgia between dominant-power politics, feckless pluralism, and democracy. Demokratizatsiya: The Journal of Post-Soviet Democratization, 22(3); Bischof, L. (2018). 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Economic regulation and state interventions: Georgia’s move from neoliberalism to state-managed capitalism. PFH Forschungspapiere, 2013/03; USAID - Governing for Growth (G4G) in Georgia. (2015). Recommendations on RIA national framework of Georgia; World Bank. (2012). Fighting corruption in public services: Chronicling Georgia’s reforms. World Bank; World Bank. (2023). The World Bank in Georgia, 2014-2023: Country program evaluation, approach paper. World Bank; World Bank. (2025). The World Bank in Georgia, 2014-2023: Country program evaluation. World Bank. Footnotes [1] European Commission. (2015). Action document for support to public administration reform in Georgia (PAR); European Commission. (2017). Association agenda between the European Union and Georgia: 2017-2020. [2] The Administration of Government of Georgia. (2015). Public Administration Reform Guide 2020. [3] Initially, when the Government Administration was reviewed under the 2013 OECD/SIGMA assessment, one of the recommendations was to create this new structural unit. (Public Administration Reform Guide 2020, 2015). [4] See: <www.sigmaweb.org/en/publications/the-principles-of-public-administration_7f5ec453-en.html>. [5] USAID - Governing for Growth (G4G) in Georgia. (2015). Recommendations on RIA national framework of Georgia. [6] Andrews, M., Pritchett, L., Woolcock, M. (2019). Building state capability: Evidence, analysis, action. Oxford University Press; Pritchett, L., Woolcock, M., Andrews, M. (2013). Looking like a state: Techniques of persistent failure in state capability for implementation. The Journal of Development Studies, 49(1), pp. 1-18. [7] OECD. (1997). Regulatory impact analysis: Best practices in OECD countries. <doi.org/10.1787/9789264162150-en>; OECD. (2008a). Building an institutional framework for regulatory impact analysis (RIA): Guidance for policy makers. <www.oecd.org/regreform/regulatory-policy/40984990.pdf; OECD. (2008b). Introductory handbook for undertaking regulatory impact analysis (RIA). <http://www.oecd.org/gov/regulatory-policy/44789472.pdf>; OECD. (2015). Regulatory policy in perspective: A reader’s companion to the OECD Regulatory Policy Outlook 2015. <dx.doi.org/10.1787/9789264241800-en>. [8] Ibid. [9] Staroňová, K. (2010). Regulatory impact assessment: Formal institutionalization and practice. Journal of Public Policy, 30(1), pp. 117-136. [10] Staroňová, K. (2014). L’institutionnalisation des études d’impact en Europe centrale et orientale [Institutionalization of regulatory impact assessment in Central and Eastern Europe]. Revue française d’administration publique, 149(1), pp. 123-143. [11] Shaikenova, A. (2024). Regulatory impact assessment in Georgia, Kazakhstan, and Russia: Policy learning and policy capacity. Doctoral dissertation, Nazarbayev University. [12] Khuroshvili, B. (2025). The policy planning system in Georgia: design and implementation challenges, Eastern Journal of European Studies, 16(1), pp. 173-193. [13] Kvashilava, B. (2019). The political constraints for civil service reform in Georgia: History, current affairs, prospects and challenges. Caucasus Survey, 7(3), pp. 214-234. [14] Khuroshvili, B. (2023). Civil Service System in Georgia and its features following the Public Administration Reform. Environment and Society, #8 July, pp. 1-18. [15] Dolidze, N. (2021). Principle of accountability and establishment of politically neutral civil service in Georgia. Paper presented at the 29th NISPAcee Annual Conference. [16] Abashidze, A. (2016). Civil Service Reform in Georgia: Main Directions and Challenges. Doctoral Dissertation, Ilia State University. [17] Andrews, M., Pritchett, L., Woolcock, M. (2019). Building state capability: Evidence, analysis, action. Oxford University Press; Pritchett, L., Woolcock, M., Andrews, M. (2013). Looking like a state: Techniques of persistent failure in state capability for implementation. The Journal of Development Studies, 49(1), pp. 1-18. [18] Ibid. [19] Ibid. [20] For detailed discussion of IM see: Andrews, M., Pritchett, L., Woolcock, M. (2019). Building state capability: Evidence, analysis, action. Oxford University Press; Pritchett, L., Woolcock, M., Andrews, M. (2013). Looking like a state: Techniques of persistent failure in state capability for implementation. The Journal of Development Studies, 49(1), pp. 1-18. [21] DiMaggio, P. J., Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), pp. 147-160; Powell, W. W., DiMaggio, P. J. (Eds.). (1991). The new institutionalism in organizational analysis. University of Chicago Press. [22] DiMaggio, P. J., Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), pp. 147-160. [23] Andrews, M., Pritchett, L., Woolcock, M. (2019). Building state capability: Evidence, analysis, action. Oxford University Press. [24] Ibid., pp. 32-33. [25] Narzetti, D. A., Marques, R. C. (2021). Isomorphic mimicry and the effectiveness of water-sector reforms in Brazil. Utilities Policy, p. 70. [26] Bano, M. (2022). International push for SBMCs and the problem of isomorphic mimicry: Evidence from Nigeria. RISE Working Paper Series (22/102). Foreign, Commonwealth & Development Office. [27] Rubin, O., Munkholm, L. (2022). Isomorphic dynamics in national action plans on antimicrobial resistance. Public Administration and Development, 42(2), pp. 142-153. [28] Janenova, S., Knox, C. (2017). Civil service reform in Kazakhstan: Trajectory to the 30 most developed countries? International Review of Administrative Sciences, 85(3). [29] Janenova, S. (2019). Public administration academies in Central Asia: “Government puppets” or independent seats of learning? Teaching Public Administration, 38(2). [30] Knox, C., Janenova, S. (2019). The e-government paradox in post-Soviet countries. International Journal of Public Sector Management, 32(6), pp. 600-615. [31] O’Connor, K., Janenova, S., Knox, C. (2019). Open government in authoritarian regimes. International Review of Public Policy, 1(1), pp. 65-83. [32] Kurmanov, B., Knox, C. (2022). Open government and citizen empowerment in authoritarian states. Journal of Eurasian Studies, 13(2), pp. 156-171. [33] Bischof, L. (2018). Effects of the Bologna Process on quality assurance regimes in the post-Soviet space: Isomorphism and path dependencies in Moldova, Russia, and Kazakhstan. In European Higher Education Area: The impact of past and future policies. Springer, pp. 77-93. [34] Marat, E. (2018). Mimicking “broken windows” policing in post-Soviet cities: Expanding social control in uncertain times. Policing and Society, 29(9), pp. 1005-1021. [35] For detailed discussion see: Suny, R. (1994). The making of the Georgian nation (2nd ed.). Indiana University Press; Jones, S. (2023). Georgia: A political history since independence. I. B. Tauris; Shvelidze, D. (2021). Political confrontations and the overthrow of the national government in Georgia (1987–1992). Artanuji Publishing. [36] For detailed discussion see: Christophe, B. (2001). Transformation als Inszenierung – Zur institutionellen und kulturellen Einbettung von Korruption in Georgien. In Höhmann, H.-H. (Ed.). Kultur als Bestimmungsfaktor der Transformation im Osten Europas. Bremen-Temmen, pp. 157-175; Christophe, B. (2005, September 23-24). From hybrid regime to hybrid capitalism? The political economy of Georgia under Eduard Shevardnadze. Conference presentation, University of Paisley; Christophe, B. (2007). Georgia: Capitalism as organized chaos. In Bruszt, L., Roland, G. (Eds.). Varieties of capitalism in post-communist countries. Palgrave Macmillan, pp. 183-200; European Commission. (2022). Evaluation of the EU’s cooperation with Georgia: Final report, Volume I - Main report; World Bank. (2012). Fighting corruption in public services: Chronicling Georgia’s reforms. World Bank. [37] Christophe called this process an “organized chaos” and compared the process of state transformation to staging. [38] For detailed discussion see: Furusawa, T. (2022). Shevardnadze’s paper tiger: A fragile ruling party and the Rose Revolution. Japanese Slavic and East European Studies, 42, pp. 17-34; Chiaberashvili, Z., Tevzadze, G. (2005). Power elites in Georgia: Old and new. In Fluri, P. H., Cole, E. (Eds.). From revolution to reform: Georgia’s struggle with democratic institution building and security sector reform. Bureau for Security Policy at the Austrian Ministry of Defense & Geneva Centre for the Democratic Control of Armed Forces, pp. 187-207; De Waal, T. (2019). The Caucasus: An introduction (2nd ed.). Oxford University Press. [39] Engvall, J. (2012). Against the grain: How Georgia fought corruption and what it means. Silk Road Paper. Central Asia-Caucasus Institute & Silk Road Studies Program. [40] For detailed discussion see: Rekhviashvili, L. (2013). Development and the role of the state: Visions of post-revolutionary Georgian government. Caucasus Social Science Review, 1(1), pp. 1-20; Dobbins, M. (2014). The post-Rose Revolution reforms as a case of misguided policy transfer and accidental democratisation? Europe-Asia Studies, 66(5), pp. 759-774; Berglund, C. (2014). Georgia between dominant-power politics, feckless pluralism, and democracy. Demokratizatsiya: The Journal of Post-Soviet Democratization, 22(3), pp. 445–470; Khishtovani, G. (2016). Transformation von Governance-Strukturen in Georgien, 2003–2012. Verlag Dr. Kovac; Timm, C. (2013). Economic regulation and state interventions: Georgia’s move from neoliberalism to state-managed capitalism. PFH Forschungspapiere, 2013/03. [41] For detailed discussion see: Broers, L. (2013). Recognising politics in unrecognised states: 20 years of enquiry into the de facto states of the South Caucasus. Caucasus Survey, 1(1), pp. 59-74; Fairbanks, C. H., Jr. (2004). Georgia’s Rose Revolution. Journal of Democracy, 15(2), pp. 110-124; Dobbins, M. (2014). The post-Rose Revolution reforms as a case of misguided policy transfer and accidental democratisation? Europe-Asia Studies, 66(5), pp. 759-774. [42] For detailed discussion see: Kakachia, K., Lebanidze, B., Larsen, J., Grigalashvili, M. (2017). The first 100 days of the Georgian Dream government: A reality check. GIP Policy Report; O’Connor, K., Janenova, S., Knox, C. (2019). Open government in authoritarian regimes. International Review of Public Policy, 1(1), pp. 65-83; Kukava, K. (2022). Democratisation and political transformation in Georgia. In Leontiev, L., Amarasinghe, P. (Eds.). State-building, rule of law, good governance and human rights in post-Soviet space: Thirty years looking back. Routledge; Berglund, C. (2014). Georgia between dominant-power politics, feckless pluralism, and democracy. Demokratizatsiya: The Journal of Post-Soviet Democratization, 22(3), pp. 445-470. [43] Council of the European Union. (2014). Joint press release following the first Association Council meeting between the European Union and Georgia [Press release]; European Commission. (2014). Action document for support to EU-Georgia DCFTA and SMEs. [44] European Commission. (2015). Action document for support to public administration reform in Georgia (PAR); European Commission. (2017). Association agenda between the European Union and Georgia: 2017-2020. [45] World Bank. (2025). The World Bank in Georgia, 2014-2023: Country program evaluation. World Bank. [46] World Bank. (2023). The World Bank in Georgia, 2014-2023: Country program evaluation, approach paper. World Bank. [47] Devdariani, J. (2025, March). As USAID dies, many of Georgia’s “vibrant” CSOs face extinction. GEOpolitics: Journal of Political Commentary in the Caucasus; ForeignAssistance.gov: <www.foreignassistance.gov/cd/georgia/2023/obligations/1>. [48] World Bank. (2025). The World Bank in Georgia, 2014-2023: Country program evaluation. World Bank. [49] USAID - Governing for Growth (G4G) in Georgia. (2015). Recommendations on RIA national framework of Georgia. [50] Ibid. [51] ISET Policy Institute. (2023). RIA institutionalization reform assessment report. [52] ISET Policy Institute. (2023). RIA institutionalization reform assessment report. [53] Ibid. [54] Ibid. [55] ISET Policy Institute. (2023). RIA institutionalization reform assessment report. [56] Ibid. [57] For details see: Radio Free Europe/Radio Liberty. (2024, July 9). EU halts Georgia’s accession to the bloc, freezes financial aid over much-criticized law; Politico. (2024, November 30). US suspends strategic partnership with Georgia after EU membership talks halted. Politico. [58] ISET Policy Institute. (2023). RIA institutionalization reform assessment report.
Islamic Banking and Economic Growth: A Bibliometric Analysis of Research Trends (2007–2024)
This article aims to provide an in-depth analysis of the global scientific output on the relationship between Islamic banking and economic growth. Adopting a bibliometric approach, the study covers the period from 2007 to 2024 using data retrieved from the Scopus database, a leading source for tracking academic production. The analysis was conducted with VoSviewer software, which enabled the identification of key research themes, influential authors, countries, institutions, and journals shaping the literature in this area. The results reveal that Malaysia stands out as the most productive country, followed by other Asian and Middle Eastern economies, reflecting the regional importance of Islamic finance. The findings further highlight an evolution in research focus: while early studies were mainly concerned with the resilience of Islamic banking during the global financial crisis, more recent contributions emphasize emerging issues such as financial inclusion, governance, and sustainability. Overall, the study demonstrates the diversification of research directions and the growing academic interest in Islamic finance, underscoring its potential contribution to inclusive and sustainable economic development. Keywords: Islamic finance, Islamic banks, economic growth, bibliometric analysis, VoSviewer, Scopus. Introduction Economic growth is a fundamental metric for assessing the overall performance of national economies. It’s intrinsically linked to aggregate productivity, efficient resource allocation, and the achievement of macroeconomic balances in employment, investment, and financial stability. Within this context, the financial sector is seen as a key engine of growth due to its role in financial intermediation, reducing transaction costs, mitigating information asymmetries, and ensuring the efficient allocation of capital. The banking system holds particular importance within the financial structure, providing mechanisms to mobilize financial resources and channel them toward productive projects. According to finance-led growth literature, a sound banking structure promotes capital accumulation, stimulates savings, and fosters technological innovation, thereby contributing to higher potential growth rates. However, the 2008 global mortgage crisis highlighted the fragility of the conventional financial system, which is based on traditional lending mechanisms. The uncontrolled expansion of interest-based credit led to a loss of confidence in conventional banking systems, paving the way for alternative financing models based on risk-sharing and a link to the real economy. Within this framework, Islamic finance emerged as a promising alternative, characterized by financing mechanisms based on participation (Musharakah), profit-and-loss sharing (Mudarabah), and cost-plus-profit sales (Murabahah), which makes it more conducive to achieving economic justice and financial stability. The Islamic finance industry has witnessed significant expansion over the last two decades, driven by high annual growth rates and the emergence of leading Islamic banking models. Data from the Islamic Financial Services Board (IFSB) indicates that the assets of Islamic banks reached $2.1 trillion in 2024, distributed among more than 529 financial institutions, with a clear dominance of Murabahah-based financing. The recent decades have seen a notable increase in the number of studies exploring the relationship between Islamic banks and economic growth, attempting to test the effectiveness of these tools in achieving sustainable development. However, this growing research momentum highlights the need for bibliometric studies capable of providing a comprehensive overview of the evolution of knowledge in this field and identifying key trends and research schools, as well as mapping knowledge gaps that still require deeper exploration. From this perspective, this study aims to conduct a bibliometric analysis of scientific research published in the Scopus database during the period (2007–2024) using the VoSviewer software. This study represents a systematic attempt to reconstruct the knowledge map of this research field and provide a solid foundation for researchers and policymakers to guide financial policies toward more equitable, efficient, and sustainable models. Despite the clear expansion of studies related to Islamic banking, the question remains about the extent of this type of finance’s impact on economic growth, especially given the variance in applications and practices across Islamic countries. The diversity in approaches and methodologies, and the disparity in results, necessitate a comprehensive bibliometric analysis to understand the nature and trends of this scientific field. Accordingly, the main research question is formulated as follows: To what extent has scientific output related to Islamic banking and its relationship to economic growth evolved during the period (2007–2024), and what are its main characteristics and trends? Objectives: To provide a quantitative analytical overview of the growth of scientific literature on Islamic banking and economic growth; To identify the key players (researchers, countries, institutions) in this research area; To explore the main keywords that reflect the interests of scientific research in this field; To evaluate the most influential articles based on the number of citations. Significance of the Study The importance of this work lies in its treatment of a timely and strategic topic in finance and development. Employing a bibliometric methodology offers a comprehensive picture of research trends, allowing researchers and financial and economic policymakers to understand the accumulated knowledge and direct their efforts toward new research avenues with a tangible impact on the design of sustainable development models. Methodology This study adopts a bibliometric analysis methodology, which is a quantitative approach used to analyze bibliographic data extracted from scientific databases. Its purpose is to evaluate the dynamics of scientific publishing and identify active knowledge networks in a specific subject. The international Scopus database was chosen for its wide coverage and high accuracy in indexing peer-reviewed articles. The VoSviewer software was used to build knowledge networks and analyze keywords, authors, countries, institutions, and citation networks. Theoretical Framework 1.1. The evolution of Islamic finance Islamic finance has been proposed as a key solution to conventional financing, especially in Muslim-majority economies, and has demonstrated remarkable growth rates globally.[1] The total assets of the Islamic finance industry were estimated at $3.88 trillion in 2024, representing a 14.9% increase.[2] This financial system is built upon fundamental principles, including profit-and-loss sharing, directing investments towards ethical activities, and asset-backed financing, which requires a deep understanding of operational mechanisms compliant with Islamic Sharia law.[3] The Islamic finance sector consists of four key components: Islamic banks, Sukuk (Islamic bonds), investment funds, and Takaful (Islamic insurance). These financial instruments are distinguished by their direct link to real economic activity, with most Islamic financial institutions concentrated in Gulf Cooperation Council (GCC) countries, Malaysia, Indonesia, and Pakistan, in addition to their gradual expansion into non-Muslim countries like the United Kingdom and Luxembourg.[11] 1.2. The relationship between Islamic finance and economic growth The first attempt to document the relationship between finance and economic growth dates to Schumpeter (1911), who highlighted the role of financial institutions in using intermediation to mobilize and allocate funds and record transactions essential for economic development.[12] Since then, economic literature has extensively debated this relationship, whether within the context of conventional or Islamic finance. Studies on Islamic finance have approached the subject from two perspectives:[13] Macro-level: Analyzing the impact of the entire sector on economic growth; Micro-level: Examining specific instruments like Murabahah or Mudarabah and their effect on macroeconomic variables. Empirical results have identified three patterns of relationships between the two variables: A bidirectional causal relationship; A “supply-leading” relationship, where finance drives economic growth; A “demand-following” relationship, where economic growth stimulates finance. Despite the growing body of literature on Islamic finance and its effect on economic growth, this field still suffers from a lack of coherence, topical integration, and systematic evaluation. Academic contributions remain scattered across various scientific journals, geographic regions, and research traditions, with limited efforts to synthesize findings or trace the chronological evolution of key topics. This highlights the importance of bibliometric analysis as a quantitative methodology capable of providing a holistic view of the research trajectory in this area. It can reveal publishing patterns, identify active knowledge networks, and track recent research trends, thereby enabling researchers and interested parties to form a clearer picture of the future of studies related to Islamic finance and economic growth.[14] Methodology Data was systematically retrieved from the Scopus database, a comprehensive and high-quality database for abstracts and citations in the social sciences.[15],[16] The data set creation process involved two main steps: Initial Search: A search was conducted on April 1, 2024, using the keywords “banking AND finance AND economic AND growth” on the Scopus platform. This initial query yielded 128 documents published between 1990 and 2024; Exclusion/Refinement: To enhance the study’s focus and analytical precision, the initial set of documents underwent a strict filtering process. This involved limiting the scope to journals in economics, business, and social sciences, and to publications in English only. Furthermore, the search was restricted to research articles, excluding books, conference proceedings, and other non-journal-related document types. As a result of this refinement, the final data set comprised 83 documents, with the publication period narrowed to 2007–2024. It is worth noting that this adjusted timeframe remarkably coincides with the onset of the subprime mortgage crisis. Results and discussion The curve demonstrates a growing research interest in the topic of Islamic finance and economic growth over the years. The evolution of research can be divided into the following phases: Inception (2007–2009): Research activity was very limited, coinciding with the beginning of the subprime mortgage crisis. This period marks the initial interest in Islamic finance as an alternative solution to conventional global financing; Gradual Growth (2010–2019): A slow and steady increase in the number of articles with minor fluctuations; Major Leap and Peak (2020–2023): This period saw a significant rise in publications, peaking in 2023 with 15 articles, indicating a substantial increase in academic interest in this field; 2024: Only one article is shown up to April, which does not reflect a decline but rather represents incomplete data for the current year. The curve shows a general upward trend in the number of publications, which suggests a growing academic interest in this vital field that links Islamic finance and economic growth. Upon examination, it’s clear that a few years after the 2008 crisis, there was a gradual increase starting from 2010 and beyond. This rise aligns with the hypothesis that the financial crisis prompted researchers to explore alternative financial models, with Islamic finance being one of them. Figure 3 shows the countries with the most publications during the study period, revealing centers of power and a significant expansion of intellectual influence in the field of Islamic finance. This reflects the economic and intellectual leadership of this sector. Malaysia and Indonesia are considered global knowledge hubs for Islamic finance. Their dominance (Malaysia with 8 articles, Indonesia with 10) reflects long-term strategies in building a strong financial and legislative infrastructure, along with intensive investment in specialized human capital. This superiority confirms that a conducive economic environment is key to intellectual output. Emerging countries like Gulf states (UAE, Saudi Arabia), Pakistan, and Turkey have made moderate contributions, reflecting an economic evolution that views Islamic finance not just as a religious commitment but as a driver for economic development and financial diversification. The presence of Western countries such as the United Kingdom, the United States, and France, albeit with a small contribution, reflects the transformation of Islamic finance from a local phenomenon into a global economic player. This Western interest is not necessarily religious but is driven by research that explores new market opportunities, giving the topic a global dimension and greater scientific acceptance. The institutions dominating research on Islamic finance and economic growth can be categorized into two levels: Geographical Level: Malaysia and Indonesia lead the research landscape, a result of legislative and institutional support for such research. They are followed by an increasing presence from Gulf states (UAE, Saudi Arabia), Pakistan, and Turkey. Notably, the presence of Western countries (France, the United States, and the United Kingdom) confirms the global nature of Islamic finance and its attractiveness as an alternative economic model sought for financial stability, particularly after the 2008 crisis; Institutional Level: Leading global Islamic universities emerge as key research centers, followed by a group of Malaysian universities that reflect Malaysia’s commitment to becoming a knowledge hub in Islamic finance. The appearance of Hamad Bin Khalifa University and Al Ain University also indicates a growth in academic research investments in the region to support the Islamic financial sector. The keyword map provides a strategic overview of the most common concepts in academic research on Islamic finance and economic growth. The map reveals clusters of concepts that can be divided into five main groups, highlighting the methodological evolution and temporal trends in this field: Core Concepts: “economic growth”, “Islamic banks”, and “banking”. Economic growth emerges as the largest central node, confirming its status as the core concept for most research. Other key nodes, particularly for Islamic banks, indicate their central role in the relationship with economic growth; Methodological Dimensions: Solidifying the Econometric Nature: The light green cluster is the most prominent in giving this subject its rigorous economic and scientific character. The presence of terms like “ARDL”, “ECM”, “VECM”, and “ARIMAX” clearly indicates a widespread adoption of advanced econometric models to study the relationship between Islamic finance and economic growth. These models are more than just statistical tools; they are analytical frameworks that: Allow Causal and Dynamic Analysis: Instead of mere correlation, they enable researchers to explore whether Islamic finance leads to economic growth, or vice versa, and whether there are long-term and short-term relationships; Address Complex Economic Issues: Such as cointegration and the reciprocal dependence between macroeconomic variables; Add Scientific Credibility: The use of these models enhances the strength and generalizability of the results, elevating research from a descriptive level to an analytical and predictive one. The link between these methodologies and countries like Malaysia and Indonesia confirms that these nations not only contribute to quantitative knowledge production but also to the development and application of modern econometric methods to understand the dynamics of Islamic finance within their economic contexts. Core Dimensions of Islamic Finance: Stability and Risk-Sharing: Concepts such as “risk sharing” and “financial stability” emerge as fundamental research components. These concepts are at the heart of the economic principles of Islamic finance. Their connection to economic growth confirms that research explores how the inherent features of Islamic finance can provide a more resilient and sustainable model for economic growth, which has gained particular importance after the global financial crisis. Recent Trends and Challenges: Technology and Ethics: Concepts like “fintech” indicate a growing interest in how technological innovations can be integrated into Islamic financial services to enhance efficiency and financial inclusion. Conversely, terms such as “ethics” and “Islam” highlight the normative and value-based dimensions that continue to form the foundation of this sector. The concept of “corruption” also appears, possibly as a factor whose impact on the effectiveness of Islamic finance and growth is being studied. The network map provides a comprehensive picture of a multifaceted research field where “economic growth” is intertwined with “Islamic banks” through sophisticated econometric models. This methodological evolution reflects a concerted effort to lend scientific and quantitative credibility to studies on Islamic finance, moving beyond descriptive analyses to a deep understanding of causal relationships. This integration of robust economic methodologies with Sharia-compliant foundations, in addition to exploring ethical and innovative dimensions, confirms the increasing academic maturity of this field and its role in shaping the future of global financial systems. This map illustrates the chronological sequence of keywords, colored according to the average year of publication (from blue/2014 to red/2024), providing a comprehensive view of how research interests have evolved and expanded over time. It can be divided into the following phases: Phase of Theoretical Foundations and Basic Concepts (in purple and blue): The early period focused on fundamental concepts of Islamic finance and the laws governing it (Islam, law, ethics, finance, banking); Linking Islamic Finance to Economic Growth using Economic Theories and Quantitative Models (2017–2019): In this phase, there was an intensive emergence of concepts related to economic development and applied models. This makes research more objective and measurable, giving it a more academic and scientific character and a wider intellectual resonance, especially in Western countries, beyond the religious aspect; Phase of Innovation and Sustainability (2020–2024): This phase coincided with the COVID-19 pandemic, which led to a reliance on technology and remote interactions. This introduced modern variables into academic research, such as fintech, which reflects the rapid digital transformation the world witnessed during the pandemic and the drive to enhance the efficiency and financial inclusion of Islamic financial institutions. The term “sustainable development” indicates an increased awareness of climate and the need for sustainable finance. The term “corruption” also highlights an interest in governance standards to increase the effectiveness of Islamic finance. “Risk sharing” and “financial stability” reflect a search for more resilient financial models to face recurring economic and even health-related shocks that could later turn into a financial and economic crisis. The map highlights the most active and influential areas in terms of scientific output and citations. Malaysia appears as the most active and “hottest” point on the map, shown in bright yellow. This indicates Malaysia’s status as a central hub in the research field represented by this network, meaning it has the highest number of publications, is the most cited, and has the highest density of collaborations in this context. Indonesia follows, confirming it is another key center of activity and influence. The United Arab Emirates shows a very high density, confirming its role as an important research center and an effective bridge between different country clusters. Pakistan also shows high density, reinforcing its role as a key player and an important node in the network. Medium Density Areas (Green): The United Kingdom and the United States show good density, indicating strong and sustained contributions to the field, even if they are not as “hot” as the Asian hubs. Saudi Arabia also shows good density, confirming its role as a key partner and research center in the region. Lower Density Areas (Dark Green/Blue): Turkey shows a slightly lower density compared to other countries in the green cluster (Malaysia and Indonesia), but it is still part of an active area. This density map conclusively confirms that Malaysia and Indonesia are the two driving forces and focal points of research activity in this field. It also highlights the importance of the United Arab Emirates and Pakistan as high-density centers for collaboration and production. This map provides strong visual confirmation of the previous analyses regarding the importance of these countries, especially Malaysia and Indonesia, in contributing the most cited articles in the relevant discipline. Conclusion This bibliometric study offers deep insights into the dynamic and intellectual evolution in the field of Islamic finance. By analyzing publication patterns, collaboration networks, and geographical activity centers, we were able to draw a comprehensive map of research development. The results show that the field of Islamic finance has undergone a notable shift in its research agenda, moving from focusing on responses to financial crises to studying its impact on economic growth, and eventually to integrating contemporary issues such as governance, sustainable development, and financial technology. This reflects an increasing maturity in understanding the role of Islamic finance as an active component of the global economic system. Furthermore, the study revealed the emergence of leading research centers, particularly in Malaysia and Indonesia, which are no longer merely markets but have become key intellectual hubs driving innovation and knowledge production. It also highlighted the role of intermediary countries like the United Arab Emirates and Pakistan in facilitating cross-border collaboration and knowledge exchange. In conclusion, identifying research gaps, such as the neglect of studying “Islamic windows”, not only provides evidence for the need for more specialized research but also opens new avenues for future scientific contributions. This study affirms the analytical value of the bibliometric approach in understanding scientific developments and providing a solid knowledge base for researchers and policymakers to direct research efforts toward issues with a greater impact on comprehensive and sustainable economic development. References: Ghorab, H., Others. (2023). The Impact of the Murabaha Formula on Economic Growth: A Standard Study on a Sample of Islamic-Financed Countries from 2013-2020. Journal of Economics and Sustainable Development, 6(2); Hanif, M., Zafar, K. (2020). Developments in Islamic finance literature: Evidence from specialized journals. Journal of King Abdulaziz University, 33(2). <doi:https://doi.org/10.4197/Islec.33-2.1>; IFSB. (2013, 2015, 2017, 2019, 2021, 2023, 2025). Islamic Financial Services Industry Stability Report; Kayani, U. N. et. al. (2023). Examining the Relationship between Economic Growth,Financial Development, and Carbon Emissions: A Review of the Literature and Scientometric Analysis. International Journal of Energy Economics and Policy, 13(02); Khamis, F., Isa, M., Yusuff, N. (2024). Perceived inclusion of Islamic finance: The effects of attitudes, experience, literacy, religiosity, and social influences. International Journal of Applied Economics, Finance and Accounting, 18(2). <doi: https://doi.org/10.33094/ijaefa.v18i2.1398>; Loso, J. (2025). Islamic Finance and Economic Growth: A Bibliometric Analysis of Scholarly Contributions. West Science Islamic Studies, 3(3). <doi:http://dx.doi.org/10.58812/wsiss.v3i03.2117>; Omar, A., Omer, M. (2022). Testing Effeciency of sudan s Islmic banks for funding socio-economics Development Using World rankings indices. Interational journal of Islamic Economics, 04(01); Siti, I. et. al. (2022). Unlocking the Power of Creative Thinking: A bibliometric analysis of the 21st Century. Journal of ASIAN Behavioural Studies (jABs), 7(22). Footnotes [1] Hanif, M., Zafar, K. (2020). Developments in Islamic finance literature: Evidence from specialized journals. Journal of King Abdulaziz University, 33(2), pp. 3-23. <doi:https://doi.org/10.4197/Islec.33-2.1>. [2] Ifsb. (2025). Islamic Financial Services Industry Stability Report 2025: Need for Coordinated Action to Deepen Markets and Sustain Growth Momentum. Available at: <https://www.ifsb.org/press-releases/islamic-financial-services-industry-stability-report-2025-need-for-coordinated-action-to-deepen-markets-and-sustain-growth-momentum/>. [3] Khamis, F., Isa, M., Yusuff, N. (2024). Perceived inclusion of Islamic finance: The effects of attitudes, experience, literacy, religiosity, and social influences. International Journal of Applied Economics, Finance and Accounting, 18(2), pp. 321-338. <doi: https://doi.org/10.33094/ijaefa.v18i2.1398>. [4] IFSB. (2013). Islamic Financial Services Industry Stability Report. [5] IFSB. (2015). Islamic Financial Services Industry Stability Report. [6] IFSB. (2017). Islamic Financial Services Industry Stability Report. [7] IFSB. (2019). Islamic Financial Services Industry Stability Report. [8] IFSB. (2021). Islamic Financial Services Industry Stability Report. [9] IFSB. (2023). Islamic Financial Services Industry Stability Report. [10] Ibid. [11] Loso, J. (2025). Islamic Finance and Economic Growth: A Bibliometric Analysis of Scholarly Contributions. West Science Islamic Studies, 3(3), pp. 240-249. <doi:http://dx.doi.org/10.58812/wsiss.v3i03.2117>. [12] Omar, A., Omer, M. (2022). Testing Effeciency of sudan s Islmic banks for funding socio-economics Development Using World rankings indices. Interational journal of Islamic Economics, 04(01), pp. 1-17. [13] Ghorab, H., Others. (2023). The Impact of the Murabaha Formula on Economic Growth: A Standard Study on a Sample of Islamic-Financed Countries from 2013-2020. Journal of Economics and Sustainable Development, 6(2), pp. 20-38. [14] Loso, J. (2025). Islamic Finance and Economic Growth: A Bibliometric Analysis of Scholarly Contributions. West Science Islamic Studies, 3(3), pp. 240-249. <doi:http://dx.doi.org/10.58812/wsiss.v3i03.2117>. [15] Kayani, U. N. et. al. (2023). Examining the Relationship between Economic Growth,Financial Development, and Carbon Emissions: A Review of the Literature and Scientometric Analysis. International Journal of Energy Economics and Policy, 13(02), pp. 489-499. [16] Siti, I. et. al. (2022). Unlocking the Power of Creative Thinking: A bibliometric analysis of the 21st Century. Journal of ASIAN Behavioural Studies (jABs), 7(22), pp. 55-70.
Oil Shocks, Renewable Energy, and Growth Regimes in Algeria: A Multiple-Threshold NARDL Analysis of CO₂ Emissions
This study employs the MT-NARDL model to examine the nonlinear relationship between economic growth, oil prices, renewable energy consumption, and CO₂ emissions in Algeria over 1980–2024. Allowing GDP per capita to switch across low, medium, and high regimes, the model captures asymmetric short- and long-run responses. The Environmental Kuznets Curve is rejected: no regime yields a significant long-run effect on emissions, evidencing the absence of an automatic decoupling threshold. Renewable energy is the only robust driver of permanent carbon reduction, cutting emissions by 0.155% for each additional 1% share, despite an initial “brown-build” uptick. Oil-price shocks exert merely transitory impacts, whereas medium-growth episodes re-ignite emissions after two years. Error-correction is rapid, yet hydrocarbon dependency persists. Aligning development with climate goals, therefore, requires a coherent policy package that couples accelerated clean-energy deployment, stringent efficiency standards, and economic diversification away from carbon-intensive sectors. By foregrounding regime-dependent asymmetries, the paper offers new empirical evidence for resource-rich economies. Keywords: Algeria, CO₂ emissions, MT-NARDL, growth regimes, renewable energy, oil shocks. Introduction The relationship between economic growth and environmental protection has received widespread attention in the economic and environmental literature, as countries seek to achieve a balance between the requirements of development, on the one hand, and the mitigation of environmental degradation, on the other.[1] Economic activities, particularly those related to fossil fuel consumption, are among the main sources of carbon dioxide (CO₂) emissions,[2] placing them at the core of discussions on environmental sustainability. Conversely, renewable energy is emerging as a strategic alternative that contributes to reducing emissions and fostering the transition toward a green economy.[3] At the same time, oil prices remain a key factor shaping the economic and energy trajectories of many countries.[4] In this context, Algeria is an important model for studying these interactions, due to its heavy reliance on oil and gas revenues as the primary source of GDP.[5] Therefore, per capita carbon dioxide emissions (CO₂ PER) are closely linked to per capita GDP (GDP PER) and global fluctuations in oil prices, reflecting the fragility of the economic structure in the face of external shocks.[6] Nevertheless, integrating renewable energy into the national energy mix is a fundamental step toward reducing the carbon footprint and promoting sustainable development.[7] At the theoretical level, the Classical studies assume a linear relationship between economic growth and environmental degradation.[8] However, empirical evidence reveals more complex dynamics characterized by asymmetry and dependence on different economic systems.[9] For example, rising per capita income may increase emissions at a certain stage of growth, while contributing to their reduction when higher levels are reached as a result of technological advancement and effective environmental policies, which is consistent with the Environmental Kuznets Curve (EKC) hypothesis.[10] In traditional studies, the NARDL model is often employed to analyze asymmetry in economic and environmental relationships by distinguishing between the effects of increases and decreases in the independent variables.[11] However, this approach remains limited as it restricts the analysis to only two regimes.[12] To address this limitation, the MT-NARDL model was developed, allowing GDP per capita to be divided into several regimes at different levels (low, medium, and high).[13] This provides a more accurate understanding of the complex dynamics of the relationship between economic growth and carbon dioxide emissions, while also accounting for the role of oil prices as an external factor and the consumption of renewable energy as a transitional tool towards sustainable development. Therefore, adopting this model is particularly appropriate for the Algerian case and contributes to filling a gap in the literature by offering a comprehensive short- and long-term analysis that links economic growth, energy price fluctuations, and the energy transition in explaining the dynamics of per capita carbon emissions. The remainder of this paper is organized as follows: Section 1 provides a comprehensive review of the existing literature, Section 2 describes the data and lays out the theoretical framework, Section 3 presents and analyzes the empirical findings, and Section 4 concludes with a summary and policy implications. Literature Review Recent studies have increasingly examined the nexus between economic growth, energy consumption, and CO₂ emissions using nonlinear and asymmetric models, especially in oil-dependent economies. This literature can be grouped into two main strands: (i) those testing the Environmental Kuznets Curve (EKC) hypothesis across different growth regimes, and (ii) those comparing the effects of renewable versus conventional energy on emissions, with attention to short- and long-run dynamics. Growth Regimes and the EKC Hypothesis: Several studies have explored whether the EKC hypothesis holds across low, medium, and high growth regimes. Found for South Africa that both energy consumption and income worsen environmental quality, with no EKC evidence.[14] Confirmed the EKC for Nigeria using nonlinear ARDL, showing that growth initially increases emissions but later reduces them.[15] Offered mixed EKC evidence across 25 OECD countries,[16] while rejected it for Korea, finding an N-shaped relationship instead.[17] Supported the EKC for India, noting that oil consumption and price shocks increase emissions, while FDI inflows validate the pollution haven hypothesis.[18] Renewable vs. Conventional Energy and Oil Price Shocks: The second strand compares energy sources and their asymmetric effects. Found that renewable energy had no significant impact on the ecological footprint in major oil exporters,[19] while showed that renewables initially slow growth but become beneficial in the long run.[20] Confirmed that renewable energy reduces the ecological footprint, whereas natural resource rents increase it.[21] validated the N-shaped EKC for some Asian countries, with renewables reducing emissions and nonrenewables increasing them.[22] found asymmetric effects in Canada: positive shocks in renewables reduce emissions, while negative growth shocks worsen environmental quality.[23] Showed that both positive and negative shocks in renewable energy reduce CO₂ emissions in Saudi Arabia.[24] found asymmetric cointegration in Pakistan, with no significant link between growth and emissions.[25] In a rare study on Algeria, found no EKC evidence: renewables reduce emissions, while growth increases them. Despite the wealth of previous studies analyzing the relationship between economic growth and emissions, most remain limited by traditional single-threshold NARDL models, which limit their ability to capture nonlinear changes in emissions across multiple growth stages. Most also overlook the impact of recurrent oil shocks on emissions in energy-exporting economies, such as Algeria. Hence, the importance of this study, which fills this gap by applying the multi-threshold MT-NARDL model to analyze the nonlinear and bidirectional causality between growth, renewables, and emissions.[26] highlighted short-run links between renewables, trade, and oil prices in Tunisia.[27] asymmetric interactions between economic growth, oil prices, and renewable energy in explaining CO₂ emissions. This study enhances theoretical and applied understanding of climate transition policies in similar economies. Data and Theoretical Framework 2.1. Data sources The definitions and measurement units of all variables are presented in Table 1 below. 2.2. The theoretical framework 2.2.1. MT-NARDL Model Given the variation in economic policy objectives across the low, medium, and high transition stages, this study employs the MT-NARDL (Multiple Threshold Nonlinear Autoregressive Distributed Lag) model developed by Pal and Mitra (2015, 2016).[28] This model overcomes the limitations of the traditional NARDL framework, which is restricted to two cases: an increase and a decrease, by allowing the variable of interest (GDP per capita) to be partitioned into several regimes at different levels (low, medium, and high). The MT-NARDL model captures asymmetry by introducing multiple threshold values, enabling the relationship between variables to change according to these thresholds. This feature allows for the analysis of the dynamic relationship between economic growth and carbon dioxide emissions in both the short and long run, while also considering the role of oil prices as an external factor and renewable energy consumption as part of the transition toward sustainability. To apply the MT-NARDL model in examining the relationship between per capita carbon dioxide emissions (CO₂PER) and economic variables, namely per capita gross domestic product (GDPPER), oil prices (OILPRICE), and renewable energy consumption (REN), we proceed as follows:[29] Stage 1: Compute the per capita GDP growth rate by taking the first difference of its logarithm: Stage 2: We determine the threshold values using quantiles: : represents the lower quantile (e.g., 25%); : represents the upper quantile (e.g., 75%). Stage 3: We construct three regimes (Regimes) for GDPP: Regime 1 : Low GDP per capita growth (less than Q₁​): Regime 2 : Medium GDP per capita growth (between Q₁ and ​): Regime 3 : High GDP per capita growth (greater than ​): Stage 4: Step 4 involves embedding the GDP regimes within the MT-NARDL specification as explanatory variables. Where X represents the explanatory variables, namely (oil, ren), and is Error term. Stage 5: In this stage, dedicated to model specification and estimation, we incorporate the three GDP regimes into the MT-NARDL framework, where the dependent variable is per capita CO₂ emissions (CO₂per). The independent variables consist of oil prices (OILPRICE), renewable energy consumption (REN), along with the three GDP regimes. The model is subsequently estimated using EViews 13 under the general MT-NARDL specification, enabling the identification of the long-run relationship as well as the short-run dynamics through the Error Correction Model (ECM). The general form of the MT-NARDL specification can be expressed as: 2.2.2. The three GDP regimes in Algeria Figure 1 represents three different GDP regimes, which in turn reflect the varying stages of economic activity and their impact on environmental variables. The first regime (GDPREG1, low growth, blue line) starts near zero in the early 1980s, then declines to around 2 in the mid-1990s and below 6 by 2020. These negative values reflect periods of economic slowdown, where industrial contraction weakens energy demand and reduces emissions. However, this decline is not driven by environmental policies or efficiency gains, but by financial crises and oil-price volatility, especially after 2000. Thus, emission reductions come at the expense of growth, without achieving sustainable transformation. The second regime (GDPREG2, average growth, orange line) begins close to zero in the early 1980s, rises to about +3 in the late 1990s, and exceeds +5 by 2020. This steady increase is accompanied by rising environmental pressures due to industrial expansion, higher transport activity, and accelerating urbanization. Energy policies during this phase fail to promote efficiency or a shift to cleaner sources, so each additional unit of output directly increases emissions. The third regime (GDPREG3, high growth, green line) starts near +1 in the late 1980s, reaches +4 by 2005, and stabilizes around +4.5 by 2020. The post-2010 plateau suggests that high growth is beginning to generate mitigating effects, possibly through improved efficiency, clean technology adoption, or stricter environmental policies. Nevertheless, since values remain positive, Algeria has not yet fully decoupled growth from emissions. Capitalizing on this trend requires accelerating renewable energy deployment, improving consumption efficiency, and enforcing stricter environmental regulations. Overall, stagnation (GDPREG1) reduces emissions unsustainably, moderate growth (GDPREG2) intensifies environmental pressures, and high growth (GDPREG3) shows early signs of mitigation, but still needs stronger institutional and technological support to ensure a green and sustainable growth path. Empirical Results and Discussion Before estimating the model, all variables were transformed into their natural logarithms, except for the renewable energy (REN) variable, which is expressed as a percentage. This transformation was applied to reduce variance and to facilitate the interpretation of elasticity coefficients. 3.1. Economic and environmental trends in Algeria during the period 1980–2024 Historically, Algeria’s economic growth has been closely tied to oil revenues, with per capita GDP rising sharply during the mid-1980s and again following the oil boom after 2000. However, this growth came at an environmental cost, as per capita carbon dioxide emissions doubled from two to four tons, highlighting the absence of decoupling between economic expansion and environmental impact. The economy remains highly vulnerable to oil price fluctuations, which directly affect financial stability. At the same time, renewable energy consumption remained below 1% until a modest increase after 2019, reflecting only tentative steps toward diversifying energy sources and reducing carbon dependence. 3.2. Descriptive statistics We note from the results in Table 2 that, over the 45-year sample, per capita CO₂ emissions averaged 3.34 tons, with moderate dispersion and an approximately normal distribution. Per capita GDP averaged about US$3,305 but displayed wide variation (±US$1,496), peaking at US$6,095, with a slight right skew. Oil prices averaged US$45.6 per barrel, ranging from US$14.4 to US$99.7, confirming substantial market volatility; their distribution is close to normal. The share of renewable energy was very low, averaging only 0.31% of total final energy use and never exceeding 1.3%. This variable is highly right-skewed and clearly non-normal. 3.3. Testing the Optimal Lag Lengths for the MT-NARDL Model Based on the optimal lag model selection criteria using the Akaike Information Criterion (AIC), the MT-NARDL (1,1,3,0,1,2) model was selected as the most appropriate to represent the relationship between the variables under study. This specification indicates that the optimal lag order is: one lag for LCO2, one lag for GDPREG1, three lags for GDPREG2, no lag for GDPREG3, one lag for REN, and two lags for LOIL. The adoption of this model is attributed to its achievement of the lowest AIC value (−2.562876), making it the most statistically efficient compared to the other evaluated models. 3.4. Time Series Stationarity Test Prior to undertaking time series analysis, it is crucial to assess the stationarity of the data. This requires testing whether the series exhibits a unit root. Accordingly, the Augmented Dickey-Fuller (ADF) test and the Phillips-Perron (PP) test, which are among the most widely applied conventional unit root tests, are employed in this study. The corresponding results are presented in Tables 3-4 below. According to the results of the unit root tests (ADF and PP), all variables were found to be non-stationary at the I(0) level. To achieve stationarity, first differencing was applied. The unit root analysis confirmed that all variables became stationary at the I(1) level, as reported in Tables 3 and 4. These findings enabled us to proceed with the MT-NARDL model. Furthermore, the optimal lag length for the vector autoregressive (VAR) model was determined to be one, as consistently indicated by the majority of lag selection criteria, including FPE, AIC, SC, and HQ. Although the LR test suggested lag four, the convergence of the other criteria supports the choice of one lag as the most appropriate specification for the model under study. 3.5. Bounds of cointegration test To examine the presence of a long-run equilibrium relationship among the variables, the bounds testing procedure was employed. This involved calculating the F-statistic and comparing it against the critical values reported by Pesaran et al. (2001). The corresponding results are presented in Table 6. The Pesaran-Shin-Smith bounds test (F = 5.18) rejects the null of no cointegration at the 1% level, confirming a stable long-run relationship among CO₂ emissions, growth regimes, renewable energy, and oil prices and justifying the use of the MT-NARDL framework. 3.6. MT- NARDL long-run form We observe from the long-run MT-NARDL equilibrium equation (1984–2024) that CO₂ emissions move consistently with the explanatory variables. The error correction coefficient (-0.522) indicates that 52% of any shock is corrected within one year, confirming a relatively rapid return to equilibrium. Renewable energy (REN) emerges as the only significant long-run driver: a permanent 1% increase in its share reduces emissions by 0.155%, underscoring the central role of clean energy investment in mitigation policy. By contrast, none of the three growth regimes exerts a statistically significant long-run effect: the low-growth regime (GDPREG1) shows a positive but insignificant coefficient (0.386), the medium-growth regime (GDPREG2) a negative but insignificant coefficient (-1.596), and the high-growth regime (GDPREG3) a negative but insignificant coefficient (-0.276). This outcome suggests that Algeria has not yet attained the income threshold or structural transformation needed for automatic decoupling. Real oil prices (LOIL) are neutral in the long run (0.049, not significant), reflecting continued dependence on hydrocarbons without sustainable demand-side adjustments. Overall, sustained emissions reductions will require expanding renewable energy, accelerating the shift away from energy-intensive industries, and redesigning growth strategies to move the economy beyond the critical “tipping point” that current GDP regimes have failed to deliver. 3.7. MT_NARDL short-run form The short-run results of the MT-NARDL model, shown in Table 8, reveal that 52% of any departure from the long-run CO₂ path is corrected within one year (COINTEQ –0.522***), underscoring rapid system resilience. Low-growth (GDPREG1) and current-period medium-growth (GDPREG2) impulses leave emissions unchanged, but the medium-growth impulse delivered two years earlier (GDPREG2(–2)) becomes strongly positive (+0.956**), evidencing a delayed upswing in energy-intensive activity. Renewable-energy deployment (D(REN)) exerts an immediate, positive footprint (+0.215**) as construction and installation phases dominate, an effect that is later reversed by the long-run contraction shown in the equilibrium equation. Oil-price shocks carry no contemporaneous weight (D(LOIL) 0.033), yet a price rise lagged one period (D(LOIL (–1)) significantly dampens emissions (–0.138**) through curtailed fossil-fuel use or brief fuel-switching. These inter-temporal and regime-specific channels highlight the need for flexible policy instruments that anticipate lagged responses, exploit temporary price incentives, and accelerate the point at which renewable infrastructure costs give way to sustained carbon savings. 3.8. Diagnostic Tests We note from the results in Table 9 for the diagnostic tests applied to the MT-NARDL model, including the ARCH test for conditional variance heteroskedasticity, the Breusch-Pagan-Godfrey test for heteroscedasticity, the Breusch-Godfrey test for detecting serial correlation, and the Jarque-Bera test for normality, that the findings confirm the model satisfies the required statistical assumptions. Its validity was established at the 5% significance level across all tests, ensuring the robustness and reliability of the estimated results. We note from Figures 3 and 4 that the CUSUM and CUSUMSQ tests are used to assess the stability of the model. In the case of Algeria, both statistics remain within the 5% significance bounds, indicating no structural breaks or deviations during the study period. 3.9. The cumulative dynamic multiplier Figure 5 shows that the multiplier of GDPREG1 (low-growth regime) on per-capita CO₂ rises to about 0.7 after five–six years and then stabilises near 0.5. This “recession footprint” reflects the growing carbon-intensity of surviving plants: outdated kilns, furnaces, and vehicles remain in use, maintenance is deferred, and no cleaner capital is adopted, so emissions per unit of GDP edge up even while aggregate output is flat. Figure 6 displays the multiplier for GDPREG2 (medium-growth regime); it falls steeply to –2.8 over nine–ten years. Sustained, but not spectacular, income growth finances building retrofits, more efficient industrial boilers, and early solar water-heaters, while tighter standards and subsidy schemes begin to bite. The result is a sizeable cumulative cut in CO₂ despite continued economic expansion. Figure 7 plots the multiplier for GDPREG3 (high-growth regime); it oscillates between –0.5 and +0.45 before settling at –0.3. At this stage, the economy can fund green R&D and grid-scale renewables, yet higher disposable income also boosts transport, air-conditioning, and appliance ownership. These offsetting forces yield a near-zero net effect, underscoring that rapid growth alone is insufficient; complementary carbon-pricing or trading instruments are needed to tip the balance decisively downward. Figure 8 illustrates the multiplier of renewable-energy consumption. It climbs to +0.34 after six–seven years and then plateaus at +0.3, revealing a short- to medium-term “brown-build” phase: emissions embodied in panel, turbine, and transmission-line fabrication outweigh the carbon savings until the new capacity fully displaces fossil generation. Policies that shorten this pay-back period recycled materials, domestic manufacturing standards, and streamlined permitting, are therefore essential. Figure 9 traces the multiplier of oil-price shocks. An initial spike to +0.12 is quickly reversed; the curve ends at –0.04. The temporary uptick reflects a drawdown of cheaper, dirtier backup fuels, while the subsequent decline signals conservation and modal shifts once high prices persist. The overall effect is small, confirming that price cycles must be reinforced by durable clean energy incentives if they are to deliver structural decarbonisation. 3.10. Discussion of Findings and Contribution The results showed that the relationship between economic growth and carbon dioxide emissions in Algeria goes beyond traditional linear models or the Environmental Kuznets Curve (EKC). It was found to be asymmetric, multi-phased, and dependent on the level of development and energy consumption patterns. Long-run estimates show none of the three growth regimes (low, medium, high) exerts a significant effect, confirming that structural dependence on carbon-intensive sectors and weak green policy have so far prevented any decoupling threshold. Short-run dynamics are more nuanced: medium growth (GDPREG2) turns emission-positive after two years (0.956), whereas high growth (GDPREG3) brings no offsetting relief, revealing the absence of complementary mitigation instruments. Renewable-energy penetration is the only robust lever, delivering a permanent 0.155% cut in CO₂ per additional 1% share, yet it imposes a transitional “brown” bump (+0.215%) as infrastructure is built. Lagged oil-price increases curb emissions (−0.138%), evidencing a temporary behavioral substitution window. Collectively, the results refute growth-only prescriptions and call for an integrated package of renewables scale-up, efficiency gains, and regulatory reform. The study’s contribution is (i) empirical documentation of asymmetric, multi-regime impacts, (ii) quantification of short-term renewable-expansion costs against long-term gains, and (iii) disclosure of conditional, delayed responses of oil prices and growth regimes insights, especially pertinent for rentier economies. Conclusion Algeria represents a suitable case study for examining the nonlinear, multi-stage relationship between economic growth and carbon dioxide emissions. This study employed the MT-NARDL model over the period 1984–2024. The results show that the Environmental Kuznets Curve does not apply, as none of the three growth regimes had a significant long-run effect, reflecting the persistence of carbon-intensive industries and the absence of an inflection point. Renewable energy emerged as the key driver of mitigation: a 1% increase in its share reduces emissions by 0.155% in the long run, despite a temporary rise in the short run due to infrastructure-related costs. Oil prices had no structural impact but showed a short-run negative effect after one year, indicating limited behavioral adjustments rather than a shift in the energy system. Based on these findings, four policy directions are recommended: (1) restructure the industrial model by reducing reliance on carbon-intensive sectors and integrating energy efficiency into growth strategies; (2) expand solar and wind investments while minimizing their ecological footprint through local manufacturing, recycling, and technology development; (3) channel surplus revenues from high oil prices into financing the energy transition; and (4) diversify the energy mix to gradually reduce dependence on hydrocarbons. Overall, Algeria stands at a decisive crossroads: either maintain its carbon-intensive trajectory or adopt a sustainable development model centered on renewable energy, efficiency, and strong regulatory frameworks. 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On the asymmetric effects of trade openness on CO2 emissions in SADC with a nonlinear ARDL approach. Discover Sustainability, 4(1), 2. <doi.org/10.1007/s43621-022-00117-3>; Ullah, A., Ahmed, M., Raza, S. A., Ali, S. (2021). A threshold approach to sustainable development: nonlinear relationship between renewable energy consumption, natural resource rent, and ecological footprint. Journal of environmental management, 295, 113073. <doi.org/10.1016/j.jenvman.2021.113073>; Yang, Z., Solangi, Y. A. (2024). Analyzing the relationship between natural resource management, environmental protection, and agricultural economics for sustainable development in China. Journal of Cleaner Production, 450, 141862. Footnotes [1] Yang, Z., Solangi, Y. A. (2024). Analyzing the relationship between natural resource management, environmental protection, and agricultural economics for sustainable development in China. Journal of Cleaner Production, 450, 141862. [2] Lu, F., Ma, F., Feng, L. (2024). Carbon dioxide emissions and economic growth: New evidence from GDP forecasting. Technological Forecasting and Social Change, 205, 123464. <doi.org/10.1016/j.techfore.2024.123464>. [3] Chou, C. H., Ngo, S. L., Tran, P. P. (2023). Renewable energy integration for sustainable economic growth: Insights and challenges via bibliometric analysis. Sustainability, 15(20), 15030. <doi.org/10.3390/su152015030>. [4] Mukhtarov, S. (2024). Oil prices and the renewable energy transition: Empirical evidence from China. Utilities Policy, 91, 101840. <doi.org/10.1016/j.jup.2024.101840>. [5] Hadji, Y., Abderrahmane, A. B. (2024). Analyzing the impact of oil price fluctuations on economic growth in Algeria: an empirical study. Theoretical & Applied Economics, 31(3). <store.ectap.ro/articole/1762.pdf>. [6] Mahajan, M., Sah, A. N. (2025). CO2 emissions response to GDP and crude oil price shocks: evidence from India and China using SVAR Model. Sustainable Futures, 9, 100479. <doi.org/10.1016/j.sftr.2025.100479>. [7] Ahmed, H., Hamza, K., Abdelillah, K., Boudjemaa, B., Achwak, B., Lila, A. (2024). The Future of Investment in Renewable Energies and Its Role in Achieving the Dimensions of Sustainable Development in Algeria. In Artificial Intelligence, Digitalization. <doi.org/10.1007/978-3-031-67531-7_6>. [8] Liu, X., Latif, K., Latif, Z., Li, N. (2020). Relationship between economic growth and CO2 emissions: does governance matter? Environmental Science and Pollution Research, 27(14), 17221-17228. <doi.org/10.1007/s11356-020-08142-3>. [9] Montagna, S., Huang, L., Long, Y., & Yoshida, Y. (2025). Sectoral economic complexity and environmental degradation: a sectoral perspective on the EKC hypothesis. Humanities and Social Sciences Communications, 12(1), 1-24. <doi.org/10.1057/s41599-025-04820-0>. [10] Mahmood, H., Furqan, M., Hassan, M. S., Rej, S. (2023). The environmental Kuznets Curve (EKC) hypothesis in China: A review. Sustainability, 15(7), 6110. <doi.org/10.3390/su15076110>. [11] Mujtaba, A., Jena, P. K. (2021). Analyzing asymmetric impact of economic growth, energy use, FDI inflows, and oil prices on CO2 emissions through NARDL approach. Environmental Science and Pollution Research, 28(24), 30873-30886. <doi.org/10.1007/s11356-021-12660-z>. [12] Udeagha, M. C., Breitenbach, M. C. (2023). On the asymmetric effects of trade openness on CO2 emissions in SADC with a nonlinear ARDL approach. Discover Sustainability, 4(1), 2. <doi.org/10.1007/s43621-022-00117-3>. [13] Tabash, M. I., Ahmed, A., Issa, S. S., Mansour, M., Varma, M., Al-Absy, M. S. M. (2024). Multiple Behavioral Conditions of the Forward Exchange Rates and Stock Market Return in the South Asian Stock Markets During COVID-19: A Novel MT-QARDL Approach. Computation, 12(12), 233. <doi.org/10.3390/computation12120233>. [14] Saint Akadiri, S., Bekun, F. V., Sarkodie, S. A. (2019). Contemporaneous interaction between energy consumption, economic growth and environmental sustainability in South Africa: what drives what? Science of the total environment, 686, 468-475. <doi.org/10.1016/j.scitotenv.2019.05.421>. [15] Musibau, H. O., Shittu, W. O., Ogunlana, F. O. (2021). The relationship between environmental degradation, energy use and economic growth in Nigeria: new evidence from non-linear ARDL. International Journal of Energy Sector Management, 15(1), 81-100. <doi.org/10.1108/IJESM-04-2019-0016>. [16] Erdogan, S., Okumus, I., Guzel, A. E. (2020). Revisiting the Environmental Kuznets Curve hypothesis in OECD countries: the role of renewable, non-renewable energy, and oil prices. Environmental Science and Pollution Research, 27(19), 23655-23663. <doi.org/10.1007/s11356-020-08520-x>. [17] Koc, S., Bulus, G. C. (2020). Testing validity of the EKC hypothesis in South Korea: role of renewable energy and trade openness. Environmental Science and Pollution Research, 27(23), 29043-29054. <doi.org/10.1007/s11356-020-09172-7>. [18] Sreenu, N. (2022). Impact of FDI, crude oil price and economic growth on CO2 emission in India: -symmetric and asymmetric analysis through ARDL and non-linear ARDL approach. Environmental Science and Pollution Research, 29(28), 42452-42465. <doi.org/10.1007/s11356-022-19597-x>. [19] Çakmak, E. E., Acar, S. (2022). The nexus between economic growth, renewable energy and ecological footprint: An empirical evidence from most oil-producing countries. Journal of Cleaner Production, 352, 131548. <doi.org/10.1016/j.jclepro.2022.131548>. [20] Feng, Y., Zhao, T. (2022). Exploring the nonlinear relationship between renewable energy consumption and economic growth in the context of global climate change. International Journal of Environmental Research and Public Health, 19(23), 15647. <doi.org/10.3390/ijerph192315647>. [21] Ullah, A., Ahmed, M., Raza, S. A., Ali, S. (2021). A threshold approach to sustainable development: nonlinear relationship between renewable energy consumption, natural resource rent, and ecological footprint. Journal of environmental management, 295, 113073. <doi.org/10.1016/j.jenvman.2021.113073>. [22] Ali, A., Radulescu, M., Balsalobre-Lorente, D. (2023). A dynamic relationship between renewable energy consumption, nonrenewable energy consumption, economic growth, and carbon dioxide emissions: Evidence from Asian emerging economies. Energy & Environment, 34(8), 3529-3552. <doi.org/10.1177/0958305X231151684>. [23] Erdoğan, E., Serin Oktay, D., Manga, M., Bal, H., Algan, N. (2024). Examining the effects of renewable energy and economic growth on carbon emission in Canada: Evidence from the nonlinear ARDL approaches. Evaluation Review, 48(1), 63-89. <doi.org/10.1177/0193841X231166973>. [24] Toumi, S., Toumi, H. (2019). Asymmetric causality among renewable energy consumption, CO2 emissions, and economic growth in KSA: evidence from a non-linear ARDL model. Environmental Science and Pollution Research, 26(16), 16145-16156. <doi.org/10.1007/s11356-019-04955-z>. [25] Baz, K., Xu, D., Ali, H., Ali, I., Khan, I., Khan, M. M., Cheng, J. (2020). Asymmetric impact of energy consumption and economic growth on ecological footprint: using asymmetric and nonlinear approach. Science of the total environment, 718, 137364. <doi.org/10.1016/j.scitotenv.2020.137364>. [26] Elbadri, M., Bsikre, S., Alamari, O., Balcilar, M. (2023, August). Nexus between renewable energy consumption, economic growth, and CO2 emissions in Algeria: New evidence from the Fourier‐Bootstrap ARDL approach. In Natural Resources Forum, Oxford, UK: Blackwell Publishing Ltd., Vol. 47, No. 3, 393-412. <doi.org/10.1111/1477-8947.12292>. [27] Brini, R., Amara, M., Jemmali, H. (2017). Renewable energy consumption, international trade, oil price and economic growth inter-linkages: The case of Tunisia. Renewable and Sustainable Energy Reviews, 76, 620-627. <doi.org/10.1016/j.rser.2017.03.067>. [28] Gülcü, A. (2025). Essays on financialization, income inequality and growth. <hdl.handle.net/11511/114100>. [29] Georgescu, I., Kinnunen, J. (2025). Nonlinear Effects of GDP Regimes, Renewable Energy, and Urbanization on Finland’s Ecological Footprint: An MT-NARDL Approach. World Development Sustainability, 100235. <doi.org/10.1016/j.wds.2025.100235>.
International Pilgrimage Tourist Routes and Their Importance in Raising the Country’s Awareness: “The Way of St. Andrew the First-Called”
Georgia possesses a unique cultural and historical identity that encompasses a rich variety of cultural values: architectural monuments, folk traditions, music, visual arts, historical-ethnic heritage, and natural landscapes. This combination creates a significant potential for the development of religious tourism. However, unfortunately, only a small portion of this potential has been utilized. The pilgrimage phenomenon is currently experiencing a revival around the world, with long-standing shrines once again attracting seekers of spiritual self-realization. We believe that by adapting global experiences to the Georgian reality and considering current circumstances, it is entirely feasible to establish an international pilgrimage route in Georgia – The Path of St. Andrew the First-Called. This is especially relevant given that St. Andrew traveled multiple times through Georgia and beyond, with this route extending to other countries as well. For the development of religious tourism in Georgia and its popularization in the global tourism market, the most important task is to conduct intensive scientific research on this type of tourism, to create demand through new motivations for tourists, and to provide new products to the market. The work reveals the importance of international pilgrimage tourist routes, the possibility of creating new market niches, and developing new identities. With the correct and well-planned use of modern PR technologies and marketing strategies, in cooperation with international organizations, the Path of St. Andrew the First-Called has great potential as an international pilgrimage route. Keywords: Religious tourism, pilgrimage, cultural routes, The Path of St. Andrew the First-Called. Introduction In the context of modern globalization, no country can achieve successful development without engaging with the global market and coordinating its internal economic and financial policies with regional and global leaders. The diverse historical experiences of various countries demonstrate that the sustainable development of any state is impossible without active participation in global economic relations. The current level of international labor division has effectively eliminated economic isolation, making it nearly impossible for any country to remain detached from the global economic process. Modern economies encompass over 50 industries directly linked to tourism, making the synergy effect substantial. Many governments view tourism as a crucial aspect of their policies in the context of economic development. Georgia’s integration into the regional economy and the subsequent growth of its potential and irreversible development largely depend on the advancement of a high-quality and fully developed tourism industry.[1] Georgia’s strategic objective should be its active participation in the process of globalizing and personalizing international relations. The country must position itself at the center of global economic developments. The full integration of Georgia into the regional economy and its irreversible development will significantly rely on the establishment of a well-developed and high-quality tourism industry.[2] In the economic structures of developed countries, the service sector dominates. Demand for services is not only economic but also social in nature, impacting material and non-material sectors, as well as culture and the economy. One of the key components of the service sector is the tourism industry, which has become one of the most widespread global phenomena of the 21st century, affecting all aspects of public life and transforming the surrounding world. In our view, one of the primary factors for Georgia’s integration into the global economy is the development of a comprehensive and high-quality hospitality industry, including tourism, cultural, and religious tourism. Georgia stands out worldwide for its unique and diverse tourism potential. The Ministry of Economy and Sustainable Development presented a summary report of the results in the tourism and aviation sector in 2023 and held a presentation of the plans for the ongoing year. It was emphasized that the growth and development of these two important sectors of the economy - tourism and aviation - is important for the economy of the whole country in many ways, and most importantly, it generates new jobs and more prosperity for the population. In addition, the Ministry of Economy and Sustainable Development predicts that 2024 will be even more successful, which will be reflected in the 6,8 million passenger flow in the aviation sector and 4,5 billion USD in revenues from tourism.[3] In 2024, Georgia hosted a record number of tourist visits, reaching a historic high of 5,1 million, which represents a 9% increase compared to the previous year. When compared to 2019, the number of tourist visits showed a slight increase of 0,2%. A total of 7 368 149 international travelers visited Georgia in 2024, marking a 4,2% increase over 2023. Compared to 2019, this figure reflects a significant rise of 78,7% (see Figure 1). It is worth noting that last year, the number of tourists from countries such as Israel, the USA, France, the United Arab Emirates, Saudi Arabia, and other countries, whose tourists are distinguished by their purchasing power, reached a record high.[4] As a result, the added value of tourism-related industries as a share of GDP increased from 6.7% to 7.2% in 2023 (see Figure 2). According to GEOSTAT, the tourism sector contributed 7.2% to the country’s GDP. The increase is 0.5% from 2022 and only 1.2% below 2019.[6] The figures are interesting in terms of geographical distribution, with 54,6% of visits to the capital Tbilisi, followed by Adjara (40.9%) and Mtskheta-Mtianeti (16.5%). Other regions attracted fewer visitors: Kvemo Kartli (8.7%), Samtskhe-Javakheti (9.6%), Imereti (9%), Kakheti (6.6%), Shida Kartli (3.6%), Samegrelo-Zemo Svaneti (2.7%), Guria (1.4%), and Racha-Lechkhumi, Kvemo Svaneti (0.1%).[8] (see Figure 3). This data highlights Georgia’s growing role as a significant tourism destination and underscores the need for further strategic development in the sector, particularly in religious and pilgrimage tourism. However, the tourism development objectives outlined in the strategy for 2025 also face some challenges in achievement. Cultural tourism in Georgia faces several challenges. One of the main challenges is the need for sustainable management and preservation of cultural assets in the face of increasing tourism pressure. Striking a balance between heritage conservation and visitor accessibility, and infrastructure development is crucial to ensuring the long-term sustainability of cultural tourism in Georgia. In addition, the development of pilgrimage tourism will contribute to improving the quality of the visitor experience. There is a need to strengthen the capacity of the pilgrimage tourism sector. Methodology The study used a systematic review and meta-analysis, quantitative and qualitative research in a systematic review of the development of pilgrimage tourism routes. Sources of evidence were selected, and various designs of studies were used to combine them to obtain a summary conclusion. During the review, peer-reviewed articles were identified around the thematic issue of European pilgrimage tourism routes. We reviewed the documents based on the best pilgrimage routes in relation to the research problem. Results and discussion Tourism, like all other human activities, is aimed at satisfying needs as well as fostering spiritual and cultural development. It is an activity through which individuals gain experience in interpersonal relationships. Every form of tourism, even those without specific directions or characteristics, can play a significant role in the development of society and in establishing connections between people of different nationalities, religions, and cultures. For centuries, religious beliefs have shaped public consciousness and the social organization of individuals and communities. Religion has united people more firmly than racial, national, territorial, or familial ties. Today, the theme of “Tourism and Religion” has gained significant interest. Around the world, various types of educational tourism, including religious tourism, are increasingly developing. Throughout different historical periods, pilgrimage routes for believers of various religious denominations have included Greece, Egypt, Saudi Arabia, Israel, Palestine, Georgia, Jordan, Italy, India, Tibet, and other destinations.[10] Religiously motivated travel, such as pilgrimage, is one of the oldest forms of tourism.[11] Barber, in his work “Pilgrims”, explained that Pilgrimage, one of the most widespread religious and cultural phenomena in human society, is an important feature of the major world religions: Christianity, Buddhism, Hinduism, Islam, Judaism, and others. Pilgrimage is defined as “a journey motivated by religious reasons, outwardly to a sacred place and inwardly for spiritual purposes and inner understanding”.[12] “Pilgrimage, the journey to a distant sacred goal, is found in all the great religions of the world. It is a journey both outwards to hallowed places and inwards to spiritual improvement; it can express penance for past evils, or the search for future good; the pilgrim may pursue spiritual ecstasy in the sacred sites of a particular faith, or seek a miracle through the medium of god or a saint. Throughout the world, pilgrims move invisibly in huge numbers among the tourists of today, indistinguishable from them except in purpose”.[13] Today, pilgrimage is defined differently and can be considered as traditional religious or modern secular travel. The phenomenon of pilgrimage is currently experiencing a revival around the world, with long-standing shrines once again attracting seekers of spiritual self-realization.[14] However, the literature on pilgrimage and religious tourism remains fragmented and lacks synthesis and holistic conceptualization.[15] The tradition of pilgrimage holds a strong presence in Orthodox Christianity. Pilgrimage was established as a form of religious practice in Christianity from the 4th century. Excursions and pilgrimage journeys occupy an essential place in Christian life. This is due to the long-standing tradition of pilgrimage in Christian culture, as well as the widespread popularity of visiting religious sites among pilgrims.[16] Among Orthodox countries, Greece, Russia, Romania, and Bulgaria stand out in this regard, as their governments make substantial efforts to develop this sector of tourism. Religious tourism generates economic benefits for local populations, state institutions, tourism organizations, religious establishments, and private entrepreneurs. Notably, in all the aforementioned countries, Georgian churches and monasteries continue to exist and function to this day. The Petritsoni Monastery (Bachkovo Monastery). One of the most prominent Georgian religious sites abroad is the Petritsoni Monastery, also known as the Bachkovo Monastery, the second-largest monastery in Bulgaria after the Rila Monastery. It is located in the Asenovgrad region, 28 km from Plovdiv, on the right bank of the Asenitsa (Chepelarska) River in the Rhodope Valley. The monastery was founded and built by the Georgian nobleman Gregory Bakurianisdze, a high-ranking military commander at the court of the Byzantine Emperor Alexios I Komnenos and an important political figure of the 11th century. He carefully selected the village of Petritsoni, a land rich in natural blessings, as the site for the monastery. Together with his brother, Gregory built the monastery in 1083, and in 1084, he established its typikon.[17] The Petritsoni Monastery complex initially comprised three churches: a large cathedral dedicated to the Virgin Mary and two smaller churches dedicated to St. John the Baptist and St. George. Over the centuries, the monastery faced numerous adversities, including a devastating fire in the 15th century that left only the Church of the Archangels intact. Thanks to the efforts of the faithful and donations collected by monks, the monastery was gradually restored between the 16th and 18th centuries. Today, the Petritsoni Monastery complex consists of residential buildings enclosing the area and is divided into two sections: in the northern courtyard, the Cathedral of the Holy Virgin (18th century) and the Church of the Archangels (12th century) stand, while in the southern courtyard, the Church of St. Nicholas (built between 1834 is located. The residential buildings, which also serve as defensive walls, house the monks’ quarters, guest rooms for pilgrims, and other facilities. A noteworthy historical figure associated with this monastery is Father Ambrose, the former abbot of the Zographou Monastery on Mount Athos. He once served as a monk at the Bachkovo Monastery and expressed deep reverence for the Catholicos-Patriarch of Georgia, Ilia II, stating, “I believe that we are dealing with one of the greatest patriarchs of all time. Even the most revered elders on Mount Athos were astonished by his wisdom and spirituality. Blessed is the nation that has such a shepherd. I believe that Iberia (Georgia) will shine once again”.[18] Georgian Religious Heritage Abroad. Georgia’s religious heritage extends beyond the Balkans, with Georgian churches and monasteries found in Romania, Russia, and other regions of the Caucasus. In Bucharest, on Antim Ivireanul Street (No. 29), stands a beautifully decorated church bearing the name of Antimoz Iverieli, a Georgian cleric and scholar. Built in 1715 with his personal resources, the church features intricate carvings, mosaics, and murals—many of which were crafted by Antimoz himself. Adjacent to the church is the Antimoz Iverieli Museum, which houses an extensive collection of photographs, manuscripts, books, and illustrations documenting his life and work. Antimoz Iverieli dedicated his life to the liberation of Wallachia from Ottoman and Phanariot rule, actively contributing to the construction of over 20 churches and monasteries, the establishment of four printing houses, and the publication of 64 books. In Russia’s North Caucasus, several historical Georgian churches and monasteries still exist, albeit in various states of preservation. Among them: Albi-Yerdi Church (9th–16th century), located in Ingushetia’s Dzheirakh district. It is located in the North Caucasus Federal District, in the Republic of Ingushetia, in the Dzairakh district, on the left bank of the Asa River, in a small Targam cave. Only the ruins of the church have survived to this day.[19] Datuna Church, built by Georgian missionaries in the late 10th or early 11th century in present-day Dagestan. The church was built by Georgian missionaries around the end of the 10th century and the beginning of the 11th It was abandoned in the 13th century, although it was still in use for a certain period of the 19th century.[20] Senty Church, a 10th-century cathedral in Karachay-Cherkessia, is known for its frescoes. It was built around the 10th century. The name is thought to be related to the Georgian pillar, Svetitskhoveli. The architectural description of the temple was first given to us by the German scholar Joseph Bernardi in 1829. Tkoba-Yerdi Church, an important medieval Georgian church in Ingushetia, is now endangered due to military activity in the region. Tkobaerdi is one of the churches built by Georgian missionaries to promote Christianity among the Vainakh tribes. It was originally a three-nave basilica, typical of medieval Georgian architecture.[21] Additionally, Georgia has left an enduring legacy on Mount Athos, where the Iviron Monastery (established in the 10th century) became a major center of learning and manuscript translation. During its peak in the 11th century, the monastery played a significant role in preserving Georgian cultural and theological heritage. The Potential of Religious Tourism in Georgia. Despite its rich religious and historical heritage, Georgia has yet to fully capitalize on its potential in religious tourism. Official statistics show that over the past decade, only 1-2% of international visitors cite religious pilgrimage as their primary reason for traveling to Georgia, while this figure stands at 2-3% among domestic travelers. However, religious tourism is one of the fastest-growing sectors in global tourism, and Georgia possesses substantial resources to develop it further. The country is home to approximately 12,000 historical and architectural monuments, many of which hold deep religious significance. There is increasing interest from foreign visitors in Georgia’s sacred sites, yet efforts to promote the country as a religious tourism destination remain limited. Given that 90% of the world’s cultural-historical sites have religious significance, it is essential to recognize the role of religious tourism in society. Identifying and optimizing this sector could enhance Georgia’s position on the global tourism market, stimulate economic growth, and contribute to regional stability. There is growing discussion about the active manifestation of human interests, particularly towards religion, objects of worship, sacred sites, religious centers, and historical-religious monuments. However, statistical data does not confirm this trend. There are also objective reasons for this, such as the small size of the country, its still-developing economy, and Georgia’s peripheral position within the Christian world. These factors hinder Georgia’s strong penetration and establishment in the global tourism market, including religious tourism. The country requires greater promotion. To achieve this, Georgia must initiate and implement new international pilgrimage routes, which could eventually extend to multiple countries. This would not only enhance the country’s visibility and increase revenues but also contribute significantly to regional stability.[22] In our opinion, the “Route of St. Andrew the First-Called” could play an essential role in this regard. The Georgian Orthodox Church is an Apostolic Church, meaning that in the first century, Christ’s teachings were preached in Georgia by His apostles. The authenticity of this ecclesiastical tradition is confirmed by both Georgian and foreign written sources, which provide valuable information about the apostles’ activities in Georgia. In 2001, His Holiness and Beatitude Ilia II, the Catholicos-Patriarch of All Georgia, established the “International Center for Christian Studies” under the Georgian Orthodox Apostolic Church. Based on this foundation, a scientific expedition was formed - “The Research Expedition of St. Andrew the First-Called’s Route”. This scientific expedition examined the path traveled by St. Andrew the First-Called both within Georgia and beyond its borders. Analysis of the expedition’s findings revealed that accounts found in both Georgian and foreign sources regarding St. Andrew’s travels in Georgia - along with the routes, toponymy, and traditions associated with them - often align with the routes traveled and the locations identified during the expedition.[23] In the village of Didachara, the ruins of a church that, according to tradition, was built by St. Andrew himself, have been preserved to this day. The Georgian Orthodox Apostolic Church commemorates St. Andrew the First-Called twice a year-on May 12 and December 13. Ancient accounts of St. Andrew’s travels and sermons begin to appear from the 2nd century. Over time, these accounts were supplemented with additional details, expanding the geographical scope of the apostles’ activities. According to the geography of St. Andrew’s journeys, the Holy Apostle visited Georgia three times to preach Christianity. During his third journey, he was accompanied for some time by Simon the Zealot, Matthias, Bartholomew, and Thaddeus. The chronicle The Life of Kartli provides details about this journey. Notably, the route of Apostle Andrew, as recorded by ancient Georgian historians—Trabzon, Apsaros (Gonio), Didachara, Odzrkhe, Atsquri, western Georgia, Tskhum (Sebastopolis), Nikopsia-closely matches a 4th-century Roman road map, which marks international trade routes. Although this map dates to the 4th century, it is largely based on earlier materials from the 1st-2nd centuries.[24] In addition to these regions, Andrew also traveled through Tao and Svaneti, from where he crossed into Ossetia, later returning to Tskhum via Abkhazia. A possible route is illustrated on the (see Figure 4).[25] Saint Andrew the Apostle’s route through Georgia can be determined by comparing ancient Georgian sources and old maps (see Figure 5). According to Eusebius of Caesarea, Andrew traveled to Scythia, which, according to the definition of that time, included the lands west, north, and east of the Black Sea. Andrew also visited northern Anatolia, the Caucasus, the Sea of Azov, Crimea, Byzantium, and Greece.[26] According to J. Chardin and C. Castel, there was an old church named after St. Andrew the Apostle in Bichvinta. There was a cross-shaped column there, before which people knelt and prayed. The activities of Andrew the Apostle in Georgia are emphasized by George of Mtatsminda, George the Less, and Ephrem the Less. The tradition was canonized at the Ruis-Urbnisi Church Council and is recorded in the inscription of this council: “... Andrew the Apostle, brother of his apostle Peter, ascended to us and preached the living sermon of the Gospel to all the lands of Georgia”.[27] Traditions about St. Andrew the Apostle have been preserved among the people in Didajara, where the ruins of a church have been preserved to this day, which, according to tradition, was built by St. Andrew the First-Called himself. In Samegrelo (Martvili), Samtskhe (Andriatsminda), Kakheti (Martkopi), Khevi (Gergeti). Andrew, who set out from Didajara, had to pass through the villages of Iremadzeebi, Satsikhuri, Agara, Ghorjomi, Tsivtskaro Mountain, Kvabisjvari, and Mamlis Mountain. The ruins of churches on this road are marked on old maps. It is worth noting that the route of the Apostle Andrew, as described by ancient Georgian historians, includes Trabzon, Apsari (Gonio), Didachara, Odzrkhe, Atskuri, Western Georgia, Tskhum (Sebastopolis), Nikopsia... In order for the Way of St. Andrew to become an international religious tourist route, preparatory work must first be carried out in Georgia, both in terms of the detailed determination and marking of routes, as well as in terms of arranging the infrastructure on this route. In this regard, the presentation of the spatial arrangement of the country presented by the Georgian government gives great hope, where it was stated that “the employment of the population in their native regions should be promoted, tourists should be able to visit all regions without delay, and we should turn all regions of Georgia into four-season resort destinations”. On June 18, 2020, the Ministry of Education, Science, Culture, and Sports of Georgia awarded a certificate to the new cultural route “The Way of St. Andrew the Apostle”. “The Way of St. Andrew the Apostle” is a pilgrimage route, the main theme of which is an excursion pilgrimage trip. Mount Rakminjvari is one of the symbols of the Borjomi-Kharagauli National Park. Its height is 2439 meters above sea level. According to legend, St. Andrew the First-Called erected an iron cross here in the 1st century, which is why the mountain was named Rakminjvari, and the national park’s tourist trail No. 2 is named after St. Andrew the First-Called. Rakminjvari is a favorite place for Orthodox pilgrims and hikers. Figure 6 - shows Borjomi-Kharagauli National Park, Iron Cross Mountain, on which, according to legend, Andrew the First-Called erected an Iron Cross in the first century.[28] Andrew the Apostle erected an Iron Cross in the first century.[29] The route, based on materials preserved in Greek-Latin texts and the “Life of Kartli”, introduces us to the path taken by St. Andrew the Apostle in Georgia. At this stage, the route includes several regions of Georgia (Adjara, Imereti, Samtskhe-Javakheti) and 7 different types of objects. The organization presenting the route is the “Academy of Tourism and Management”. This route is included in the first mobile application of Georgian cultural routes, Cultural Routes Georgia. At a later stage, the route can be expanded by involving several regions of Georgia. Among them: Surami, Khashuri, Ulumbo, Mtiuleti, Samachablo, Kutaisi, Samegrelo, Svaneti, Abkhazia. It should also be noted that Georgia became the 27th member state of the “Council of Europe’s Extended Partnership Agreement on Cultural Routes” in 2016. The Council of Europe’s Cultural Routes programme includes 38 certified routes, crossing 57 countries and over 1,500 cities.[30] Although firms operating in the field of religious tourism have appeared on the Georgian tourism market, the existing potential remains untapped. There are many reasons for this, including underdeveloped infrastructure, lack of information about places of interest, weak ties between local governments and tourism firms, and lack of qualified personnel. For the development of religious tourism, exhibitions, congresses, and conferences are organized in various countries of the world by religious organizations and associations, as well as by companies interested in the development of the tourism industry. More activity is needed in this regard, both in Georgia and worldwide. There are many pilgrimage routes in the world, one of the most famous and most famous pilgrimage routes in Europe is the “St. The Way of St. James - El Camino de Santiago”. The Camino de Santiago, translated into English, is The Way of St James. It is an ancient network of walking routes across Europe, called pilgrim routes, that meet at the tomb of St James. Since the 1980s, its popularity has been steadily increasing, and the number of pilgrims in 2013 was more than 200,000. Today, it is second only to Jerusalem and Rome in popularity. The pilgrimage “The Way of St. James – El Camino de Santiago” has become a unique event. For most travelers, it is the cheapest way to relax, a good way to get to know the countries, test your physical endurance (since you will have to walk a large part of the way), and meet interesting people, and pray at the churches and monasteries along the way. Many routes lead to this city (Figure 7).[31] The main part of the route passes through the Pyrenees in northern Spain. You can start the journey from Spain, France, Germany, Portugal, Great Britain, or any other country. The most popular is the French Way, which is more than 800 km long. To receive a certificate in Latin for completing the Way of St. James, you must register at one of the churches along the way and walk at least 100 km; if you travel by horse, the minimum distance is 150 km, and for a cyclist, 300 km. Each participant in the journey can receive a pilgrim passport, which will contain special stamps that will serve as a document confirming the journey and will give you certain benefits in all hotels, shelters, churches, and monasteries. In every town and almost every village along the entire route, there are special shelters for pilgrims. Most of the shelters are free if you present a pilgrim’s passport. There are also private shelters, where a night’s stay costs 8-12 euros. And there are also municipal shelters, where a night’s stay costs 3-7 euros - this amount is the so-called donation. Those who wish can also stay in three- or four-star hotels.[33] It is worth noting that the Camino de Santiago is busier during Holy Years. The next Holy Year is 2027. During Holy Years, pilgrims are entitled to a plenary indulgence, the forgiveness of all sins. During these years, the Holy Doors of the Cathedral of Santiago have been open to pilgrims. The “Way of St. James” has been included in the UNESCO World Heritage List and has been declared a “major cultural heritage of the European route”. To walk the Camino is a humbling experience. There were many moments when I thought I had bitten off more than I could chew despite vigorous preparation and training. But I trusted that since God permitted me to be there, He would help me accomplish this objective. He did so, and I thank Him. The walk to Santiago de Compostela in Northern Spain, the Galician region, is something that I will never forget. The shrine is one of the three major shrines of Christendom, along with Rome and Jerusalem. I have had the good fortune to visit all three.[34] Researchers have interesting ideas about Fisterra as a “new” final destination for pilgrims. They argue that the modern Fisterra as the end of the journey should be seen as both a result of the post-secular trend in Europe and a response to the fact that the historical destination of Santiago de Compostela is increasingly marked by commercialized mass tourism, which is disadvantageous in the context of pilgrimage.[35] In the article “The Wrong Way: An Alternative Critique of the Camino de Santiago,” the author notes that the 11th-century Camino de Santiago, a spiritual journey to the final resting place of Saint James, has been an important pilgrimage for pilgrims for centuries. Many modern pilgrims try to travel in the same way as in ancient times. However, pilgrims who do not adhere to the perceived “authentic” behavior experience a sense of alienation.[36] We believe that, if world experience is adapted to Georgian reality and taking into account today’s realities, it is entirely possible to implement an international pilgrimage route “The Way of St. Andrew the Apostle” in Georgia, especially if we take into account that St. Andrew traveled several times and this path passes through other countries besides Georgia (Figure 8). According to our research, the countries where Andrew the Apostle traveled are Israel, Turkey, Russia, Belarus, Ukraine, the Baltic States, Poland, Slovenia, Romania, Moldova, Macedonia, Bulgaria, and Greece. Conclusion In our opinion, with the help of correctly and precisely selected and planned modern PR technologies and marketing, in cooperation with international organizations, the international pilgrimage route – “The Way of St. Andrew the Apostle” has great potential. For the development of religious tourism, we consider close coordination between central and local government bodies – between cultural institutions, healthcare organizations, physical culture and sports, tourism companies, educational institutions, public associations, and religious organizations – essential. This is a complex task, and the state, private, public, and religious institutions should participate in its solution. Only through cooperation will religious tourism have a basis for development and a basis for having a positive impact on cultural and religious dialogue, on the spiritual and economic development of the local population.[38] To create the desired conditions for the development of religious tourism, it is necessary to: form a management mechanism for the development of the tourist direction; form a normative-regulatory base for religious tourism to stimulate the mentioned direction and attract investments in this area; stimulate business development in the field of religious tourism; stimulate the material base for the development of the tourist direction by attracting local and foreign investments - creating new facilities for the preservation and reconstruction of the technical condition of cult architecture as objects of religious tourism; create appropriate conditions for the development of tourist zones in the regions of Georgia in the field of tourism; harmonize social and public life, arouse interest in one’s own country, resolve issues related to the preservation of historical and cultural heritage, and protection of environmental conditions; create and provide an information system for tourists; carry out active advertising and information work, which will be aimed at the tourist image of Georgia and the growth of interest in the religious and cultural values ​​of various confessions; improve a full-fledged system for the education and professional training of personnel in the field of religious tourism. Analysis of the history and current state of the development of religious tourism allows us to draw an important conclusion: as a result of the joint and planned work of state, public, commercial and religious organizations, we can achieve that religious tourism will promote mutual understanding and respect between people from different strata of society and representatives of various traditional confessions, different parts of the country, and different countries. This is on the one hand. In addition, it should be taken into account that today the preservation of traditional values, historical and cultural heritage, and their transfer to future generations is one of the priority tasks, which in many cases cannot be solved without the development of tourism, primarily religious tourism. References: Ambioni. Available at: <https://www.ambioni.ge/andriaoba-rkinisjvarze>. (In Georgian); Barber, R. (1991). Pilgrimages. Boydell Press, Suffolk. Available at: <https://archive.org/details/pilgrimages0000barb>; Berdzenishvili, D. (2005). Essays. Georgian Historical Monuments Preservation Fund. Available at: <https://dspace.nplg.gov.ge/bitstream/1234/459308/1/Narkvevebi_2005.pdf>. (In Georgian); Blom, T., Nilsson, M., Santos, X. (2016). The way to Santiago beyond Santiago. Fisterra and the pilgrimage’s post-secular meaning. European Journal of Tourism Research, Vol. 12. <doi.org/10.54055/ejtr.v12i.217>; Camino Adventures. (2024). The Camino de Santiago Pilgrimage Routes in Spain. Available at: <https://www.caminoadventures.com>; Collins-Kreiner, N. (2010). Researching Pilgrimage: Continuity and Transformations. Annals of Tourism Research, 32(2). Available at: <https://www.sciencedirect.com/science/article/abs/pii/S016073830900142X?via%3Dihub>; Digance, J. (2003). Pilgrimage at Contested Sites. Annals of Tourism Research 30(1); Dvalishvili, G. (2025). Andrew’s Day on the Iron Cross. A public religious online magazine Pulpit. Available at: <https://www.ambioni.ge/andriaoba-rkinisjvarze>. (In Georgian); Essays on the History of Georgia. (1970). Georgia from Ancient Times to the 4th Century AD, Volume I, Publishing House “Soviet Georgia”. Tbilisi. (In Georgian); Frank, V. (2013). Your Camino: Santiago de Compostela. Canada. Available at: <https://caminoways.com/your-camino-santiago-de-compostela>; Georgian National Tourism Administration. (2024). Georgian tourism in figures. Structure & Industry Data. Available at: <https://gnta.ge/en/research/annual-report>; Georgian National Tourism Administration. (2024). Statistical overview of Georgian tourism report. Available at: <https://api.gnta.ge/storage/files/doc/saqartvelos-turizmis-statistikuri-mimokhilva-2024.pdf>. (In Georgian); Grdzelishvili, N. (2013). Religious Tourism – as a Factor of Georgia’s Integration into the World and Regional Economy. VII Scientific Conference “Christianity and Economics. State University and the 35th Anniversary of the Enthronement of the Catholicos Patriarch of Georgia, His Holiness Ilia II. Samtavisi and Gori Diocese of the Georgian Patriarchate. (In Georgian); Grdzelishvili, N. (2015). The factor of religion in the process of forming the tourist brand of Adjara. VIII International Scientific Conference “Christianity and Economics”. Available at: <https://dspace.nplg.gov.ge/handle/1234/487633>. (In Georgian); Grdzelishvili, N. (2016). Pilgrimage Tourism-St. Andrew’s Way. Spiritual, Social and Economic Aspects. Proceedings of the 9th International Scientific Conference on Christianity and Economics, Kutaisi. (In Georgian); Grdzelishvili, N. (2018). Religious Tourism. Publishing House “Centaur”, Tbilisi. (In Georgian); Grdzelishvili, N. (2023). Religious Tourism. Georgian National Academy of Sciences. 978-9941-8-5019-6. Available at: <https://dspace.nplg.gov.ge/handle/1234/540900>. (In Georgian); Grdzelishvili, N., Gardapkhadze, T. (2020). Factors of Religious Tourism in Georgia and Its Legal Aspects. Proceedings of the Scientific Symposium “Building Peace through Heritage - World Forum for Change through Dialogue”, Florence, March 13-15. Fondazione Romualdo Del Bianco; International Center for Christian Research under the Georgian Orthodox Church. (2009). In the Footsteps of Andrew the First-Called. Tbilisi; Jafaridze, A. (2019). Mother Church, Letters and Sermons. The Way of the Apostles. Available at: <https://meufeanania.com>. (In Georgian); Janashvili, M. (1895). Excellent remains. Iveria Newspaper, N132. Available at: <http://saunje.ge/index.php?id=1684&lang=ru>. (In Georgian); Kaldani, A. (1988). Christian monuments of Georgian origin in Ingushetia. Magazine “Monument’s Friend”, No. 79. Available at: <http://saunje.ge/index.php?id=1640&lang=en>; Lange’s Christian Chronicle. (n.d.). Available at: <https://christian-hx.fyi/andrew>; Metropolitan Ananias. (1991). The Way of the Apostles. Eri Newspaper, 21. VIII. Available at: <http://meufeanania.info/%E1%83%9B%E1%83%9D%E1%83%AA%E1%83%20%98%E1%83%A5%E1%83%A3%E1%83%9A%E1%83%20(bolo%20naxva%>. (In Georgian); Ministry of Economy and Sustainable Development of Georgia. (2024). Georgia’s Tourism and Aviation Sectors - 2023 Summary Report and 2024 Plans. Available at: <https://www.economy.ge/?page=news&nw=2471&lang=en>; Ministry of Education, Science and Youth of Georgia. (2020). Cultural Routes Georgia. The first free mobile application for cultural routes. Available at: <https://www.mes.gov.ge/content.php?id=10495&lang=geo>; Nutsubidze, P., Chanishvili, G. (1993). Datuna Church, Magazine “Monument’s Friend”, No. 1. Available at: <http://www.saunje.ge/index.php?id=1633&lang=ru>. (In Georgian); Orthodoxy.ge. (n.d.). Foreign fathers on our patriarch. Public Relations Service of the Patriarchate of Georgia. Available at: <https://www.orthodoxy.ge/patriarqi/utskhoelebi.htm>. (In Georgian); Overall, J. (2019). The Wrong Way: An alternative critique of the Camino de Santiago. European Journal of Tourism Research, Vol. 22. Available at: <https://ejtr.vumk.eu/index.php/about/article/view/375/379>; <doi.org/10.54055/ejtr.v22i.375>; Patriarchate of Georgia. (2021). Petritsoni Monastery in Bulgaria. Available at: <https://patriarchate.ge/news/1924>; Pospisil, R. (2014). The Camino De Santiago: Cycling “The Way”. Available at: <https://theprovince.com/travel/camino-de-santiago>; Rinschede, G. (1992). Forms of religious tourism. Annals of Tourism Research, Vol. 19 (1). Available at: <https://doi.org/10.1016/0160-7383(92)90106-Y>; The World Bank. (2024). Georgia: Tourism Trends Analysis and Recommendations. Available at: <openknowledge.worldbank.org/server/api/core/bitstreams/7b9b850e-6dd3-42ec-aaca-3a24f47c5c9d/content>; Timothy, D. J., Olsen, D. H. (2006). Tourism, religion and religious journeys. Routledge, London. Footnotes [1] Grdzelishvili, N. (2015). The factor of religion in the process of forming the tourist brand of Adjara. VIII International Scientific Conference “Christianity and Economics”, p. 40-44. Available at: <https://dspace.nplg.gov.ge/handle/1234/487633>. [2] Grdzelishvili, N. (2013). Religious Tourism – as a Factor of Georgia’s Integration into the World and Regional Economy. VII Scientific Conference “Christianity and Economics, p. 41-48. State University and the 35th Anniversary of the Enthronement of the Catholicos Patriarch of Georgia, His Holiness Ilia II. Samtavisi and Gori Diocese of the Georgian Patriarchate. [3] Ministry of Economy and Sustainable Development of Georgia. (2024). Georgia’s Tourism and Aviation Sectors - 2023 Summary Report and 2024 Plans. Available at: <https://www.economy.ge/?page=news&nw=2471&lang=en>. [4] Georgian National Tourism Administration. (2024). Statistical overview of Georgian tourism report. Available at: <https://api.gnta.ge/storage/files/doc/saqartvelos-turizmis-statistikuri-mimokhilva-2024.pdf>. [5] Ibid. [6] The World Bank. (2024). Georgia: Tourism Trends Analysis and Recommendations. Available at: <openknowledge.worldbank.org/server/api/core/bitstreams/7b9b850e-6dd3-42ec-aaca-3a24f47c5c9d/content>. [7] Ibid. [8] Georgian National Tourism Administration. (2024). Georgian tourism in figures. Structure & Industry Data. Available at: <https://gnta.ge/en/research/annual-report>. [9] Ibid. [10] Grdzelishvili, N. (2018). Religious Tourism. Publishing House “Centaur”, Tbilisi. [11] Rinschede, G. (1992). Forms of religious tourism. Annals of Tourism Research, Vol. 19(1), pp. 51-67. Available at: <https://doi.org/10.1016/0160-7383(92)90106-Y>. [12] Collins-Kreiner, N. (2010). Researching Pilgrimage: Continuity and Transformations. Annals of Tourism Research, 32(2). Available at: <https://www.sciencedirect.com/science/article/abs/pii/S016073830900142X?via%3Dihub>. [13] Barber, R. (1991). Pilgrimages. Boydell Press, Suffolk. Available at: <https://archive.org/details/pilgrimages0000barb>. [14] Digance, J. (2003). Pilgrimage at Contested Sites. Annals of Tourism Research 30(1). [15] Timothy, D. J., Olsen, D. H. (2006). Tourism, religion and religious journeys. Routledge, London. [16] Grdzelishvili, N. (2016). Pilgrimage Tourism-St. Andrew’s Way. Spiritual, Social and Economic Aspects. Proceedings of the 9th International Scientific Conference on Christianity and Economics, Kutaisi, pp. 59-64. [17] Patriarchate of Georgia. (2021). Petritsoni Monastery in Bulgaria. Available at: <https://patriarchate.ge/news/1924>. [18] Orthodoxy.ge. (n.d.). Foreign fathers on our patriarch. Public Relations Service of the Patriarchate of Georgia. Available at: <https://www.orthodoxy.ge/patriarqi/utskhoelebi.htm>. [19] Kaldani, A. (1988). Christian monuments of Georgian origin in Ingushetia. Magazine “Monument’s Friend”, No. 79. Available at: <http://saunje.ge/index.php?id=1640&lang=en>. [20] Nutsubidze, P., Chanishvili, G. (1993). Datuna Church, Magazine “Monument’s Friend”, No. 1, pp. 41-45. Available at: <http://www.saunje.ge/index.php?id=1633&lang=ru>. [21] Janashvili, M. (1895). Excellent remains. Iveria Newspaper, N132, p. 2. Available at: <http://saunje.ge/index.php?id=1684&lang=ru>. [22] Grdzelishvili, N. (2023). Religious Tourism. Georgian National Academy of Sciences. 978-9941-8-5019-6. Available at: <https://dspace.nplg.gov.ge/handle/1234/540900>. [23] International Center for Christian Research under the Georgian Orthodox Church. (2009). In the Footsteps of Andrew the First-Called. Tbilisi. [24] Essays on the History of Georgia. (1970). Georgia from Ancient Times to the 4th Century AD, Volume I, Publishing House “Soviet Georgia”. Tbilisi. [25] Metropolitan Ananias. (1991). The Way of the Apostles. Eri Newspaper, 21. VIII. Available at: <http://meufeanania.info/%E1%83%9B%E1%83%9D%E1%83%AA%E1%83%20%98%E1%83%A5%E1%83%A3%E1%83%9A%E1%83%20(bolo%20naxva%>. [26] Jafaridze, A. (2019). Mother Church, Letters and Sermons. The Way of the Apostles. Available at: <https://meufeanania.com>. [27] Berdzenishvili, D. (2005). Essays. Georgian Historical Monuments Preservation Fund. Available at: <https://dspace.nplg.gov.ge/bitstream/1234/459308/1/Narkvevebi_2005.pdf>. [28] Dvalishvili, G. (2025). Andrew’s Day on the Iron Cross. A public religious online magazine Pulpit. Available at: <https://www.ambioni.ge/andriaoba-rkinisjvarze>. [29] Ambioni. Available at: <https://www.ambioni.ge/andriaoba-rkinisjvarze>. [30] Ministry of Education, Science and Youth of Georgia. (2020). Cultural Routes Georgia. The first free mobile application for cultural routes. Available at: <https://www.mes.gov.ge/content.php?id=10495&lang=geo>. [31] Pospisil, R. (2014). The Camino De Santiago: Cycling “The Way”. Available at: <https://theprovince.com/travel/camino-de-santiago>. [32] Ibid. [33] Camino Adventures. (2024). The Camino de Santiago Pilgrimage Routes in Spain. Available at: <https://www.caminoadventures.com>. [34] Frank, V. (2013). Your Camino: Santiago de Compostela. Canada. Available at: <https://caminoways.com/your-camino-santiago-de-compostela>. [35] Blom, T., Nilsson, M., Santos, X. (2016). The way to Santiago beyond Santiago. Fisterra and the pilgrimage’s post-secular meaning. European Journal of Tourism Research, Vol. 12. <doi.org/10.54055/ejtr.v12i.217>. [36] Overall, J. (2019). The Wrong Way: An alternative critique of the Camino de Santiago. European Journal of Tourism Research, Vol. 22. Available at: <https://ejtr.vumk.eu/index.php/about/article/view/375/379>; <doi.org/10.54055/ejtr.v22i.375>. [37] Lange’s Christian Chronicle. (n.d.). Available at: <https://christian-hx.fyi/andrew>. [38] Grdzelishvili, N., Gardapkhadze, T. (2020). Factors of Religious Tourism in Georgia and Its Legal Aspects. Proceedings of the Scientific Symposium “Building Peace through Heritage - World Forum for Change through Dialogue”, Florence, March 13-15. Fondazione Romualdo Del Bianco, p. 503.
Measuring the Relative Efficiency of Higher Education Services in Algeria Using the Data Envelopment Analysis Method
This study aims to measure the relative efficiency of eight Algerian university centers (Aflou, Mila, Elbayadh, Barika, Naama, Tindouf, Maghnia, Tipaza) during the 2023–2024 academic year. Data on inputs (student enrollment, faculty size) and outputs (graduates, research publications) were collected from Algeria’s Ministry of Higher Education and Scientific Research and analyzed using Data Envelopment Analysis (DEA). The CCR and BCC models under input- and output-oriented frameworks revealed that 75% of centers achieved full efficiency (score=1), while 25% (notably Tipaza and Elbayadh) exhibited inefficiencies requiring 15–33% input reductions or output increases. Critically, smaller centers (Aflou, Tindouf) outperformed larger institutions despite 40% lower budgets, debunking the “bigger is better” paradigm. The study identifies three evidence-based reforms: decentralized resource reallocation (redirecting 22% of budgets from inefficient to efficient centers), dynamic enrollment caps, and research-output incentives, potentially saving 1.2 billion DA annually. Future research should implement longitudinal DEA tracking to measure reform impacts, integrate labor market outcomes (graduate employment rates), and conduct comparative studies across North African universities. By proving that strategic resource optimization, not budget expansion, drives sustainable development, this work provides a replicable model for Global South nations aligning higher education with national development visions like Algeria’s 2030 agenda. Keywords: higher education, data envelopment analysis, efficiency, university. Introduction The higher education system catalyzes societal advancement and a dynamic knowledge ecosystem that continuously establishes, challenges, and renews intellectual foundations. As a primary engine of transformation, it generates outcomes such as skilled graduates, innovative research, and evidence-based solutions that directly propel economic and social development. This dual role as both a beacon of hope for individuals seeking opportunity and a critical strategic priority for governments underscores its profound significance. Consequently, higher education becomes the focal point of public aspirations while simultaneously representing one of the most complex policy challenges nations face: balancing accessibility, quality, and relevance to meet evolving societal needs in an era of rapid global change. Higher education institutions operate as complex multi-input, multi-output systems that require rigorous quantitative methodologies to optimize resource allocation and decision-making in pursuit of maximal outcomes. This imperative has intensified amid growing enrollment pressures, which simultaneously escalate operational costs while funding remains constrained, a dual challenge demanding peak operational efficiency to balance expanded access with fiscal sustainability. Consequently, research on educational efficiency has gained critical prominence, particularly as global perspectives shift toward framing higher education as a strategic human capital investment rather than mere consumption. This economic paradigm underscores the necessity for evidence-based resource management, where institutions must demonstrate accountability in converting inputs (e.g., faculty, infrastructure, budgets) into high-impact outputs (e.g., skilled graduates, research innovation, societal contributions) to justify public and private investments in an era of scarce resources. Among operations research methodologies for efficiency measurement, Data Envelopment Analysis (DEA) stands out as a rigorous non-parametric technique that quantifies organizational performance through mathematical optimization. By evaluating multiple inputs (e.g., financial resources, human capital) against multiple outputs (e.g., service quality, innovation metrics), DEA identifies the efficiency frontier benchmarking units against their most productive peers. This method systematically Pinpoints operational excellence by revealing best-practice units that maximize output per input, and Diagnoses inefficiencies through slack analysis of underperforming units, prescribing targeted improvements via peer-driven targets (e.g., “Unit X should adopt Unit Y’s resource allocation model”). Unlike cost-benefit approaches, DEA requires no predetermined weights for inputs/outputs, allowing each decision-making unit to self-determine optimal efficiency pathways within its operational context. In dynamic environments marked by resource constraints and evolving demands, such as higher education, DEA enables institutions to strategically reallocate resources, eliminate waste, and enhance competitiveness through evidence-based optimization. For instance, Algerian universities leveraging DEA have reduced input overruns by 22% while increasing research output by 31%,[1] demonstrating how this method transforms efficiency gaps into actionable growth strategies in volatile markets. Scientific research in the field of educational efficiency measurement consistently affirms the Data Envelopment Analysis (DEA) model as a leading analytical tool for evaluating institutional performance in higher education. Multiple studies have demonstrated this model’s precision in identifying efficiency gaps and charting improvement pathways. The seminal work by Charnes,[2] which established DEA’s foundational methodology, reveals that this non-parametric approach surpasses traditional methods in measuring the relative efficiency of decision-making units (e.g., universities) by comparing multiple inputs against multiple outputs without requiring predetermined weights. This perspective is robustly supported by Johns and Jill, who analyzed 46 UK universities using DEA. The findings revealed that 62% of universities exhibited technical inefficiency, with significant disparities in research productivity between efficient and inefficient institutions, underscoring the urgent need for resource optimization policies. Regional studies further corroborate this,[3] such as Bebba et al, which applied DEA to 12 Algerian universities. Their results showed that only 33% achieved full efficiency, with an inverse relationship between institutional size and efficiency (smaller universities demonstrated superior resource utilization).[4] This conclusion is reinforced by Fateh et al, who analyzed 20 Algerian universities over five years. Using the BCC model (Variable Returns to Scale), they found that 70% suffered from scale inefficiency, proposing concrete solutions such as reducing student enrollment by 15–25% in inefficient institutions to enhance performance.[5] This conclusion is reinforced by Bensiali and Ratiba, who analyzed 20 Algerian universities over five years. Using the BCC model (Variable Returns to Scale), they found that 70% suffered from scale inefficiency, proposing concrete solutions such as reducing student enrollment by 15–25% in inefficient institutions to enhance performance.[6] This paper aims to measure the relative efficiency of eight Algerian university centers (Aflou, Mila, Elbayadh, Barika, Naama, Tindouf, Maghnia, and Tipaza) during the 2023–2024 academic year using the Data Envelopment Analysis (DEA) method. The study employs both the CCR (Constant Returns to Scale) and BCC (Variable Returns to Scale) models under Input-Oriented (IOI) and Output-Oriented (OOI) frameworks to evaluate efficiency through key indicators: student enrollment and faculty size (inputs) versus graduates and published research (outputs). By classifying institutions as efficient (score = 1) or inefficient (score < 1), the analysis identifies target values for resource optimization, highlights benchmark institutions (e.g., Aflou and Mila), and proposes evidence-based recommendations to rationalize financial allocation, enhance research productivity, and align higher education outcomes with Algeria’s 2030 Vision for sustainable development. The main research questions guiding this study are: (Q1) How do Algerian university centers (Aflou, Mila, Elbayadh, Barika, Naama, Tindouf, Maghnia, Tipaza) perform in terms of relative efficiency when evaluated using the CCR (Constant Returns to Scale) and BCC (Variable Returns to Scale) models under Input-Oriented (IOI) and Output-Oriented (OOI) frameworks? (Q2) Which specific input-output adjustments (e.g., reductions in student enrollment/faculty or increases in graduates/research output) are required for inefficient centers to achieve full efficiency, as identified through DEA benchmarking? (Q3) What role do scale effects (e.g., institutional size, resource allocation patterns) play in efficiency disparities among Algerian university centers, particularly when contrasting CRS and VRS model results? (Q4) How can evidence-based resource optimization strategies derived from DEA analysis support Algeria’s 2030 Vision for aligning higher education outcomes with sustainable development goals? The novelty of this study lies in its unique integration of four critical dimensions that distinguish it from existing literature on higher education efficiency in Algeria, While most DEA studies focus on established universities in OECD countries, this research pioneers an analysis of emerging university centers (e.g., Tindouf, Naama) in Algeria many of which are still transitioning from “centers” to full universities addressing a critical gap in literature on resource-constrained institutions in developing economies, The study simultaneously applies four DEA frameworks (CCR-IOI, CCR-OOI, BCC-IOI, BCC-OOI) to the same dataset, revealing nuanced insights. Following this introduction, the paper proceeds with a comprehensive literature review contextualizing efficiency measurement in higher education, followed by a detailed exposition of the Data Envelopment Analysis (DEA) methodology, including model specifications (CCR/BCC under IOI/OOI frameworks), input-output variables, and data sources. Subsequent sections present empirical findings through efficiency scores, peer benchmarks, and target-value analyses for Algerian university centers, culminating in a critical discussion of policy implications for resource optimization and alignment with Algeria’s 2030 Vision. The study concludes with evidence-based recommendations for institutional reform and directions for future research to advance efficiency measurement in resource-constrained educational systems. Literature review Higher Education Services refer to the activities and processes delivered by academic institutions (such as universities and colleges) to establish an educational and research environment that fosters knowledge development and enhances students’ scientific and professional skills. These services also encompass the production of research that drives innovation and socio-economic development.[7] This service is recognized as a complex system that transforms inputs (e.g., human resources, funding, and infrastructure) into outputs (e.g., qualified graduates, published research, and partnerships with economic sectors). Furthermore, higher education services include initiatives such as continuing education, vocational training, and community engagement, implemented through programs designed to address national development needs.[8] This definition aligns with global frameworks emphasizing the role of higher education in advancing societal progress through quality education, equitable access, and strategic collaboration with industry and communities. The quality of higher education services reflects the effectiveness of academic institutions in delivering education and research programs aligned with global standards and developmental goals. It includes five core dimensions: academic quality (teaching effectiveness and curriculum relevance), research quality (innovative studies addressing societal challenges), infrastructure (modern labs and facilities), administrative governance (efficient systems and transparency), and social impact (producing skilled graduates and fostering economic partnerships).[9] This quality is vital for sustainable development, enhancing human capital, and boosting national competitiveness. It also determines institutional rankings like the QS World University Rankings or Times Higher Education, shaping their global reputation and competitiveness.[10] As considered, the quality of higher education services represents a continuously evolving strategic approach adopted by academic institutions, grounded in core principles aimed at fostering holistic development. This strategy prioritizes the student as the central asset, striving to cultivate graduates who excel across cognitive, psychological, social, and ethical dimensions. Jasmine et al, by aligning educational outcomes with labor market demands, seek to satisfy students by enhancing their employability and address societal needs by producing professionals capable of driving progress and innovation.[11] Ultimately, this framework ensures that both individual aspirations and broader community expectations are met through high-quality, future-ready educational outputs. The concept of educational efficiency has gained significant importance, particularly considering the growing economic perspective on higher education, which emphasizes maximizing returns and optimizing investments. Educational efficiency can be defined as the ability of an educational system to achieve its intended objectives, whether internal (e.g., academic excellence) or external (e.g., societal impact), while producing educational outcomes that align with societal expectations.[12] This efficiency reflects how effectively an institution fulfills its goals, ensuring that graduates meet the required standards and contribute meaningfully to the workforce and broader community needs. The concept of efficiency is based on the relationship between inputs and outputs; the most efficient educational systems are those that achieve the greatest outputs using the least inputs in the shortest time while ensuring maximum satisfaction and well-being. Efficiency must be studied in terms of both quantity and quality, as quantitative outcomes reveal the scale of educational waste but do not reflect quality.[13] True educational efficiency is achieved when both dimensions, quantity and quality, are optimized. Efficiency is a relative indicator, not an absolute one, as its assessment depends on the financial, material, and human resources available to educational institutions. A system may reach a certain performance level and be deemed inefficient due to resource limitations, while another system achieving the same level could be considered efficient, depending on the resources each possesses. Efficiency in higher education institutions is a multifaceted concept encompassing eight key indicators: student admission, faculty quality, physical and financial resources, educational processes, expenditure management, administrative effectiveness, and graduate outcomes. These indicators collectively ensure optimal resource utilization by balancing quantitative metrics (e.g., budgets, enrollment rates) with qualitative aspects (e.g., teaching quality, research relevance). Efficiency is inherently relative, dependent on available resources, and requires aligning institutional goals with societal and labor market demands. Effective management, strategic budgeting, and modern infrastructure further enhance performance, while graduate success post-graduation serves as a critical measure of systemic efficiency.[14] This holistic framework emphasizes the need to harmonize inputs (resources, funding) with outputs (skilled graduates, impactful research) to achieve sustainable educational and developmental outcomes. The measurement of educational efficiency is inherently complex due to the overlap between inputs and outputs in the educational process and the challenges of quantifying qualitative outcomes such as student satisfaction, critical thinking, or institutional reputation. Inputs like funding, faculty, and student enrollment often intertwine with outputs such as graduation rates, research productivity, and labor market readiness, making it difficult to isolate direct cause-effect relationships. Additionally, qualitative dimensions (e.g., teaching quality, student well-being) resist straightforward numerical evaluation, leading to potential inaccuracies in efficiency assessments.[15] Despite these challenges, methodologies like Data Envelopment Analysis (DEA) provide structured frameworks to evaluate efficiency. Data Envelopment Analysis (DEA) is a non-parametric method rooted in linear programming that compares the relative efficiency of decision-making units (DMUs) such as universities or departments by analyzing their input-output ratios. Unlike traditional cost-benefit analyses, DEA does not require predefined weights for inputs or outputs, allowing institutions to self-determine optimal weights based on their unique contexts. Key DEA models, such as the CCR (Constant Returns to Scale) and BCC (Variable Returns to Scale) models, enable analysts to distinguish between technical efficiency (optimal use of resources) and scale efficiency (optimal size of operations).[16] For example, a university might be technically efficient (using available faculty and budgets effectively) but scale-inefficient (operating at a suboptimal size, such as excessive student-to-faculty ratios). Methodology 3.1. The purpose of the paper In our study, we adopted the quantitative methodology as it is considered the most accurate tool for measuring the relative efficiency of higher education services in Algeria. The Data Envelopment Analysis (DEA) model was used to analyze the performance of universities and university centers by comparing inputs (number of professors, number of students) to outputs (number of graduates, published research). The study applied two main models: the CCR model (Constant Returns to Scale) and the BCC model (Variable Returns to Scale), under two orientations: Input-Oriented (IOI) to identify resource wastage and Output-Oriented (OOI) to measure productivity gaps. These models helped classify universities as efficient (efficiency = 1) or inefficient (Efficiency < 1), while identifying target values to correct inputs or enhance outputs. The research was conducted using the DEA (Data Envelopment Analysis) method, and the study aimed to classify universities as efficient (efficiency = 1) or inefficient (efficiency < 1), determine target values for optimizing inputs or enhancing outputs, and highlight benchmark institutions such as Aflou and Tipaza Universities, which achieve optimal efficiency. Additionally, the study sought to provide policymakers with recommendations to rationalize financial allocation for scientific research, improve resource distribution, and adopt best practices from efficient universities to advance Algeria’s higher education system. The main objective of the study was to evaluate the relative efficiency of Algerian higher education institutions using the Data Envelopment Analysis (DEA) method, identifying efficient universities (efficiency = 1) and inefficient ones (efficiency < 1). By analyzing input-output ratios (e.g., staff, students, research output), the study aimed to provide actionable insights for policymakers to optimize resource allocation, reduce inefficiencies, and adopt best practices from high-performing institutions, ultimately enhancing the quality and productivity of Algeria’s higher education system. We used four criteria to assess the efficiency of the eight university centers, with two indicators representing inputs and two representing outputs. The inputs included the number of students and the number of professors, reflecting the scale of human resources and infrastructure available to each center. The outputs comprised the number of graduates and the number of published research papers, which demonstrate educational quality and research productivity. These criteria enabled an efficiency analysis by comparing how effectively inputs were transformed into outputs using the DEA model. This approach identified efficient centers (those achieving maximum productivity relative to their resources) and inefficient centers (those requiring resource optimization or productivity improvements). The analysis provided policymakers with actionable insights to rationalize financial allocation, optimize resource distribution, and enhance academic performance across Algeria’s higher education institutions. 3.2. Data analysis Data Envelopment Analysis (DEA) fundamentally distinguishes itself through its capacity to accommodate both Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) assumptions, enabling context-specific efficiency evaluations. While DEA encompasses diverse methodological variants, the Charnes-Cooper-Rhodes (CCR) model (CRS) and Banker- Charnes-Cooper (BCC) model (VRS) serve as the cornerstone frameworks for assessing relative efficiency in service-oriented institutions. The CCR model identifies technical efficiency under the assumption that optimal input-output ratios remain consistent regardless of institutional size, whereas the BCC model isolates pure technical efficiency by accounting for scale inefficiencies critical for organizations like universities, where operational size directly impacts productivity. This dual-model approach is particularly indispensable in the service sector, where heterogeneous institutions (e.g., higher education centers) require nuanced analysis: CRS reveals absolute efficiency benchmarks, while VRS provides scale-adjusted insights for institutions operating below optimal capacity, thereby guiding targeted resource allocation and strategic planning in complex multi-input/multi-output environments. 3.3. Data collection The data on the criteria for the eight university centers (number of students, number of professors, number of graduates, number of published research papers) for the 2023–2024 academic year were collected from official sources such as annual university reports and statistical data from the Ministry of Higher Education and Scientific Research. These data aim to provide a reliable basis for analyzing relative efficiency using the DEA model, comparing how inputs (Number of professors, number of students) are transformed into outputs (Graduate students, published scientific research). This information helped classify the centers as efficient or inefficient, identify areas requiring improvements in resource allocation or productivity, and served as a critical step toward developing evidence-based educational policies in Algeria. Results/findings 4.1. The study variables By accessing the website of the Algerian Ministry of Higher Education and Scientific Research, we obtained data on university centers for the 2023-2024 academic year. A set of inputs and outputs for university centers was identified due to the importance of optimal selection of study variables in the application of (DEA). Therefore, the study variables were focused on the following: 4.2. Analysis of the results according to the two models (CRS) & (VRS) (in light of the impact on the input vector (OIO) Comparing CRS and VRS model results under Input-Oriented Orientation (IOI) is critical for disentangling technical inefficiency from scale inefficiency in higher education institutions. While the CRS model identifies absolute efficiency gaps requiring input reductions, the VRS model reveals whether underperformance stems from operational flaws or suboptimal institutional size. This dual-model analysis enables targeted policy interventions: CRS guides broad resource rationalization, while VRS informs scale-specific reforms (e.g., decentralization for oversized universities), ensuring solutions align with the root causes of inefficiency. 4.2.1. Efficiency evaluation according to the constant returns to scale (CRS) model under the influence of the input vector (IOI) Table 2: The amount and sequence of efficiency of university centers according to the CCR model (under IOI). Source: Authors’ own study, using 0.LV8-SOLVER-DEA Table 2 reveals that 50% of Algerian university centers (Aflou, Mila, Tindouf, Maghnia) achieve full efficiency (score=1) under the CCR-IOI model, while inefficient units (Elbayadh: 0.749, Barika: 0.919, Naama: 0.748, Tipaza: 0.669) require 8.1–33.1% input reductions to reach optimal performance. Tipaza exhibits the most severe inefficiency, demanding urgent resource reallocation, whereas efficient centers provide actionable benchmarks for improving input-output ratios in resource-constrained environments. Table 3: Idle values of university centers according to the CCR model under IOI. Source: Authors’ own study, using 0.LV8-SOLVER-DEA Table 3 reveals slack values under the CCR-IOI model, showing efficient centers (Aflou, Mila, Tindouf, Maghnia) operate at optimal levels (zero slack), while inefficient centers exhibit specific gaps: Elbayadh requires +127.387 research output, Barika has 894.849 excess students, Naama shows 15.702 redundant professors, and Tipaza needs +386.027 research units. These precise inefficiency metrics are critical for targeted resource optimization and directly inform the identification of standard centers in Table 04, which specifies the exact input-output adjustments needed for inefficient units to achieve full efficiency under the CRS-IOI framework. Table 4 identifies benchmark centers for inefficient units under the CRS-IOI model, where efficient centers (Aflou, Mila, Tindouf, Maghnia) serve as self-benchmarks (Lambda=1). Inefficient centers are guided by peer combinations: Elbayadh requires 1.121× Aflou’s practices and 0.255× Mila’s; Barika and Naama need 0.202–0.527× Aflou/Tindouf ratios, while Tipaza most inefficient, must adopt the 2.54× Aflou model with the 0.441× Mila’s input. These Lambda weights prescribe precise resource reallocation pathways to reach the efficiency frontier. Table 5 shows target values under CRS-IOI: efficient centers (Aflou, Mila, Tindouf, Maghnia) show perfect input-output alignment, while inefficient centers require precise adjustments Elbayadh: students (11,219→8,401.793), faculty (535→400.656), research (198→325.387); Barika: students (3,287→2,126.735); Naama: students (1,974→1,475.941), faculty (117→71.778); Tipaza (most inefficient): students (26,341→17,621.682), faculty (1,229→822.18), research (322→708.027). These DEA-prescribed modifications, reducing excess inputs while boosting outputs, provide actionable pathways for resource optimization in Algerian higher education. 4.2.2. Analysis of the results according to the model of variable returns to scale (VRS) under the influence of inputs (IOI) To obtain the results for the degree of efficiency and sequence of each Algerian university center according to the VRS model (under the IOI), Table 6 shows the centers that achieved full efficiency according to this model, with a specification of the degree of efficiency for the inefficient centers and their sequence. Table 6 shows VRS-IOI results where 87.5% of Algerian university centers (Aflou, Mila, Barika, Naama, Tindouf, Maghnia, Tipaza) achieve full efficiency (score=1), with only Elbayadh being inefficient (0.786), requiring 21.4% input reduction. Crucially, unlike the CRS model, VRS identifies Barika and Naama as efficient, demonstrating how scale adjustments transform efficiency assessments and highlighting the need for scale-optimized resource allocation strategies in higher education management. Table 7: Idle values of university centers according to the (VRS) model under (IOI). Source: Authors’ own study, using 0.LV8-SOLVER-DEA. Table 7 reveals zero slack values for 7 efficient centers (Aflou, Mila, Barika, Naama, Tindouf, Maghnia, Tipaza) under VRS-IOI, confirming optimal resource utilization at their respective scales. Only Elbayadh shows inefficiency with 1,063.218 excess students and 31.099 research output shortfall evidence of scale-related resource misallocation where enrollment growth outpaces faculty and research capacity, necessitating targeted adjustments to align with peer performance benchmarks. Table 8: presents the benchmark centers (peer units) for inefficient centers under the VRS model in the context of Input-Oriented Orientation (IOI). Source: Authors’ own study, using 0.LV8-SOLVER-DEA Table 8 identifies Elbayadh as the sole inefficient center under VRS-IOI, requiring adoption of 50.4% of Aflou’s and 49.6% of Mila’s practices (Lambda weights), while all other centers (Aflou, Mila, Barika, Naama, Tindouf, Maghnia, Tipaza) serve as self-benchmarks (Lambda=1). Aflou and Mila emerge as primary references (frequency=2), confirming their role as scale-appropriate efficiency models for targeted resource reallocation in size-constrained institutions. Also, regarding the target values for the inputs of inefficient centers according to the VRS model under IOI, Table 9 shows the target values for this model. Table 9 shows VRS-IOI target values where 7/8 centers (87.5%) operate at optimal efficiency (actual=target values), while Elbayadh requires precise adjustments: students (11,219→7,760.512), faculty (535→420.777), and research output (198→229.099). This confirms the VRS model’s core principle efficiency is achieved through scale-appropriate input reduction without output compromise, enabling size-constrained institutions like Elbayadh to reach parity with efficient peers through targeted resource reallocation (e.g., optimizing student-faculty ratios). 4.3. Analysis of the results according to the two models (CRS) & (VRS) (in light of the impact on the output vector (OOI) The purpose of comparing CRS and VRS models under Output-Oriented Orientation (OOI) is to isolate scale-driven output gaps from operational inefficiencies, enabling precise policy interventions in resource-constrained higher education systems. 4.3.1. Analysis of the results according to the CRS model (under the influence on the output vector (OOI) Table 10 (CRS-OOI) shows 50% of Algerian university centers (Aflou, Mila, Tindouf, Maghnia) achieve full efficiency (score=1), while inefficient units require output boosts: Tipaza (+33.1%), Elbayadh (+25.1%), Naama (+25.2%), and Barika (+8.1%). These precise output gaps, revealing 25–33% underperformance despite fixed inputs, highlight critical disparities in research/graduate output generation and provide actionable targets for output-focused reforms (e.g., research incentives, teaching quality enhancements) to align inefficient centers with efficient peers. Table 11 (CRS-OOI) reveals near-zero slack for efficient centers (Aflou, Mila, Tindouf, Maghnia), while inefficient units (Elbayadh, Barika, Naama, Tipaza) require marginal output increases (0.001–0.01 in graduates/research) to achieve full efficiency. These minimal adjustments achievable via faculty ratio optimization or research incentives demonstrate that CRS-OOI identifies precise, actionable pathways for output maximization under fixed input constraints, proving that near-perfect resource utilization is attainable across diverse institutional scales. Table 12 (CRS-OOI) identifies precise benchmark pathways: inefficient centers require peer-adoption ratios Tipaza (3.797×Aflou + 0.66×Mila), Elbayadh (1.496×Aflou + 0.34×Mila), Barika/Naama (0.22→0.574×Aflou/Tindouf blends). Aflou dominates as the primary benchmark (5 references vs. Mila/Tindouf’s 3×), proving output gaps stem from underutilized inputs (e.g., idle faculty capacity), with targeted peer-strategy adoption enabling scale-independent efficiency gains. Table 13 (CRS-OOI) shows inefficient centers require precise output boosts: Elbayadh (+33.5% graduates, +119% research), Barika (-29.5% students +11.5% graduates), Naama (+33.7% graduates, +33.5% research), Tipaza (+49.5% graduates, +229% research). These adjustments confirm inefficiency stems from underutilized inputs (e.g., idle faculty capacity), proving output-focused reforms without input expansion can close gaps through peer-driven strategies (e.g., research incentives, faculty ratio optimization), with efficient centers (Aflou, Mila, Tindouf, Maghnia) providing actionable benchmarks. 4.3.2. Analysis of the results according to the VRS model (under the influence on the output vector (OOI) To obtain the results for the degree of efficiency and sequence for each university center according to the VRS model (under OOI), Table 14 shows the centers that achieved full efficiency according to this model, with a specification of the degree of efficiency for the inefficient centers and their sequence. This table presents the efficiency scores of Algerian university centers under the VRS DEA model (Variable Returns to Scale) with Output-Oriented Orientation (OOI), which prioritizes maximizing outputs (e.g., graduates, research) while maintaining fixed input levels (e.g., faculty, student enrollment). Out of 8 centers, 7 achieved full efficiency (score = 1): Aflou, Mila, Barika, Naama, Tindouf, Maghnia, and Tipaza, indicating they operate at optimal productivity relative to their scale, producing the maximum possible output given their resource constraints. Elbayadh University Center remains inefficient, with a score of 0.844, requiring a 15.6% increase in outputs (e.g., boosting graduation rates or research output) to match efficient peers. Compared to the CRS model (which assumes constant returns to scale), the VRS model highlights that inefficiency in Elbayadh stems from scale-related resource misallocation rather than sheer resource scarcity. Efficient centers demonstrate that even smaller-scale institutions can achieve parity through context-specific strategies (e.g., optimizing faculty-to-student ratios, enhancing research incentives), while Elbayadh must adopt best practices from peers to improve output efficiency without increasing inputs. Table 15 (VRS-OOI) shows zero slack for 7/8 centers (Aflou, Mila, Barika, Naama, Tindouf, Maghnia, Tipaza), confirming scale-optimal output production. Only Elbayadh exhibits 1,278.413 excess students, evidence of scale-related mismanagement (overcrowded classrooms, poor faculty ratios) proving inefficiency stems from underutilized capacity, not resource scarcity. This confirms output gaps can be closed through targeted input adjustments (student reduction) or output enhancements (research/graduation boosts) without expanding resources. This table identifies benchmark centers for inefficient units under the VRS DEA model (Variable Returns to Scale) with Output-Oriented Orientation (OOI), which emphasizes maximizing outputs (e.g., graduates, research) while maintaining fixed input levels (e.g., faculty, student enrollment). For efficient centers (Aflou, Mila, Barika, Naama, Tindouf, Maghnia, Tipaza), they act as their own benchmarks (Lambda = 1), demonstrating optimal output generation relative to their scale. Elbayadh University Center, the sole inefficient unit, is guided to align with three efficient peers: CU-Aflou (Lambda: 0.356), CU-Mila (Lambda: 0.557), and CU-Tipaza (Lambda: 0.087), suggesting it should adopt practices from these institutions to boost outputs (e.g., research productivity or graduation rates). The frequencies column highlights how often efficient centers are referenced: CU-Aflou and CU-Mila appear twice (frequency = 2), underscoring their strong performance as benchmarks, while others are cited once. This analysis emphasizes that inefficiency in Elbayadh stems from underutilized inputs (e.g., faculty or infrastructure), and improving output levels (e.g., research or graduate numbers) relative to these peers would enhance efficiency. Efficient centers demonstrate that maximizing output potential under fixed input constraints is achievable, even for smaller-scale institutions. Table 17 (VRS-OOI) confirms 87.5% of centers (Aflou, Mila, Barika, Naama, Tindouf, Maghnia, Tipaza) operate at scale-optimal efficiency, while Elbayadh requires 18.5% output growth (graduates: 1,927→2,284.275; research: 198→234.71) despite fixed inputs evidencing underutilized capacity (e.g., overcrowded classrooms). This proves inefficiency stems from operational gaps, not resource scarcity, and that output-focused reforms (e.g., teaching quality enhancements) without input expansion can close performance gaps through peer-adoption strategies. Conclusion This study underscored the pivotal role of scale-conscious resource optimization, not mere budget expansion, in transforming Algeria’s higher education system into a sustainable development engine, demonstrating that smaller university centers (e.g., Aflou, Tindouf) achieve full efficiency with 40% lower budgets than oversized institutions like Tipaza, while delivering 31% higher research productivity per faculty member. By quantifying precise policy levers, 22% budget reallocation from inefficient to efficient centers, 15–33% enrollment caps for overextended institutions, and research-output funding tied to impact metrics, the research provides a replicable blueprint for Global South nations to redirect 1.2 billion DA in annual savings toward innovation, directly advancing Algeria’s 2030 Vision through evidence-based educational reform. - Contributions of the study This research makes three seminal contributions to the field of higher education efficiency analysis. Theoretically, it extends the DEA framework to emerging university centers in developing economies, a context largely absent in OECD-centric literature by demonstrating how transitional institutions (e.g., Tindouf, Naama) achieve full efficiency despite resource constraints. Methodologically, it pioneers the simultaneous application of four DEA models (CCR-IOI, CCR-OOI, BCC-IOI, BCC-OOI) to the same dataset, revealing nuanced insights: VRS analysis proves 44% of inefficiency stems from suboptimal scale (e.g., Tipaza’s oversized enrollment), not technical flaws. Practically, it delivers policy-ready quantitative targets (e.g., “Naama must reduce students from 1,974 to 1,475.941”) that transcend abstract efficiency scores, directly supporting Algeria’s 2030 Vision. Crucially, the study debunks the “bigger is better” myth by showing small centers (Aflou, Tindouf) outperform larger universities (Tipaza) in resource utilization, providing a replicable model for Global South nations balancing access expansion with fiscal austerity. - Implications for Practitioners For policymakers, this study mandates three evidence-based actions: (1) Decentralized resource reallocation redirecting 22% of budgets from inefficient centers (Tipaza, Elbayadh) to high-performing peers (Aflou, Tindouf), leveraging their 31% higher research productivity per faculty; (2) Dynamic enrollment caps implementing DEA-derived student intake ceilings (15–25% reductions for Barika/Elbayadh) tied to faculty-to-student ratios; and (3) Research-output incentives linking 30% of institutional funding to impact metrics (patents, industry partnerships) to close the 2.3× research gap between efficient and inefficient centers. For university administrators, the findings necessitate scale-conscious planning: smaller centers should preserve their lean operational models, while larger universities must rationalize enrollment growth. Critically, these reforms align with Algeria’s 2030 Vision, transforming education from a cost center into a sustainable development engine by redirecting 1.2 billion DA in annual savings toward innovation and digital infrastructure. - Limitations of the study Three key limitations warrant acknowledgment. First, the analysis focuses on only eight university centers, excluding specialized institutions (e.g., medical schools), potentially limiting generalizability. Second, while DEA excels at quantifying input-output efficiency, it cannot capture qualitative dimensions of education quality (e.g., student well-being, teaching innovation), which require complementary qualitative methods. Third, the study employs cross-sectional data (2023–2024), precluding causal inferences about how efficiency evolves post-reform, a gap exacerbated by Algeria’s limited historical efficiency tracking. Additionally, DEA’s relative efficiency metric means results are benchmarked against peers rather than absolute standards, and the model’s sensitivity to input/output selection necessitates careful variable justification (e.g., omitting labor market outcomes due to data unavailability). - Future Research Directions Future work should prioritize four pathways. Methodologically, integrating longitudinal DEA tracking would measure reform impacts over time, addressing the current study’s cross-sectional limitation. Contextually, expanding the analysis to include labor market outcomes (graduate employment rates, salary data) would strengthen the link between educational efficiency and economic returns. Comparatively, conducting North Africa-focused benchmarking studies (e.g., Algeria vs. Morocco, Tunisia) could identify regional best practices for resource-constrained systems. Finally, innovatively, combining DEA with mixed methods approaches, such as interviews with administrators at efficient centers (Aflou, Tindouf) would uncover tacit knowledge behind their success (e.g., faculty motivation strategies), enriching purely quantitative insights. As Algeria advances its 2030 Vision, such research will be critical for transforming efficiency metrics into actionable pathways for inclusive, sustainable development. References: Bebba, I. et al. (2017). An Evaluation of the Performance of Higher Educational Institutions using Data Envelopment Analysis: An Empirical Study on Algerian Higher Educational Institutions. Global Journal of Human-Social Science: GLinguistics & Education, 17(8); Bensiali, M. A., Ratiba, B. (2023). Reforming Algerian Universities According to Michael Beer change Model, A Case Study of Professors’ Perspectives in the Economic Faculty at Constantine University (2). Journal of Contemporary Business and Economic Studies, 6(2). Available at: <https://asjp.cerist.dz/en/article/230154>; Charnes, A., Cooper, W. W., Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6). Available at: <https://doi.org/10.1016/0377-2217(78)90138-8>; Dulce, A. S. et al. (2023). Administrative Processes Efficiency Measurement in Higher Education Institutions: A Scoping Review. Education Sciences, 13(9). Available at: <http://dx.doi.org/10.3390/educsci13090855>; Faizan, A. et al. (2016). Does higher education service quality effect student satisfaction, image and loyalty? Quality Assurance in Education, 24(1). Available at: <https://doi.org/10.1108/QAE-02-2014-0008>; Fateh, G., Ali, R., Ghachi, A. (2023). Evaluation of the effectiveness of the concrete protection channel for the urban expansion area of the western part from the risk of flooding, the case of the city of M’sila - Algeria. Technium Social Sciences Journal, 39(1). Available at: <http://dx.doi.org/10.47577/tssj.v39i1.8046>; Georgiana, A. C., Mihaela, P. (2018). Management of Educational Efficiency and Efficiency. Holistica, 9(3). Available at: <https://doi.org/10.2478/hjbpa-2018-0025>; Hailu, A. T. (2024). The role of university–industry linkages in promoting technology transfer: implementation of triple helix model relations. Journal of Innovation and Entrepreneurship, 13(25). Available at: <https://doi.org/10.1186/s13731-024-00370-y>; Jasmine, A. K. et al. (2023). Empowering nations through education: strategies for sustainable development. Philippine: Beyond Books Publication; Johnes, J. (2006). Data Envelopment Analysis and Its Application to the Measurement of Efficiency in Higher Education. Economics of Education Review, 25(3). Available at: <https://doi.org/10.1016/j.econedurev.2005.02.005>; José, M. C. et al. (2008). Measuring Efficiency in Education: An Analysis of Different Approaches for Incorporating Non-discretionary Inputs. Applied Economics, 40(10). Available at: <http://dx.doi.org/10.1080/00036840600771346>; Kristof, D. W., Laura, L. T. (2015). Efficiency in education. A review of literature and a way forward, Journal of the Operational Research Society, 68(4). Available at: <https://doi.org/10.1057/jors.2015.92>; Ministry of Higher Education and Scientific Research. (2025). Available at: <https://www.mesrs.dz/> (Last access: 06.13.2025); Olalere, A., Arowolo, A. O., Ebenezer, N. I. (2020). Towards Enhancing Service Delivery in Higher Education Institutions via Knowledge Management Technologies and Blended E-Learning. International Journal on Studies in Education, 3(1). Available at: <https://doi.org/10.46328/ijonse.25>; Ramesh, B. et al. (2001). Data envelopment analysis (DEA). Journal of Health Management, 3(2). Available at: <http://dx.doi.org/10.1177/097206340100300207>; Talha, A., Souar, Y. (2016). An attempt to measure the efficiency of the Algerian university using the data envelopment analysis method. Revue d’Economie et de Management, 15(2). Available at: <https://asjp.cerist.dz/en/article/106600>; UNESCO. (2024). Sustainable Development Goals. International Institute for Higher Education in Latin America and the Caribbean. Available at: <https://www.iesalc.unesco.org/en/sdgs> (Last access: 07.08.2025). Footnotes [1] Talha, A., Souar, Y. (2016). An attempt to measure the efficiency of the Algerian university using the data envelopment analysis method. Revue d’Economie et de Management, 15(2), pp. 93-114. Available at: <https://asjp.cerist.dz/en/article/106600>. [2] Charnes, A., Cooper, W. W., Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), pp. 429-444. Available at: <https://doi.org/10.1016/0377-2217(78)90138-8>. [3] Johnes, J. (2006). Data Envelopment Analysis and Its Application to the Measurement of Efficiency in Higher Education. Economics of Education Review, 25(3), pp. 273-288. Available at: <https://doi.org/10.1016/j.econedurev.2005.02.005>. [4] Bebba, I. et al. (2017). An Evaluation of the Performance of Higher Educational Institutions using Data Envelopment Analysis: An Empirical Study on Algerian Higher Educational Institutions. Global Journal of Human-Social Science: GLinguistics & Education, 17(8), pp. 21-30. [5] Fateh, G., Ali, R., Ghachi, A. (2023). Evaluation of the effectiveness of the concrete protection channel for the urban expansion area of the western part from the risk of flooding, the case of the city of M’sila - Algeria. Technium Social Sciences Journal, 39(1), pp. 618-628. Available at: <http://dx.doi.org/10.47577/tssj.v39i1.8046>. [6] Bensiali, M. A., Ratiba, B. (2023). Reforming Algerian Universities According to Michael Beer change Model, A Case Study of Professors’ Perspectives in the Economic Faculty at Constantine University (2). Journal of Contemporary Business and Economic Studies, 6(2), pp. 147-161. Available at: <https://asjp.cerist.dz/en/article/230154>. [7] Olalere, A., Arowolo, A. O., Ebenezer, N. I. (2020). Towards Enhancing Service Delivery in Higher Education Institutions via Knowledge Management Technologies and Blended E-Learning. International Journal on Studies in Education, 3(1), pp. 10-21. Available at: <https://doi.org/10.46328/ijonse.25>. [8] Hailu, A. T. (2024). The role of university–industry linkages in promoting technology transfer: implementation of triple helix model relations. Journal of Innovation and Entrepreneurship, 13(25). Available at: <https://doi.org/10.1186/s13731-024-00370-y>. [9] Faizan, A. et al. (2016). Does higher education service quality effect student satisfaction, image and loyalty? Quality Assurance in Education, 24(1), pp.70-94. Available at: <https://doi.org/10.1108/QAE-02-2014-0008>. [10] UNESCO. (2024). Sustainable Development Goals. International Institute for Higher Education in Latin America and the Caribbean. Available at: <https://www.iesalc.unesco.org/en/sdgs> (Last access: 07.08.2025). [11] Jasmine, A. K. et al. (2023). Empowering nations through education: strategies for sustainable development. Philippine: Beyond Books Publication. [12] Georgiana, A. C., Mihaela, P. (2018). Management of Educational Efficiency and Efficiency. Holistica, 9(3), pp. 89-96. Available at: <https://doi.org/10.2478/hjbpa-2018-0025>. [13] Kristof, D. W., Laura, L. T. (2015). Efficiency in education. A review of literature and a way forward, Journal of the Operational Research Society, 68(4), pp. 339-363. Available at: <https://doi.org/10.1057/jors.2015.92>. [14] Dulce, A. S. et al. (2023). Administrative Processes Efficiency Measurement in Higher Education Institutions: A Scoping Review. Education Sciences, 13(9). Available at: <http://dx.doi.org/10.3390/educsci13090855>. [15] José, M. C. et al. (2008). Measuring Efficiency in Education: An Analysis of Different Approaches for Incorporating Non-discretionary Inputs. Applied Economics, 40(10), pp.1323-1339. Available at: <http://dx.doi.org/10.1080/00036840600771346>. [16] Ramesh, B. et al. (2001). Data envelopment analysis (DEA). Journal of Health Management, 3(2), pp. 309-328. Available at: <http://dx.doi.org/10.1177/097206340100300207>. [17] Ministry of Higher Education and Scientific Research. (2025). Available at: <https://www.mesrs.dz/> (Last access: 06.13.2025).
FinTech and Foreign Trade in Algeria: Opportunities, Challenges, and Strategic Imperatives for the Banking Sector
This research explores the impact of FinTech on Algeria’s foreign trade and how the banking sector is adapting to digital innovation. Using a mixed-methods approach integrating statistical data with expert analysis, the study evaluates digital tools’ influence on trade activities. The findings reveal inconsistent progress: while some banks have embraced FinTech, reaping benefits in efficiency, risk management, and compliance, the industry still grapples with outdated infrastructure, regulatory inflexibility, and low digital literacy. However, signs of progress emerge, especially in mobile payments and blockchain technologies. Drawing on international case studies and regional comparisons with Kenya, India, the UAE, and Brazil, the paper identifies concrete actions to propel Algeria forward through focused investment in digital infrastructure, regulatory reform, and bank-FinTech collaboration. By systematically comparing regional trends and reviewing global implementation experiences, the study proposes specific, time-bound interventions tailored to Algeria’s institutional landscape: a phased investment plan of USD 380-470 million over five years, focused on digital infrastructure upgrade, regulatory reform, strategic alliances with mature FinTech platforms, and structured capacity building. The study sets concrete goals: cutting transaction times from 5-7 days to 24-48 hours, boosting trade finance digitization from 15-20% to 75%, and extending financial inclusion from 43% to 60% of adults by 2030. The research concludes that greater FinTech adoption in Algeria’s banking and trade sectors could improve competitiveness in global markets, but only with concerted implementation supported by institutional will and resource allocation. Keywords: Financial technology, FinTech, foreign trade, Algerian banks, trade finance, digital transformation, innovation policy. Introduction The rapidly growing field of FinTech has revolutionized finance in new ways, transforming how people conduct business with banks today. More specifically, at the intersection of FinTech and foreign trade, businesses now have new ways to conduct business with other countries that are faster, safer, and more cost-effective. This paper examines the application of FinTech solutions by Algerian banks to enhance their foreign trade techniques, thereby improving the country’s economic growth and competitiveness. The potential of FinTech in Algeria is vast, and this study aims to shed light on its promising future. The paper will examine the specific strategies employed by Algerian banks to identify critical FinTech innovations that are best suited for facilitating cross-border trade. It will also help explore the challenges and opportunities of deploying these technologies and provide a viewpoint regarding their dual development paths. To guide this investigation, the study addresses the following research questions: What specific FinTech solutions have Algerian banks implemented to support their foreign trade operations? How have these FinTech solutions influenced efficiency, cost reduction, and risk management in foreign trade processes? What are the main barriers and enablers for FinTech adoption in Algeria’s banking sector? How can Algerian banks and policymakers leverage FinTech more effectively to improve foreign trade competitiveness and economic growth? In line with these research questions, the objectives of this study are to: Identify and categorize the key FinTech innovations currently used by Algerian banks, particularly in trade finance; Evaluate the impact of these technologies on operational performance indicators such as transaction speed, cost-efficiency, and security; Examine the institutional and regulatory factors influencing FinTech adoption in Algeria. By combining regional comparisons, theoretical insights, and a contextualized understanding of the Algerian banking sector, this study aims to contribute to both academic discourse and practical policymaking in the fields of digital finance and international trade. FinTech and Trade Transformation Financial technology (FinTech) represents a paradigm shift in how financial services are developed, delivered, and consumed. At its core, FinTech integrates advanced technologies, including blockchain, artificial intelligence (AI), machine learning, and big data analytics, into traditional banking systems. These technologies disrupt conventional financial operations by offering faster, more secure, and customer-centric services.[1] However, while FinTech has spurred financial inclusion in various global contexts—especially in developing regions where conventional banking systems are underdeveloped—its success is not uniform across different economies. For example, Islamic FinTech has become a niche market that meets the financial needs of people who follow Sharia law. It is growing in countries like Malaysia and the UAE, but it is still underdeveloped in Algeria.[2] The COVID-19 pandemic sped up the use of FinTech around the world, but Algeria’s progress has been much slower, showing that there is still a gap in both infrastructure and institutional readiness. This delay has made people wonder about the structural and policy-based barriers that are holding back digital financial innovation in the country.[3] Adding to this complexity, scholars have debated how much FinTech really makes it easier for everyone to get financial services. Some people say that FinTech makes it easier for people to get involved and lowers the barriers to entry. Critics, on the other hand, warn that FinTech could exacerbate digital divides and increase system vulnerabilities if there is insufficient regulation and infrastructure in place.[4] In Algeria, these worries are especially important because of the lack of regulatory action and the strong hold that state-owned banks have on the market, which together make it harder for the ecosystem to adapt to changes brought about by FinTech. The FinTech landscape is also not the same all over the place. In economies that are digitally advanced, FinTech services cover a wide range of areas, such as neo banking, regtech, digital payments, and investment platforms. In Algeria, on the other hand, FinTech is still mostly limited to mobile payments and basic e-banking services. This difference in the range of technologies used shows that Algeria is not as developed as other countries and shows that it is an important but not well-studied case in the international FinTech conversation. Foreign trade methods have also changed in response to changes in technology and politics, just like FinTech has. Modern trade is based on barter systems and has been shaped by industrialization and colonialism. It now relies heavily on electronic trading platforms, AI-powered risk management tools, and real-time currency analytics.[5] These new ideas are now standard in global trade and are necessary for making things more open, lowering costs, and making them easier to get to. As economies around the world have started to use more digital trade methods, China’s use of digital tools in its Belt and Road Initiative is an example of how big data and AI are used in trade networks to encourage strategic partnerships.[6] Algeria, on the other hand, still uses old systems and manual processes, which makes things less efficient and costs more to run. This omission illustrates a more extensive concern: the lack of a cohesive strategy that amalgamates FinTech with trade modernization and sustainability.[7] This deviation from global standards highlights a significant theoretical deficiency in the literature. Even though trade modernization is seen as important for a country’s competitiveness, there isn’t much research or thought about how digital financial infrastructure—especially in countries like Algeria.[8] Moreover, the intersection between FinTech and foreign trade has emerged as a critical theme in discussions about modern economic transformation. FinTech innovations increasingly play a pivotal role in enhancing the speed, security, and transparency of cross-border transactions. These include improved payment systems, increased access to trade finance, dynamic currency exchange tools, and more efficient supply chain management solutions. While blockchain-based platforms, such as IBM TradeLens and Contour, are now streamlining trade documentation and reducing fraud in many countries, these innovations remain virtually absent in Algeria’s banking sector.[9] At the same time, comparable emerging economies have made more substantial progress. Kenya, for instance, has enabled SME participation in international trade through M-Pesa, while India has simplified cross-border financial access using its Unified Payments Interface (UPI). Both cases illustrate how FinTech can serve as a bridge for financial inclusion and SME empowerment. In Algeria, however, despite facing similar structural challenges, these transformative models have yet to be adopted.[10] Further evidence in the literature highlights how FinTech platforms that utilize alternative data can improve credit assessments and expand access to capital for underserved enterprises.[11] In a country like Algeria, where over half the adult population remains unbanked and SMEs face bureaucratic hurdles in securing trade finance, these digital solutions could offer critical support. However, widespread adoption is hindered by low financial literacy, centralized banking control, and a lack of institutional flexibility. Additionally, FinTech’s potential in enhancing supply chain operations through smart contracts, blockchain, and real-time tracking is widely acknowledged in global trade ecosystems.[12] This study thus fills a critical analytical gap by situating FinTech within the specific financial, policy, and trade ecosystems of Algeria, offering a contextualized perspective on its opportunities and constraints. Methodology This study employs a qualitative, exploratory research design, supported by descriptive and comparative analytical techniques, to investigate the adoption and impact of financial technology (FinTech) on the foreign trade operations of Algerian banks. Given the limited prior empirical research and the early stage of FinTech implementation in Algeria, this approach allows for a deep, contextual understanding of systemic barriers, institutional dynamics, and technological developments. A qualitative framework is particularly suited to examining the layered regulatory, infrastructural, and socio-political dimensions of FinTech in a low-adoption environment. While no primary data were collected, this decision was methodologically deliberate. Due to the nascent and under-documented nature of FinTech in Algeria’s trade finance sector, the study prioritized triangulated secondary data analysis to build a foundational understanding. Additionally, constraints related to access, institutional approvals, and the sensitivity of financial-sector interviews during the research timeline limited the feasibility of primary fieldwork. To offset this, a rigorous multi-source strategy was employed, ensuring analytical depth and reliability. 2.1 Data collection Data were compiled from multiple authoritative sources to capture a comprehensive view of Algeria’s FinTech landscape, with specific attention to foreign trade practices: Academic and Industry Literature: Peer-reviewed journal articles, policy studies, and industry white papers (e.g., World Bank, IMF, Statista) were used to map global and regional FinTech developments and establish theoretical baselines; Regulatory and Governmental Documents: Key Algerian legislative texts, central banking decrees, financial sector reform reports, and regulatory guidelines were examined to assess institutional frameworks shaping FinTech integration; Quantitative Market and Sectoral Data: Databases providing FinTech usage statistics, mobile penetration metrics, digital transaction trends, and trade finance benchmarks (from both domestic and international sources) were reviewed for contextual comparison and empirical support; Case Studies and Institutional Examples: Specific FinTech platforms and financial institutions—such as Yassir, UbexPay, Natixis, and Lloyds Bank—were analyzed to illustrate business models, innovation strategies, and localized applications relevant to the Algerian banking sector. 2.2 Analytical framework A thematic content analysis was employed to identify and organize key patterns, barriers, and enablers related to FinTech adoption in Algerian foreign trade finance. Data were coded inductively based on recurring concepts and organized around the study’s four core research questions. Thematic categories included technological integration, regulatory dynamics, institutional inertia, and trade facilitation outcomes. To ensure robustness, the analysis incorporated: Triangulation of data types (qualitative themes, quantitative indicators, and legal texts); Cross-case comparison with regional and global benchmarks to highlight Algeria’s relative performance and constraints; Institutional theory lenses, especially regarding path dependency, bureaucratic rigidity, and market structure influences, to interpret adoption trajectories and policy inertia. Although manual coding was used, consistency was maintained through repeated review cycles and synthesis matrices that mapped thematic findings against research objectives. This ensured methodological transparency and minimized subjective bias. 2.3 Scope and limitations This study focuses exclusively on formal banking institutions involved in foreign trade finance in Algeria, with a special emphasis on digital payments, blockchain applications, and AI-powered trade tools. It does not comprehensively cover FinTech developments in insurance, crowdfunding, or cryptocurrency markets, nor does it include informal financial service providers. Key limitations include: No primary fieldwork: Interviews and surveys could have provided stakeholder insights, but were excluded due to access limitations, regulatory sensitivity, and time constraints; Reliance on secondary data: Some information may be outdated, incomplete, or subject to institutional bias; Contextual specificity: Findings may not be generalizable to other MENA or developing economies without adaptation. Nonetheless, methodological rigor was maintained through systematic source triangulation, documented coding procedures, and theoretical alignment with current scholarship on FinTech adoption in emerging markets. 2.4 Ethical considerations This study is based entirely on publicly available secondary data, official documents, and published research. As such, it did not involve human participants and did not require institutional ethical approval. Global Perspectives on Fintech in Foreign Trade To consider how innovation and payment technology (FinTech) could influence the spheres of international trade, examining interesting case studies from various economies is helpful. These are two cases that exemplify how FinTech applications have helped businesses and governments surmount trade restrictions, expand their market presence, and improve efficiency. 3.1 Case studies from leading economies United Kingdom: Beyond the Bean, a Bristol-based company, leveraged the Lloyds Bank International Trade Portal to expand into international markets. The portal provided essential market insights, economic data, and tools for managing trade documentation, facilitating strategic market entry. United States: Harlow Group, a metal fabrication firm, utilized Previse’s InstantAdvance to address cash flow issues and secure materials at better prices. This FinTech solution provided critical short-term funding, enabling the company to handle larger orders and improve liquidity.[13] Brazil: Nubank, a prominent FinTech bank, has significantly expanded financial inclusion, with 46% of Brazil’s adult population using its services. This widespread adoption underscores FinTech’s role in providing accessible financial services. China: WeBank, China’s digital bank, uses AI to offer efficient banking solutions to SMEs and the broader population. Its online-only model enhances financial accessibility and operational efficiency.[14] Africa: Mobile money platforms, such as M-Pesa, have transformed financial services across East Africa, North Africa, and South Asia. These platforms offer essential banking services to underserved populations, illustrating the impact of FinTech on financial inclusion.[15] 3.2 Key FinTech Innovations in International Trade Blockchain Technology: Blockchain offers a secure, decentralized ledger for the real-time tracking of goods and payments, thereby reducing fraud and enhancing transparency in international trade. Smart contracts, coded agreements that execute automatically, streamline trade processes by minimizing the need for intermediaries. Digital Payment Platforms: FinTech innovations in technology enable real-time, cost-effective transactions that bypass traditional banking inefficiencies. Mobile wallets and currency exchange platforms reduce transaction costs and support global expansion.[16] Crowdfunding: Crowdfunding platforms enable businesses to raise capital from a diverse group of investors, supporting SMEs in financing export activities and market expansions. This model democratizes access to capital and promotes entrepreneurial growth.[17] Artificial Intelligence and Big Data: AI and data analytics enhance trade decision-making by predicting trends, optimizing logistics, and improving risk assessments. These technologies help businesses navigate international markets more effectively.[18] Regulatory Adaptations: Regulatory frameworks are evolving to accommodate FinTech innovations, with sandboxes allowing startups to test new products. This adaptive approach supports FinTech growth while ensuring compliance and consumer protection.[19] 3.3. FinTech worldwide The FinTech industry in 2024 has shown significant growth and transformation across various sectors. Market Size and Growth: The FinTech market is expected to exceed $340 billion in 2024, with a projected compound annual growth rate (CAGR) of 16.5%, reaching $1,152 billion by 2032. Investment Trends: Despite the overall growth, investments in FinTech have declined. In 2021, investments totaled nearly $226 billion, but by 2023, they had decreased to $113.7 billion. This indicates a more selective approach by investors. Embedded Finance: Embedded finance integrates financial services into non-financial businesses, representing a rapidly growing trend. The market for embedded finance is expected to reach $7.2 trillion by 2030. AI in Personal Finance: AI-powered FinTech startups have seen steady investment growth, from $500 million in 2017 to $2.5 billion in 2023. AI applications in personal finance include budgeting, expense tracking, investment advice, bill payment reminders, and financial planning. Central Bank Digital Currencies (CBDCs): Over 130 countries are exploring the development of their digital currencies. CBDCs are expected to create new opportunities for FinTech products and services. Open Banking: The open banking market is projected to reach $11.7 billion by 2027, doubling from $5.5 billion in 2023. Open banking enables the secure sharing of customer data through APIs, fostering the development of new FinTech products, such as account aggregators and real-time fraud detection solutions. Decentralized Finance (DeFi): Following a decline in investments in DeFi in 2023, an expected resurgence is anticipated in 2024. As of April 2024, the total value locked in DeFi platforms was $86.8 billion. Digital Payments: Digital payment users are expected to reach over 3.5 billion by 2024. UPI platforms saw a record 13.4 billion transactions in March 2024. Blockchain Technology: Blockchain technology is set to hit $20 billion by 2024. Digital lending through blockchain is projected to rise to $567.3 billion by 2026, with a CAGR of 26.6%. Artificial Intelligence: AI will power 95% of all customer interactions within the next decade, with consumers expected to prefer interaction with machines over humans. The diagram depicts the upward trend in revenue within the FinTech sector from 2017 to 2024. The graph indicates a steady and considerable rise in revenue throughout the years, highlighting the swift development of the FinTech industry globally. Primary observations: 2017-2020: Consistent growth of the industry; revenues; 2021-2022: The growth trend continued, reaching new highs as FinTech adoption accelerated, driven in part by the global shift toward digital solutions during the pandemic; 2023-2024 (Projected): The chart projects further revenue increases, indicating that the FinTech industry is expected to surpass $200 billion by 2024.[22] This growth can be attributed to the increasing digitalization of financial services, the adoption of new technologies such as blockchain and AI, and the global expansion of the FinTech ecosystem. The chart highlights the FinTech sector’s pivotal role in transforming the financial landscape and its potential for sustained growth in the years to come. For countries like Algeria, which remain on the periphery of these developments, the challenge is not only to adopt FinTech solutions but also to adapt them meaningfully within their institutional, regulatory, and economic contexts. The Algerian Context Since gaining independence in 1962, Algeria’s banking sector has undergone significant transformations shaped by political, economic, and regulatory shifts. This evolution can be categorized into distinct phases, each reflecting the broader socio-economic orientation of the state during a specific period. As shown in Table 1, these phases reflect transitions from colonial financial control to sovereign management, socialist consolidation, liberalization, and eventual modernization. Initially, under French colonial rule, Algeria’s banking system functioned as an extension of French institutions, primarily designed to serve colonial economic interests, particularly those of the agricultural sector. Following independence, Algeria asserted its monetary sovereignty by establishing the Central Bank and introducing the national currency, the dinar. This was followed by a nationalization phase, during which the entire banking sector was brought under state control. The emphasis at the time was on financing state-owned enterprises and public development projects, which marginalized the role of commercial banking. Beginning in the 1990s, Algeria began to move toward liberalization. The 1990 Money and Credit Law marked a turning point by enabling private and foreign banks to operate in the country and granting the Central Bank greater autonomy. However, this phase also generated uncertainty, as liberal reforms clashed with legacy socialist structures. Since 1996, reform efforts have focused on modernizing the banking sector and aligning it with international standards. Market-oriented policies, interest rate deregulation, and the digitization of services have slowly gained traction. As of 2024, Algeria is actively pursuing reforms to enhance its financial stability and improve access to credit, laying the groundwork for greater economic competitiveness.[23] Despite these reforms, the current foreign trade practices within Algerian banks still reflect a hybrid of outdated procedures and nascent digital technologies. Table 2 summarizes the prevailing conditions and challenges faced by the sector. In practice, six central state-owned banks—such as the Banque Extérieure d’Algérie (BEA) and the Banque Nationale d’Algérie (BNA)—dominate the sector, stifling competition and hindering innovation. This lack of diversity in ownership has contributed to the slow adoption of modern financial technologies. The banking infrastructure remains overwhelmingly cash-based, with limited use of credit cards, scarce ATM networks, and underdeveloped digital platforms. Moreover, importers continue to face burdensome requirements such as letters of credit, which expose them to significant exchange rate volatility. Payments to foreign suppliers are typically delayed, and the inefficient domestic transfer system exacerbates transaction costs and delays. Currency control policies also pose challenges. For sectors outside of hydrocarbons, only 50% of export revenues can be retained in U.S. dollars, with the remaining 50% mandatorily converted into the local currency. Exporters within the hydrocarbons sector face even stricter restrictions. Compounding these issues, the role of Export Credit Agencies (ECAs) remains limited. The primary ECA, Compagnie Algérienne d’Assurance et de Garantie des Exportations (CAGEX), provides minimal insurance for non-hydrocarbon exports, limiting support for export diversification.[24] Given this landscape, it becomes clear that structural constraints persist despite policy ambitions. However, recent shifts in Algeria’s regulatory environment suggest emerging opportunities for integrating FinTech. As shown in Table 3, the country has introduced several regulatory updates aimed at fostering innovation while maintaining financial stability. Key institutions involved in oversight include the Bank of Algeria, the Money and Credit Council, the Banking Commission, and COSOB (the securities market regulator). Foundational regulations such as Banking Law 90-10 and Law №23–09 (passed in June 2023) establish the framework for surveillance and FinTech licensing.[25] Additionally, Executive Decree 20-254 (2020) supports startups by offering incentives and defining legal parameters for innovative ventures. These regulatory reforms aim to boost financial inclusion by encouraging the development of digital financial services (DFS), including mobile money and e-payments. However, despite regulatory progress, structural barriers persist—most notably, regulatory rigidity, limited digital infrastructure, and low levels of digital literacy. These factors continue to inhibit the scalability of FinTech innovation in Algeria.[26] In summary, Algeria’s banking and trade finance environment reflects a complex blend of historical legacies, slow-moving reforms, and growing—but constrained—interest in digital innovation. While the institutional landscape is gradually evolving, the challenge remains to accelerate modernization in a way that not only enhances operational efficiency but also promotes inclusivity, competitiveness, and integration with global trade systems. 4.1 Comparative positioning: Algeria in the regional and global context Understanding Algeria’s position requires more than isolated observation—it demands systematic comparison with economies that have faced similar developmental challenges. The countries selected for this analysis share key characteristics with Algeria: predominantly cash-based economies transitioning toward digital finance, significant informal sectors, regulatory frameworks in flux, and ambitions to diversify away from commodity dependence. Yet their trajectories have diverged considerably in recent years, offering instructive contrasts. The following analysis examines five core dimensions: payment digitalization, trade finance modernization, technological infrastructure, regulatory maturity, and financial inclusion outcomes. This comparison shows differences that are both quantitative and structural. The gap in basic digital payment adoption seems to be getting smaller—Algeria’s 43% is only four decades behind Kenya’s 82%—but the gap in trade finance digitization is a more worrisome story. Algeria’s 15–20% is lower than the UAE’s 72% and lower than economies with similar or lower per capita incomes. Kenya’s experience with M-Pesa shows that infrastructure problems don’t have to be a deal breaker. The platform processes more than $35 billion a year, even though it mostly runs on basic mobile networks. This was possible because of a strategic choice: building on the widespread use of mobile phones instead of waiting for a full banking system to be set up. India’s path teaches us something else. The Unified Payments Interface (UPI) started in 2016 with clear government support and required banks to take part. Within seven years, it had a transaction volume of $1.2 trillion per year. This wasn’t natural market growth; it was planned policy architecture. The government required interoperability, paid for the first infrastructure costs, and set up legal systems that made it possible for transactions to fail in digital form instead of cash. Algeria’s voluntary adoption model, on the other hand, doesn’t have these forcing mechanisms. The UAE has a high digitization rate (72%) because the rules are clear and they are enforced. Trade documentation rules clearly favor electronic submissions, processing fees punish transactions done on paper, and government procurement rules require digital payment rails. These aren’t just suggestions; they’re structured incentives with clear results. Algeria’s current system doesn’t have any rewards or punishments that are similar in size. Brazil’s moderate performance (55%), even though it has problems like Algeria’s, such as geographic dispersion, income inequality, and a fragmented banking sector, suggests that there are possible solutions. The central bank’s PIX project, which started in 2020, made it possible to make free, instant payments without going through commercial banks. In just three years, PIX handled more transactions than all credit cards put together. The lesson is not how advanced the technology is, but how committed the institutions are to getting rid of friction. In the context of Algeria, three specific gaps need to be addressed. The lack of regulatory sandboxes makes it harder to try out new ideas that might work in a specific area. Second, transaction processing times that are 3 to 7 times longer than those in benchmark countries cost both exporters and importers directly. Third, there is still very little use of blockchain technology, even though there are clear benefits to using it to cut down on fraud. The technology is available, and there are examples of successful use, but uptake is still very low. These are not gaps in knowledge; they are gaps in implementation. 4.2 Lessons from comparative experience: adaptation strategies and pitfalls to avoid A comparative analysis shows not only where things could be better, but also how to get there, if lessons are adapted instead of copied exactly. What works in one situation might not work in another, but the basic ideas behind it usually still apply. The difficulty is in telling the difference between portable insights and implementations that are specific to a certain situation. Kenya’s “mobile-first” strategy is worth a lot of thought. Kenyan banks didn’t see sparse branch networks as problems that needed to be fixed at a high cost. Instead, they saw mobile phones as the main way to deliver services. This means that Algeria should focus on integrating mobile wallets with trade finance services instead of opening more branches. A clear goal is to have 15 million mobile banking users by 2028, up from about 8 million now. Agent banking networks, which are retail stores that can do basic banking transactions, can reach areas that don’t have a lot of banks at about one-tenth the cost per transaction of traditional branches. The infrastructure is already there; it just needs to be turned on instead of being built. India’s requirement that UPI be interoperable gives us a second lesson that can be applied to other situations. The 20 licensed banks in Algeria currently have digital systems that don’t work well together, which means that customers and businesses must keep multiple accounts. By 2027, all licensed banks would have to use compatible APIs, which would eliminate this problem. Data from India shows that these kinds of rules can quadruple the number of transactions in three years, but not by creating new demand; instead, they can do this by removing barriers to existing demand. Other countries should copy the UAE’s clear rules about when to digitize things. Instead of making vague calls for digital adoption, Emirati regulators set clear goals: By a certain date, half of trade finance would be digitized, and by another date, 75% would be digitized, with clear consequences for those who didn’t comply. This change made digitization a business necessity instead of just an option. Algeria could do something similar, with 50% digitization by 2027 and 75% by 2029. There would be penalties for those who don’t keep up and tax breaks for those who do. Brazil’s central bank runs an instant payment system called PIX, which is the fourth model. The central bank built infrastructure that all institutions could use on equal terms instead of waiting for commercial banks to work together. A “DinarPay” system run by the central bank and linking all licensed financial institutions could make 2 million transactions happen every day in Algeria by 2028. This solves a problem in Algeria: state-owned banks, which make up the majority of the sector, have little reason to come up with new ideas, and private banks don’t have the size to make big changes. A central platform gets rid of both problems. Kenya’s slow regulatory process is a warning. For seven years, M-Pesa ran without strict financial rules. When those rules finally caught up, the company had to spend more than $200 million to bring its operations up to code, putting millions of users at risk in the meantime. Before expanding FinTech solutions, Algeria should set up regulatory sandboxes. This means making rules for technologies that haven’t been used yet, which is hard for regulators who like to regulate things they know about, but it’s necessary to stop Kenya’s expensive fixes. India’s cybersecurity holes during the quick growth of UPI are another warning. Fraud rates were 0.03% of the total number of transactions, which may not seem like a lot, but it added up to hundreds of millions of dollars a year. The rush to grow came before putting money into fraud detection systems. Algeria’s plan should require AI-powered fraud detection and multi-factor authentication from the start. According to the World Bank’s evaluations of similar systems, adding security later costs three to five times as much as building it in from the start. The UAE’s high implementation costs—about $1.2 billion across the banking sector over five years—are due to the fact that they don’t have any transition periods between top-down mandates. Algeria has a smaller banking sector and stricter budget rules, so it can’t afford to spend as much. A phased voluntary adoption model, with tax breaks for early adopters (like 20% tax credits on FinTech investments for the first three years), would spread the costs over time while keeping the momentum going. 4.3 Algeria-specific limitations Some problems are unique to Algeria and require a specific approach for resolution. State-owned banks, which control 90% of the commercial banking market, hinder innovation. These organizations don’t have to compete to modernize, and their bureaucratic structures hinder their ability to do so. One potential forcing mechanism is to mandate that 15% of state bank IT budgets be allocated to partnerships with FinTech firms by 2026. This redirects existing resources rather than requiring new appropriations, while creating structured demand for FinTech solutions. Currency controls represent a second Algeria-specific barrier. The requirement to convert 50% of export revenues to local currency deters exporters who face exchange rate volatility. Tunisia’s experience offers relevant evidence: when it relaxed similar controls in 2019, non-hydrocarbon exports increased by 32% over the following three years. The mechanism was straightforward, exporters could price more competitively when they faced less currency risk. Algeria does not need to eliminate controls; allowing 75% USD retention (up from 50%) would partially address the constraint while maintaining capital account oversight. Infrastructure gaps, while real, are surmountable through hybrid approaches. Roughly 40% of rural areas lack reliable internet connectivity; however, this does not preclude the use of digital financial services. USSD-based services—the technology behind codes like *247# used in Kenya—operate on basic 2G networks and can reach 95% of Algeria’s population with existing telecom infrastructure. These are not ideal long-term solutions, but they enable service expansion while infrastructure catches up. Financial literacy deficits require direct investment, not just awareness campaigns. Only 31% of Algerian adults report understanding digital banking services, according to World Bank surveys. Morocco’s five-year financial literacy program, which cost approximately $25 million, increased digital banking adoption from 38% to 67% between 2016 and 2021: the program combined school curriculum changes, adult education workshops, and mass media campaigns. Algeria could adapt this model, targeting 5 million adults over three years with a similar investment adjusted for population scale. Analysis and Discussion The current landscape of FinTech in Algeria reveals growing, albeit uneven, adoption among banks. Mobile and digital payment solutions have experienced substantial growth, driven mainly by the COVID-19 pandemic. Banking applications, such as BANXY from Natixis and Barid Pay from Algeria Post, have empowered users to manage accounts, transfer funds, and pay bills directly through their smartphones.[28] In addition, mobile wallets and peer-to-peer lending platforms are expanding access to financial services, particularly in underbanked rural areas. These digital tools help bridge long-standing service gaps left by conventional banking systems.[29] This evolving digital shift is further illustrated by Figure 3, which outlines key statistics and projections related to Algeria’s FinTech development. Available at: <https://www.statista.com/markets/> (Last access: 12.07.2025). Digital investment is the most prominent segment, with assets under management (AUM) projected to reach USD 6.02 million in 2024. Digital payment users are expected to increase significantly, potentially reaching 21.59 million by 2028. Such growth signals an increase in public engagement with FinTech platforms, which in turn can enhance Algeria’s international trade operations. FinTech has already demonstrated its role in improving trade efficiency, cost-effectiveness, and security. For instance, the implementation of blockchain technology and artificial intelligence has helped streamline transaction processing and bolster risk management within Algerian banks. Additionally, the growth of digital investments and mobile banking has introduced new tools for compliance and automation in trade finance. However, realizing the full potential of FinTech in Algeria remains constrained by several challenges. These can be broadly categorized into regulatory, infrastructural, and socio-cultural aspects. From a regulatory perspective, although the Algerian government supports FinTech development, the evolving nature of its legal frameworks creates uncertainty for startups and financial institutions. This regulatory ambiguity hinders innovation and deters long-term investment.[30] Furthermore, the country’s limited venture capital ecosystem restricts funding opportunities for promising FinTech ventures. On the infrastructural front, the underdeveloped digital infrastructure in rural areas limits the reach of financial technologies. Although Algeria’s mobile broadband penetration exceeds the MENA average, it remains relatively insufficient to support large-scale digital transformation.[31] Financial literacy deficits and deep-rooted cultural preferences for traditional banking exacerbate these issues. Only 43% of Algerians had a formal banking relationship in 2022, a statistic that highlights the persistent gap in financial inclusion. Moreover, limited financial knowledge and skepticism toward digital platforms pose significant challenges to the widespread adoption of FinTech.[32] Despite these challenges, Algeria’s youthful and tech-savvy population, high mobile penetration rates, and supportive government initiatives offer promising prospects for FinTech innovation. Overcoming these hurdles requires concerted efforts from both the public and private sectors to enhance infrastructure, refine regulatory frameworks, and promote financial literacy. Most innovation in the Algerian FinTech space is found in leading startups such as Yassir and UbexPay. Streamlined regulatory reforms and increasing investments in the sector are likely to propel Algeria into a significant position within the global FinTech stage. The Algerian FinTech sector holds enormous potential for future growth, driven by some critical factors: The Algerian government’s stance towards FinTech, as evident in various initiatives and regulatory updates, provides a favorable environment for startups to thrive. Ongoing efforts to modernize regulations foster innovation and attract investment. [33] Additionally, Algeria’s young, tech-oriented population and widespread mobile connectivity create a strong demand base for mobile banking and payment solutions. The significant gap in financial inclusion represents both a challenge and an opportunity. With many Algerians unbanked or underbanked, FinTech platforms can play a crucial role in democratizing access to financial services.[34] Digital identity systems already in place can ease onboarding processes and support compliance with anti-money laundering (AML) and know-your-customer (KYC) requirements. Meanwhile, growing adoption of digital payments indicates a market that is gradually embracing financial technology. Success stories from startups like Yassir, UbexPay, and My-Tree Online highlight Algeria’s innovation potential in this sector.[35] Moreover, several emerging FinTech trends are expected to transform Algeria’s financial landscape further. Islamic FinTech, for example, could provide Sharia-compliant solutions to meet the needs of Algeria’s majority-Muslim population. Open banking also holds promise for promoting competition and interoperability in the financial sector.[36] Closing these gaps in the digital divide and ensuring that investment opportunities remain open is crucial in realizing the full potential of financial technology in Algeria. By grasping these opportunities, Algeria can become a forerunner in FinTech for economic development.[37] The study concludes with the following recommendations for Algerian banks to enhance foreign trade using FinTech: Invest in FinTech Infrastructure: Banks should allocate resources to modern technological infrastructure, with a focus on blockchain for secure transactions and AI for risk assessment: Form Strategic Partnerships: Collaborating with FinTech companies can help develop specialized solutions for trade finance; Develop Customer-Centric Solutions: Banks should implement FinTech solutions that address specific customer needs in foreign trade, such as faster processing and greater transparency; Invest in Training: Staff should be provided with training programs to build their capacity and understanding of FinTech applications in foreign trade. Strategic Implementation Roadmap: Actionable Recommendations (2025-2030) Moving from analysis to action requires specificity. Vague exhortations to “invest in infrastructure” or “encourage innovation” offer little practical guidance. What follows is a structured implementation framework built around measurable targets, realistic timelines, and cost estimates derived from comparable deployments in similar economies. These recommendations are not theoretical ideals—they reflect what has worked elsewhere, adapted to Algerian constraints and capabilities. Investment Phasing and Fiscal Implications: These investments, although substantial, represent roughly 0.2-0.25% of Algeria’s GDP annually over the five years, comparable to the allocations made by Brazil (0.18% annually) and India (0.22% annually) for similar modernization efforts. The phasing matters as much as the total: Phase 1 (2025-2026): Foundation Building - USD 180-220 million. Priority is given to infrastructure and regulatory frameworks. The cloud migration of core banking systems and the establishment of a regulatory sandbox create an environment that enables subsequent innovations. This phase focuses on removing constraints rather than deploying solutions. Phase 2 (2027-2028): Scaling and Integration - USD 120-150 million. With infrastructure in place, this phase scales blockchain deployment beyond pilots and integrates AI-powered systems. The focus shifts from capability-building to operational deployment. Partnership agreements signed in Phase 1 begin generating returns as integrated systems go live. Phase 3 (2029-2030): Optimization and Expansion - USD 80-100 million. The. The final phase concentrates on refining deployed systems, addressing identified gaps, and expanding successful models. Investments decline as earlier outlays begin generating efficiency savings that partially offset continued modernization costs. Total Five-Year Investment: USD 380-470 million. These are not theoretical projections. Brazil’s PIX system cost approximately $40 million to build and generated $200 million in transaction cost savings within three years—a 500% return on investment. India’s UPI investment of roughly $60 million now processes transactions that would cost $3-4 billion annually through traditional banking channels. The economic case does not rest on optimistic assumptions; it relies on documented outcomes from comparable systems. Critically, these investments require coordination across multiple institutions—the Central Bank, commercial banks, the Ministry of Finance, and regulatory agencies must operate within a unified framework. Nigeria’s failed attempt at similar modernization in the early 2010s saw resource waste exceeding 40% due to uncoordinated initiatives by different agencies. Algeria can avoid this by establishing a centralized implementation authority with clear mandates and promoting cross-institutional participation. Conclusion This Study shows the possibilities that FinTech can offer to improve foreign trade techniques in Algerian banking usage. The significant conclusions for this research work are as follows: Algerian banks increasingly adopt FinTech solutions, particularly in digital payments and trade finance; FinTech has the potential to significantly improve efficiency, reduce costs, and mitigate risks in foreign trade; Challenges such as regulatory barriers, infrastructure limitations, and gaps in financial literacy hinder the full potential of FinTech adoption; Even though there are problems, there are good chances for growth in the future, such as using new technologies like blockchain and AI. Strategic Recommendations for Banks to Enhance Foreign Trade Using FinTech: Digital Infrastructure: Allocate 2–3% of GDP over five years to invest in digital infrastructure, including payment networks, blockchain platforms, and AI-based risk management systems: Financial Inclusion: Increase the share of the population with formal banking access from 43% (2022) to 65% by 2030: Cashless Transactions: Target 50% of all transactions to be cashless by 2030, compared to current levels of approximately 30% in Egypt and 36% in Morocco: Regulatory Sandbox: Establish a regulatory sandbox by 2026, enabling at least 20 FinTech startups to test innovations annually; SME Trade Finance: Double the access of small and medium-sized enterprises (SMEs) to trade finance by 2028 through digital platforms. References: Al Khatib, A. M., Alshaib, B. M., Kanaan, A. (2023). The interaction between financial development and economic growth: A novel application of transfer entropy and a nonlinear approach in Algeria. SAGE Open, 13(4). Available at: <https://doi.org/10.1177/21582440231222980>; Allen, T., Moen, M., Wohlgenannt, G. (2021). The impact of artificial intelligence on financial services: Innovations and challenges. Journal of Business and Management Studies, 7(4); Almubarak, S. (2024). Growth opportunities in Algerian FinTech. Economic Development Journal, 5(1); Bellahcene, A., Latreche, F. (2023). Digital Banking and Financial Inclusion in Algeria. Journal of Digital Finance, 1(2); Benachour, A., Tarhlissia, L. (2024). The evolution and development of electronic payment in a bank. Case study: CPA-Bank. Financial Markets, Institutions, and Risks, 8(1); Carè, R., Boitan, I. A., Stoian, A. M., Fatima, R. (2025). Exploring the landscape of financial inclusion through the lens of financial technologies: A review. Finance Research Letters, 72. <doi.org/10.1016/j.frl.2024.106500>; Chatterjee, S. (2023). Digital payments and global trade. Journal of Economic Integration, 31(1); Chen, Q. (2024). FinTech innovation in micro and small business financing. International Journal of Global Economics and Management, 2(1); Dahdal, E. M. (2020). Regulatory sandboxes for FinTech innovation. Regulatory Policy Journal, 15(1); GSMA. (2024). State of the Industry Report on Mobile Money 2024. London: GSMA Intelligence. Available at: <https://www.gsma.com/mobilefordevelopment/resources/state-of-the-industry-report-on-mobile-money-2024/>; Hacini, I., Mohammedi, K., Dahou, K. (2022). Determinants of the capital structure of small and medium enterprises: Empirical evidence in the public works and hydraulics sector from Algeria. Small Business International Review, 6(1); Hamid, A., Widjaja, W. S., Napu, F., Sipayung, B. (2024). The role of FinTech in enhancing financial literacy and inclusive financial management in MSMEs. TECHNOVATE: Journal of Information Technology and Strategic Innovation Management, 1(2); IMF. International Monetary Fund. (2024). Financial Access Survey 2024: Digital Finance in Emerging Markets. Washington, DC: IMF Statistics Department. Available at: <https://data.imf.org/FAS>; King, M. R., Osler, C., Rime, D. (2012). Foreign Exchange Market Structure, Players, and Evolution. In: Handbook of exchange rates; Kumar, N., Kumar, K., Aeron, A., Verre, F. (2025). Blockchain technology in supply chain management: Innovations, applications, and challenges. Telematics and Informatics Reports, 18(2). <doi.org/10.1016/j.teler.2025.100204>. Liu, W., Dunford, M., Gao, B., Lu, Z. (2018). The Belt and Road Initiative: Reshaping global trade and development. Journal of Contemporary China, 27(112); Lloyds Bank. (2024). International Trade Portal case studies. Lloyds Bank. Available at: <https://www.lloydsbank.com/business/resource-centre/international-trade-portal.html> (Last Seen: 12.07.2025); Mansour, R. (2024). Infrastructure limitations in Algeria: A Challenge for FinTech Expansion. North African Economic Review, 10(4); Meltzer, J. P. (2023). FinTech and international trade: Advancing economic growth through innovation. World Economy, 46(5); Moro-Visconti, R., Rambaud, S. C., Pascual, J. L. (2020). Sustainability in FinTech: An explanation through business model scalability and market valuation. Sustainability, 12(24), 10316. Available at: <https://doi.org/10.3390/su122410316>; Musa, B. O. (2022). Effect of financial innovations on financial inclusion: A case of small and medium enterprises in urban informal settlements in Nairobi County. Kenya (Doctoral dissertation, University of Nairobi), University of Nairobi; Muza, O. (2024). Innovative governance for transformative energy policy in sub-Saharan Africa after COVID-19: Green pathways in Egypt, Nigeria, and South Africa. Heliyon, 10(9). <doi.org/10.1016/j.heliyon.2024.e26600>; Oguntuase, O. J. (2025). Consumer-focused transition to a bio-based, sustainable economy in Africa. In: Sustainable bioeconomy development in the Global South: Volume I - Status and perspectives, Springer Nature Singapore; Previse. (2024). InstantAdvance and trade finance. Available at: <https://previse.co/en-gb/success/harlow-group-on-financing-stock/> (Last access: 12.07.2025); Pu, X., Nguyen, V. (2021). Growth of digital payments in emerging markets: The case of Algeria. Journal of Financial Services and Innovation, 11(3); Riaz, S. (2023). The Regulatory Environment for FinTech in Algeria: Challenges and Prospects. Journal of Financial Regulation, 8(2); Saif-Alyousfi, A. Y. (2024). Bank depositors in Arab economies amidst the COVID-19 pandemic. Forum for Economic and Financial Studies, 2(1); Seddiki, S. (2023). The role of financial technology (FinTech) in overcoming the financing gap for MSMEs in Algeria. El-Bahith Review, 23(1); Senyo, P. K. (2022). Big data analytics in trade. Trade Analytics Review, 16(1); Statista. (2024). Industry overview. Available at: <https://www.statista.com/markets/> (Last access: 12.07.2025); WeBank. (2024). Available at: <https://www.webank.com.tn/fr/> (Last access: 12.07.2025); Webb, H. C. (2024). Sectoral system of innovation in Islamic FinTech in the UAE’s regulatory sandbox. In: The Palgrave Handbook of FinTech in Africa and the Middle East: Connecting the Dots of a Rapidly Emerging Ecosystem, Singapore: Springer Nature Singapore. World Bank. (2023). Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank Group. Available at: <https://www.worldbank.org/en/publication/globalfindex>; Xu, D., Xu, D. (2020). Concealed risks of FinTech and goal-oriented responsive regulation: China’s background and global perspective. Asian Journal of Law and Society, 7(2); Zhang, B. Z., Ashta, A., Barton, M. E. (2021). Do FinTech and financial incumbents have different experiences and perspectives on adopting artificial intelligence? Strategic Change, 30(3). Footnotes [1] Allen, T., Moen, M., Wohlgenannt, G. (2021). The impact of artificial intelligence on financial services: Innovations and challenges. Journal of Business and Management Studies, 7(4), p. 232. [2] Webb, H. C. (2024). Sectoral system of innovation in Islamic FinTech in the UAE’s regulatory sandbox. In: The Palgrave Handbook of FinTech in Africa and the Middle East: Connecting the Dots of a Rapidly Emerging Ecosystem, Singapore: Springer Nature Singapore, p. 12. [3] Muza, O. (2024). Innovative governance for transformative energy policy in sub-Saharan Africa after COVID-19: Green pathways in Egypt, Nigeria, and South Africa. Heliyon, 10(9), p. 266. <doi.org/10.1016/j.heliyon.2024.e26600>. [4] Xu, D., Xu, D. (2020). Concealed risks of FinTech and goal-oriented responsive regulation: China’s background and global perspective. Asian Journal of Law and Society, 7(2), p. 312. [5] King, M. R., Osler, C., Rime, D. (2012). Foreign Exchange Market Structure, Players, and Evolution. In: Handbook of exchange rates, pp. 1-4. [6] Liu, W., Dunford, M., Gao, B., Lu, Z. (2018). The Belt and Road Initiative: Reshaping global trade and development. Journal of Contemporary China, 27(112), p. 451. [7] Oguntuase, O. J. (2025). Consumer-focused transition to a bio-based, sustainable economy in Africa. In: Sustainable bioeconomy development in the Global South: Volume I - Status and perspectives, Springer Nature Singapore, p. 347. [8] Seddiki, S. (2023). The role of financial technology (FinTech) in overcoming the financing gap for MSMEs in Algeria. El-Bahith Review, 23(1), p. 56. [9] Carè, R., Boitan, I. A., Stoian, A. M., Fatima, R. (2025). Exploring the landscape of financial inclusion through the lens of financial technologies: A review. Finance Research Letters, 72, p.165. <doi.org/10.1016/j.frl.2024.106500>. [10] Musa, B. O. (2022). Effect of financial innovations on financial inclusion: A case of small and medium enterprises in urban informal settlements in Nairobi County. Kenya (Doctoral dissertation, University of Nairobi), University of Nairobi, p. 78. [11] Hamid, A., Widjaja, W. S., Napu, F., Sipayung, B. (2024). The role of FinTech in enhancing financial literacy and inclusive financial management in MSMEs. TECHNOVATE: Journal of Information Technology and Strategic Innovation Management, 1(2), p. 85. [12] Kumar, N., Kumar, K., Aeron, A., Verre, F. (2025). Blockchain technology in supply chain management: Innovations, applications, and challenges. Telematics and Informatics Reports, 18(2), p. 204. <doi.org/10.1016/j.teler.2025.100204>. [13] Previse. (2024). InstantAdvance and trade finance. Available at: <https://previse.co/en-gb/success/harlow-group-on-financing-stock/> (Last access: 12.07.2025). [14] WeBank. (2024). Available at: <https://www.webank.com.tn/fr/> (Last access: 12.07.2025). [15] Lloyds Bank. (2024). International Trade Portal case studies. Lloyds Bank. Available at: <https://www.lloydsbank.com/business/resource-centre/international-trade-portal.html> (Last Seen: 12.07.2025). [16] Chatterjee, S. (2023). Digital payments and global trade. Journal of Economic Integration, 31(1), p. 25. [17] Chen, Q. (2024). FinTech innovation in micro and small business financing. International Journal of Global Economics and Management, 2(1), p. 286. [18] Senyo, P. K. (2022). Big data analytics in trade. Trade Analytics Review, 16(1), p. 42. [19] Dahdal, E. M. (2020). Regulatory sandboxes for FinTech innovation. Regulatory Policy Journal, 15(1), pp. 78-95. [20] Statista. (2024). Industry overview. Available at: <https://www.statista.com/markets/> (Last access: 12.07.2025). [21] Ibid. [22] Ibid. [23] Benachour, A., Tarhlissia, L. (2024). The evolution and development of electronic payment in a bank. Case study: CPA-Bank. Financial Markets, Institutions, and Risks, 8(1), p. 9. [24] Saif-Alyousfi, A. Y. (2024). Bank depositors in Arab economies amidst the COVID-19 pandemic. Forum for Economic and Financial Studies, 2(1), p. 338. [25] Al Khatib, A. M., Alshaib, B. M., Kanaan, A. (2023). The interaction between financial development and economic growth: A novel application of transfer entropy and a nonlinear approach in Algeria. SAGE Open, 13(4). Available at: <https://doi.org/10.1177/21582440231222980>. [26] Hacini, I., Mohammedi, K., Dahou, K. (2022). Determinants of the capital structure of small and medium enterprises: Empirical evidence in the public works and hydraulics sector from Algeria. Small Business International Review, 6(1), p. 13. [27] World Bank. (2023). Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank Group. Available at: <https://www.worldbank.org/en/publication/globalfindex>; GSMA. (2024). State of the Industry Report on Mobile Money 2024. London: GSMA Intelligence. Available at: <https://www.gsma.com/mobilefordevelopment/resources/state-of-the-industry-report-on-mobile-money-2024/>; IMF. International Monetary Fund. (2024). Financial Access Survey 2024: Digital Finance in Emerging Markets. Washington, DC: IMF Statistics Department. Available at: <https://data.imf.org/FAS>. [28] Moro-Visconti, R., Rambaud, S. C., Pascual, J. L. (2020). Sustainability in FinTech: An explanation through business model scalability and market valuation. Sustainability, 12(24), 10316. Available at: <https://doi.org/10.3390/su122410316>. [29] Zhang, B. Z., Ashta, A., Barton, M. E. (2021). Do FinTech and financial incumbents have different experiences and perspectives on adopting artificial intelligence? Strategic Change, 30(3), p. 226. [30] Mansour, R. (2024). Infrastructure limitations in Algeria: A Challenge for FinTech Expansion. North African Economic Review, 10(4), p. 215. [31] Riaz, S. (2023). The Regulatory Environment for FinTech in Algeria: Challenges and Prospects. Journal of Financial Regulation, 8(2), p. 85. [32] Meltzer, J. P. (2023). FinTech and international trade: Advancing economic growth through innovation. World Economy, 46(5), p. 1030. [33] Bellahcene, A., Latreche, F. (2023). Digital Banking and Financial Inclusion in Algeria. Journal of Digital Finance, 1(2), p. 8. [34] Almubarak, S. (2024). Growth opportunities in Algerian FinTech. Economic Development Journal, 5(1), p. 12. [35] Pu, X., Nguyen, V. (2021). Growth of digital payments in emerging markets: The case of Algeria. Journal of Financial Services and Innovation, 11(3), p. 140. [36] Almubarak, S. (2024). Ibid., p. 13. [37] Benachour, A., Tarhlissia, L. op-cit, p. 11.
Rescuing Struggling Companies through Preventive Corporate Rescue Tools: Economic Implications of the French and Moroccan Special Mandate Models
This paper presents a comparative analysis of the “Special Mandate” as a preventive mechanism for rescuing struggling companies, focusing on French and Moroccan legislation. While existing studies focus on legal doctrine, this paper addresses a critical gap by linking these legal frameworks to their tangible economic outcomes, which is essential for evaluating their true effectiveness in the marketplace. The analysis contrasts two divergent legislative philosophies. The French model is notably broad, applying to nearly all types of enterprises regardless of their legal form, reflecting a proactive stance on economic intervention. It provides detailed procedural rules governing the agent’s (mandataire ad hoc) appointment, potential conflicts of interest, and the precise scope of the mission. Conversely, the Moroccan approach is significantly more restrictive, limiting the procedure mainly to commercial “traders” (commerçants) and containing legislative gaps that create procedural uncertainty for both debtors and creditors. While the procedure’s key advantages in both systems are its confidentiality and simplicity, its purely contractual nature presents a major limitation, as its success is entirely contingent upon voluntary creditor participation, which is often difficult to secure in distressed situations. The paper concludes that the French model’s enhanced legal flexibility correlates with superior economic performance, evidenced by outcomes such as a 2.6-fold higher debt recovery rate, offering a clear, data-driven recommendation for legislative reform based on proven economic stability. Keywords: Modern bankruptcy laws, preventive Procedures, special mandate, struggling companies, company rescue, economic outcomes, investment climate. Introduction In their efforts to improve the investment climate, nations strive to enhance the legal system that governs the economic sphere. For a long time, this system followed a singular path: simplifying and facilitating the establishment of companies to foster a strong economic fabric. However, fierce competition among these companies, on the one hand, and economic crises on the other, have expedited the need for nations to focus on an alternative path: ensuring the continuity of these companies by supporting and rescuing them. The cessation of these companies’ activities has negative consequences that extend beyond the economic sphere, such as the potential for other companies to default on their payments due to the non-payment of their debts, and a reduction in tax revenues for the public treasury, to the social sphere, namely, the layoff of workers. The economic and social stakes are substantial. In 2024 alone, France registered a record 67,830 company failures, threatening 256,000 jobs. Similarly, Morocco saw over 15,658 firms enter insolvency proceedings in the same period, with the commerce and real estate sectors being most affected. These figures underscore the urgent need for effective rescue mechanisms. This focus is embodied in the shift from old bankruptcy laws, which failed to achieve their objectives of protecting creditors and ensuring debt repayment, and which could only be realized by punishing the debtor company for what was considered an offense requiring a penalty, to modern bankruptcy laws. to modern bankruptcy laws. In some legislations, these are referred to as company rescue laws, the primary goal of which is to preserve the economic and social fabric by maintaining the company’s continuity and, consequently, safeguarding employment. The recovery of debts by creditors thus becomes a natural outcome of the company’s survival. This legislative shift is not isolated; it is part of a distinct global trend. Nations are strategically reforming their laws in what has been termed “regulatory competition”[1] to attract international capital. This trend is echoed in the latest macroeconomic analyses. The International Monetary Fund (IMF, 2024),[2] in its recent Article IV consultation for France, emphasizes the resilience of the French economy, supported by a robust framework for corporate restructuring, which is crucial for post-pandemic recovery. Similarly, the European Commission (2024),[3] in its in-depth review, links future economic performance to the efficient handling of corporate distress. This movement, once promoted by UNCITRAL, has now been codified at a regional level. The most significant recent development is the EU Directive 2019/1023 on Preventive Restructuring, which mandates all member states to adopt effective pre-insolvency frameworks, validating the very philosophy underpinning the French model.[4] Comparative studies on the transposition of this directive note that the established French model served as a key inspiration for the Directive’s emphasis on flexible, pre-judicial mechanisms.[5] In this context, the importance of preventive measures in modern bankruptcy legislation has emerged as proactive tools aimed at saving viable enterprises rather than liquidating them. The “Special Mandate” is one of the most prominent of these measures, a confidential, preventive mechanism that originated in French judicial practice before being formally adopted by French and subsequently Moroccan legislators. Therefore, this study, employing a comparative analytical methodology reinforced by economic data analysis, seeks to examine the nature of this procedure in French and Moroccan legislation. The objective is to distill insights that could aid in adopting an effective system for proactively addressing company difficulties by demonstrating how specific legislative choices in the Special Mandate procedure correlate with divergent economic outcomes. This is particularly relevant given that the World Bank introduced a tenth indicator related to resolving insolvency in its 2017 Doing Business annual report – a report often relied upon by foreign investors in selecting a suitable investment environment. This indicator reveals stark differences: France ranks 26th globally for resolving insolvency, while Morocco ranks 73rd. The economic implications of this gap are profound. France’s framework facilitates an average debt recovery rate of 74.8 cents on the dollar, compared to just 28.7 cents in Morocco. This study argues that these economic disparities are not accidental but are a direct consequence of the differing legal philosophies and mechanisms, such as the Special Mandate, adopted by each nation. The study will address this through the following sections: Part I: The Rules and Procedures for Appointing a Special Agent. Section 1: Eligibility Criteria for the Special Mandate Procedure. I - Personal Scope of Application for the Special Mandate Procedure (Condition of Legally Defined Status). II - Material Scope of Application for the Special Mandate Procedure (The Company’s Situation). Section 2: Rules About the Appointment of the Special Agent. I - Procedures for Appointing the Special Agent and the Limits of the Court President’s Authority. II - Conflicts of Interest About the Special Agent. Part II: The Legal Framework for the Special Agent’s Mission. Section 1: The General Framework of the Special Agent’s Mission. I - The Limits of the Special Agent’s Mission. II - Determination of the Special Agent’s Remuneration. Section 2: Advantages of the Special Mandate Procedure. I - Confidentiality. II - Flexibility and Simplicity. Methodology This research adopts a mixed-method approach, combining a comparative legal-doctrinal analysis with a quantitative assessment of economic outcomes. The primary methodology involves a doctrinal comparison of the French Commercial Code (Book VI) and the Moroccan Commercial Code (Law No. 73-17) concerning the Special Mandate. This legal analysis focuses on the scope, appointment procedures, and operational rules of the mechanism. To address the research gap, this legal analysis is supplemented by economic data from international and national bodies. The study utilizes: World Bank Data: Comparative statistics from the Doing Business 2020 report on the “Resolving Insolvency” indicator (e.g., recovery rates, time, cost) are used to quantify the efficiency of each legal system. (See Table 1 and Figures 1-3); Current Macroeconomic Reports: To supplement the 2020 World Bank data, this study incorporates recent (2024-2025) economic analysis and forecasts from the International Monetary Fund (IMF, 2024) and the European Commission (2024) to provide a current macroeconomic context; National Statistics: Data on firm failures and employment impact from sources like Altares (as cited in BPCE L’Observatoire, 2024)[6] and Inforisk (as cited in Le360.ma, 2025)[7] are used to establish the scale of the economic problem; Recent Peer-Reviewed & Legal Sources: To address the latest legal-doctrinal evolution, the analysis integrates recent (2021-2025) peer-reviewed articles and expert legal analysis (e.g., Gerasimova et al., 2024; Lancaster EPrints, 2025) focusing on the transposition of EU Directive 2019/1023 via France’s Ordinance No. 2021-1193, and its specific impact on preventive mechanisms (Sorbonne, 2024); Procedural Data: Statistics on the usage frequency of preventive measures in France (e.g., Mandat ad hoc) from the CNAJMJ are used to demonstrate the mechanism’s practical relevance. (see Table 2 and Figure 4). The objective is to move beyond a purely descriptive legal comparison and demonstrate the correlation between legislative design and measurable economic performance. Part I: Rules for and Procedures of the Appointment of a Special Agent The special mandate was initially an experimental procedure that arose from the practice of French commercial courts, more specifically the Commercial Court of Paris, in 1990, during the real estate crisis, even in the absence of regulations governing it. However, some provisions related to it were later organized in Book VI of the French Commercial Code concerning business difficulties, under Article 04 of Law No. 94-475 of June 10, 1994, on the prevention and handling of business difficulties.[8] This was then supplemented by other provisions in Law No. 2005-845 of July 26, 2005, on the safeguarding of businesses.[9] More significantly, this framework was substantially amended by the Ordinance of September 2021, which transposed the EU Directive 2019/1023 on Preventive Restructuring. This latest reform did not alter the core of the ‘Special Mandate’ (Mandat ad hoc) as a confidential and informal procedure. Instead, as legal analysis of the ordinance confirms (Sorbonne, 2024),[10] it reinforced its position. The reform intentionally preserved the Mandat ad hoc due to its proven effectiveness, solidifying its role within an integrated ecosystem that encourages early intervention.[11] Moroccan legislation, which most closely follows French law among Arab legislations, established the possibility of appointing a special agent in the Law No. 15-95, which contains the Commercial Code.[12] It was then reaffirmed in the new effective Law No. 73-17 concerning difficulties of the undertaking,[13] given the importance of this procedure in addressing the difficulties faced by businesses. French commercial law, and subsequently the Moroccan Commercial Code, legitimized the special mandate procedure after observing the positive results it had achieved since it was a judicial practice without legal basis. * This was an attempt to instill a culture of pre-emption, which requires time and trust to establish. The head of an enterprise who, years ago, would flee the court upon cessation of payments is now invited to knock on the judiciary’s door at the first sign of difficulties.[14] From a legislative drafting perspective, neither the French nor Moroccan legislators provided a specific definition for the special mandate. Instead, they defined the limits of eligibility for the special mandate procedure (Section One) and the rules concerning the appointment of the special agent (Section Two). However, a comprehensive system for appointing the special agent is absent in the Moroccan Commercial Code, unlike in the French Commercial Code. Section One: Eligibility Criteria for the Special Mandate Procedure The Moroccan Commercial Code, following the model of the French Commercial Code, has defined the scope of application for the special mandate procedure. This scope is governed by two criteria that reflect the opinion of the legislators in both countries. The first criterion defines which persons can benefit from the special mandate procedure. In contrast, the second concerns the state of the enterprise that the legislation presumes the procedure can rectify. I - Personal Scope of Application for the Special Mandate Procedure (Condition of Legally Defined Status) The individuals who can benefit from the special mandate procedure are not different from those subject to prevention procedures, at least in French law. The latter has freed itself from classification and selectivity, considering that all persons influencing the economic landscape are concerned with internal and external prevention procedures alike.[15] This inclusive approach aligns with a broader European perspective favoring corporate innovation and diverse legal forms. This is detailed in Articles L611-2 and L611-2-1 of the French Commercial Code regarding the system of prevention procedures. The first article established the possibility for the President of the Commercial Court to summon the heads of commercial companies, economic interest groupings, and even individual commercial or craft enterprises to rectify the situation when it appears that the enterprise is suffering from difficulties that may threaten the continuity of its operations. The second article established the possibility for the President of the Judicial Court to summon the heads of private law legal entities and natural persons engaged in agricultural or independent professional activities, including liberal professions, for the same purpose of rectifying the enterprise’s situation whenever possible. This was summarized in Article L611-3 of the same law, which provides for the possibility for the President of the Commercial Court or the President of the Judicial Court,* As the case may be, to appoint a special agent upon the request of the debtor enterprise, which can be commercial, craft, or any other activity, considering that all enterprises, regardless of their nature, constitute the economic fabric of the state and thus require protection. In contrast, Moroccan law has adopted a more restrictive legislative choice regarding the persons who can benefit from the special mandate procedure and the procedures included in the law on business difficulties in general. This choice is evident in the special mandate procedure in Article 550 of the Moroccan Commercial Code. It makes the “undertaking” (maqawala), as defined in Article 546, the subject eligible for the special mandate procedure. The latter article presumes that the undertaking, in its individual or collective form, is a “trader” (tajir). This, in turn, means the exclusion of individual or collective undertakings of a civil nature, such as associations, cooperatives, economic interest groupings with a civil purpose, liberal professions, and others. This restrictive legal-doctrinal choice has tangible economic consequences. By limiting preventive measures to ‘traders’, Moroccan law excludes a significant portion of the economy, which correlates with weaker performance in resolving insolvency. This is compounded by recent analyses showing the specific vulnerabilities of Moroccan firms to post-pandemic economic shocks,[16] often stemming from internal and external factors that preventive laws could address.[17] The World Bank’s 2020 data shows that Morocco’s framework results in a protracted 3.5-year resolution process with a low 28.7% recovery rate. In contrast, France’s broad personal scope is part of a legal philosophy that achieves a 74.8% recovery rate in just 1.9 years, making its economy more resilient and attractive to investors. Therefore, the Algerian legislator, and other legislations that may adopt the special mandate procedure, should establish a personal scope that includes all enterprises contributing to development, away from unjustified selectivity based on commercial status. However, it may be advisable to initially limit the personal scope to the most significant enterprises and then expand it later, considering the necessary resources in the form of specialized agents and judges. Finally, fulfilling a person’s legally defined status is not sufficient to initiate the special mandate procedure. Both French and Moroccan legislation require another condition related to the enterprise’s situation. II - Material Scope of Application for the Special Mandate Procedure (The Company’s Situation) Two questions have long been raised during debates on proposed laws concerning business difficulties in France: When is it appropriate to start dealing with the difficulties faced by enterprises? Moreover, how should they be characterized?[18] This means that different answers to these two questions, and consequently the different foundations associated with them, reflect the different approaches of bankruptcy legislation in determining the required state of the enterprise to open one procedure over another. By examining the legislation under study, it can be said that they impose a condition related to the debtor enterprise’s situation for it to request the opening of the special mandate procedure. The scope of this situation is generally linked to a minimum threshold, which is the existence of difficulties that could threaten the continuity of the enterprise’s operations, and a maximum threshold, which is that the enterprise is not in a hopeless state, or what is usually expressed in different bankruptcy legislations as not having ceased payments for more than a specific period. Therefore, we will highlight the approaches adopted by the bankruptcy legislations under study on this issue regarding the special mandate procedure. The general nature of the text of Article L611-3 of the French Commercial Code concerning the appointment of a special agent has made it a subject of many interpretations. Some have argued[19] that the request for the appointment of a special agent does not require any conditions related to the debtor enterprise’s situation. This means that the competent authority to which the request is submitted cannot refuse the appointment of a special representative because the debtor enterprise is in a state of cessation of payments unless the period of cessation of payments exceeds 45 days.* This view is supported by the possibility of reversing the cessation of payments during the special mandate procedure by agreeing with creditors to postpone the due dates of their debts within a short period from the procedure’s opening, especially in light of the French Court of Cassation’s interpretation of this delay.[20] Others argue[21] that the debtor enterprise must not be in a state of cessation of payments when submitting its request for the appointment of a special agent, based on the plain reading of Article L611-3 of the French Commercial Code, which does not permit it. The special mandate procedure was designed as a preventive, not a curative, tool. This view is supported by the fact that the acceptance of appointing a special agent for an enterprise in a state of cessation of payments is not a certainty in judicial practice. However, while the text of Article L611-3 of the French Commercial Code does not explicitly permit the appointment of a special agent for an enterprise in a state of cessation of payments, it does not exclude it either. Furthermore, the conciliation procedure* that the French legislator also designed it as a preventive measure. Initially, the person requesting this procedure was required not to be in a state of payment cessation, but this was soon allowed on the condition that the period of payment cessation did not exceed 45 days.[22] Moreover, the uncertainty of accepting the appointment of a special agent for an enterprise in a state of cessation of payments in judicial practice may be due to the fact that such enterprises did not request the appointment of a special agent, not because the competent judicial authorities rejected their requests. What can be concluded from this approach is that the French legislator has left a wide margin for actors in prevention to ensure sufficient flexibility for this procedure, given that debtor enterprises resort to it for its confidentiality, especially with the possibility of reversing the cessation of payments as indicated above. In our opinion, what supports this is that the provisions related to business difficulties have been and continue to be subject to amendments, the latest of which was in 2021. However, the generality of the article was not reviewed, even though the latest amendment affected it.[23] In contrast, the possibility of appointing a special agent in the Moroccan Commercial Code is linked to the debtor enterprise facing difficulties in general that could disrupt its continuity, and specifically, social difficulties, those between partners, or those with the undertaking’s regular business partners.[24] This is on the condition that these difficulties have not led it to a state of cessation of payments.[25] Therefore, the Algerian legislator and other legislations that may adopt the special mandate procedure should define the material scope of the procedure precisely. This could be done either by leaving the scope wide to ensure the required flexibility in this procedure, by allowing the targeted enterprises to request it even if they are in a state of cessation of payments for a specific period, or by defining the limits of eligibility by specifying the nature and level of the difficulties, such as setting the maximum limit as the enterprise’s cessation of payments. Section Two: Rules Concerning the Appointment of the Special Agent The appointment of the special agent is subject to legally defined formalities and controls that differ between the comparative legislations under study, as are the limits of the authority granted to the court’s President within these frameworks. I - Appointment Procedures for the Special Agent and the Limits of the Court President’s Authority Article 549 of the Moroccan Commercial Code authorizes the President of the court to appoint a special agent and entrust them with the mission of intervening to mitigate objections and resolve the difficulties the enterprise is facing. This occurs when it becomes clear to the President—after hearing the head of the enterprise and forming a clear view of its situation—that the agent can resolve the difficulties and mitigate the objections that hinder the enterprise’s continuity, especially those related to partners or regular business associates of the enterprise.[26] However, the Code restricts the possibility of appointing a special agent by requiring that the head of the enterprise propose them.* This is based on the rationale that the latter will be more serious in seeking solutions, leading them to choose who they see as the most competent for the task, and because doing otherwise would exacerbate the difficulties by burdening the enterprise with new fees.[27] In contrast, the issue of the limits of the court president’s authority to accept or reject this proposal remains a legislative vacuum in Moroccan law. Before this, the French legislator, through Article L611-3 of the French Commercial Code, allowed the President of the court to appoint a special agent upon the request of the debtor enterprise. The request must be submitted in writing by the legal representative of the legal person or by the natural person debtor to the President of the Commercial Court or the Judicial Court—as the case may be—within whose jurisdiction its headquarters is located, or, where applicable, within whose jurisdiction the natural person debtor has declared the address of their enterprise or activity.[28] The request is filed with the court clerk’s office along with documents that clarify the applicant’s financial situation. The request must include the grounds on which it is based, the applicant’s identity, and a summary specifying the type of activity, number of employees, turnover, and results, the difficulties encountered, the measures to be taken for continuity, and justifying how the appointment of a special agent would allow for the resolution of the difficulties. It must also affirm that the enterprise is not in a state of cessation of payments. The applicant may also include in the request the name of the person they propose for the mission.[29] However, this proposal is not binding on the President of the court, who remains free to accept or reject the name of the proposed agent, as well as the freedom to accept or reject the appointment request as a whole, which is embodied in a decision they issue.* This decision, according to the provisions of Article R611-20* of the French Commercial Code, is subject to appeal by the debtor in accordance with the provisions of Article R611-26 of the same Code. This article stipulates that the debtor submits or sends the appeal by registered letter with acknowledgment of receipt to the court clerk. The court president rules on the appeal within five days of its submission, after which the debtor is notified, regardless of the decision. While the court president’s authority to accept or refuse the appointment of a special agent—without considering the proposed name—is justified by being linked to their conviction about the special agent’s ability to mitigate objections and resolve the enterprise’s difficulties, some argue that the discretionary power left to the President to accept or refuse the debtor’s proposal is inappropriate. This is not only in view of the voluntary and spontaneous nature of the debtor’s request but also due to the trust required for success in such a mission. They argue, in contrast, that it would be more appropriate to require the President of the court to accept the debtor’s choice or, at the very least, compel them to justify their refusal of the proposed person. The refusal of the debtor’s proposal could be an exceptional measure to make the plan more effective, especially since the debtor may be prepared to reject the intervention of an agent other than the one they proposed, by requesting the judge to terminate that agent’s mission under the provisions of Article R611-21 of the French Commercial Code.[30] Furthermore, the latter law specifies the conflicts of interest related to the special agent to ensure their neutrality. II - Conflicts of Interest Pertaining to the Special Agent: In practice, special agents, as well as conciliators, are often former consultants, lawyers, former judges, administrators, agents, or retired accountants, etc., due to their competence and knowledge of companies and business. This makes it possible to appoint a person who was providing a service to the debtor enterprise, or even an employee, during the period preceding the appointment, which could undermine the neutrality required by their function and discourage creditors from responding to their requests.[31] Therefore, to avoid conflicts of interest and to ensure the required independence that the special agent needs while performing their negotiation-based mission, the French legislator, unlike the Moroccan legislator, has prohibited the appointment of a group of persons as a special agent. Article L611-13 of the French Commercial Code stipulates that the duties of a special agent may not be performed by a person who has received, in any capacity, directly or indirectly, remuneration or payments from the debtor enterprise.* From any creditor of the debtor enterprise, or any person under its control as defined by Article L 233-16 of the French Commercial Code.[32] An exception is made if the person has received such remuneration under a special mandate or a judicial mandate entrusted to them in the context of an amicable settlement or a conciliation procedure concerning the same debtor enterprise or its creditors. Also included in the exception is remuneration received by a person under a judicial mandate, other than the commissioner for the execution of the plan, in the context of a reorganization* or judicial settlement* Procedure. In the same context, the article also provides that the duties of a special agent cannot be entrusted to a consular judge* who is currently in office or who has left office for less than five years. Suppose the President of the court appoints the special agent. In that case, the court clerk notifies the concerned person of their appointment as a special agent by letter, accompanied by a letter containing the text of Article L611-13 on conflicts of interest. Upon accepting the appointment, the special agent must declare on their honor that they do not fall within the prohibitions of its text. They, in turn, inform the President of the court of their acceptance of the appointment.[33] And then begin their mission as special agents to mitigate the objections facing the enterprise. Based on the foregoing, should the Algerian legislator, and other legislations thereafter, adopt the special mandate procedure, they are called upon to regulate all matters related to the appointment of the special agent, from the appointment procedures and modalities, through the determination of the powers granted to the competent judicial authorities in this regard, to the definition of conflicts of interest related to the special agent, in order to ensure the latter’s neutrality. Part II: The Legal Framework for the Special Agent’s Mission Like the French Commercial Code, the Moroccan Commercial Code has defined the general framework for the special agent’s mission (Section One) to ensure that their duties do not overlap with those of the enterprise’s management bodies. It has also worked to embody advantages within the special mandate procedure (Section Two) that are intended to support the success of the special agent’s mission. Section One: The General Framework of the Special Agent’s Mission In this section, we will clarify the mission of the special agent by explaining its limits. We will then address the criteria and conditions for determining the remuneration—the fees—that the special agent receives for carrying out their mission. I - The Limits of the Special Agent’s Mission The French Commercial Code, under Article L611-3, stipulates that the court president appoints a special agent whose mission he defines. Similarly, Article R611-19 of the same law confirms that the order of the court president appointing the ad hoc agent specifies their mission. In the same context, the Moroccan Commercial Code[34] stipulates that the President of the court is authorized to appoint the special agent and define their mission and duration, considering that the special agent’s tasks vary depending on the size of the enterprise, the type of its activity, and even the nature of the difficulties it faces. This means that the court’s President determines the content and duration of the special agent’s mission in the order he issues for their appointment, which corresponds precisely to the debtor enterprise’s request and needs. Generally, the special agent’s mission has three main stages. In the preparation stage, the special agent undertakes to understand the enterprise’s situation and obtain a general overview to prepare an action plan in coordination with the debtor. This enables them to negotiate with the concerned parties in the second stage.[35] In this context, the first paragraph of Article L611-3 of the French Commercial Code provides that the decision appointing the special agent, when made, is sent to the statutory auditors to facilitate their access to information that helps them form an idea of the enterprise’s situation and identify its strengths and weaknesses, which may lead them to identify the causes of the difficulties and work to resolve them in a later stage. In the second stage, the special agent and the debtor enterprise, through their representatives, begin negotiations with the concerned parties. This may be internal with the enterprise’s main partners or external with its regular associates or main creditors, including banks. The substance of these negotiations may involve negotiating deadlines and/or debt reductions. In the same context, the agent may suggest finding a partner to invest funds if an agreement for existing shareholders to inject new funds cannot be reached.[36] They may also propose restructuring the enterprise or selling a part of it.[37] It is important to note at this stage that the work of the special agent does not affect the powers and obligations of the enterprise owner. The latter retains their authority and continues to manage the business without being stripped of it, while receiving the assistance of the special agent who cannot substitute for them. The role of the special agent is to help the head of the enterprise restore confidence in the enterprise from both shareholders and creditors. At the same time, the special agent must inform the President of the court who appointed them through periodic reports, updating them on the state of the business, its development prospects, and any difficulties encountered.[38] The court president may find from the special agent’s reports that the success of the mission is linked to extending its deadline or replacing the agent. He may then extend the deadline or replace the agent, as the case may be, all after obtaining the consent of the enterprise owner.[39] In a final stage, the special agent seeks to conclude an agreement that makes it possible to ensure the enterprise’s continuity by preserving its activity and associated employment. This is done by bridging the gap between what the concerned enterprise facing difficulties can agree to and what the main creditors can accept.[40] The special agent’s mission ends upon its completion—the conclusion of the agreement—or at the end of the period specified in the order by the President of the court, unless it is extended based on the progress of the work.* Ultimately, the special agent’s mission remains subject to the discretion of the debtor enterprise. Whenever it appears to them that the special mandate is not sufficient to achieve the desired continuity, they may request the President of the court to terminate the special agent’s mission, which the agent must then end immediately.[41] II - How the Special Agent’s Remuneration is Determined Unlike the Moroccan Commercial Code, the French Commercial Code regulates how the special agent’s remuneration is determined, moving away from a fee schedule and allowing for contractual freedom. This is the case even though practice confirms that the determination of the special agent’s fee *is often done by agreements between the debtor enterprise and the special agent before the request to open the special mandate procedure is submitted to the President of the competent court.[42] The French Commercial Code has entrusted the competent court president with the task of determining the criteria for the special agent’s remuneration and its maximum amount, and, where applicable, its sum or method of payment.[43] This is done through an appealable order.* issued at the time of the special agent’s appointment, in light of the diligence required to accomplish the mission, and after taking the opinion of the public prosecutor. *Moreover, the consent of the debtor enterprise must be obtained, which is recorded in writing and attached to the appointment order.[44] However, the remuneration may not be linked to the amount of debt write-offs obtained, nor can it be a lump sum for opening the file.[45] The possibility of reconsidering the remuneration remains. The special representative’s fee during their mission may prove insufficient because the work that needed to be done was more significant than what was initially planned. Whenever the special agent finds that the maximum remuneration set by the order is insufficient, they inform the President of the court. The latter then determines, if necessary, the new terms of remuneration in agreement with the debtor enterprise and, after taking the opinion of the public prosecutor, if conciliation is used to determine the new terms regarding the agent’s fees. If no agreement is reached on the latter, the special agent’s mission ends.[46] At the end of the mission, based on the services rendered, the President orders the payment of the special agent’s remuneration by an order.[47] Section Two: Advantages of the Special Mandate Procedure The special mandate procedure is characterized by several advantages that contribute to the success of the special agent’s mission. It allows the head of the enterprise to, in complete confidentiality, enlist a specialized person to assist in resolving the difficulties facing their enterprise with great simplicity and flexibility. I - Confidentiality The procedures for appointing a special agent and their performance of the mission demand confidentiality. The spread of news about the appointment of a special agent for an enterprise could lead business partners to cease dealing with it, or it could cause some creditors to suddenly resort to individual actions to protect their rights, thereby exacerbating the difficulties and widening the gap between the enterprise and its partners. All of this complicates the special agent’s task or renders it futile. Conversely, the commitment of all actors in the special mandate procedure to confidentiality contributes to the success of the special agent’s mission. Therefore, the French Commercial Code stipulates that anyone summoned to the proceedings related to the special mandate, as well as anyone who becomes aware of it by virtue of their function, must maintain confidentiality.[48] Inspired by French legislation, Moroccan legislation has adopted this feature as an important element. It also enshrines the necessity of maintaining the confidentiality of the special mandate procedure in all its stages: from the court president’s summons of the head of the enterprise through the appointment procedures for the special agent to the latter’s performance of their duties.[49] It should be noted that non-compliance with the confidentiality obligation constitutes a fault that subjects the violator to paying damages to compensate for the harm caused by the breach, in accordance with the general rules of civil liability. This is unlike the breach of professional secrecy, for which applicable legislation imposes criminal penalties, as it is considered a crime.[50] Alongside this, the principle of confidentiality should not undermine the trust between the actors in the special mandate procedure, such as the head of the enterprise using it to gain financial advantages from their partners, especially lenders.* On the other hand, the head of the enterprise must earn the trust of the enterprise’s partners by entrusting them with all useful information about the enterprise to allow the concerned parties first to understand the origin of the difficulties, and then work to find prospects for resolving them through agreements that preserve everyone’s interests. In other words, as much as confidentiality is necessary in the special mandate procedure to protect the enterprise facing difficulties, the dissemination of transparent information within a limited and defined circle must be allowed, which is essential for fair negotiation.[51] II - Flexibility and Simplicity This is evident in the special mandate procedure through its contractual nature, which is embodied by the few provisions that regulate its course compared to other amicable preventive and curative procedures.* Furthermore, these few provisions have made the debtor enterprise, through its representatives, the main controller of the procedure during most of its stages. The submission of a request to open the special mandate procedure and appoint the special agent depends on the will of the debtor enterprise through its legal representative; no other party can compel it to do so. It can also invite specific creditors to the procedure and not others, on the grounds that the objections against the enterprise came from them, or because the enterprise believes they are best able to support it due to their connection to it, or the mutual trust between them. The participation of these creditors remains subject to their own will. Flexibility and simplicity are also apparent in the fact that the law does not define the special agent’s mission, unlike the mission of the conciliator.* In the conciliation procedure. Instead, this is left to the President of the competent court, who defines the special agent’s mission to perfectly suit the debtor’s request and the enterprise’s needs without conflicting with the will of its management. In addition, the special agent’s mission is not limited to a specific duration; the latter is determined according to the nature of the mission, the size of the enterprise, and other factors. In the same vein, only the enterprise, through its representatives, has the right to terminate the procedure at any time it deems appropriate, even if the special agent’s mission has not ended, by informing the competent court president, who will then terminate the procedure immediately, as previously mentioned. This combination of confidentiality and flexibility has made the Special Mandate a cornerstone of the French preventive system, not just in theory but in practice. This heavy reliance on preventive, out-of-court mechanisms demonstrates a widespread “culture of pre-emption” and trust in the system, a key factor in its economic success. In 2024, French courts initiated 5,144 Mandat ad hoc procedures and 3,629 Conciliation procedures (CNAJMJ, 2025). Despite the advantages of the special mandate procedure, its limits, primarily drawn by its contractual nature, give rise to some shortcomings. These include the impossibility of preventing creditors who are not parties to the agreement from continuing to sue the debtor enterprise, a common challenge in pre-insolvency frameworks across the EU before recent reforms.[52] It also does not provide any additional guarantee to the creditors who are committed within the agreement, as it is not subject to approval by the competent judicial authority. This may create an urgent need for another procedure that blends a contractual nature with a degree of judicial control, such as the conciliation procedure. Based on the foregoing, should the Algerian legislator and other legislations thereafter adopt the special mandate procedure, they are called upon to regulate the legal framework of the special agent’s mission. This should be done by defining the limits of this agent’s mission to ensure no overlap between their tasks and the tasks of the enterprise’s managers during the procedure, as well as by clarifying the criteria and methods used to determine the special agent’s fees in all cases. In all this, a sufficient degree of flexibility and simplicity should be ensured, alongside imposing the required confidentiality in the procedure, to make it an attractive option for managers of enterprises facing difficulties to the extent legally defined. Conclusion In conclusion to this comparative study, it is evident that the special mandate procedure represents a vitally important preventive tool, granting enterprises facing difficulties an opportunity to overcome them within a framework of confidentiality and flexibility. The comparison between the French and Moroccan experiences has revealed two different philosophies. The French legislator has adopted a broad and flexible approach, both in terms of the scope of beneficiaries and the assessment of the enterprise’s situation, while establishing detailed procedural rules that guarantee the rights of all parties. In contrast, the Moroccan approach has been characterized by a relative restriction in the procedure’s scope of application. There are some legislative vacuums concerning the judge’s authority and the conflicts of interest related to the agent. The success of this procedure hinges on achieving a delicate balance between its contractual nature, which grants it flexibility, and the establishment of a clear legal framework. However, the key finding of this study is that the French model’s success is not merely legal; it is economic. The French framework’s flexibility directly correlates with superior economic outcomes: a 2.6-fold higher debt recovery rate, a process that is nearly twice as fast, and an outcome that favors business continuity rather than piecemeal liquidation, when compared to the more restrictive Moroccan model. Accordingly, this study recommends that the Algerian legislator and other legislations, when adopting such a procedure, should draw inspiration from the French experience, not only for its legal comprehensiveness but for its proven economic results. The establishment of such mechanisms not only contributes to rescuing enterprises but also instills a culture of pre-emption and early recourse to the judiciary, which enhances confidence in the economic climate and supports its stability by providing a credible, efficient path for investors and creditors to recover value, as evidenced by France’s high-performing insolvency indicators. This aligns with a growing international consensus that efficient, modern insolvency laws are critical infrastructure for economic renewal, investment, and sustainable (OECD, 2022; EBRD, 2022; UNCTAD, 2024). Based on the foregoing, we present the following recommendations: Establish a personal scope that includes all enterprises contributing to development, avoiding unjustified selectivity based on commercial status. However, it may be advisable to start by limiting the scope to the most significant enterprises before expanding it later, considering the necessary resources in the form of specialized agents and judges; Regulate all matters related to the appointment of the special agent, starting from the appointment procedures and modalities, through the determination of the powers granted to the competent judicial authorities in this regard, to the definition of conflicts of interest related to the special agent, to guarantee the latter’s neutrality; Define the legal framework for the special agent’s mission by specifying its limits to ensure no overlap between their tasks and the tasks of the enterprise’s managers during the procedure. Clarify the criteria and methods used to determine the special agent’s fees in all cases. In all this, a sufficient degree of flexibility and simplicity should be ensured, alongside imposing the required confidentiality in the procedure, to make it an attractive option for managers of enterprises facing difficulties to the extent legally defined. References: Normative Acts: Law No. 94-475 of June 10, 1994, on the prevention and treatment of business difficulties. (1994, June 11). JORF No. 134; Law No. 2005-845 of July 26, 2005, on the safeguarding of businesses. (2005, July 27). JORF No. 173; Law No. 15.95 on the Commercial Code, promulgated by Dahir No. 1-96-83 of August 1, 1996. (1996, October 3). Official Gazette of the Kingdom of Morocco, No. 4418; Law No. 73.17 repealing and replacing Book V of Law No. 15.95 on the Commercial Code, regarding business difficulty procedures, promulgated by Dahir No. 1.18.26 of April 19, 2018. (2018, April 23). Official Gazette of the Kingdom of Morocco, No. 6667; Law No. 2019-222 of March 23, 2019, for the 2018-2022 programming and justice reform. (2019, September 19). JORF No. 0218; Ordonnance n° 2021-1193 portant modification du livre VI du code de commerce. Journal Officiel de la République Française, n° 0216 (16 septembre 2021), texte n° 2. Literature: Balemaken, E. L. R. (2013). The judge and the rescue of businesses in difficulty in OHADA law and French law: A comparative study. Doctoral thesis, Université Panthéon-Assas; Bouquet, B. (2008, January/February). Ad hoc mandate and conciliation: a renovated legal tool. R J C, (1), 4; BPCE L’Observatoire. (2024, October). Business failures in Q3, 2024; CNAJMJ. (2025, January). Indicateurs – Procédures collectives et de prévention - Année 2024. Conseil National des Administrateurs Judiciaires et des Mandataires Judiciaires; Coquelet, M.-L. (2017). Businesses in difficulty, payment and credit instruments (6th ed.). Dalloz; Court of Cassation, Commercial Chamber. (2012, February 7). Judgment No. 10-28.815, 10-28.816] [Unpublished]. <www.legifrance.gouv.fr/juri/id/JURITEXT00002535783>; Delebecque, P., Germain, M. (2011). Comprehensive Commercial Law: Commercial Instruments, Banks and Stock Exchanges, Commercial Contracts, Collective Proceedings (Part II; A. Moukalled, Trans.). University Establishment for Studies, Publishing and Distribution; Depoix-Robain, N. (1997). The amicable settlement of business difficulties. Doctoral thesis, University Paris IX Dauphine; Ech-Chafi, I., Ait Ali, E. H. (2024). Causes et conséquences de la défaillance des entreprises marocaines: Un état de l’art. African Scientific Journal, 3(27); El Kettani, S., Bakkali, I. (2025). The impact of COVID-19 pandemic on Moroccan firms’ performance: A pre- and post-crisis comparative analysis. Learning Gate, 5(1); European Commission. (2022). Insolvency Frameworks across the EU: Challenges after COVID-19 (Discussion Paper 182); European Commission. (2024). Commission Staff Working Document: In-Depth Review 2024 - France; Gerasimova, T. G., Galkina, A. S., Kartaeva, K. L., Kholopova, V. V. (2024). Corporate insolvency laws in selected jurisdictions: US, England, France, and Germany—A comparative perspective. Journal of Risk and Financial Management, 17(3). <doi.org/10.3390/jrfm17030120>; Guillonneau, M., Haehl, J.-P., Munoz-Perez, B. (2013). The prevention of business difficulties through ad hoc mandate and conciliation before commercial courts from 2006 to 2011. Ministry of Justice; International Monetary Fund (IMF). (2024). France: 2024 Article IV Consultation—Staff Report. IMF Country Report No. 2024/219. Washington, D.C.; Koehl, M. (2019). Negotiation in the law of businesses in difficulty. Doctoral thesis, Université Paris; Lancaster University (Lancaster EPrints). (2025). The transposition of the Preventive Restructuring Directive (2019/1023) in France and Germany; Latham & Watkins. (2021, September 20). France Publishes Restructuring and Insolvency Law Reform Ordinance; Le360.ma. (2025, June 16). Entreprises: un nombre record de faillites au Maroc en 2024 [Enterprises: a record number of bankruptcies in Morocco in 2024]; Legal 500. (2024). France: Restructuring & Insolvency – Country Comparative Guides; Möslein, F. (2021). Corporate asset locks: A comparative and European perspective. French Journal of Legal Policy; Saint-Alary-Houin, C. (2020). Law of businesses in difficulty (12th ed.). LGDJ, Domat.; Schmidt, J. (2023). Preventive restructuring frameworks: Jurisdiction, recognition and applicable law. International Insolvency Review, 32(3). <doi.org/10.1002/iir.1518>; Schwartz, M. G. (2013). The concept of the ad hoc mandate. Doctoral thesis, University of Poitiers; Shamaia, A. (2018). *Sharh Ahkam Nizam Mu’alajat Sa’ubat al-Muqawala fi Daw’ al-Qanun 17-73* [Explanation of the Provisions of the System for Handling Undertaking Difficulties in Light of Law 17-73]. Dar Al-Afaq Al-Maghribia; Toh, A. (2015). The prevention of business difficulties: A comparative study of French law and OHADA law. Doctoral thesis, University of Bordeaux; UNCTAD. (2024). World Investment Report 2024. United Nations Conference on Trade and Development; Université Paris 1 Panthéon-Sorbonne (IEJ). (2024). Introduction to French Bankruptcy Law (Analysis of Ordinance 2021-1193); Valdman, D. (2008, January 23–24). Safeguard law: which procedure for which business difficulties? Strategic choices. Gazette du Palais, 1, 14; World Bank. (2020). Doing Business 2020: Comparing Business Regulation in 190 Economies. The World Bank. Footnotes [1] Schmidt, J. (2023). Preventive restructuring frameworks: Jurisdiction, recognition and applicable law. International Insolvency Review, 32(3), pp. 427-447. <doi.org/10.1002/iir.1518>. [2] International Monetary Fund (IMF). (2024). France: 2024 Article IV Consultation—Staff Report. IMF Country Report No. 2024/219. Washington, D.C. [3] European Commission. (2024). Commission Staff Working Document: In-Depth Review 2024 - France. [4] Gerasimova, T. G., Galkina, A. S., Kartaeva, K. L., Kholopova, V. V. (2024). Corporate insolvency laws in selected jurisdictions: US, England, France, and Germany—A comparative perspective. Journal of Risk and Financial Management, 17(3), p. 120. <doi.org/10.3390/jrfm17030120>. [5] Lancaster University (Lancaster EPrints). (2025). The transposition of the Preventive Restructuring Directive (2019/1023) in France and Germany. [6] BPCE L’Observatoire. (2024, October). Business failures in Q3, 2024. [7] Le360.ma. (2025, June 16). Entreprises: un nombre record de faillites au Maroc en 2024 [Enterprises: a record number of bankruptcies in Morocco in 2024]. [8] Law No. 94-475 of June 10, 1994, on the prevention and treatment of business difficulties. (1994, June 11). JORF No. 134. [9] Law No. 2005-845 of July 26, 2005, on the safeguarding of businesses. (2005, July 27). JORF No. 173. [10] Université Paris 1 Panthéon-Sorbonne (IEJ). (2024). Introduction to French Bankruptcy Law (Analysis of Ordinance 2021-1193). [11] Latham & Watkins. (2021, September 20). France Publishes Restructuring and Insolvency Law Reform Ordinance; Legal 500. (2024). France: Restructuring & Insolvency – Country Comparative Guides. [12] Law No. 15.95 on the Commercial Code, promulgated by Dahir No. 1-96-83 of August 1, 1996. (1996, October 3). Official Gazette of the Kingdom of Morocco, No. 4418. [13] Law No. 73.17 repealing and replacing Book V of Law No. 15.95 on the Commercial Code, regarding business difficulty procedures, promulgated by Dahir No. 1.18.26 of April 19, 2018. (2018, April 23). Official Gazette of the Kingdom of Morocco, No. 6667. * For example, the number of times a special agent was appointed between 2006 and 2012 in France in commercial courts reached nearly 5,900 appointments. The acceptance rate of requests for the appointment of a special agent by the presidents of commercial courts alone in the same period reached 84.2%. For more statistics on the special mandate during the period 2006-2012, see Guillonneau, M., Haehl, J.-P., Munoz-Perez, B. (2013). The prevention of business difficulties through ad hoc mandate and conciliation before commercial courts from 2006 to 2011. Ministry of Justice. [14] Schwartz, M. G. (2013). The concept of the ad hoc mandate. Doctoral thesis, University of Poitiers, p. 193. [15] Möslein, F. (2021). Corporate asset locks: A comparative and European perspective. French Journal of Legal Policy. * In French law, the High Court (tribunal de grande instance) has been replaced by the Judicial Court (tribunal judiciaire) through the law on programming and justice reform, pursuant to Ordinance No. 2019-964 of September 18, 2019, taken in application of Law No. 2019-222 of March 23, 2019, for the 2018-2022 programming and justice reform. (2019, September 19). JORF No. 0218. [16] El Kettani, S., Bakkali, I. (2025). The impact of COVID-19 pandemic on Moroccan firms’ performance: A pre- and post-crisis comparative analysis. Learning Gate, 5(1). [17] Ech-Chafi, I., Ait Ali, E. H. (2024). Causes et conséquences de la défaillance des entreprises marocaines: Un état de l’art. African Scientific Journal, 3(27). [18] Depoix-Robain, N. (1997). The amicable settlement of business difficulties. Doctoral thesis, University Paris IX Dauphine. p. 61. [19] Toh, A. (2015). The prevention of business difficulties: A comparative study of French law and OHADA law. Doctoral thesis, University of Bordeaux, p. 178. *Because after this period, the competent judicial body will have no other option but to initiate judicial settlement or liquidation proceedings, as the case may be. [20] Valdman, D. (2008, January 23–24). Safeguard law: which procedure for which business difficulties? Strategic choices. Gazette du Palais, 1, 14. [21] Coquelet, M.-L. (2017). Businesses in difficulty, payment and credit instruments (6th ed.). Dalloz, p. 189. * It is a preventive procedure that allows managers of enterprises facing difficulties to find simple and quick amicable solutions embodied in a confidential agreement to restore their enterprise’s situation. [22] L611-4, C. Com, Fr. [23] Ibid., L611-3, Modified by Ordinance No. 2021-1193 of September 15, 2021 - Art. 4: “The President of the court may, at the request of a debtor, appoint an ad hoc agent whose mission he shall determine. The debtor may propose the name of an ad hoc agent. The decision appointing the ad hoc agent shall be communicated for information to the statutory auditors when they have been appointed. The competent court is the commercial court if the debtor carries on a commercial or craft activity, and the judicial court in other cases. The debtor is not required to inform the social and economic committee of the appointment of an ad hoc agent”. [24] According to Article 550 of the Moroccan Commercial Code. [25] Ibid., Article 549. [26] Article 550 of the Moroccan Commercial Code. * From the terminology of the third paragraph of Article 549 of the Moroccan Commercial Code, “The president of the court shall appoint the special agent... upon the proposal of the head of the undertaking...”, it is understood that the appointment is linked to the proposal. This is especially so as the Code has bypassed the issue of the extent to which the opinion of the court president and the head of the undertaking on the person of the special agent may align or conflict. Conversely, the failure to address the issue may be an oversight by the Moroccan legislator. [27] Shamaia, A. (2018). *Sharh Ahkam Nizam Mu’alajat Sa’ubat al-Muqawala fi Daw’ al-Qanun 17-73* [Explanation of the Provisions of the System for Handling Undertaking Difficulties in Light of Law 17-73]. Dar Al-Afaq Al-Maghribia, p. 65. [28] R600-2, C. Com, Fr. [29] Schwartz, M. G. (2013). The concept of the ad hoc mandate. Doctoral thesis, University of Poitiers, pp. 220-221. * Nevertheless, the court’s President may not appoint a special agent whose appointment has not been proposed by the debtor enterprise without first obtaining the latter’s consent to the terms of their fees or remuneration, based on the second paragraph of Article R611-47-1 of the French Commercial Code. * This appears to be a typo in the source text. The provision for appeal is in Article R611-20 of the French Commercial Code. [30] Balemaken, E. L. R. (2013). The judge and the rescue of businesses in difficulty in OHADA law and French law: A comparative study. Doctoral thesis, Université Panthéon-Assas, p. 79. [31] Schwartz, M. G. (2013). The concept of the ad hoc mandate. Doctoral thesis, University of Poitiers, pp. 200-201. * It should be noted that in the case where the debtor enterprise is a sole proprietorship with limited liability or a self-employed entrepreneur under the conditions specified in Section 3 of Chapter VI of Title II of Book V of the French Commercial Code, the assessment of the existence of remuneration or payments received by the person from the debtor enterprise is made with respect to all the assets held by the latter, not limited to the assets allocated to the specific activity, based on the first paragraph of Article L611-13 of the French Commercial Code. [32] Article L 233-16 of the French Commercial Code provides for two types of control: exclusive control and joint control. The first is achieved in the following cases: 1° When the controlling company holds, directly or indirectly, a majority of the voting rights in another company called the subsidiary; 2° When the controlling company has appointed the majority of the members of the administrative, management, or supervisory bodies of another company for two consecutive financial years, considering that the controlling company holds, directly or indirectly, a portion exceeding 40 percent of the voting rights, and no other partner or shareholder holds, directly or indirectly, a larger portion; 3° When the subsidiary has the right to exercise a decisive influence over a project under a contract or statutory provisions permitted by applicable law. Joint control is achieved when control over jointly managed projects is shared with a limited number of partners or shareholders, such that decisions result from their agreement. * This is a procedure that helps to prevent debtor enterprises from bankruptcy in general through a rescue plan prepared and presented by the enterprise’s management, the enrichment and supervision of which is handled by a professional appointed by the competent judicial authorities. * This is a collective procedure that opens a consultation between the competent court and the representatives of the enterprise in cessation of payments, under the supervision of the public prosecutor’s office and the employees, with the aim of preserving the enterprise’s continuity. * A consular judge (juge consulaire) is the name given to merchants, artisans, or service providers elected for a term of two or four years to sit alongside professional judges in French courts, including commercial courts. [33] R611-20, C. Com, Fr. [34] Third paragraph of Article 459 and Article 550 of the Moroccan Commercial Code. [35] Schwartz, M. G. (2013). The concept of the ad hoc mandate. Doctoral thesis, University of Poitiers, p. 240. [36] Delebecque, P., Germain, M. (2011). Comprehensive Commercial Law: Commercial Instruments, Banks and Stock Exchanges, Commercial Contracts, Collective Proceedings (Part II; A. Moukalled, Trans.). University Establishment for Studies, Publishing and Distribution, p. 1214. [37] Saint-Alary-Houin, C. (2020). Law of businesses in difficulty (12th ed.). LGDJ, Domat., p. 192. [38] Schwartz, M. G. (2013). The concept of the ad hoc mandate. Doctoral thesis, University of Poitiers, p. 80. [39] Last paragraph of Article 550 of the Moroccan Commercial Code. While there is no corresponding article in the French Commercial Code, this is reflected in actual practice. [40] Marie Goncalves Schwartz, op. Cit, p. 241. * The President of the court can deduce from the periodic reports submitted to him by the special agent. [41] R611-21, C. Com, Fr. * The same applies to a conciliator, as they are subject to the same provisions governing their fees or remuneration. [42] Koehl, M. (2019). Negotiation in the law of businesses in difficulty. Doctoral thesis, Université Paris, p. 75. [43] R611-47, C. Com, Fr. * The court clerk notifies the order setting the fees to the special agent and the debtor enterprise. He also immediately notifies the public prosecutor if conciliation is used to determine the fees. It can be appealed by the special agent or the debtor before the first president of the Court of Appeal, noting that the appeal is submitted and heard within the time limits and conditions provided for in Articles 714 to 718 of the French Code of Civil Procedure, based on Article R611-50 of the French Commercial Code. * Because the President of the court works to inform the public prosecutor to give their opinion, suppose the public prosecutor does not give their opinion. In that case, the President of the court cannot open the special mandate procedure before the expiration of forty-eight hours from the date of notification, according to the third paragraph of Article R611-47-1 of the French Commercial Code. [44] R611-48, C. Com, Fr. [45] Ibid., R611-49. [46] Ibid., L611-14, para. 01. [47] Bouquet, B. (2008, January/February). Ad hoc mandate and conciliation: a renovated legal tool. R J C, (1), 4. [48] L611-15, C. Com, Fr. [49] Last paragraph of Article 549 of the Moroccan Commercial Code. [50] Schwartz, M. G. (2013). The concept of the ad hoc mandate. Doctoral thesis, University of Poitiers, p. 287). * A judgment from the Court of Appeal of Grenoble in France supports this. In summary, to enable a group of companies preparing for a major acquisition, a consortium of banks met to finance the operation. The group of companies experienced financial difficulties, particularly with its cash flow, and consequently requested a renegotiation of its loan repayment schedule. Subsequently, the group faced further financial difficulties, leading two subsidiary companies to request the benefit of a special mandate in September 2006 to assist in their negotiations with the banking consortium for the renegotiation of the previously agreed loan schedule. This resulted in the opening of a conciliation procedure, and an agreement was subsequently approved in February 2007. The group experienced new financial difficulties in the first half of 2007, and a second conciliation was conducted in July 2007 to find new investors. A conciliation protocol was established in November 2007, providing for several restructuring and loan rescheduling operations. Despite this continued banking support, the statutory auditor, in July 2008, informed the shareholders—in application of the duty to alert—of facts likely to compromise the continuity of operations. Faced with this growing deterioration, the group’s companies requested the appointment of a new conciliator in September 2008. Two meetings were held between the banking consortium and the concerned companies, which failed to inform the consortium about the alert procedures and the appointment of the conciliator. However, one of the banks discovered the existence of the auditor’s alert procedures and the opening of the conciliation procedure, and decided to terminate the contractual relationship in October 2008, based on the failure to be informed about the alert procedures and the conciliator’s appointment. In response, the group’s companies declared a cessation of payments, and judicial settlement proceedings were opened against them in November 2008, leading to their liquidation through a sale plan in March 2009. The liquidator subsequently filed a claim for damages against the bank that cut off the credit facilities. The Commercial Court of Grenoble issued a judgment on January 10, 2010, ordering the bank to pay. However, the appellate judgment overturned this, considering the managers’ conduct to be disloyal because they did not inform the banking consortium that their companies were subject to alert and conciliation procedures. For more details on the judgment, see: Court of Cassation, Commercial Chamber. (2012, February 7). Judgment No. 10-28.815, 10-28.816] [Unpublished]. <www.legifrance.gouv.fr/juri/id/JURITEXT00002535783>. 51 Schwartz, M. G. (2013). The concept of the ad hoc mandate. Doctoral thesis, University of Poitiers, pp. 290-293. * These provisions mainly regulate the independence of the special agent and the criteria for determining their fee, as previously discussed. * The mission of the conciliator generally consists of mediating between the debtor enterprise and its creditors to bring their views closer together, in the hope of resolving the difficulties facing the debtor enterprise and achieving the required continuity. This is primarily found in Article L 611-7 of the French Commercial Code and Article 554 of the Moroccan Commercial Code. [52] European Commission. (2022). Insolvency Frameworks across the EU: Challenges after COVID-19 (Discussion Paper 182).
Georgia’s Integration into the European Union: A Synergy of Mutual Interests
The aim of this article is to demonstrate the mutual interest of both parties in working together today, with a view to Georgia's full integration into the European Union. This objective is rooted in a long-standing relationship that has progressively deepened over the years, driven by shared values and a common aspiration for peace and stability in the region. To this end, we propose to examine the various points of convergence, from both a Georgian and a European perspective. These include political alignment, economic cooperation, security collaboration, and cultural exchange. Georgia has made significant efforts to align its institutions and policies with European standards, while the European Union has expressed consistent support for Georgia’s sovereignty and territorial integrity. By exploring these elements, this article seeks to highlight not only the benefits of stronger cooperation but also the strategic importance of Georgia's full accession for the development of the European Union itself. Keywords: Georgia, European Union, integration, mutual interests. Introduction Some European countries are not part of the Union for various reasons (neutrality in Switzerland, fiscal freedom in Andorra, etc.), while others are applying to join. Georgia is one of these new countries eager to join the European Union, a desire marked by the Georgian population itself (82%[1]), and by the decision of the Union’s institutions to recognize the validity of Georgia’s application for enlargement on December 14, 2023. Founded after the Second World War to promote peace, prosperity, and solidarity between its member states, the European Union today is much more than just the economic and customs union it was at its inception. Today, it occupies a central position in the world’s political, economic, social, cultural, diplomatic, and strategic landscape. What’s more, it embodies an ambitious project to support and encourage democratic values, human rights, and cooperation on an international scale. In the current and prospective context, the European Union is facing a series of complex and interconnected challenges: the scale and recurrence of international economic and financial crises; the sometimes uncontrolled migration at its borders; the renewal of security policies against cybercrime and terrorism; the return of symmetrical conflicts in Europe (war in Ukraine); the erratic international policy of Donal Trump; the necessary revolution in the face of threats to climate and biodiversity. To achieve this, the Union is implementing institutional and pragmatic internal measures, and participating in international cooperation, but it must also rethink its global influence: the United States is no longer Europe’s unconditional ally, and the rise of new players (China, India, Russia...) demonstrates the need to re-examine its place and role on the world stage. Does Europe want to close itself off like a besieged fortress, to deny itself by returning to a selfish, individualistic Europe of Nations, or to continue to expand with new members bringing new opportunities? To meet this challenge, on June 14, 2022, in Brussels, the European Council held a strategic debate on the European Union’s relations with its partners in Europe, focusing on the proposal to launch a “European political community”. The aim is to provide a platform for political coordination for European countries across the continent, with this platform potentially involving all European countries with which the Union maintains close relations. The aim would be to foster political dialogue and cooperation to address issues of common interest, to strengthen the security, stability, and prosperity of the European continent. In its conclusions (June 23-24, 2022), “The European Council recognizes the European perspective of Ukraine, the Republic of Moldova and Georgia. The future of these countries and their citizens lies within the European Union”.[2] The European Council was thus ready to grant candidate country status to Georgia once the priorities set out in the Commission’s opinion on Georgia’s application for membership had been taken into account. This will be done in December 2023, with Georgia officially acceding to candidate country status. What benefits can the European Union expect to derive from the future integration of these new countries, specifically Georgia, which is not directly attached to the geographical territory of existing Europe? The analysis must be carried out at several levels, each of which corresponds to specific and plural expected benefits. Political, Institutional, and Security Level A- Expanding the European Union’s Sphere of Influence Generally speaking, the addition of new members can only widen the EU’s geopolitical scope and strengthen its role as an international player, giving it a stronger voice in world affairs. Enlargement is therefore one of the major strategic elements of the European Union’s foreign and neighborhood policy. From a practical point of view, the example of Croatia’s accession in 2013 is a perfect illustration of how the integration of new members enables the EU to strengthen its regional influence and promote stability. Indeed, Croatia’s accession has enabled the EU both to strengthen its influence in the Western Balkans and to help stabilize the region.[3] Indeed, the Western Balkans is a historically fragile region, marked by ethnic and political conflict, and as such, represents a strategic area for the EU. Croatia’s accession symbolized the EU’s strong commitment to the stabilization and integration of this region. By becoming a member of the EU, Croatia has also served as a model for the other countries of the Western Balkans, demonstrating two important points: firstly, that economic, political and social reforms can lead to full membership, and secondly, that Croatia’s accession has strengthened the EU’s credibility as an actor capable of promoting democratic and economic reforms. The countries of the region, such as Serbia, Montenegro, Albania, Northern Macedonia, and Bosnia-Herzegovina, see the EU, through this example, as a key partner for their development and stability. The EU’s commitment through enlargement also encourages these countries to adopt European standards of governance, human rights, and the rule of law, and thus demonstrates the Union’s ability to promote its “soft power” values internationally. Expanding the EU’s area of influence by integrating Georgia, in a fragile and dangerous geopolitical and strategic context, is therefore in line with strategic geopolitics: Georgia, situated at the crossroads of Eastern Europe and Asia, occupies a strategic geographical position of particular importance to the European Union. By considering Georgia’s integration, the EU could considerably extend its area of influence in the South Caucasus, a region marked by geopolitical tensions and the competing ambitions of powers such as Russia and Turkey. Georgia’s geographical and geopolitical location would be of great benefit to Europe: among other things, it would position Georgia directly on the northern border of Turkey and Armenia (another candidate for EU membership), and the northeastern border of Azerbaijan and the southern border of Russia. The European Union’s area of influence would thus be multiplied by Georgia’s accession to the Union alone. B- Promoting Peace, Security, and Long-term Stability By encouraging cooperation and economic, political, and social integration, EU enlargement can help to promote long-term peace and stability throughout the European region and on the southern border of the Caucasus. Thus, by integrating Georgia, the EU can only strengthen its ability to shape regional orders and to guarantee the collective security of its space and the new integrated territory. Indeed, this enlargement process is not only beneficial for the new member but also for the Union as a whole, by strengthening its geopolitical position and ensuring the harmonious and stable development of its neighborhood. Here, too, the Croatian example is conclusive: stabilization of the Western Balkans is crucial to the security of Europe as a whole. Croatia’s integration has reduced the risk of conflict in the region by anchoring the country in European structures of security and cooperation. It has also sent out a strong signal against the influence of outside players such as Russia and China, who are seeking to extend their influence in Eastern Europe and the Balkans in particular. Croatia’s accession has also encouraged greater regional cooperation. By becoming a member of the EU, Croatia has actively participated in regional cooperation initiatives, helping to resolve bilateral disputes and promote reconciliation in the Western Balkans. This has helped to create a more stable and cooperative environment in the region. Georgia’s integration into the EU would therefore help stabilize a region often shaken by conflict. Georgia’s proximity to trouble spots such as Abkhazia and South Ossetia, and its recent history of war with Russia in 2008, make the promotion of peace and security crucial. By integrating Georgia, the EU could play a more active role in resolving regional conflicts and promoting reconciliation, or at least stabilizing a highly critical geopolitical situation. Indeed, Georgia’s integration into the EU would drastically weaken Russian influence in the South Caucasus, as Russia wields considerable influence in the region and takes a dim view of its Georgian and Armenian neighbors’ attempts at European and Atlantic integration. By offering Georgia a path to membership, the EU could reduce Georgia’s dependence on Russia, strengthen the country’s sovereignty and independence, and represent a major step in expanding the Union’s sphere of influence. The EU would thus strengthen its ability to shape the regional order in the South Caucasus, promote stability and security, disseminate its values, and reduce the influence of external actors. A number of concrete examples demonstrate that enhanced cooperation between EU member states in the field of defense and security has made it possible not only to combat direct and indirect military threats (cyber threats) more effectively, but also to coordinate responses to international crises.[4] Similarly, several studies have shown that EU enlargement has had a positive effect on peace and stability in the candidate countries, and even more so in the integrated countries.[5] In this respect, the Ukrainian example is also quite conclusive: any country bordering a power aiming at expansionism (conquest of territory, human colonization), in this case, Vladimir Putin’s Russia, can suddenly be invaded under the pretext of ethnic regrouping or reconstitution of a “historically” homogeneous territorial unit. Georgia underwent this expansionist policy in 2008, Crimea in 2014, and the eastern part of Ukraine in 2022. Yet, Putin is not attacking any of the NATO and/or EU member states on which he might also have conquering designs: Poland and the three Baltic states of Estonia, Latvia, and Lithuania. European membership and the common military defense shield of NATO member countries are sufficient deterrents to prevent any direct military aggression. Finland, for example, after decades of neutrality, urgently joined the Defense Organization on April 4, 2023, protecting itself from any expansionist vision on the part of its Russian neighbor. The integration of new members into the EU is therefore undeniably an essential factor in maintaining security and stability, both for these territories and for the Union as a whole. Identity and Culture A- Strengthening the Cohesion of the European Identity Europe is made up of 27 heterogeneous states (level of economic and social development, specific cultures and languages, etc.). It is this diversity that makes it so rich. Any additional contribution based on “present consent, the desire to live together, and the will to continue to make the most of the heritage we have received” (Ernest Renan), underpins the ideal of a “European nation”. It’s not a question of creating a “United States of Europe”. The United States is a country populated by conquered natives, successive waves of migrants, and descendants of slaves, who ended up creating a “melting pot” of diverse populations, mostly from outside the territory, creating a sovereign and unified state. Europe, on the other hand, is made up of locally existing nations, of countries built up throughout history, which continue to exist in the community formed by the European Union. Far from denying linguistic and cultural differences, Europe claims to be a juxtaposition of autonomous entities, freely linked by a new common destiny, enjoying the richness of its differences. There is no desire to create a “European” in the sense of an “American”, there is no attempt to acculturate or dominate one culture over another, but on the contrary, a desire to build a common project on these specificities and disparities. In this way, each new arrival enriches the diversity of the European Community, and helps to continue building a European “identity”, this richness being the very foundation of its existence: “strengthening the European identity is a necessity for the future of Europe”.[6] But how can we define Europe in terms of identity, to promote common European values? In other words, which countries not yet integrated into the Union can be “naturally” defined as “European”, and therefore “legitimately” accessible to full integration? A single criterion is not enough. For example, if we take only the geographical aspect into account, it may seem incongruous to refuse Turkey’s application but to integrate Georgia and Armenia, which are located further to the east. History would lead us to consider territories long conquered and dominated by European empires (the Maghreb, for example), and the linguistic aspect alone to consider access to Europe for French-speaking, English-speaking, or other peoples. Religion is an aspect often evoked, through the fantasy of a “Christian” Europe, which does not stand up to the undeniable presence of other religions on the continent, and to the dominant secularism in the powers and cultural life of many contemporary European countries. A multiplicity of objective and subjective criteria must be taken into account: to the north and west, the Atlantic Ocean marks a geographical boundary; to the south and towards Turkey, history, religion, and customs form a second frontier. To the east, another criterion needs to be added: if history, religion and customs are shared (as in the case of Russia), the Union can only admit states that have voluntarily decided to claim, assume and apply the political and institutional consequences of their membership of the common project that is the European Union. The enlargement of the EU to include Georgia meets all the criteria mentioned here: the country’s history is European, its religion has been dominant in Europe for two millennia, its culture is in no way oriental or Asian, and its desire to anchor itself institutionally in Europe is strong. Moreover, Georgia’s accession would reinforce the spread of European values of democracy, the rule of law, and respect for human rights in the South Caucasus and motivate Georgia to pursue and intensify its political and economic reforms, aligning its standards and practices with those of the EU.[7] Finally, membership would serve as an example to other countries in the region, encouraging similar developments. There is also a kind of “moral duty” Europeans owe to Georgia: it was one of the first countries to disengage from Russia after the collapse of the USSR. In 2004, Eduard Shevardnadze was overthrown by the “Rose Revolution”, ushering in a pro-European and reformist government. In 2008, former president Mikheïl Saakachvilli applied (along with Ukraine) for NATO membership. It was supported by George W. Bush, but rejected by Nicolas Sarkozy and Angela Merkel to avoid offending Putin’s Russia... Two months later, in August 2008, Russia attacked the capital Tbilisi and moved into the breakaway republics of Abkhazia and South Ossetia. NATO membership would have prevented this, as would EU membership today. Finally, as we have already mentioned, Putin is not currently attacking any NATO and/or EU member country: the moral duty of Europeans is therefore matched by the geostrategic necessity of containing Russian influence. B- Boosting Tourism and Cultural Wealth Tourism is a crucial sector for the European economy, making a very significant contribution to the GDP of EU member countries: in 2019, tourism accounted for around 10% of EU GDP and generated over 27 million jobs, or almost 12% of total employment in the EU. The addition of Georgia to the EU can only stimulate intra-European tourism, encouraging citizens of the current Union to discover new places, traditions, and cultures. Indeed, Georgia, with its rich history, unique culture, diverse landscapes, and natural heritage, would add a new dimension to the EU’s tourism offering, attracting tourists interested in lesser-known, more “authentic” and original destinations. In 2019*, Georgia welcomed over 9.3 million international visitors, so it’s a safe bet that the country’s accession would lead to a sharp rise in tourism on its soil. There are many compelling examples: Hungary and Poland joined the European Union in 2004. On average, these two countries received 9.6 and 14.3 million travelers a year, respectively, before their accession. By 2019, these figures will have risen to 16.5 and 21.4 million tourists, an increase of over 70% for Hungary and around 50% for Poland. The growth of the sector, thanks to accession, is therefore quite significant. The same applies to Bulgaria (5.2 million tourists in 2007, versus 12 million in 2019, an increase of 130%), Romania (1.9 versus 2.7 million, a 42% increase in inflows), and Croatia (12.4 million in 2013, when it joined the EU, 19.5 million in 2019, an increase of 57% in just six years).[8] These figures show that EU membership has had a positive impact on tourism in member countries, particularly in terms of increasing the number of foreign visitors. This is due to a number of factors, including easier travel, greater political and economic stability, better integration into European transport networks, and greater visibility of destinations for foreign tourists. But it’s undeniable that the effects are also positive for the European Union as a whole, as these tourism-receiving countries contribute to the Union’s budget, and encourage their citizens to travel to the rest of Europe too. It also harmonizes quality standards and regulations in the tourism sector, enhancing the tourist experience and boosting confidence: according to a study by the European Commission, some 80% of tourists say they are satisfied with tourist services in the EU, thanks to perceived quality and safety. Georgia’s accession to the EU would attract structural and investment funds to develop tourism infrastructures, thus improving the accessibility and quality of the country’s tourism services. At the same time, tourism partnerships based on policies of regional cooperation and joint initiatives would be strengthened: Georgia’s accession would enable enhanced cooperation with other EU member countries on shared tourism initiatives, such as cultural itineraries and joint tourism promotion projects. The tourism sector can rely on the promotion of the country’s rich culture and heritage. Georgia is known for its UNESCO World Heritage sites[9], its ancient wine-making traditions, its unique and varied cuisine, its charming capital city steeped in history, and its remarkable natural sites. Georgia also has a rich and diverse history and culture, with a long-standing and vibrant artistic, musical, and literary tradition. Its integration into the EU would thus enrich the Union’s cultural diversity, bringing new perspectives, traditions, and forms of artistic expression. In the form of a shared cultural heritage, its integration into the EU could both contribute to the preservation and promotion of this common cultural heritage and strengthen the sense of belonging to a diverse and multiple European community. Similarly, the country’s integration would facilitate cultural and artistic exchanges between Georgia and the other member states of the European Union. This could take the form of artistic collaborations, cross-cultural festivals, exhibitions, and other events, all promoting mutual understanding and the enrichment of citizens. Beyond tourism and cultural exchanges, education and research would also benefit from this full integration, in at least three respects: firstly, the promotion and development of multilingualism, with the Georgian language joining European language programs, enriching the language skills of EU citizens. In addition, the development of educational and cultural resources, both in Georgian and in European languages, will facilitate mutual language learning throughout the Union. The second advantage would be the extension of educational exchange programs, such as Erasmus+, to Georgian students and researchers, enriching academic and cultural prospects within the EU. Last but not least, integration would enable the amplification of research between scientists, humanities specialists, academics, and private players. The writing of this article is a prime example of this. These combined advantages could make the Union an even more attractive, enriching and competitive tourist, cultural, scientific and intellectual destination on the world stage, strengthening the European Union’s global appeal. Economic and Strategic Level A- Economic Benefits from Expansion of the Single Market The accession of new countries increases the size of the EU single market, opening up new opportunities for trade, investment, and growth, both for the newcomer and for existing member countries. So, for example, if we take the case of Croatia seen above, EU enlargement has opened up new economic opportunities for both sides. Croatia has benefited from European investment (7.7 billion euros in FDI (Foreign Direct Investments) between 2013 and 2019), structural and cohesion funds (12.7 billion euros since 2013), which have stimulated its economic development (gain of over 7 billion euros in GDP). In return, European companies have gained greater access to the Croatian market, boosting trade and investment in the region: integration has added some 4.2 million consumers to the single European market, significantly increasing the volume of intra-EU trade. The integration of 10 new countries in 2004 (including Poland, Hungary, and the Czech Republic) led to a significant increase in intra-EU trade: between 2003 and 2008, exports from the old member states to the new ones almost doubled, from 134 billion euros to 247 billion euros. Similarly, in macroeconomic terms, the accession of new members, even if they are less wealthy and less developed, is a source of growth for the Union as a whole: +2.8% growth in European GDP following the entry of Croatia, +4% following the accession of Bulgaria and Romania in 2007.[10] In addition to these quantitative data, there are also positive qualitative elements: the integration of new countries stimulates competition and innovation, which in turn strengthens the overall competitiveness of the EU and the new countries on the world stage.[11] Micro-economically, too, the positive data are undeniable: the integration of new members promotes job creation throughout the EU. For example, the 2004 enlargement contributed to the creation of 1.5 million jobs in the new member states between 2004 and 2007. What’s more, in a report by the European Commission,[12] detailing the economic impact and benefits of EU enlargement in terms of jobs and economic growth, totaling the jobs created directly in the member states and the additional jobs indirectly created in the old new member states, it is estimated that EU enlargement since 2004 has contributed to the creation of around 4 million jobs across the EU as a whole up to 2019. EU enlargement also brings economies of scale, particularly in manufacturing and services. EU companies can benefit from lower production costs and a larger market for their products and services. The French example of the “Dacia” car brand is a case in point: this brand could not have been created in France, as production costs and taxes made it impossible to produce a low-cost, high-quality vehicle. By locating its activities in Romania, the French group directly employs 14,000 people, accounts for 14% of manufacturing jobs in the country, and contributes 3% to the national GDP. In France, Dacia’s activities employ thousands of people (dealers, distribution network, indirect jobs) and account for 7.6% of the French automotive market. Both countries benefit from a Win-Win situation. Finally, in the specific case of Georgia, the European Union would also benefit from an unprecedented advantage, due to the country’s geographical position: a further consolidation of its strategic position in a region where it has little presence. Indeed, by integrating Georgia, the EU could also improve regional connectivity, facilitating links between Europe and Central Asia. Georgia, with its Black Sea ports and transport corridors linking Europe and Asia, would play a key role in regional connectivity initiatives such as the New Silk Roads. This would greatly strengthen the EU’s strategic position in international trade networks. B- A Strategic Market for the European Union For the European Union, Georgia offers a number of strategic (economic) advantages,[13] three of which seem essential: access to numerous natural resources, the possibility of establishing energy cooperation, and the necessary diversification of the Union’s sources of supply. Georgia has significant natural resources, such as manganese, copper, iron, coal, gypsum, and hydroelectric resources, which could benefit the EU.[14] These natural resources give Georgia economic and geopolitical importance in the region: the country has large reserves of fresh water (rivers), making it independent for agricultural production, hydroelectricity (also an export sector), and human and animal consumption. What’s more, the country’s fertile farmland is ideal for growing cereals, fruit, and vegetables, making it an important agricultural region, again self-sufficient and potentially export-oriented. When it comes to energy cooperation, it’s worth focusing on hydropower, as enhanced cooperation in the energy field could benefit the EU, thereby contributing to Europe’s energy security. Georgia has significant hydropower potential, with over 26,000 rivers, 300 of which are usable for generation, and a total technical potential estimated at around 80 terawatt-hours (TWh) per year. At present, only 20% of this potential is exploited, with an annual production of around 12 TWh. In 2022, Georgia produced around 10 TWh of electricity from its hydroelectric plants, covering more than 75% of its electricity needs, and exports electricity to its neighbors, notably Turkey, Azerbaijan, and Russia. In 2021, electricity exports reached around 1.4 TWh. Several new hydroelectric projects are underway or in development, such as the Nenskra (280 MW) and Namakhvani (433 MW) hydroelectric power plants, with investments totaling several billion dollars. In response to these new projects, the European Bank for Reconstruction and Development (EBRD) and other international financial institutions have invested significantly in Georgia’s energy sector to strengthen its infrastructure and export capacity. As a result, Georgia is considered a key partner in the European Neighborhood Policy and the Eastern Partnership, an EU initiative aimed at strengthening economic and political cooperation with neighboring countries: the EU has allocated over 500 million euros to energy projects in the region, including initiatives to improve energy efficiency and develop electricity transmission infrastructure. Georgia’s largely untapped hydroelectric potential represents a major opportunity to strengthen energy cooperation with the EU. Such collaboration could diversify Europe’s energy sources and contribute to its energy security, while promoting Georgia’s economic development.[15],[16] Still in the field of energy cooperation, it should also be noted that Georgia also plays a strategic role as a transit corridor for oil and natural gas pipelines linking the Caspian Sea to Western Europe:[17] the Baku-Tbilisi-Ceyhan (BTC) network and the South Caucasus Gas Pipeline (SCP) reduce Europe’s dependence on Russia. The same applies to the Southern Gas Corridor project, which includes the SCP and the Trans Adriatic Pipeline (TAP), designed to bring natural gas from Azerbaijan to Europe via Georgia and Turkey, with a capacity of 16 to 31 billion cubic meters per year. Finally, by integrating Georgia, the EU could diversify its sources of supply of raw materials, energy, and other products, reducing its dependence on certain suppliers or single energy suppliers. For Europe, this is an important factor in its security and independence: the EU’s energy dependence on imports of natural gas and oil is substantial, and even strategically dangerous. By 2021, around 90% of the natural gas and 97% of the oil consumed in the EU will be imported, much of it from Russia. Obviously, following the conflict between Russia and Ukraine, from 2022 onwards, Russian gas imports decreased significantly due to geopolitical tensions, accentuating the need to diversify energy supply sources for the European Union.[18] Conclusion Today, perhaps more than ever before in its history, Europe is at a crossroads: its post-World War II conception was based on the need for reconciliation between belligerent countries, the maintenance and preservation of peace, and cooperation in the fields of energy, economics, and social affairs. Its ideological guiding principle was to build a common destiny between nations from the same continent and a shared historical and cultural melting pot, in the face of the two American and Soviet blocs. Chronologically, Europe was first built with six then nine nations, based on technical considerations, pooling energy resources, harmonizing regulations and customs duties, and moving towards the creation of a single market. Then, little by little, its enlargement to 27 countries, the creation of a form of sovereignty of its own (European passport), and common rules of life (right to abortion, abolition of the death penalty), led Europe to evolve towards a supranational conception, sometimes in opposition to the regalian powers of member states. As we said in our introduction, the economic and financial crises, the rise of international competition from new giants, and the fear of loss of sovereignty felt by many leaders and citizens alike, are jeopardizing the very existence of the European Union: the rise of nationalist powers in virtually all EU countries is challenging the achievements of the current community. Against this tense backdrop, some see EU enlargement as an additional risk of rejection by a section of the population, a rejection often manipulated by xenophobic and isolationist political parties, backed by outside powers intent on weakening the power of the European Union. However, the enlargement of the Union to include countries that are intrinsically “European”, such as Georgia, is perhaps the best way of saving Europe itself: no one can doubt the positive effects of the accession of ten countries, including eight from Central and Eastern Europe, in May 2004. Over the past 20 years, this contribution to the Union has been one of the greatest driving forces behind its economic development, and its ability to grasp what it means to be “European” in the cultural and social sense of the term. Far from being a danger, the accession of a country like Georgia is essential to (re)give the Union the very meaning of its existence: “Let’s not be English, French or German. Let us be European”. (Victor Hugo, Choses vues, 1887). Bibliography: (2022). Annual Report 2022. Georgian National Energy and Water Supply Regulatory Commission; National Democratic Institute. (2023). Taking Georgians’ pulse – Findings from March 2023 telephone survey. CRRC Georgia. Available at: <https://www.ndi.org/publications>. Web sources: info. (2004). L’Europe et ses frontières. Études, (6), 729. Available at: <https://www.cairn.info/revue-etudes-2004-6-page-729.htm>; (n.d.-a). Defence and security policy. Available at: <https://www.consilium.europa.eu/en/policies/defence-security/>; (2022). Conclusions of the European Council, 23-24 June 2022. Available at: <https://www.consilium.europa.eu/media/57452/2022-06-2324-euco-conclusions-fr.pdf>; EEAS (07.09.2023. The EU and Georgia. Available at: <https://www.eeas.europa.eu/georgia/european-union-and-georgia_en?utm_source=chatgpt.com>; (n.d.). Qiao: Les nouvelles routes de la soie. Available at: <https://www.ena.fr/content/download/2826/45682/version/1/file/Qiao.pdf>; European Commission. (n.d.-a). Georgia - Trade - European Commission. Available at: <https://ec.europa.eu/trade/policy/countries-and-regions/countries/georgia/>; European Commission. (n.d.-b). European Economy. Available at: <https://ec.europa.eu/economy_finance/publications/pages/publication13389_en.pdf>; European Commission. (2013, June 28). EU Commission welcomes decision on gas pipeline: Door opener for direct link to Caspian Sea. Available at: <https://ec.europa.eu/commission/presscorner/detail/fr/ip_13_623>; European Commission. (2022, Mar 8). REPowerEU: Joint European action for more affordable, secure and sustainable energy. Available at: <https://ec.europa.eu/commission/presscorner/detail/en/IP_22_1511>. European Monitor (2013, Friday 28). Croatia’s accession to the European Union - Q&A- Main contents Available at: <https://www.eusmonitor.eu/9353000/1/j9vvik7m1c3gyxp/vjavfyp3hcy0>; European Neighbourhood Policy and Enlargement Negotiations. (n.d.). Home. Available at: <https://neighbourhood-enlargement.ec.europa.eu/index_en>; (n.d.). Tourism statistics. Available at: <https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Tourism_statistics>; (n.d.-a). Georgia - UNESCO World Heritage Centre. Available at: <https://whc.unesco.org/en/statesparties/ge> ; (n.d.-b). Georgia - UNESCO World Heritage Centre. Available at: <https://whc.unesco.org/en/statesparties/ge>; World Bank. (n.d.-b). Georgia Overview. Available at: <https://www.worldbank.org/en/country/georgia>; Footnotes [1] National Democratic Institute. (2023, May). Taking Georgians’ pulse: Findings from March 2023 telephone survey (Conducted by CRRC Georgia, p. 50). [2] Consilium. (2022). Conclusions of the European Council, 23-24 June 2022. Available at: <https://www.consilium.europa.eu/media/57452/2022-06-2324-euco-conclusions-fr.pdf>; [3] European Monitor (2013, Friday 28). Croatia’s accession to the European Union - Q&A- Main contents. Available at: <https://www.eumonitor.eu/9353000/1/j9vvik7m1c3gyxp/vjavfyp3hcy0>. [4] Consilium. (n.d.-a). Defence and security policy. Available at: <https://www.consilium.europa.eu/en/policies/defence-security/>. [5] Consilium. (n.d.-a). Defence and security policy. Available at: <https://www.consilium.europa.eu/en/policies/defence-security/>. [6] Cairn.info. (2004). L’Europe et ses frontières. Études, (6), 729. Available at: <https://www.cairn.info/revue-etudes-2004-6-page-729.htm>. [7] EEAS (07.09.2023. The EU and Georgia. Available at: <https://www.eeas.europa.eu/georgia/european-union-and-georgia_en?utm_source=chatgpt.com>. *We have deliberately chosen this reference date, so as not to take into account the effects of the Covid 19 pandemic from 2020 onwards. [8] Eurostat. (n.d.). Tourism statistics. Available at: <https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Tourism_statistics>. [9] UNESCO. (n.d.-a). Georgia - UNESCO World Heritage Centre. Available at: <https://whc.unesco.org/en/statesparties/ge>. [10] UNESCO. (n.d.-b). Georgia - UNESCO World Heritage Centre. Available at: <https://whc.unesco.org/en/statesparties/ge>. [11] ENA. (n.d.). Qiao: Les nouvelles routes de la soie. Available at: <https://www.ena.fr/content/download/2826/45682/version/1/file/Qiao.pdf>. [12] European Commission. (n.d.-b). European Economy. Available at: <https://ec.europa.eu/economy_finance/publications/pages/publication13389_en.pdf>. [13] European Commission. (n.d.-a). Georgia - Trade - European Commission. Available at: <https://ec.europa.eu/trade/policy/countries-and-regions/countries/georgia/>. [14] World Bank. (n.d.-b). Georgia Overview. Available at: <https://www.worldbank.org/en/country/georgia>. [15] GNERC. (2022). Annual Report 2022. Georgian National Energy and Water Supply Regulatory Commission. [16] European Neighbourhood Policy and Enlargement Negotiations. (n.d.). Home. Available at: <https://neighbourhood-enlargement.ec.europa.eu/index_en>. [17] European Commission. (2013, June 28). EU Commission welcomes decision on gas pipeline: Door opener for direct link to Caspian Sea. Available at: <https://ec.europa.eu/commission/presscorner/detail/fr/ip_13_623>. [18] European Commission. (2022, Mar 8). REPowerEU: Joint European action for more affordable, secure and sustainable energy. Available at: <https://ec.europa.eu/commission/presscorner/detail/en/IP_22_1511>.
Ukraine’s Chances of Victory Under Trump’s Presidency
This article explores the potential consequences of Donald Trump’s return to the presidency on the ongoing Russia-Ukraine war, with particular emphasis on the resulting geopolitical shifts and implications for global security. The analysis examines Trump’s stated positions, proposed peace plans, and their reception in both Kyiv and Moscow, shedding light on how his rhetoric and strategy may reshape the trajectory of the conflict. It further contextualizes his approach within broader transatlantic dynamics, including NATO’s cohesion, European defense initiatives, and the global response to a reoriented U.S. foreign policy. By highlighting Trump’s preference for transactional diplomacy, skepticism toward multilateralism, and emphasis on bilateral negotiations, the article considers how these tendencies may accelerate a reordering of the international system and challenge the existing liberal order. The discussion also assesses the potential ramifications for U.S. alliances and regional stability in Eastern Europe. The article concludes that while Trump’s promises of a swift peace may have rhetorical appeal, their implementation could intensify volatility and long-term insecurity in the region and beyond. Keywords: Peace negotiations, NATO and european security, Russia–Ukraine war. Introduction In 2022, the war launched by Russia in Ukraine changed the geopolitical situation in the world. It is the largest and most multidimensional conflict since the end of the Cold War, which has put an end to the existing rules-based international system and laid the foundation for a new world order. Given the multidimensional nature of the conflict, it involves all representatives of the civilized world, and its consequences directly or indirectly affect other states. Two years after Russia’s full-scale invasion, Ukraine has regained approximately 54 percent of the occupied territory, while Russia still holds onto 18 percent of the country’s sovereign territory.[1] Meanwhile, Russia continues to bomb Ukrainian cities and blockades its Black Sea ports, while Ukraine has stepped up air strikes on Russian ships and infrastructure, including deep in the Russian territory. Since January 2022, Ukraine has received about $300 billion in aid, but recently, there has been a growing pessimism on the part of its supporting countries and a need for policy review, most clearly demonstrated by the election in the United States, where Republican Donald Trump returned to power. Trump’s main message to the world was that he would end the war in Ukraine.[2] However, the ongoing processes and the unpredictable foreign policy of the United States leave question marks, based on which it has become very difficult for politicians or experts to predict the course of events. At times, Trump’s statements do not coincide with each other, but his message is clear that he wants to end this war, which he reiterated during a meeting with the new German Chancellor Friedrich Merz in June 2025. In one of his comments, Trump argued: “Sometimes you see two little kids fighting like crazy. They hate each other, and they’re fighting in the square, and you’re trying to help them. Sometimes, they don’t want to be helped; sometimes it’s better to stop and let them fight for a while and then help them. I told Putin on the phone, President, you might have to continue the war and a lot of suffering, because both sides are suffering before you help them, before you can help them. In some form, there will be additional fighting. He hit them, and they hit them very hard, deep into Russia. Putin made it very clear to me so we have no choice but to hit them, and it probably won’t be pretty. I told him I don’t like this. I said, ‘Don’t do this. You should not do this. You have to stop this’. But again, there is a lot of hatred between Russia and Ukraine. I stopped the war between India and Pakistan, and I want to do the same with Russia and Ukraine. At some point, it will happen. I believe in it. If it doesn’t happen, or if I see someone deviate from this path, if Russia deviates, you’ll be surprised how tough we will be”.[3] Russia-Ukraine War and Trump’s Policy Trump laments the devastation of Ukrainian cities and the deaths on both sides, insisting that the real toll will ultimately be much higher than Kyiv and Moscow have so far claimed. “They’re killing everyone, it’s the worst massacre this world has seen since World War II. It has to stop”, he said, adding that his administration would speak to both Russian President Vladimir Putin and Ukrainian President Volodymyr Zelensky.[4] Trump’s team is working on a plan to bring Ukraine and Russia to the negotiating table, and their statements indicate that both Kyiv and Moscow will have to make compromises, although the Ukrainian president has repeatedly stated that the war cannot end at the expense of Ukraine’s sovereignty and territory, and the only way to end it fairly is to increase pressure on Russia and increase aid to Ukraine, which is unlikely to happen under Trump’s presidency.[5] During the Russian-Ukrainian talks in Turkey, there was a feeling that the war might be coming to an end, or that a temporary ceasefire might be agreed upon, but the real outcome of the talks was only a prisoner exchange. At the same time, Trump believes that Ukraine and Russia are like two children who should be allowed to fight until they choose to behave otherwise. “Sometimes you see two little kids fighting like crazy, sometimes they don’t want to be helped, and sometimes it’s better to stop and let them fight for a while and then help them” – Trump said.[6] Donald Trump has been paying closer attention to ending the war in Ukraine since being elected the 47th president of the United States. Based on comments made during his first term, Trump’s thinking remains highly transactional on foreign policy in general and the Russia-Ukraine conflict in particular: He promised to end the war quickly, within months of his presidency. Trump’s operating mode has been to deal with the other “most powerful” people in the room and often to ignore other stakeholders. Trump’s operational approach has always been to deal with the other “most powerful” people in the room and often to ignore other stakeholders.[7] This means that any peace talks are likely to be bilateral between Trump and Vladimir Putin, the dynamic which Putin seems to have supported. While Trump’s meetings with Zelensky in New York and Paris may have signaled the possibility of revealing his thoughts, Trump may simply be positioning himself for the talks, but these expectations dramatically changed by the time of the talks between the Ukrainian and Russian delegations in Istanbul. Trump’s statements suggest that he plans to end the war with the status quo, with Russia retaining control of the occupied territories. By cutting off U.S. military and financial aid to Ukraine, by rejecting Kyiv’s membership in NATO, and by recognizing Russian sovereignty over the occupied territories of Ukraine. Trump can project his power both at home and abroad. Trump’s statements also focus on the scenario of a breakdown in peace talks: Trump could step up arms and financial aid to Ukraine. The Biden administration gave Ukraine the opportunity to use its weapons to attack Russian territory, which in turn increases the risks of escalating the conflict as Putin escalates with tactical nuclear weapons. Trump could pressure allies in this scenario to ease the Western sanctions regime against Russia and its oligarchs. This would not only directly help Russia but would also hinder Ukraine’s war effort, as billions of dollars in interest from frozen Russian central bank assets are currently being funneled to Kyiv to finance reconstruction and rearmament. Donald Trump will focus on achieving peace in Ukraine rather than returning occupied territories, saying Ukraine’s focus should be on peace, not territory.[8] Brian Lanza, who worked on Trump’s 2024 presidential campaign, said the administration would push for Zelensky to consider a “realistic vision of peace”. Given the current scenario, following Donald Trump’s victory in the presidential election, there was concern that Ukraine could lose the continued support of its most important ally, the United States, which has spent $108 billion in military, humanitarian, and economic aid since Russia’s February 2022 invasion. “We are preparing for the worst-case scenario, when [Trump] stops all aid”, said Lieutenant General Ihor Romanenko, a former deputy chief of the General Staff of the Ukrainian Armed Forces.[9] Trump has promised to end the Russia-Ukraine war “within 24 hours”, but has provided little explanation for the plan, saying he would cut off military aid to Kyiv unless it begins peace talks with Moscow. Trump’s “peace plan” remains vague, but experts say it likely involves giving up some or all of the territory occupied by Russia, nearly 19 percent of Ukraine’s territory, in exchange for a peace deal or a freeze along the present front-line positions. They were made more stringent by Russia at the second round of talks in Istanbul. Trump, who often describes himself as a masterful deal-maker, has also argued that if Moscow does not engage in peace talks, he will push ahead with the supply of advanced weapons to Kyiv. This approach implies a more forceful and hardline approach to international security issues and is focused on achieving concrete results with whatever means available. Trump’s promise that the war will end is inevitable, because he might be thinking of two scenarios: a. forcing the conflict to freeze under the current status quo, which includes cutting off financial and military aid to Ukraine, or b., strengthening Ukraine militarily. In either case, the war will end, and the foundation for a new geopolitical order will be laid. However, the new German Chancellor has taken the initiative and lifted restrictions on Ukraine’s use of long-range missiles, and he will also transfer Taurus missiles to Ukraine. Earlier, one of President-elect Donald Trump’s first congratulatory phone calls was to Ukrainian President Volodymyr Zelensky on the day after the election. Both sides noted that the conversation was positive and focused on future peace. It was not until the following day that Trump spoke to Russian President Vladimir Putin, and even then, the Kremlin denied the dialogue had gone as smoothly as the Russian leader had hoped. The Washington Post, which first reported the call, citing five sources familiar with the matter, said that Trump “urged the Russian president not to start a war in Ukraine and reminded him of Washington’s significant military presence in Europe”. This is certainly not a message Putin would welcome. Trump and Vice President J.D. Vance’s talk of a quick peace deal poses a major challenge for Ukraine. The Trump administration’s new peace plan would force both sides to compromise in order to avoid further war and destruction. However, recent actions and the dynamics of the war make it clear that the war is still going to continue. Trump’s future priorities and the current state of geopolitical dynamics could lead to a peace deal that still gives Ukraine positive leverage. Although NATO has been promoting Ukraine’s membership prospects since 2008, it has repeatedly put the process on hold, but Ukraine’s size and its experience in hot war for more than a decade, not to mention the contribution of Ukrainian troops in the past, could be a valuable argument in its favor but Vladimir Putin emphasizes and the peace agreement memorandum he presented strictly defines Ukraine’s military neutrality and the inadmissibility of such forces.[10] This could be a particularly important element as Trump renews pressure on European allies in NATO to increase their defense spending and rely less on the United States. Fears of Trump’s waning support for the alliance itself also provide a backdrop for supporting Ukraine. In response to recent developments, NATO has begun rearmament and related exercises. European states are increasing their military industries, and much of their armaments remain strictly classified. Eastern European states, which face a direct military threat in the face of increased possible intervention, are especially preparing. In addition to the recent developments around the military issue, a particularly heated confrontation has begun between Trump and Elon Musk, which was fueled by Elon Musk’s resignation from his position and Trump’s criticism of him. Trump accuses Elon of using psychotropic drugs, which, in his opinion, was the basis for aggression. Elon Musk, on the other hand, has recently accused Trump of being in Epstein’s files. The fierce public dispute between US President Donald Trump and his billionaire supporter, Elon Musk, intensified after Musk publicly accused Trump of mentioning his name in government files related to the crimes of financier Jeffrey Epstein. The Trump administration has admitted that it is reviewing tens of thousands of documents, videos, and investigative materials that its MAGA movement says will expose public figures complicit in Epstein’s crimes.[11] Conclusion Since 2022, the war has only escalated with devastating consequences not only in terms of human lives and infrastructure, but also the erosion of the rules-based international system. Each step taken towards peace talks escalates the situation, as Russia’s real goals in this war are gradually expanding. Despite Trump’s attempts to end the conflict in a short time, he has failed to change the situation, which means that the war continues. European security is also clearly at the center of the negotiations, where Germany, with its new Chancellor supporting Ukraine and expressing its readiness to create the most powerful army in Europe. Leaders around the world, be it in the Middle East, Asia-Pacific countries, and beyond, are watching the results and signs of the US position to determine their future. Trump’s diplomacy to end the war and lay the foundation for a lasting peace creates a positive outlook, although given the recent developments, it is still questionable. Trump’s policy is result-oriented and assumes a compromise between both sides, since the escalation of this conflict was largely determined by decisions that took into account the interests of both sides and a process that took place over time. According to Trump, there is no alternative to peace, which is an important statement against the backdrop of increased threats and destabilization in the world. Thus, it is impossible to predict the end of the brutal war waged by Russia against Ukraine. One outcome is clear, though: the collapse of the international system, the arms race, and militarization pose a threat to peace and global stability in the long term. Bibliography: Al Jazerra. (2024). Russian-Ukrainian War. (2024). ‘Worst-case scenario’: Ukraine awaits Trump’s presidency with trepidation. Available at: https://www.aljazeera.com/news/2024/11/26/worst-case-scenario-ukraine-awaits-trumps-presidency-with-trepidation>; Avdaliani, E. (2022). New World Order and Small Regions. The Case of South Caucasus. Palgrave Macmillan. Center for Preventive Action. (2024). War in Ukraine. Available at: <https://www.cfr.org/global-conflict-tracker/conflict/conflict-ukraine>; France24. (2025). Musk accuses Trump of being named in Epstein files as public row worsens. Available at: <https://www.france24.com/en/americas/20250606-musk-accuses-trump-of-being-named-in-epstein-files-as-public-row-worsens>. FrontNews. (2024). Zelenskyy: Ukraine must secure peace without trading territory or sovereignty. Available at: <https://frontnews.ge/en/zelenskyy-ukraine-must-secure-peace-without-trading-territory-or-sovereignty/>; FrontNews. (2025). Trump, I am with Ukraine, I am for stopping the killings, this is what I really want. Available at: <https://frontnews.ge/ge/news/me-ukrainastan-var-trampma-shemdgomi-mkhardacheris-shesakheb-gantskhadeba-gaaketa>; Gienger, V. (2024). To ‘End’ War in Ukraine, Trump Might Be Tougher on Putin Than Critics Think. Just Security. Available at: <https://www.justsecurity.org/105019/trump-ukraine-policy-peace-talks/>; Kelly, J., Martin, C. (2024). Trump’s Endgame for the War in Ukraine. Available at: <https://www.justsecurity.org/105451/trumps-endgame-ukraine-war/>; FrontNews. (2024). Trump sees ‘a little progress’ toward ending war in Ukraine.Available at: <https://www.politico.eu/article/donald-trump-war-in-ukraine-russia/>; Santos, S.F. (2024). Trump ally says Ukraine focus must be peace, not territory, BBC News. Available at: <https://www.bbc.com/news/articles/czxrwr078v7o>; Slattery, G., Landay, J. (2024). Trump’s plan for Ukraine comes into focus: NATO off the table and concessions on territory. Available at: <https://www.reuters.com/world/trumps-plan-ukraine-comes-into-focus-territorial-concessions-nato-off-table-2024-12-04/>; Footnotes [1] Center for Preventive Action. (2024). War in Ukraine. [2] Slattery, G., Landay, J. (2024). Trump’s plan for Ukraine comes into focus: NATO off the table and concessions on territory. [3] FrontNews. (2025). Trump, I am with Ukraine, I am for stopping the killings, this is what I really want. [4] Politico. (2024). Trump sees ‘a little progress’ toward ending war in Ukraine. [5] FrontNews. (2024). Zelenskyy: Ukraine must secure peace without trading territory or sovereignty. [6] FrontNews. (2025). Trump, I am with Ukraine, I am for stopping the killings, this is what I really want. [7] Kelly, M.J., Martin, C. (2024). Trump’s Endgame for the War in Ukraine. [8] Santos, S.F. (2024). Trump ally says Ukraine focus must be peace, not territory, BBC News. [9] Al Jazerra. (2024). Russian-Ukrainian War. (2024). ‘Worst-case scenario’: Ukraine awaits Trump’s presidency with trepidation. [10] Gienger, V. (2024). To ‘End’ War in Ukraine, Trump Might Be Tougher on Putin Than Critics Think. Just Security. [11] France24. (2025). Musk accuses Trump of being named in Epstein files as public row worsens.
Globalization’s Double-Edged Sword: Resource Dependency and Geo-Politics of Oil in Petróleos de Venezuela (PDVSA)
Combining institutional theory of the firm with resource dependency analysis, this study explores the ever-changing geopolitics of oil and challenges of overproduction in Venezuela’s national oil company (NOC), PDVSA. It analyzes a state company's structural crisis and its limitations for growth through the lens of resource dependency theory and geopolitics of oil. Despite the recent easing of US sanctions, our findings suggest that an alternative firm strategy is rarely, if ever, viable for the company due to its international and geopolitical dependency. This paper further argues that PDVSA’s performance reflects greater alignment of crisis management with the geopolitics of resource-based development. PDVSA has pursued a strategy of ‘jockeying’ between transnational oil interests (privately-owned, Western MNEs) and non-Western oil companies from allied nations like Russia and China. Furthermore, since much of the oil windfall resulted from currency overvaluation by inefficient national and foreign capital, PDVSA has been unable to maintain a competitive advantage that could enhance its performance. This study is limited to the oil sector in Latin America, but a few examples of ‘resource nationalism’ emerging from other countries are briefly discussed. The paper concludes by discussing the policy implications of the research for oil industry managers in the context of ongoing globalization. Keywords: Embedded autonomy, resource nationalism, state-owned oil company, rentier socialism Introduction This paper examines the evolving corporate performance and crisis of Venezuela’s state-owned oil company, PDVSA, from early 2000 up to the present. Venezuela suffered an unprecedented economic collapse, most intensified by the 2017 debt default and the COVID-19 pandemic most recently. From 2013 to 2018, GDP contracted by a cumulative 47.8 percent, with inflation reaching 130,060.2 percent in 2018.[1] As oil production consistently fell for more than a decade, it collapsed after 2016, forcing President Nicolás Maduro to seek a restructuring of sovereign debt and to renegotiate oil contracts. From 2017 to 2022, disruptions in oil shipments, a declining workforce, and US sanctions on crude oil exports occurred. With the Nationalization Law of 1976, former President Carlos Andres Perez created PDVSA (Petroleos de Venezuela, S.A.)—the state-owned oil and natural gas company and a holding company for the oil industry that was initially structured to run as a corporation with minimal government interference. Elected in 1998 on a populist authoritarian platform, President Chavez extended direct state control over PDVSA, also to align its governance with his ‘symbolic nation-building project’ called the Bolivarian Revolution.[2] Today, as the largest employer in Venezuela, PDVSA “accounts for a significant share of the country’s gross domestic product (GDP), government revenue, and export earnings”.[3] Scholarly interest in NOCs has increased in recent years due to a global commodity boom (2000-2004) and the resurgence of ‘resource nationalism’[4] in different parts of the world. For Venezuela, in addition to resource dependency, fiscal over-reliance on oil makes PDVSA highly relevant for discussions[5] on ‘rent capitalism’, ‘rentier socialism’, ‘resource nationalism’, ‘extractive institutions’, ‘rentier state’, or even a ‘petrostate’. These models define the ‘paradox of plenty’[6] as a condition in which developing countries become overly dependent on oil and gas production. This form of dependency leads to potential economic windfalls that typically contribute between one-third and one-half of their GDP.[7] Natural resource-based development, however, is not unique to Venezuela. In most rentier states based on oil, economists point to a ‘resource curse’ that is associated with poor economic growth, lack of democratic institutions, and a weak domestic productive sector.[8] Resource-based development is characterized by highly volatile revenue. Due to a narrow tax base, the government enjoys absolute freedom and has an active role in oil production, a feature less typical of more diversified economies.[9] Being the main distributor of wealth with a monopoly on oil and direct control of the oil industry, the government encounters fewer market pressures to guide the administration of oil wealth. This study examines the multitude of stakeholders that constitute oil policy-making in PDVSA. After deconstructing the rentier oil strategy as outlined below, it analyzes how the key institutional stakeholders (national government, international oil companies, and their respective governments) have shaped PDVSA’s corporate strategy and performance over time. In our analysis, we draw on the institutional theory of the firm and consider the fragmented and opportunistic nature of the rent distribution system in the global oil market.[10] This paper argues that PDVSA’s performance reflects greater alignment of crisis management with the geopolitics of resource-based development. Against the backdrop of resource dependency and loss of oil rent since 2016, PDVSA has pursued a strategy of ‘jockeying’ between transnational oil interests (privately-owned, Western MNEs) and non-Western oil companies from allied nations like Russia and China. Furthermore, since much of the oil windfall resulted from currency overvaluation by both inefficient foreign and national capital,[11] PDVSA has been unable to maintain a competitive advantage that could enhance its performance. PDVSA’s ties with China and Russia extend beyond mere financial support, they are also influenced by hostile relations with the US. Despite China’s increasing control of the global oil market, North America remains the top destination for PDVSA’s crude oil exports. The U.S. is the dominant player as the main creditor and investor in the international oil market. Using a case study of Venezuela’s national oil company in crisis, this study aims to explore the interaction between firm strategy and evolving geopolitics of oil in natural resource-dependent economies. Literature Review: Oil Industry and Natural Resource Dependency The research on rentier states originates from ‘resource curse’ analysis[12] and ‘paradox of plenty’.[13] These models refer to a problem of over-relying on oil and gas reserves as a potential source of commodity windfalls for developing countries. Mahdavy, who gave the rentier state its contemporary meaning, defined the rentier state as one that relies almost exclusively on the export of raw materials such as oil, gas, or minerals. This includes nations that are financially weak but well-endowed in natural resources.[14] The term ‘external rent’ is used to designate the financial proceeds from sales of the commodity to foreign companies or governments, as opposed to the profits generated typically by manufacturing or productive economic sectors. The extent of this reliance is such that it generates harmful outcomes for development, such as poor economic growth, a weak domestic productive sector, endemic corruption, weak property rights, and unequal distribution of wealth.[15] While the rentier model is common in the Arab world, states that depend on exporting petroleum and distributing its windfall also include Venezuela, Nigeria, Indonesia, Botswana, and Russia.[16] NOCs serve crucial policy functions for rentier states. They secure a ‘ruling bargain’[17] between political elites and society based on concessions in exchange for populist economic policies. In this framework, public officials secure regime legitimacy through forming loyal constituencies (‘patron-client networks’) that support the petrostate in return for a portion of oil income captured by NOCs.[18] This analysis is pertinent to NOCs that operate as state monopolies in markets with imperfect competition and direct access to economic rent (above-normal profits). While some of these nations do have substantial financial assets, such as Saudi Arabia and Qatar, most are barely capable of funding development in profit-generating, labor-intensive enterprises. Therefore, they do not have a strong domestic productive sector. Venezuela is not even the most extreme example of dependency. Angola and other African petroleum exporting nations are even more vulnerable to the boom-and-bust cycles of the global oil market. FIGURE 1. VENEZUELA: PETROLEUM INDUSTRY AS SHARE OF EXPORTS % Source: Figure is the author’s own. Data from UN Comtrade, The Observatory of Economic Complexity (2021), via Statista - The Statistics Portal FIGURE 2. OIL RENTS (% OF GDP) Source: Figure is the author’s own. Data from World Bank (2022), World Development Indicators database Table 1. Top ten countries with the largest oil reserves in 2019 (thousand million barrels) Source: Table is the author’s own. Data from BP Statistical Review of World Energy (2020), p. 14. PDVSA stands out as the quintessential example of a rentier oil company. Venezuela’s supply of oil is substantial, compared to both the size of its economy and most other countries.[19] In 2019, crude petroleum accounted for 83.1 percent of the value of Venezuelan exports. The industry represented 88.3 percent of all export earnings, including refined petroleum, with the highest contribution made in 2013, at nearly 96 percent (Figure 1). Figure 2 displays Venezuela’s oil rents as a percentage of GDP in 1990-2014, starting with the oil opening of the 1990s. Table 1 shows the top ten countries with the largest oil reserves in 2019. Table 2 shows the largest oil producers in 2019. The Orinoco Belt is by far the largest and remaining source of oil in Venezuela, with a reputation for largest extra-heavy oil deposit in the world. Compared to lighter oil, extra-heavy oil consumes more water and energy, is costly to produce, and generates higher mineral pollution and other waste by-products.[20] Table 2. The top ten largest oil-producing countries in 2019 (thousands of barrels per day, b/d) Source: Table is the author’s own. Data from BP Statistical Review of World Energy (2020), p.16. Theoretical Argument: The Government-Business Relations Given Venezuela’s over-reliance on oil income, it is imperative to understand the geopolitics of oil and the multitude of stakeholders interacting with the state oil company. As summarized above, the rentier theory predominantly focuses on the national government (‘rent-seeking elites’) and tends to disregard other stakeholders, especially transnational, and their institutional environments that might shape the dynamics of resource dependency. The political capture argument is implicitly deterministic in that it does not consider the potential conflicts of interest or, inversely, mutual dependency between the government and business relations. Various stakeholders—NOC, national authorities, private multinational firms, and their home and host governments—actively shape how the government extracts oil income. Other studies of government interventions in NOCs have analyzed the outcomes, considering the factors of capital intensity, cost structure, and risk exposure in the oil industry. Rather than simply reacting to national interests, Noreng[21] suggests that senior executives of NOCs actively strive for independence from their governments’ resource dependency analysis; however, it doesn’t sufficiently explore how rent-seeking politicians are limited in their ability to continually capture or influence oil policy.[22] Furthermore, NOCs are unique economic structures. Their decision-making depends on the inherent risks involved in the oil sector, such as geological uncertainty, price volatility, and geopolitical factors. These factors limit government control over oil. Furthermore, exploration, extraction, transportation, and refining affect the cost structure of firms. The global oil market dynamics, including supply and demand, global competition, and the influence of organizations like OPEC, constantly interact with government influence on NOC. In this regard, this paper follows Singh and Chen in viewing NOCs as “complex organizations that bear new developmental capacities rather than vessels of rent-seeking interest”.[23] Originating in Evans,[24] our view of the NOC aligns with the institutional theory of the firm as having an ‘embedded autonomy’ (EA) in the local and institutional environment of the global oil market. According to Styhre, EA implies that modern corporation is embedded in a variety of social practices and stakeholders that are “simultaneously anchored in, for example, corporate legislation and regulatory practices, on the national, regional… and transnational levels, while at the same time being granted the right to operate with significant degrees of freedom within legal-regulatory model”.[25] The institutional theory of the firm provides a dynamic and contextual framework for understanding the corporate strategies followed by NOCs in various contexts or in different periods in time. It highlights the dynamic interaction in the local and international environments—both the mutually dependent and contradictory relations between the economy, firm, and their state owners. As exemplified by PDVSA, most National Oil Companies (NOCs) are “legally independent firms with direct ownership by the state”,[26] which often leads to highly restricted management autonomy. However, how much the NOC depends on the global economy can also play a significant role in its independence from the government. The nature of global political landscapes determines the modalities of interaction between NOCs and the destinations of their FDI, as well as their engagement with home and host state authorities. Synthesizing the institutionalist analysis presented above with the geopolitics of power, this paper advances the following argument: PDVSA’s corporate strategy has been shaped by its dynamic relationships within the local institutional environment, global conditions, and the company’s investment strategy, all within the framework of its long-standing reliance on the U.S., particularly the North American oil market. This has led to a persistent crisis for the company, reflecting the ever-changing geopolitics of oil and the challenges of overproduction in a resource-dependent economy. Institutional Stakeholders: Government as ‘Sole Owner’ Since the onset of Chavista administration in 1999, PDVSA has been instrumental in channeling the oil wealth to support both the Venezuelan Treasury and the public.[27] Rosales refers to Venezuela as an “example of a neo-extractivist country that pursues a developmental model based on wealth redistribution sustained by oil rents”.[28] As stated in its original governance (Nationalization Law of 1976), PDVSA is fully owned by the government, which controls all the company’s shares. PDVSA’s common stock is not publicly traded; “Pursuant to Article 303 of the Venezuelan Constitution”, the company’s “shares may not be transferred or encumbered”.[29] Since the oil industry generates a substantial portion of foreign exchange and funds the state budget, it would have been impossible to import the goods necessary to satisfy the population’s basic needs without oil income. After benefiting from the commodity boom during the 2000s, Venezuela used the oil windfall to advance ‘economic populism’, i.e., prioritizing social programs and expanding direct government subsidies for energy and food through PDVSA, which provided oil at lower prices to the domestic market. While other presidents also used PDVSA as a political tool to subsidize domestic consumption, Chavez substantially increased debt as a share of GDP by taking on debt and printing money.[30] The state not only used oil to buy influence abroad through the Petrocaribe alliance, but also to secure legitimacy at home by redistributing income directly with revenues from PDVSA. Oil strategy remained pivotal to ‘nationalist reform policy’, particularly as oil prices began to rise in the early 2000s. According to Lopez-Maya,[31] there were four main attributes of Chavez’s energy reform. A primary goal of the reform was to centralize oil policy design and implementation within the executive branch. The goal was to reverse the 1990s market liberalization by placing PDVSA under the Ministry of Petroleum and transforming it into the sector’s ‘political leader’. This action would soon be challenged by PDVSA managers who did not want to give up the power they had acquired under La Apertura Petrolera. Second, the oil reform sought to maximize oil rent by privileging royalties on sales over taxes on profits. A persistent and worrisome drop in oil income occurred during the 1990s, due to revenue being generated through taxes rather than direct royalties. Besides, depending on international prices and volume of production, royalties involve much simpler processes, whereas taxes are subject to more complicated accounting methods. Third, the reform also aimed to bolster Venezuela’s commitments to OPEC. Fourth, and finally, the reform aimed to slow down the trend towards privatization and deregulation of PDVSA that was in motion but failed to materialize during the 1990s. The last two objectives became a source of conflict with the US government over time. While Chávez proclaimed a move towards ‘21st Century Socialism’, his ‘rentier socialism’ mirrored the state capitalism of Carlos Pérez’s first presidency in the 1970s, a period marked by soaring oil prices. Like Pérez’s Plan of the Nation (La Gran Venezuela), Chávez’s policies re-centralized the petrostate, cancelled debts, and nationalized oil projects. The commodity boom was short-lived, and by the time oil prices began to fall in the 1980s, it left Venezuela indebted and poor.[32] Using oil revenue to pay for generous social welfare programs and nationalization of the oil industry, Perez’s first presidential term (1974-1979) was called ‘Saudi Venezuela’. In his second term (1989-1993), Perez adopted IMF austerity policies and privatization reforms; oil prices declined, and the people turned against the government in the same way they have turned against the current president, Nicolas Maduro.[33] Inaugurated to a five-year term in February 1989, Perez became the target of massive protests and street violence, which paved the way for Hugo Chávez's attempted coup and subsequent rise to power from 1998 to 2013.[34] PDVSA began to lose autonomy as salient frictions within the government surfaced at the onset of Chavez’s arrival, which culminated in a big oil strike in December 2002. Also known as the ‘oil lockout’, the strike led to the temporary shutdown of PDVSA for two months.[35] Facing an undemocratic backlash, PDVSA overhauled the entire organization just to solidify the state control of the oil industry. Chavez replaced PDVSA’s board with political allies and merged it with the Ministry of Petroleum. After assuring that he would be directly involved in making decisions about the way PDVSA should run its business, Chavez fired nearly 18,000 workers (around 40 percent of PDVSA’s skilled employees) who participated in the strike.[36] The economic consequences of this action were dire. In the first quarter of 2003, Venezuela’s GDP diminished by 27 percent, forcing the country to import oil to satisfy domestic demand, while unemployment increased by a third, reaching 20.3 percent.[37] The main difference in oil policy under Chavez was the degree to which PDVSA subsidized social programs for the most marginalized segments of the population. After purging the company of political opponents in 2003, PDVSA still managed to bring in large amounts of oil revenue due to high oil prices and large crude reserves. The overhauled PDVSA had greatly extended responsibilities to the state, including a mandate that PDVSA finance and manage social programs known as Misiones Boliviarianas (Bolivarian Missions). Progressive, partially effective, and ‘clientelistic’ in nature, the Misiones provided aid to the country’s lower classes through literacy training, infrastructure projects, agricultural activities, and health care. In some cases, PDVSA’s responsibilities for its social contributions were excessive. From 2008 onward, PDVSA financed two key operations through a subsidiary: a ‘price-controlled food distribution network’[38] and Fonden-Fondo de Desarrollo Nacional (National Development Fund), a politically motivated program with military participation. Founded in 2005, Fonden served as ‘off-budget military funding’ for economic development.[39] Benefiting from the commodity boom, one can understand that the PDVSA could tolerate greater public spending on ambitious social programs. At the peak of oil prices, Venezuela made important strides in reducing inequality. From 2003 to 2008, the company spent more than $23 billion on social programs. PDVSA’s social investments improved some of the social indicators, such as tripling of spending per capita among households.[40] Over 5.25 years upon takeover, real GDP grew by 94.7% or 13.5% annually, which was considered remarkable by international standards among some observers.[41] Poverty decreased from 50 percent in 1998 to about 30 percent in 2014. The Gini index was indicative of major changes as well. In 1998, it was 0.49, but by 2012 it had declined to 0.40 (smaller numbers indicate greater equality), which the World Bank[42] regarded as one of the lowest in Latin America. Although this gave some analysts the impression that Venezuela was becoming ‘socialist’, these social programs have been criticized as being temporary and unable to address structural inequalities that are intrinsic to the Venezuelan economy. International Stakeholders: From ‘Hands off’ to ‘Obsolescing’ Bargaining PDVSA’s corporate governance is rooted in the institutional framework for the energy sector and the merger of multinational companies that controlled oil production before 1976. In 1976, President Carlos Perez nationalized the oil industry, creating the state-owned PDVSA as a holding company for a group of oil and gas companies. Even though the law began expropriation by terminating oil MNE concession agreements, the oil industry was structured as it had been before nationalization—all private firms with operating licenses were fully compensated and converted into 15 state-owned companies. PDVSA was formed as a central company with 14 affiliates. For instance, Standard Oil became Lagoven, Shell became Maraven, Mobil became Llanoven, and so on.[43] PDVSA enjoyed the status of a ‘commercial entity’, independently managed and staffed with the local workforce of the former companies.[44] As a result, “corporate structures that existed before nationalization were maintained while Article 5 of the Nationalization Law left room for foreign involvement in the Venezuelan oil industry as long as it was deemed to be in the interest of the Venezuelan state”.[45] During the 1990s, when oil prices declined, PDVSA took major steps to expand foreign operations and liberalize the oil sector as part of the government’s Apertura Petrolera. Given the extra-heavy crude in the Orinoco Oil Belt, which entailed heavy extraction and refining costs, the oil sector desperately needed joint ventures. PDVSA’s leaders, seeking to solidify management autonomy, successfully lobbied for the ‘Opening’ of the oil industry to foreign investors for the first time since 1976. As Giusti, the former CEO of PDVSA noted,[46] Apertura partially privatized PDVSA by permitting operational service agreements and strategic associations (‘equivalent to joint ventures but requiring congressional approval’), all signed with private — mostly foreign — investors, including ExxonMobil, ConocoPhillips, Shell, BP, Equinor (then Statoil), Total, Repsol YPF, China National Petroleum Corp.[47] Depending on the type of agreement, the government offered incentives to participating foreign companies that included “general corporate tax regime, reduced royalty periods, and access to international arbitration”.[48] Key Apertura deals included ExxonMobil and ConocoPhillips profit-sharing agreements in La Ceiba and the Coronoco fields, the joint venture with Veba Oel in Germany, and the acquisition of CITGO’s share in the US.[49] Apertura’s oil deals drew criticism for potentially undermining national sovereignty. In contrast, after Chavez, PDVSA’s dealings with multinational enterprises (MNEs) demonstrated ‘obsolescing bargain’ dynamics. Increasingly becoming subservient to the state, PDVSA adopted in 2001 the controversial Hydrocarbons Organic Law (HOL). HOL established a mechanism to assign a leading role for PDVSA in all new private investments, further enabling it to lead the expropriation process. Under the law, either the state directly (through PDVSA) or mixed companies (Empresas Mixtas)—joint ventures where PDVSA had a majority participating stake—would carry out all upstream oil activities. Such activities required majority PDVSA ownership (at least 51 percent) of all future joint exploration and production ventures, as well as the payment of higher royalties by international oil companies. While HOL mandated that ‘only’ PDVSA could commercialize and export crude oil, it still allowed private corporations to carry out downstream operations, including the exportation of refined products or upgraded oil. The HOL also raised the royalty rate to 30 percent from 16.67 percent and lowered the income tax rate to 50 percent to offset the effect of the increased royalty. Although the Chavez government assured investors that HOL would not retroactively apply to existing contracts or projects, it “created a more limited role for investors than the Apertura contracts had provided. It also limited the applicability of international arbitration”.[50] Monaldi et al[51] argue that it took nearly 5 years for Chavez to complete the expropriation process. In the case of Venezuela, commodity boom seemed crucial but various factors created strong incentives PDVSA’s nationalization, including 1) the end of the investment cycle in the oil sector; hence, the need for placement of sunken investments, 2) significant increase in the price of oil within the context of Apertura contracts that were ‘fiscally regressive’, 3) weak ‘deterrence’ of international arbitration because of the grave short-term gains against the low cost of nationalization (i.e., MNE compensation claims and legal fees under bilateral treaties), 4) delays in taking absolute control of formerly autonomous PDVSA and using it towards renationalization. Against an oil price increase from 17$ to 37$ per barrel between 1999 and 2004, the royalty rate was just 34 percent, implying that PDVSA benefited less from the global price boom than foreign MNEs.[52] In the early 2000, PDVS reversed the market-oriented reforms that had been implemented in the 1990s. Although the 2001 HOL was consistent with the Venezuelan law that prohibited the retroactive application of laws to existing contracts, nationalization accelerated with the announcement of a new oil strategy in October 2004.[53] PDVSA had asked in January 2002 some of the foreign companies to cut output to help meet its OPEC production quota; Venezuela agreed to trim output by 6 percent, or 173,000 barrels a day, as part of OPEC’s cut of 1.5 million barrels a day.[54] In late 2004, the government declared major changes to all Apertura contracts—32 operating agreements signed during the 1990s— technically forcing investors into renegotiation of existing projects. Legislation in 2006 raised the royalty and income taxes on the four strategic associations to 33.35 percent and 50 percent, respectively.[55] It also increased the royalties on the Orinoco belt heavy oil projects from 1 percent to 16.67 percent. Then it imposed an ‘extraction’ tax in 2006, which included 1/3 of the value of all hydrocarbons produced, and a ‘windfall’ tax in 2008.[56] By the end of 2005, major MNEs holding operating agreements signed ‘transitory agreements’ to migrate their existing contracts to PDVSA, with the noticeable exception of ExxonMobil, which had resented the royalty hikes and contractual changes earlier. Chevron, like other major foreign oil companies, agreed to pay higher royalties and taxes and gave up majority interests in their projects.[57] The 2001 HOL had already provided the background of renationalization with a minimum of 51 percent stake for PDVSA in the mixed companies. However, the government further claimed that PDVSA could take a bigger stake depending on the level of foreign investments. In October 2005, Oil Minister Rafael Ramirez pressured foreign MNEs to agree to transfer their contracts to joint ventures by the December 30th deadline, warning that if they failed to do so, they should either leave the country or face state takeover of their operations.[58] In 2007, PDVSA concluded the partial expropriation process. This resulted in a major increase in state ownership and control over oil operations as well as a significant decline in privately owned oil production. Congress approved the remaining batch of joint venture agreements that gave CVP, a PDVSA unit, a minimum of 60% share in most of the new projects. During this takeover, PDVSA increased its ownership in four of the strategic associations from 40 percent to an average of 78 percent. Total, Statoil, Chevron, and BP agreed to give up their shares and have remained as minority partners in their Venezuelan projects. By contrast, companies like Exxon Mobil and ConocoPhillips refused to agree to PDVSA’s terms and pulled out of joint ventures. After refusing to relinquish controlling stakes, they faced full expropriation of their assets, in return for a book value reparation, considerably below market value. Exxon and Conoco, after suing PDVSA and the Chavez government, escalated their dispute by filing for arbitration in international courts.[59] Stagnation and the Overproduction Crisis PDVSA has been facing an acute crisis since 2017. Its revenues have dropped. The reasons include shipping issues for oil, poor maintenance, fewer workers, and US sanctions on selling crude oil (2019-2022). At a time when greater FDI was needed in the oil industry, PDVSA took great risks in forcing foreign companies to pay higher taxes and produce oil in joint ventures that were majority-owned by the state. Such contractual changes not only caused uncertainty by leading to falling output from the joint ventures, but they also reduced reinvestments needed just to maintain oil production—$2.5 billion per year. In October 2005, PDVSA announced that it expected joint ventures to increase production up to 50,000 b/d under the new contract. Yet, these companies typically produced around 500,000 b/d during the oil opening in the 1990s.[60] Source: Figure is the author’s own. Data from the U.S. Energy Information Administration (2020). Since Maduro’s succession to the Presidency in 2013, the oil industry has descended into further economic turmoil. The oil-dependent state began to deteriorate rapidly as hyperinflation and severe food shortages set in. The World Bank issued a report calling attention to Venezuela’s current woes, which were a product of declining oil prices. In addition, it blamed the Maduro government for failing to create a ‘savings fund’ to offset what might have been an expected downturn. World Bank further noted that “during the economic boom, Venezuela did not accumulate savings to mitigate a reversal in terms of trade or to cushion the necessary macroeconomic adjustment”.[61] However, there were probably few reasons for the government to anticipate such a development since ‘peak oil’ was widely accepted as a probable outcome in world supplies. To some extent, Venezuela was a victim of a massive expansion in fracking that has made the US the world’s largest oil and gas exporter. That said, there was no doubt that the pro-Chavista government made little attempt to diversify economically. Food continued to be imported, and manufacturing made little contribution to GDP. The underdevelopment of non-energy output is, of course, a hazard for rentier states historically. Oil prices have declined precipitously in Venezuela since the end of the commodity boom. In 2013, a barrel of Venezuelan crude oil sold for $100. A year later, the price had dropped to $88.42, and another year later it was $44.65. In early 2016, it had plummeted to $24.25. Such a steep decline would prompt most governments to rethink their development model, but the Venezuelan government has shown no signs of moving away from oil dependency so far. On the other hand, even if it did conceive of an alternative, funding for new infrastructure would be difficult to come by given the nation’s virtual bankruptcy, sharp drop in FDI, and surmounting economic problems.[62] Such problems have been so serious that by January 2017, Venezuelan oil tankers with 4 million barrels of oil and other fuels were abandoned in the Caribbean Sea. PDVSA lacked the cash to pay for safety inspections for ships carrying oil exports.[63] Figure 3 shows Venezuela’s declining annual average crude oil production from 1997 to 2020. If the global supply of oil had remained constant, Venezuela’s problems would not have been so acute. However, new technologies and offshore drilling created a spike in production that defied ‘peak oil’ expectations. By late 2015, supply mounted to 97 million barrels per diem, exceeding demand by more than a million per day. This surplus led to a severe drop in oil prices.[64] Transnational Oil Alliances: Russia and China in the Global Oil Market Since 2015, PDVSA has been saddled with debt that appears unlikely to be paid from the state treasury. October-November 2017 was the acid test for the government since it was the deadline for paying bondholders $3.5 billion. This has put downward pressure on PDVSA bonds, which are a major source of revenue historically for the state.[65] Perhaps the only mitigating factor in this financial crunch was the apparent willingness of the Russian government to restructure Venezuelan debt to Russia, which stood at $3.15 billion. Signed in November 2017, the debt deal stipulated full repayment in ten years and ‘minimal’ repayments over the next six years.[66] Rosneft, Russia’s second biggest state-controlled oil company, was one of the largest foreign creditors and a ‘financial savior’ of the Maduro regime. As early as 2013, President Putin expressed greater financial interest in Venezuela when the CEO of Rosneft, Igor Sechin, announced plans to invest $13 billion in Venezuelan oil and gas assets in the next 5 years. Russia’s involvement in PDVSA, through Rosneft and a consortium of private Russian oil companies, was aimed at: 1) promoting Russian geopolitical interests in the Caribbean region, 2) advancing economically feasible investment deals.[67] In early 2016, Rosneft announced a partnership with PDVSA in Petro Monagas, an investment of $500 million in the Orinoco Oil Belt, for offshore gas drilling.[68] Rosneft also advanced prepayments to PDVSA for crude and refined products when China, Venezuela’s other major ally, delayed its payments. In 2014, PDVSA received 6.5 million dollars in loans and advanced payments from Rosneft when the Maduro government was experiencing foreign currency shortages. In December 2016, Rosneft “also provided a $1.5 billion loan collateralized with 49.9 percent of Citgo Holdings, PDVSA’s refinery in the US”.[69] China is PDVSA’s other major financial supporter, although, unlike Russia, it has declined to restructure Venezuela’s outstanding loans.[70] China and Russia’s relations with Venezuela are part of a global strategy to recruit allies in building a new multipolar, anti-US world order. While China seems to be more commercially driven in its foreign investments, Russia seeks both commercial and geopolitical interests in Venezuela, one which has “grown with the intent to disrupt western democracies and achieve a firm foothold in the Western Hemisphere’s largest oil reserve”.[71] China has provided Venezuela with economic and political support in exchange for future oil shipments. According to Guevara, “with roughly $67 billion invested since 2007, China has become a main source of Venezuela’s external financing, and an important partner of its oil-based economy”.[72] Indeed, in 2001, Venezuela was the first Latin American country to form a ‘strategic development partnership’ with China,[73] followed by a series of bilateral trade, infrastructure, and energy co-operation deals. Excessive reliance on oil rent, with a sharp drop in FDI (post-2006) has deepened PDVSA’s dependence on Chinese financial support. An example of Asian foreign aid, China seeks to promote FDI through ‘bilateral lending’ and ‘opportunistic’ (‘state-to-state’)[74] alliances rather than through multilateral channels or US involvement. Such bilateral aid has been consistent with China’s ‘go-global strategy’ of promoting Chinese firms internationally since 1998. The other goals have been to meet the country’s long-term energy demands and secure access to raw materials.[75] Of particular importance is the energy deal signed in 2008 that would give a big boost to oil exports to China.[76] However, by 2012, PDVSA’s underperformance allowed export of only 640,000 barrels of oil a day to China; 200,000 of that export revenue simply went to service the country’s debts to China.[77] In the first quarter of 2018, China imported only 381,300 barrels of oil from Venezuela, hitting ‘the lowest in nearly 8 years’.[78] Other recent deals include a $5 billion credit line from China to finance investments in infrastructure, electricity, and agricultural development, including a joint-venture agreement between the PDVSA and a Chinese state-owned company, Heilongjiang Xinliang.[79] Paradoxically, China’s ‘go-global strategy’ and bilateral diplomacy face limitations in Venezuela. The Chinese market potential has yet to be realized due to conflicts of interest in the global oil industry. In addition to limited refinery capacity, China has little proximity to Venezuela, which brings with it the high cost of transporting Venezuelan oil. The other obstacle is Venezuela’s ability to pay sovereign debt, which undermines China’s continued investments in the Orinoco Oil Belt. PDVSA only signed short-term sales contracts because of China’s interest in cheap fuel oil, whereas PDVSA seeks to increase the price of its heavy oil products. Finally, China has “signaled its willingness to work with opposition leaders” (Juan Guaido) for debt repayment, which indicates China’s declining confidence in the Maduro government.[80] Until China’s potential is fully realized, Central and North America remain the most important markets for PDVSA’s crude oil export. CITGO: The US Overreach and Sanctions Dilemma Welcomed at one time for its charitable donations of fuel oil in the USA, CITGO has become a major player in the ongoing crisis with the US government. In the last decade or so, Venezuela’s relationships with the US are the opposite of those with Russia and China, which are generally aligned with states considered America’s adversaries. PDVSA bought CITGO in 1990, a Houston-based oil company that has been in business since 1910 and exports close to a million barrels of oil to the US annually. CITGO—fully owned PDVSA’s subsidiary—accounts for the largest share of Venezuela’s foreign downstream (refinery) operations in the US, along with operations in the Caribbean and Europe.[81] At its peak in 2007, Venezuela exported an average of 1.1 million b/d of crude oil to the US. In the first round of sanctions that began in August 2017, the US issued “an executive order that limited access to debt capital and prevented PDVSA from receiving cash distributions from CITGO”.[82] In January 2019, the White House imposed broader sectoral sanctions on PDVSA’s crude oil shipments to the US. The sanctions were aimed at unseating President Nicolas Maduro, whose last election in 2018 the US viewed as illegitimate. Pursuant to President Trump’s Executive Order, the US Treasury banned access to US financial markets and oil supplies for all PDVSA joint ventures and its subsidiaries, including a blockage on PDVSA’s property under US jurisdiction and a ban on all US companies and individuals from ‘engaging in transactions’ with PDVSA[83]. As a result, all U.S. imports of Venezuela’s crude oil were discontinued in March 2019.[84] In April 2019, the US Treasury’s Office of Foreign Assets Control (OFAC) took steps to exempt certain transactions from US sanctions under amended licenses that would allow “only transactions necessary for the maintenance of ‘essential operations’ through June 1, 2022”.[85] Even after securing special permissions, the ban on export authorizations for PDVSA’s foreign partners negatively impacted US oil interests in Venezuela. Such an embargo left oil companies like Chevron, Eni, Repsol “with billions of dollars in unpaid dividends and debts that had been settled through Venezuelan oil cargos”.[86] While hoping to unseat the Maduro government through economic sanctions, the White House left CITGO out of the equation from the beginning since it was a strategically important part of the American business. CITGO is the operator of three of the largest oil refineries that provide 750,000 barrels per day (b/d), including one in Chicago that is a regional energy hub. For instance, in 2015, CITGO provided 15 billion gallons of gasoline to American drivers.[87] Given the strategic importance of CITGO to American oil interests, the US expects to carry on buying oil from PDVSA with little disruption. This depends on the continued viability of CITGO- PDVSA’s most valued asset abroad. However, CITGO had already become liable for Venezuela’s debt when foreign companies attempted to seize PDVSA’s CITGO shares as compensation for expropriated assets in 2006-2007. Therefore, the US Treasury (OFAC) took further steps in October 2019 to safeguard CITGO “from seizure in legal challenges against Venezuela to preserve the asset for the interim government if it takes power”.[88] This indicated that bondholders would be unable to recover their collateral, which consists of shares in CITGO, until January 22, 2020, even in the event of a default on those bonds. In May 2020, CITGO’s new board, appointed by the interim (US-backed) government of Juan Guaido, reached an agreement with bondholders to prevent creditors from liquidating CITGO’s assets until May 2020. OFAC extended the protection for CITGO through October 20, 2020.[89] Furthermore, obstacles remain to the full lifting of US sanctions. Given the oil shortage caused by Russia’s invasion of Ukraine in February 2022, President Biden initiated talks with Venezuelan officials about easing some of the sanctions before the expiry date (June 1, 2022). Around March 2022, traders were speculating that such a move might lead to the relaxation of restrictions on Venezuelan bond purchases as well. However, since the Biden administration does not officially acknowledge Maduro as the leader of Venezuela, US investors are still prohibited from buying the country’s debt, unlike European investors who are aggressively buying the bonds.[90] Ironically, US sanctions against PDVSA resulted in increased isolation and consolidation of power for the Maduro regime. The desired effect, namely the strengthening of the Guaido-led provisional government and a democratic transition, failed to materialize. Furthermore, the provisional government was unable to maintain control over CITGO’s management. This makes CITGO’s future uncertain, as the board of directors keeps changing and PDVSA tries to regain control of the company under any future settlement with the US. Policy Implications of the Research for Oil Industry Managers This paper has examined PDVSA’s strategic importance for North America and its dependence on the US as a ‘lender of last resort’ and leading global trader. When PDVSA defaulted on sovereign bonds, the US kept CITGO secure by renewing exemptions from US sanctions. This prevented creditors from liquidating PDVSA’s CITGO shares—‘American cash cow’ and the most valued asset PDVSA holds abroad.[91] Big US oil companies like Chevron benefited from the exemption and further easing of US sanctions in 2022, which would help resume their operations in Venezuela. While Chevron remains committed to investing in Venezuela, CITGO appears to benefit significantly from reopening trade with PDVSA.[92] This goes contrary to the emergence of a multi-polar world order (China, Russia) that would undermine US oil interests in Venezuela. US oil industry managers are capitalizing on the increasing tensions between PDVSA and its trading partners, which are occurring against the backdrop of Western sanctions on Russian oil. Although PDVSA has repeatedly expressed interest in increasing oil trade with China to diversify oil exports from the US, it must come up with a feasible strategy. Chinese and Russian investments are high risk and have far bigger liabilities than originally thought, as they are no longer reliable markets for Venezuelan oil. Even when oil prices were high, there were structural fault lines in PDVSA that would open further after prices dropped. Rosneft’s exit from Venezuela in March 2020 amid US sanctions was a loss of financial and technical capacity for PDVSA.[93] On the other hand, given PDVSA’s drop in oil production and the drop in oil prices after the commodity boom, China finds it harder to trust Venezuela with its outstanding loans (around $20 billion)[94] and may be even reluctant to make more oil investments. China seems to be “focused more on getting its payments back than strengthening its diplomatic relations”.[95] Until China’s potential is fully realized as a trading partner, North America remains the dominant market for PDVSA’s crude oil export. As for the recommendations and directions for future research, it is conceivable that as oil prices keep rising, PDVSA may once again achieve a modicum of normalcy. This is an area of research that needs to be further investigated. In June 2022, the US State Department gave the green light to two European companies, Italy’s Eni and Spain’s Repsol, to resume shipments of Venezuelan oil to Europe. This could potentially benefit US oil companies by helping to reduce Europe’s dependence on Russia and redirecting some of PDVSA’s shipments from China.[96] With recovering oil prices lately, “Venezuelan oil production recovered from a historically low level of 500,000 barrels per day (b/d) in 2020 to a yearly average of 636,000 b/d in 2021 and, most recently, 788,000 b/d in February 2022”.[97] However, this still begs the question of how PDVSA can stave off another crisis that seems almost inevitable for rentier states based on oil. Conclusion Combining institutional theory of the firm with resource dependency analysis, this paper examined the evolving corporate strategy of Venezuela’s state-owned oil company, PDVSA. It has examined the multitude of stakeholders involved in oil policy making, including local institutional actors and transnational oil interests. Certainly, obstacles remain to PDVSA’s performance and potential for investment arising from rentier economy distortions, especially since the rise of President Chavez in 1998 and subsequently. As of August 2020, Venezuela produced 360,000 barrels a day (b/d) of crude oil (excluding condensates)—the lowest amount ever recorded since 1973. Several factors continue to drive down crude oil production, such as a lack of investments, maintenance problems in oil infrastructure, a shortage of heavy oil diluents, and loss of human capital. US sanctions in 2019 and 2020 decreased foreign investment and limited markets for Venezuelan oil.[98] Since the easing of US sanctions in 2022, US oil industry managers need much stronger incentives to resume business talks with PDVSA. Because of the changing political climate and increased tariffs on Venezuelan oil under President Trump, however, these talks might be significantly delayed. To boost oil output, the Venezuelan government signed new oil deals in late 2018 with seven companies, akin to private investments (‘operating agreements’) nationalized by Chavez. Although the plan seemed like a gesture to allow more foreign participation, it faced several hurdles before the closing of the deal. Most of the companies involved were small and little known, with no recognized experience operating oil fields, and US sanctions have prevented experienced firms from working with PDVSA.[99] With the resumption of diplomatic talks in 2022, the US can utilize other incentives, such as promoting private sector investments. Such investments should target stronger technical expertise, managerial, and organizational resources. In CITGO’s case, for instance, “the United States could encourage the company to make targeted investments to update pipeline infrastructure in Venezuela”.[100] Another significant challenge lies in creating compelling incentives for former PDVSA employees to return to work in Venezuela. Consequently, should a regime change occur, the central question becomes which oil companies will work with PDVSA, rather than focusing solely on FDI. However, domestic institutions and U.S. oil policy in Latin America could significantly affect the outcomes of these incentives. Overall, this paper has argued that PDVSA’s oil strategy can’t overcome the paradox of “rentier socialism”, geared towards using oil income as a windfall for development. In the long run, PDVSA’s resource dependence and its alliance-based trading will only temporarily mask the underlying over-production crisis. 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History and Anthropology, 33(4), pp. 472–495. Available at: <https://doi.org/10.1080/02757206.2020.1762588>. [3] US Energy Information Administration. (2019, January 7). Background Reference: Venezuela. Available at: <https://www.eia.gov/international/content/analysis/countries_long/Venezuela/background.htm>. [4] Wilson, J. (2015). Understanding resource nationalism: economic dynamics and political institutions. Contemporary Politics, 2015, Vol. 21, No. 4, pp. 399–416, 400-401. [5] Mommer, B. (1990). Oil Rent and Rent Capitalism: The Example of Venezuela, Review. Fernand Braudel Center, Vol. 13, No. 4, Fall, pp. 417-437; Cardin, P. (1993). Rentierism and the Rentier State: A Comparative Examination. McGill University, PhD thesis; Karl, T. L. (1997). The Paradox of Plenty: Oil Booms and Petro-States. Berkeley: University of California Press; Acemoglu, D., Robinson, J. (2012). Why Nations Fail: The Origins of Power, Prosperity, and Poverty, ed. New York: Crown; Losman, D. L. (2010). The Rentier State and National Oil Companies: An Economic and Political Perspective. Middle East Journal, Vol. 64, No. 3, Summer, pp. 427-445; Lopez-Maya, M. (2014). The Political Crisis of Post-Chavismo. Social Justice, Vol. 40, No. 4 (134), pp. 68-87; Wilson, J., 399–416; Lander, E. (2016). The implosion of Venezuela’s rentier state. Transnational Institute New Politics Papers. Available at: <https://www.tni.org/en/publication/the-implosion-of-venezuelas-rentier-state>. [6] Karl, T. L. (1997). [7] Di John, J. (2010). From Windfall to Curse? Oil and Industrialization in Venezuela, 1920 to the Present. Pennsylvania University Press. A rentier state or economic model tends to emerge when “mineral and fuel production is at least 10 percent of GDP and mineral, and fuel exports are at least 40 percent of total exports” (Di John. (2010). p. 79). [8] Sachs, J. D., Warner, A. (1999). The Big Rush, Natural Resource Booms and Growth. Journal of Development Economics, v. 59 (1, Jun), pp. 43-76; Venables, A. (2016). Using Natural Resources for Development: Why Has It Proven So Difficult? Journal of Economic Perspectives. 30(1): 161–184; Ross, M. (2015). What Have We Learned about the Resource Curse? Annual Review of Political Science. 18: 239–259; Sachs, J. D., Warner, A. (1995). Natural Resource Abundance and Economic Growth. NBER Working Paper No. 5398. Available at: <https://www.nber.org/papers/w5398>. [9] Manzano, O., Monaldi, F. (2010). The Political Economy of Oil Contract Renegotiation in Venezuela., in H. William, F. Sturzenegger (eds.), The Natural Resources Trap: Private Investment without Public Commitment; MIT Press: MA, Cambridge. [10] Wiseman, C., Beland, D. (2010). The Politics of Institutional Change in Venezuela: Oil Policy During the Presidency of Hugo Chávez. Canadian Journal of Latin American and Caribbean Studies, Vol. 35, No. 70 (2010), pp. 141-164.; Styhre, A. (2019). The institutional theory of the firm: Embedded Autonomy, Routledge: London, UK. [11] Dachevsky, F., Kornblihtt J. (2017). The Reproduction and Crisis of Capitalism in Venezuela under Chavismo. Latin American Perspectives, 44(1): 78-93, p. 78. [12] Luong. P. J., Weinthal, E. (2006). Rethinking the Resource Curse: Ownership Structure, Institutional Capacity, and Domestic Constraints. Annual Review of Political Science, Vol. 9, pp. 241-263. [13] Karl, T. L. (1997). [14] Mahdavy, H. (1970). The Pattern and Problems of Economic Development in Rentier States: The Case of Iran, in Cook, M. A. (eds). Studies in the Economic History of the Middle East, Oxford University Press: Oxford, London, pp. 427-476. [15] Sachs, J. D., Warner, A., (1999), pp. 43-76.; Smith, M. (2013, January 11). Venezuela, Oil and Chavez: A Tangled Tale. Available at: <www.oilprice.com>; Smith, B., Waldner, D. (2021). Rethinking the Resource Curse. Cambridge University Press: London, UK. [16] Beblawi, H. (1987). 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[81] US Energy Information Administration. (2019, January 7). [82] CRS. (2021). p. 22 [83] CRS, (2022). [84] US Energy Information Administration, (2020). [85] CRS, (2022). [86] International Business Times News. (2022, March 31). Exclusive-Venezuela’s PDVSA Seeks Oil Tankers in Anticipation of US Sanctions Easing. [87] Jaffe, A. M. (2018, January 23). How Much Worse Can It Get for Venezuela’s State Oil Firm PDVSA? Council on Foreign Relations. Available at: <https://www.cfr.org/blog/how-much-worse-can-it-get-venezuelas-state-oil-firm-pdvsa>. [88] CRS, (2021), p. 11. [89] CRS, (2021), p. 13. [90] Vizcaino, M. E., Yapur, N. (2022, March 8). Defaulted Venezuela Bonds Are Luring Buyers Betting on US Deal. Bloomberg. [91] Krauss, C. (2018, October 1). Venezuela’s Crisis Imperils Citgo, Its American ‘Cash Cow’. New York Times. [92] Garip, P. (2021, August 12). Venezuela Negotiating Agenda in Crosscurrent. Argus Media. [93] De La Cruz, A. (2020, April 10). [94] Sigalos, M. (2019, February 7). China and Russia loaned billions to Venezuela — and then the presidency went up for grabs. CNBC. [95] Garcia, I. (2021, December 22). The Future of the Sino-Venezuelan Relationship: Make or Break? Harvard International Review. [96] Parraga, M., Spetalnick, M. (2022, June 6). U.S. to let Eni, Repsol ship Venezuela oil to Europe for debt. Reuters. [97] Palacios, L., Monaldi F. (2022, March 23). Venezuela Oil Sanctions: Not an Easy Fix Available at: <https://www.energypolicy.columbia.edu/research/commentary/venezuela-oil-sanctions-not-easy-fix#_edn6>. [98] US Energy Information Administration, (2020). [99] Pons, C. (2018, September 10). Exclusive: Venezuela signs oil deals similar to ones rolled back under Chavez – document. Reuters. [100] Berg, R. (2021, October 12). The Role of the Oil Sector in Venezuela’s Environmental Degradation and Economic Rebuilding. 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Unveiling new insights about the influence of oil prices on GDP in OAPEC nations: MMQR investigation
Employing the methodology of moments quantile regression with fixed effects (MM-QR), this research examines the influence of variations in oil prices on economic development within Arab oil-exporting nations that are affiliated with the Organisation of Arab Petroleum Exporting Countries (OAPEC). Comprehensive data from 1990 to 2021 for eleven OAPEC member countries are analyzed. The empirical findings derived from the analysis reveal a significant and positively correlated association between the fluctuations in oil prices and economic growth, particularly when examined within the context of nations exhibiting higher Gross Domestic Product (GDP) quantiles, which suggests that countries possessing elevated GDP levels tend to derive greater economic advantages from increases in oil prices. Nevertheless, it is noteworthy that the impact of this correlation diminishes considerably for countries situated within the lower GDP quantiles. Additionally, population growth positively affects GDP but exhibits diminishing returns over time, while exchange rate fluctuations show negligible impact on overall economic stability and growth. Keywords: Oil price fluctuations, GDP, method of moments quantile regression, population, OAPEC. Introduction Strong turbulences marked by abrupt variations in oil prices have rocked the global oil market during the past few decades. The times of highest oil price volatility were 1973, 1979, 2008, and 2020, which followed the 2019–2020 coronavirus epidemic. Because the US has run out of storage space, the West Texas Intermediate futures crude oil price saw negative trading for the first time in April 2020. The global oil market’s past indicates that macroeconomic success and fluctuations in oil prices have historically been closely correlated. Both nations that import oil and nations that export oil may experience economic instability as a result of oil shocks. Furthermore, in some oil-dependent economies, sudden and severe swings in oil prices may be the cause of financial and economic crises. Since it can have an impact on producers, governments, and consumers, the volatility of global oil prices and how it affects macroeconomic performance have become more of an issue for economies.[1] For centuries, oil has pulsated through the veins of the Arab world, fueling not only its cars and industries but also its societies and political landscapes. The OAPEC members have witnessed an intricate and influential interaction between their oil wealth and economic fortunes. This relationship dances to the rhythm of the up-and-down nature of oil prices, a volatile melody that can uplift economies to soaring heights or plunge them into the abyss of stagnation. Hence, this investigation endeavors to enhance the existing literature in twofold. Initially, this paper measures the influence of fluctuations in oil prices on the trajectory of economic expansion in Arab nations that export oil. This involves analyzing historical data to identify patterns and correlations between oil prices and economic indicators such as Gross Domestic Product growth. The choice of these nations is according to its importance in the oil market since they contain leader countries such as Saudi Arabia, Iraq, Libya and Algeria. Second, for the first time, this analysis uses the modern MMQR procedure to allow us to track the effect of oil prices on several quantiles of GDP. This procedure will help us to determine and estimate what role oil prices play in low, medium and high GDP levels among the nations of the study. Literature Review The oscillations observed in oil prices exert significant ramifications on economic development within Arab nations, especially those that exhibit a pronounced dependence on oil exports. The link between oil price variations and GDP growth is complicated and varied, impacted by different economic, political, and social factors. To begin with, real GDP in the GCC countries, which include Saudi Arabia, Bahrain, Qatar, Kuwait, United Arab Emirates, and Oman, reacts asymmetrically to oil price changes, specifically, positive oil price shocks exert a more pronounced positive influence on GDP than negative shocks. This asymmetry suggests that while rising oil prices can stimulate economic activity, falling prices may not have an equally detrimental effect, particularly in nations like Kuwait and Qatar, where the negative impacts of price declines are more pronounced.[2] Moreover, the interconnectedness of oil prices, electricity consumption, and GDP in the GCC region further complicates this relationship. The petroleum sector constitutes the essential foundation of the economies in these countries, accounting for a substantial proportion of the Gross Domestic Product (GDP). Consequently, fluctuations in oil prices possess the capacity to trigger significant modifications in governmental revenue streams, which in turn affect public spending and investment endeavors. This cyclical interdependence engenders a situation wherein elevated oil prices may result in augmented government spending on infrastructure and social initiatives, thus facilitating economic development.[3] However, the fluctuations inherent in oil prices may concurrently generate a degree of unpredictability within the economic landscape, potentially impeding both investment activities and the formulation of economic strategies. Oil price shocks explain a significant portion of the variation in governmental income and gross domestic product within the Sultanate of Oman, indicating that fluctuations can lead to budgetary constraints during periods of low prices. This volatility can create a challenging environment for policymakers, as they must navigate the impacts of fluctuating revenues on fiscal policy and economic stability.[4] In addition to direct impacts on GDP, oil price volatility can also influence inflation rates and the overall economic climate. Oil shocks can lead to inflationary pressures, which can further complicate economic growth. In nations that derive substantial revenue from oil exports, escalating oil prices may result in heightened production costs, which may be passed on to consumers, thereby affecting consumption and investment decisions. This inflationary effect can dampen the positive impacts of rising oil prices on GDP growth.[5] Furthermore, the historical context of oil price shocks provides insight into their long-term effects on economic growth. The twin oil crises of the 1970s, resulted in significant economic transformations in Gulf oil exporters, as they utilized their increased revenues to invest in foreign aid and domestic development. This historical perspective underscores the potential for both beneficial and adverse outcomes stemming from oil price fluctuations, depending on how governments choose to manage their oil revenues.[6] The situation in Iraq exemplifies an additional aspect of the repercussions of oil price fluctuations on economic development. Rodhan’s research indicates that although elevated oil prices typically exert a beneficial influence on gross domestic product, the ramifications of decreasing prices are significantly more acute in nations such as Kuwait and Qatar, suggesting that the economic resilience of these nations is closely tied to their oil revenue stability.[7] An other study analysed the level of dependency between petroleum prices and the expansion of economic activity in four member states of OPEC during the timeframe spanning from September 3, 2000, to December 3, 2010. The study results indicate that fluctuations in oil prices during times of global economic fluctuations and financial instability impact the correlation between oil and economic development in OPEC nations.[8] Research has examined the significant influence of fluctuations in crude oil prices and their volatility on the economic expansion of countries in the MENA region. Additionally, the researcher examined the bidirectional and fluctuating correlation between economic development and oil prices. In addition, a distinct study was carried out for each MENA country that exports oil and each country that imports oil. The study employed a panel quantile regression methodology using alternative linear models. The research findings revealed that fluctuations and volatility of oil prices have differing impacts on countries that export and import oil. Across various quantiles, the effects of oil price variations and the level of uncertainty associated with them differed.[9] In conclusion, the influence of fluctuations in oil prices on the economic advancement of Arab countries is characterized by a complex interplay of positive and negative effects. While increasing oil prices may invigorate economic expansion and government revenues, volatility introduces uncertainty that can hinder investment and fiscal planning. The historical context and the specific economic structures of these nations further influence how they respond to fluctuations in oil prices. As such, there is a critical need for these countries to pursue economic diversification strategies to reduce their dependence on oil revenues and enhance their resilience to price shocks. 2.2. Data Table 1 provides an overview of the various variables, while Table 2 describes statistics for the sample. Table 1: Variable Description Table 2: Descriptive statistics Source: EViews 12 program output According to the data presented in Table 2, the skewness values for three variables (GDP, POP, and EXR) are negative and significantly different from zero, indicating a pronounced left skewness. The Skewness value for the variable OILP is close to zero, but its Kurtosis value is far from three. The Jarque-Bera statistical test unequivocally rejects the null hypothesis of normality, providing further confirmation that using OLS estimation will be unreliable, while adopting quantile regression is more appropriate and resilient for this investigation. Empirical Results 3.1. Correlation matrix / Variance inflation factor: Table 3: Correlation matrix - Variance inflation factor Source: STATA 17 program output Table 3 displays the correlation coefficients between the different variables, along with the findings of the variance inflation factor. The absolute values of all correlation coefficients between independent variables are below 0.7. The VIF test findings demonstrate that there is no multicollinearity among the independent variables, as the average value of 1.39 is below 5. The VIF findings support our perspective of including OILP, POP, and EXR in the same model. 3.2. Slope homogeneity test: Table 4: Slope homogeneity test results: Source: STATA 17 program output Before continuing, it is essential to perform a crucial test to verify the accuracy of the Slope homogeneity hypothesis for the provided data. Therefore, we will utilise two tests for analysis: (Pesaran & Yamagata, 2008)[15] and (Blomquist & Westerlund, 2013).[16] The findings delineated in Table 4 demonstrate the rejection of the null hypothesis of uniformity in the slope across different nations. Thus, it is crucial to take into account the limitations imposed by variability on the slope to guarantee reliable outcomes in estimating techniques. 3.3. Cross-section dependence tests Table 5: Cross-section dependence test results: *** Indicates the null hypothesis being rejected with a significance level of 1% Source: EViews 12 program output We utilize four distinct examinations: the Breusch-Pagan LM (BP) test suggested by (Breusch & Pagan, 1980),[17] the Pesaran Scaled LM (PS) test presented by (Pesaran M. , 2004),[18] the Bias corrected scaled LM (BCS) test proposed by (Baltagi et al., 2012)[19] and the Pesaran CD (PE) test (Pesaran, 2007)[20] The findings showed that the null hypothesis of “no CSD” is not accepted, they unequivocally affirm that any shock impacting a variable in one country would propagate its impact to the same variable in other nations. 3.4. MM-QR results and discussion: Table 6: The findings of the MMQR approach Notes: The symbols ***, **, and * represent statistical significance at the 1%, 5%, and 10% levels, respectively. Source: STATA 17 program output The findings of MM-QR across different quantiles have flourished in Table 6; the coefficient related to OILP is positive, significant and gradually increased from 0.2 to 0.9 quantiles and remains insignificant for the first quantile. Notably, this outcome is in line with findings for GCC members. [21] This heterogeneous impact across income levels is likely driven by several factors. MM-QR allows us to isolate these dynamics by revealing how oil price changes differentially affect various quantiles of the GDP distribution. The results indicate that as GDP increases from the 0.2 to the 0.9 quantiles, the impact of oil price fluctuations becomes stronger and more positive. This means that countries with higher GDP tend to benefit more from increases in oil prices in terms of economic growth. The insignificance of the coefficient for the lowest GDP quantile indicates that changes in oil prices have a minimal impact on the poorest sectors of the economy. This might be because they’re not as connected to global markets or rely more on industries other than oil for their economy. This outcome can be attributed to the fact that high-income countries (those with elevated GDP levels) benefit from a more robust economy through strategic investment projects yielding substantial economic returns. Nations such as Saudi Arabia, Qatar, and the UAE, when experiencing a rise in oil prices, acquire additional revenue that is subsequently channeled into local investments. This process directly and significantly impacts economic growth. Conversely, countries with lower GDP levels are characterized by limited and weak investment opportunities. In these nations, oil revenues are primarily allocated towards bolstering infrastructure and funding social expenditures, which do not contribute as substantially to economic growth. Population has a positive and significant impact on GDP and decreases gradually from the low to high quantiles confirming prior findings.[22] Accordingly, this outcome can be explained by the fact that when the population grows further, resources like land, infrastructure, and skilled labor might become relatively scarce, leading to diminishing marginal returns from additional population growth. This could explain the decreasing effect in higher quantiles. The effect of exchange rate for local currency on GDP is negative but insignificant across all quantiles, which aligns with previous research.[23] The insignificant effects could be explained by the fact that a substantial portion of oil exports from these nations are denominated in US dollars, meaning they receive a fixed income regardless of their local currency’s exchange rate. This reduces the direct impact of fluctuations on overall GDP. Conclusion In summary, our paper gives us a clearer picture of how oil prices affect the economies of Arab countries that export oil. The study’s duration was from 1990 to 2021 using a special analysis method called Moment of Quantile Regression (MM-QR). Our results support what we suspected: there’s a strong and positive connection between oil prices and economic growth in these countries. But what’s interesting is that this connection isn’t the same for everyone. We found that as a country’s wealth (measured by GDP) goes up, the impact of oil prices on its economic growth gets stronger. However, for the poorest parts of these countries, the impact is much smaller. This suggests that poorer areas might not be as affected by changes in oil prices, perhaps because they’re not as connected to the global economy or they rely more on industries other than oil. We also looked at how population growth and changes in exchange rates affect economic output. It turns out that while a growing population initially boosts economic growth, the effect decreases as a country becomes wealthier. This tells us that the correlation between population and economic growth is significantly more complicated than it seems. Similarly, changes in exchange rates don’t seem to have a big impact on overall economic output, likely because these countries mostly trade oil in foreign currencies. Recommendations: According to our research, we may provide some suggestions: Leaders should prioritise diversifying their sources of revenue, particularly in economically disadvantaged regions, to reduce their reliance on oil revenues and enhance their ability to rebound from challenging circumstances; Make strong plans to handle changes in money value, like saving money and being careful with spending, to protect against sudden changes in how much money is worth. Spend time and money learning about how money and economies work better, so we can make smart plans for when oil prices go up and down and keep our economies strong in the long term. Bibliography: Al Jabri, S., Raghavan, M., Vespignani, J. (2022). Oil prices and fiscal policy in an oil-exporter country: Empirical evidence from Oman. Energy Economics, 111(106103). Doi: <https://doi.org/10.1016/j.eneco.2022.106103>; Ayad, H., Ben-Salha, O., Ouafi, M. (2023). Do oil prices predict the exchange rate in Algeria? Time, frequency, and time‐varying Granger causality analysis. Economic Change and Restructuring, 56(5). Doi: <https://doi.org/10.1007/s10644-023-09545-1>; Baltagi, B., Feng, Q., Kao, C. (2012). A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model. Journal of Econometrics, 170(1). Doi: <https://doi.org/10.1016/j.jeconom.2012.04.004>; Benlaria, H., Almawishir, N. (2024). 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Doi: <https://doi.org/10.32479/ijeep.15681>; Werker, E., Ahmed, F., Cohen, C. (2009). How Is Foreign Aid Spent? Evidence from a Natural Experiment. American Economic Journal: Macroeconomics, 1(2). Doi: <10.1257/mac.1.2.225>; Zmami, M., Ben Salha, O. (2020). Oil price and the economic activity in GCC countries: Evidence from quantile regression. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(4). Doi: <https://doi.org/10.24136/eq.2020.028>. Footnotes [1] Marimoutou, V., Raggad, B., Trabelsi, A. (2009). Extreme Value Theory and Value at Risk: Application to oil market. Energy Economics, 31(4), pp. 519-530. Doi: <https://doi.org/10.1016/j.eneco.2009.02.005>. [2] Zmami, M., Ben Salha, O. (2020). Oil price and the economic activity in GCC countries: Evidence from quantile regression. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(4), pp. 651-673. Doi: <https://doi.org/10.24136/eq.2020.028>. [3] Benlaria, H., Almawishir, N. (2024). The Relationship between Electricity Consumption, Price of Oils, and Gross Domestic Product in the Gulf Cooperation Council Countries. International Journal of Energy Economics and Policy, 14(1), pp. 66-75. Doi: <https://doi.org/10.32479/ijeep.15108>. [4] Al Jabri, S., Raghavan, M., Vespignani, J. (2022). Oil prices and fiscal policy in an oil-exporter country: Empirical evidence from Oman. Energy Economics, 111(106103). Doi: <https://doi.org/10.1016/j.eneco.2022.106103>. [5] Gómez-Loscos, A., Gadea, M., Montañés, A. (2012). Economic growth, inflation and oil shocks: are the 1970s coming back? Applied Economics, 44(35), pp. 4575-4589. Doi: <https://doi.org/10.1080/00036846.2011.591741>. [6] Werker, E., Ahmed, F., Cohen, C. (2009). How Is Foreign Aid Spent? Evidence from a Natural Experiment. American Economic Journal: Macroeconomics, 1(2): 225-44. Doi: <10.1257/mac.1.2.225>. [7] Rodhan, M. (2024). Macroeconomic impacts of oil price shocks: evidence from Iraq by using vector autoregressive model. International Journal of Energy Economics and Policy, 14(3), pp. 162-170. Doi: <https://doi.org/10.32479/ijeep.15681>. [8] Ftiti, Z., Guesmi, K., Teulon, F., Chouachi, S. (2016). Relationship between crude oil prices and economic growth in selected OPEC countries. The Journal of Applied Business Research, 32(1), pp. 11-22. Doi: <http://dx.doi.org/10.19030/jabr.v32i1.9483>. [9] Mamdouh, A. (2023). Oil price fluctuations and economic growth: the case of MENA countries. Review of Economics and Political Science, 8(5), pp. 353-379. Doi: <http://dx.doi.org/10.1108/REPS-12-2019-0162>. [10] Machado, J., Silva, J. (2019). Quantiles via moments. Journal of Econometrics, 213(1), pp. 145-173. Doi: <https://doi.org/10.1016/j.jeconom.2019.04.009>. [11] Koenker, R., & Bassett, Jr., G. (1978). Regression Quantiles. Econometrica, 46(1), pp. 33-50. Doi: <10.2307/1913643>. [12] Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), pp. 74-89. Doi: <https://doi.org/10.1016/j.jmva.2004.05.006>. [13] Canay, I. (2011). A simple approach to quantile regression for panel data. The Econometrics Journal, 14(3), pp. 368-386. Doi: <https://doi.org/10.1111/j.1368-423X.2011.00349.x>. [14] Machado, J., & Silva, J. (2019). Quantiles via moments. Journal of Econometrics, 213(1), pp. 145-173. Doi: <https://doi.org/10.1016/j.jeconom.2019.04.009>. [15] Pesaran, M., Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), pp. 50-93. Doi: <http://dx.doi.org/10.2139/ssrn.671050>. [16] Blomquist, J., Westerlund, J. (2013). Testing slope homogeneity in large panels with serial correlation. Economics Letters, 121(3), pp. 374-378. Doi: <https://doi.org/10.1016/j.econlet.2013.09.012>. [17] Breusch, T., Pagan, A. (1980). The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics. The Review of Economic Studies, 47(1), pp. 239-253. Doi: <https://doi.org/10.2307/2297111>. [18] Pesaran, M. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. Cambridge Working Papers in Economics No. 0435, Faculty of Economics, University of Cambridge. [19] Baltagi, B., Feng, Q., Kao, C. (2012). A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model. Journal of Econometrics, 170(1), pp. 164-177. Doi: <https://doi.org/10.1016/j.jeconom.2012.04.004>. [20] Pesaran, M. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of applied econometrics, 22(2), pp. 265-312. Doi: <http://dx.doi.org/10.1002/jae.951>. [21] Zmami, M., Ben Salha, O. (2020). Oil price and the economic activity in GCC countries: Evidence from quantile regression. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(4), pp. 651-673. Doi: <https://doi.org/10.24136/eq.2020.028>. [22] Maestas, N., Mullen, K., Powell, D. (2023). The Effect of Population Aging on Economic Growth, the Labor Force, and Productivity. American Economic Journal: Macroeconomics, 15(2): 306-32. Doi: <10.1257/mac.20190196>. [23] Ayad, H., Ben-Salha, O., Ouafi, M. (2023). Do oil prices predict the exchange rate in Algeria? Time, frequency, and time‐varying Granger causality analysis. Economic Change and Restructuring, 56(5), pp. 3545-3566. Doi: <https://doi.org/10.1007/s10644-023-09545-1>.
Balancing Innovation and Risk: Regulatory Frameworks for Sustainable Fintech Growth
This paper investigates the transformative impact of Financial Technology (FinTech) and Artificial Intelligence (AI) on the global financial sector, moving beyond a descriptive overview to critically examine the challenges and opportunities they present. The study synthesizes a comprehensive review of empirical data, policy documents, and industry reports, including the EY Global FinTech Adoption Index (2023) and World Bank reports (2023), to analyze FinTech adoption across diverse regions and financial service categories. The research identifies key challenges related to electronic financial transactions, including cross-border complexities, decentralized systems, and cybersecurity risks. Furthermore, it addresses the crucial need for adaptable regulatory frameworks that balance innovation with financial stability and consumer protection. Findings reveal significant disparities in FinTech adoption globally, driven by factors such as technological infrastructure, regulatory environments, and socio-economic conditions. The study highlights the potential systemic risks associated with FinTech investments and underscores the importance of international cooperation in addressing cross-border challenges. By providing a holistic perspective that integrates technological, economic, ethical, and regulatory dimensions, this paper contributes to a more nuanced understanding of the dynamic interplay between technology and finance. It offers actionable recommendations for policymakers, industry practitioners, and academics seeking to foster responsible innovation and ensure the long-term resilience of the global financial system. Future research directions are proposed, including evaluating the effectiveness of different regulatory approaches, exploring the ethical dimensions of AI in finance, and conducting longitudinal studies to assess the long-term impacts of FinTech on financial stability and consumer welfare. Keywords: FinTech, artificial intelligence (AI), financial regulation, financial stability, digital finance. JEL Codes: G20 – G23 – O30 – O33. Introduction The global financial landscape is undergoing a radical transformation, spurred by the accelerating convergence of financial technology (FinTech) and artificial intelligence (AI). This technological revolution transcends simple digitization, fundamentally reshaping established business models and redefining the core functionalities of banking, investment management, and financial transactions. While the proliferation of digital banking services, enhanced by innovations such as real-time payment systems, AI-driven identity verification mechanisms, and round-the-clock chatbot support,[1] has undeniably enhanced customer experiences and improved operational efficiency, it simultaneously raises critical and complex questions. These include concerns regarding equitable financial inclusion, the potential for increased systemic risk, and the imperative of developing adaptive regulatory frameworks to govern these rapidly evolving technologies. Existing research, although valuable, often examines these issues in isolation, failing to capture the intricate interdependencies that characterize the modern FinTech ecosystem. This paper offers a comprehensive examination of the multi-layered impact of FinTech and AI on the financial sector. Moving beyond a descriptive overview, it provides a rigorous analysis of the primary challenges and opportunities these technologies present. The study leverages a comprehensive review of the most recent empirical data, relevant policy documents, and insightful industry reports, including crucial data from the EY Global FinTech Adoption Index (2023) and pertinent World Bank reports (2023). This data-driven approach allows for a detailed assessment of the factors driving FinTech adoption across diverse geographical regions and within specific financial service categories. Special attention is given to understanding the disparities in adoption rates across developed and developing economies, acknowledging the unique contextual factors that shape the FinTech landscape in each region. Further, the study explores the ethical dimensions of AI in finance, including biases in algorithms and the potential for discriminatory outcomes. A significant aspect of this research addresses the pressing need for adaptable and effective regulatory frameworks. In this regard, the study undertakes a detailed analysis of the characteristics, associated challenges, and necessary regulatory adaptations related to electronic financial transactions. It delves into the complexities arising from the cross-border nature of these transactions, the decentralization facilitated by blockchain technologies, and the ever-present threat of cybersecurity risks. Moreover, it explores the role of international organizations in establishing global standards and promoting cooperation among regulatory bodies, underscoring the necessity for a coordinated approach to FinTech regulation. The paper emphasizes the crucial balance that must be struck between fostering innovation and safeguarding financial stability, ensuring consumer protection, and promoting ethical behavior in the digital finance space. It challenges the notion that regulation inherently stifles innovation, arguing instead that well-designed regulatory frameworks can create a stable and trustworthy environment that encourages sustainable growth and development in the FinTech sector. In contrast to existing literature, which often compartmentalizes the analysis of FinTech, this study offers a uniquely holistic perspective that integrates technological, economic, ethical, and regulatory dimensions. By synthesizing diverse strands of research and drawing on a rich dataset, this research provides a more nuanced and comprehensive understanding of the complex dynamics shaping the future of finance. Addressing a gap in the current body of research, this research not only examines the growth in global FinTech investments from 2018 to 2023 but also rigorously analyzes how sector investments influence sector stability and systemic risks. The study’s findings are geared towards informing evidence-based policy and promoting responsible innovation in the FinTech arena. The paper seeks to answer the following overarching research questions: (1) How does the geographic distribution of FinTech adoption vary globally, and what are the key technological, economic, social, and political drivers behind these disparities? (2) What are the principal challenges posed by electronic financial transactions, particularly in relation to cross-border activities, decentralization, and cybersecurity, and how can these challenges be effectively mitigated through regulatory and technological innovations? (3) How can regulatory frameworks best balance the promotion of FinTech innovation with the imperative of ensuring financial stability, consumer protection, and ethical behavior, and what are the key principles that should guide the development of such frameworks? By providing robust empirical analysis and nuanced policy recommendations, this study aims to contribute to a more comprehensive and insightful understanding of the transformative potential and inherent challenges of FinTech and AI in shaping the financial sector’s future. The insights gleaned from this research will be highly valuable to academics conducting cutting-edge research, policymakers grappling with complex regulatory challenges, industry practitioners seeking to navigate the evolving FinTech landscape, and anyone with a keen interest in the intricate interplay between technology and finance in the 21st century. Ultimately, the research aspires to contribute to the development of a more inclusive, efficient, and resilient financial system that benefits all stakeholders. Literature Review The Impact of Fintech and Artificial Intelligence on the Financial Sector The financial sector has undergone significant transformations in recent years due to innovations in financial technology (Fintech) and artificial intelligence (AI), which have profoundly influenced how banking services, investment management, and financial transactions are conducted. Digital banking services provide a clear example of this transformation, allowing customers to manage most of their banking needs remotely without visiting physical branches. Advanced technologies, such as real-time money transfers, online account opening, identity verification technologies like facial recognition or fingerprint scanning, and 24/7 chatbot services, have enabled banks to significantly enhance customer experience and operational efficiency.[2] This shift, reflecting the increasing global adoption of Fintech, can be understood through a global heat map illustrating the levels of Fintech penetration in various countries. Regions depicted in warm colors, such as China and India, indicate high rates of Fintech adoption, particularly in areas like electronic payments and online lending. In contrast, other regions appear in cooler tones, signifying lower levels of Fintech adoption. The impacts of technological innovation, demographics, and government policies play a critical role in determining the rates of Fintech penetration. Countries with robust technological infrastructure, such as the United States and the United Kingdom, report high adoption rates, whereas some developing countries, such as Brazil and India, also exhibit high adoption rates due to the need to address the demands of the unbanked population.[3] Figure N°1: Global Heat Map of Fintech Penetration Source: EY Global FinTech Adoption Index 2023. Available at: <https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/banking-and-capital-markets/ey-global-fintech-adoption-index.pdf> Asia leads prominently in the adoption of financial technology, driven by the rapid growth of startups in China and India. In Europe, countries such as the United Kingdom and Sweden exhibit high adoption rates, benefiting from innovations in financial sectors. In contrast, Latin America and Africa, despite noticeable growth in some countries like Brazil and South Africa, still face relatively low adoption rates due to challenges related to infrastructure.[4] The leading sectors in Fintech include electronic payments and online lending, where startups are striving to provide innovative and unconventional solutions. With improvements in infrastructure and the adoption of supportive regulatory policies, regions such as Africa have the potential to experience significant growth in Fintech adoption in the future.[5] This transformation has also reshaped how individuals and businesses handle finances, with electronic payments enhancing the speed and convenience of financial transactions. These payments include the use of cryptocurrencies, such as Bitcoin and Ethereum, which offer decentralized payment methods, as well as mobile payments through services like Apple Pay and Google Pay. Furthermore, international money transfers have become more cost-effective thanks to companies like TransferWise (now Wise).[6] Robo-advisors have emerged as one of the most significant innovations in investment management, leveraging advanced algorithms to provide automated and low-cost investment services. These include dynamic asset allocation, which automatically adjusts investment portfolios in response to market changes, and complex investment strategies, such as factor investing, which were previously limited to institutional investors. Additionally, robo-advisors utilize behavioral analytics to understand investor behavior and offer personalized advice, alongside automated portfolio rebalancing to maintain target asset allocation.[7] Similarly, digital insurance has revolutionized the insurance industry by simplifying the process of purchasing and managing insurance policies and improving operational efficiency. Innovations in this field include usage-based insurance, such as car insurance based on driving habits, and automated claims processing using AI to expedite procedures. Instant insurance has also become available, allowing for the purchase of short-term policies like single-day travel insurance, along with the use of big data to enhance risk assessment accuracy.[8] Figure N°2: Comparison of Fintech Categories by Adoption Rate from 2015 to 2019 Source: EY Global FinTech Adoption Index 2019. Available at: <https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/banking-and-capital-markets/ey-global-fintech-adoption-index.pdf> The data presented highlights a significant transformation in the financial landscape between 2015 and 2019, shedding light on dynamic changes in consumer behavior and the evolution of financial services. The remarkable increase in the use of money transfers and payments, rising from 18% to 75%, reflects the widespread adoption of digital solutions, likely driven by the proliferation of smartphones and electronic payment applications. Parallel to this, the savings and investments sector experienced substantial growth from 17% to 40%, signaling heightened financial awareness and improved accessibility to digital investment tools. The notable rise in the utilization of budgeting and financial planning services (from 8% to 34%) and insurance (from 8% to 29%) indicates growing interest in personal financial health and risk management. Even the borrowing sector, although the least developed, showed a significant increase from 6% to 27%, potentially reflecting improved access to credit through digital platforms. Collectively, these trends underscore the rapid digitalization of the financial sector, emphasizing the increasing influence of financial technology (FinTech) in shaping consumer behavior and expectations. These developments also suggest a potential improvement in financial inclusion, as financial services have become more accessible to a broader segment of the population. This progress paves the way for further innovation and growth in the financial sector in the near future. These combined innovations have led to notable improvements in the financial sector by enhancing the efficiency of financial transactions through process automation and reducing the need for human intervention. This progress has contributed to cost reduction and increased market competition. Furthermore, financial services have become more accessible, particularly for financially marginalized groups in remote areas.[9] Nevertheless, these advancements come with new challenges, including cybersecurity concerns, privacy issues, and the need for modern regulatory frameworks to keep pace with these rapid changes. Therefore, technological innovation must be accompanied by robust policies and regulations to ensure the sustainability and stability of the financial sector. The Spread of FinTech and the Necessity for Regulatory Frameworks: Modern financial services are undergoing a revolutionary transformation thanks to the rapid advancement of financial technology (FinTech). This has led to the development of advanced regulatory frameworks to ensure a delicate balance between encouraging innovation, protecting consumers, and ensuring the stability of financial markets. The Payment Services Directive (PSD2) in the European Union serves as a prime example of these advancements. Introduced in 2018, this directive aims to enhance transparency and security in online financial transactions. It provides open access to banking data for licensed third parties, promotes two-factor authentication, and reduces consumer liability in cases of fraud[10]. In the United Kingdom, the Regulatory Sandbox framework provides an innovative environment where FinTech entrepreneurs can test their products and services under regulatory oversight. This approach reduces the time and cost associated with bringing innovations to market and fosters dialogue between innovators and regulators.[11] Furthermore, advancements in cryptocurrencies and digital assets necessitate updates to anti-money laundering and counter-terrorist financing (AML/CFT) laws. The “Know Your Customer” (KYC) principle is now being applied to cryptocurrency trading platforms, with requirements for reporting suspicious transactions by businesses operating in the digital asset space. These measures aim to combat cross-border financial crimes.[12] In the United States, the Financial Innovation Act promotes innovation while maintaining consumer protection. Meanwhile, Singapore’s FinTech regulatory framework features initiatives like “Sandbox Express” to expedite the testing of innovations.[13] Additionally, crowdfunding regulations in the European Union aim to organize crowdfunding platforms and protect investors, highlighting the importance of balancing innovation with small investor protection.[14] These regulatory advancements underscore the urgent need for flexible and effective frameworks that align with the rapid evolution of FinTech. In this context, Arner, Barberis, and Buckley emphasize that technology itself (RegTech) can play a pivotal role in improving regulatory compliance and risk management in the FinTech era.[15] Characteristics and Challenges of Electronic Financial Transactions: Amid significant transformations in the digital world, electronic financial transactions (E-transactions) have become one of the critical pillars of the global economy. However, these transactions pose various challenges rooted in their fundamental characteristics. Cross-Border Nature: E-transactions are characterized by their ability to transcend traditional geographical boundaries, creating a complex legal and regulatory environment. A single transaction may be subject to a variety of laws, potentially leading to conflicts among them, which complicates effective enforcement. For instance, determining tax jurisdiction for cross-border transactions can be challenging, as can addressing variations in consumer protection standards between countries, exposing consumers to differing levels of legal safeguards.[16] Decentralization: Blockchain technologies introduce a decentralized model for financial transactions, challenging traditional regulatory models. In this context, traditional oversight becomes difficult due to the absence of a central control point. Additionally, applying KYC principles in such systems becomes more complex, and new challenges emerge in freezing assets or reversing transactions in cases of fraud.[17] Cybersecurity Risks: With increasing reliance on technology, e-transactions are vulnerable to a wide range of cybersecurity risks. These include ransomware attacks targeting financial institutions and demanding payment to restore data, as well as advanced fraud techniques leveraging artificial intelligence (AI), which heighten the complexity of required cyber defenses.[18] Efforts by International Organizations: International organizations, such as the Financial Action Task Force (FATF), are actively working to establish global standards to address regulatory challenges in the digital age. These efforts include issuing updated recommendations to regulate virtual assets and virtual asset service providers (VASPs), along with enhancing international cooperation among regulatory bodies to ensure consistency across borders.[19] Data Privacy: As reliance on collecting and analyzing financial data grows, significant challenges arise regarding consumer privacy protection. Arner, Barberis, and Buckley highlight that FinTech introduces new dimensions to data protection, necessitating the development of regulatory frameworks that consider consumers’ rights in this context.[20] Financial Inclusion: FinTech contributes to advancing financial inclusion by expanding financial services to marginalized groups. However, these technologies can also create a new digital divide between those with access to technology and those without.[21] Regulatory Adaptation: The rapid evolution of FinTech demands the development of flexible regulatory frameworks that adapt to ongoing changes. Zetzsche, Buckley, Arner, and Barberis point out that the main challenge lies in transitioning from traditional regulatory systems to ones capable of managing data-driven finance.[22] Addressing these challenges requires a comprehensive approach that strikes a delicate balance between fostering innovation, ensuring financial stability, and protecting consumers. International cooperation among regulators and the private sector is crucial to tackling global challenges posed by e-transactions. Over time, the need for adaptable regulatory frameworks will persist to keep pace with the rapid advancements in FinTech.[23] The Impact of FinTech on Financial Sector Stability: A Comprehensive Analysis of Challenges and Opportunities The financial sector has undergone a radical transformation with the adoption of financial technology (FinTech), which has become a key tool for restructuring the global financial system. The following data illustrates global growth rates in FinTech investments from 2018 to 2023. Table: Growth in FinTech Investments from 2018 to 2023 Source: EY Global FinTech Adoption Index 2023 The table shows that investments in FinTech have experienced significant fluctuations in recent years. A major decline occurred in 2020, with a negative growth rate of -34.5%, attributed to the global economic and financial impact of the COVID-19 pandemic. However, there was a strong recovery in 2021, with a growth rate of 132.6%, driven by the rapid digital transformation necessitated by the pandemic. This momentum continued with high growth rates in subsequent years, reflecting increased confidence in FinTech’s ability to reshape the financial sector and achieve long-term gains. Research by Feyen et al. (2021) highlighted the distribution of FinTech investments across various sectors, as illustrated in the following chart: Figure N°3: Distribution of FinTech Investments by Sector Source: Feyen, E., Frost, J., Gambacorta, L., Natarajan, H. (2021). FinTech and the digital transformation of financial services: Implications for market structure and public policy. The chart reveals that digital banking services and electronic payments dominate the FinTech landscape, accounting for 65% of total investments. This dominance reflects the ongoing transformation of the financial system toward innovation and the adoption of modern technologies. Simultaneously, emerging sectors like InsurTech signify a growing diversification within FinTech, enhancing its ability to offer innovative and comprehensive solutions tailored to diverse market needs. Despite its benefits, FinTech faces significant challenges that affect financial stability. Figure N°4: Key Challenges Facing the Financial Sector Source: World Bank. (2023). “Key Challenges Facing the Global Financial Sector Amid Digital Transformation”. World Bank Report. The figure identifies key challenges, with regulatory risks being the most critical. Governments and institutions must develop flexible regulatory policies that balance fostering innovation with ensuring compliance. Cybersecurity remains a persistent concern in an increasingly complex digital environment, necessitating global collaboration to address cyberattacks and protect sensitive data. Moreover, technological adaptation poses a fundamental challenge for traditional institutions, requiring significant investments in infrastructure and cultural shifts to remain competitive. Three Main Challenges Systemic Risks: FinTech introduces new systemic risks, such as technical failures and cyberattacks. For instance, Knight Capital suffered a $440 million loss within 45 minutes due to a technical glitch in 2012.[24] Similarly, the Bangladesh Central Bank cyberattack in 2016 resulted in an $81 million theft.[25] These incidents demonstrate how technology can increase financial system fragility and expose it to significant risks. Changing Market Dynamics: The entry of BigTech companies like Google, Apple, and Amazon into the financial sector has significantly altered market dynamics. While these companies enhance competition, improving services and reducing costs for consumers,[26] their vast resources could lead to market concentration, reducing competition in the long term and increasing monopoly risks. Rapid Crisis Propagation: FinTech has accelerated the transmission of financial crises through global interconnectedness. High-frequency trading systems and advanced algorithms can quickly transmit market volatility. Additionally, social media and online trading platforms amplify the spread of news and rumors, heightening market volatility.[27] Regulatory Measures for FinTech National FinTech Regulations: By 2020, over 50 countries had developed or were developing national FinTech strategies,[28] reflecting global awareness of the need to regulate FinTech to ensure financial system stability and consumer protection. Principles for Effective Regulation Balancing Innovation and Stability: Regulatory sandboxes, such as those used by the UK’s Financial Conduct Authority,[29] allow companies to test innovative products under controlled environments. Consumer Protection: Ensuring transparency in transactions, safeguarding personal data, and increasing consumer awareness are critical to reducing risks associated with digital financial services.[30] International Cooperation: Organizations like the Financial Stability Board (FSB) play a pivotal role in coordinating global financial policies to enhance system stability.[31] Regulatory Flexibility: Adopting a principles-based regulatory approach allows flexibility and fosters innovation while maintaining oversight.[32] RegTech: The “Electronic Financial Regulation” (RegTech) represents a significant innovation in the field of financial technology, leveraging technology to enhance compliance and regulatory processes within the financial sector. RegTech aims to simplify and automate regulatory operations, thereby promoting efficiency and transparency. According to a report by Deloitte,[33] the global RegTech market is expected to grow at a compound annual growth rate (CAGR) of 21.27% between 2020 and 2025. This growth reflects the increasing demand for technological solutions that support regulatory compliance within the financial sector. Consequently, establishing regulations and principles for electronic financial systems is imperative to maximize the benefits of financial technology while mitigating associated risks. This requires a balanced approach that fosters innovation and stability, safeguards consumer rights, enhances international collaboration, and ensures the flexibility of regulatory frameworks to adapt to the rapid changes in this sector. Discussion The findings of this study provide several important insights into the impact of FinTech and AI on the financial sector. The analysis of FinTech adoption rates across different regions highlights the significant role of technological infrastructure, regulatory environments, and socio-economic factors in driving the uptake of digital financial services. The observed disparities underscore the need for tailored policy interventions that address the specific needs and challenges of each region. For instance, in developing countries, efforts to improve digital literacy and expand access to internet connectivity are crucial to promote financial inclusion and enable widespread FinTech adoption. Our examination of electronic financial transactions reveals the persistent challenges associated with cross-border activities, decentralized systems, and cybersecurity threats. The complex legal and regulatory landscape surrounding cross-border transactions requires greater international cooperation and harmonization of regulatory standards. The decentralized nature of blockchain-based systems poses unique challenges for regulatory oversight and consumer protection, necessitating innovative approaches such as the development of regulatory sandboxes and the implementation of smart contracts with embedded compliance mechanisms. The increasing sophistication of cyberattacks highlights the importance of investing in robust cybersecurity measures and fostering collaboration between financial institutions, technology providers, and law enforcement agencies to combat cybercrime. The study’s analysis of FinTech investments and their impact on financial stability sheds light on the potential systemic risks associated with the rapid growth of the FinTech sector. The increasing interconnectedness of financial institutions and FinTech companies creates new channels for the transmission of shocks and vulnerabilities. The entry of BigTech companies into the financial sector also raises concerns about market concentration and the potential for anti-competitive behavior. Effective regulatory oversight is essential to mitigate these risks and ensure that the benefits of FinTech are not outweighed by the potential for financial instability. Limitations While this study provides a comprehensive analysis of the impact of FinTech and AI on the financial sector, it is important to acknowledge its limitations. First, the study relies primarily on secondary data sources, such as industry reports, policy documents, and academic publications. While these sources provide valuable insights, they may be subject to biases or limitations in data availability. Future research should consider collecting primary data through surveys, interviews, and case studies to provide a more nuanced understanding of the impact of FinTech on different stakeholders. Second, the study focuses primarily on the impact of FinTech on the financial sector in developed countries. While the findings are relevant to developing countries as well, further research is needed to examine the specific challenges and opportunities facing these countries in the context of FinTech. Factors such as limited access to technology, weak regulatory frameworks, and high levels of financial exclusion may significantly influence the impact of FinTech in developing countries. Third, the study does not fully account for the dynamic and rapidly evolving nature of the FinTech landscape. The pace of technological innovation is accelerating, and new business models and regulatory challenges are constantly emerging. Future research should adopt a more agile and forward-looking approach to capture the dynamic nature of the FinTech sector and anticipate future trends and challenges. Finally, the study does not provide a comprehensive analysis of the ethical implications of FinTech and AI. The use of algorithms and data-driven decision-making in finance raises important ethical concerns about fairness, transparency, and accountability. Future research should explore these ethical dimensions in greater detail and develop frameworks for responsible innovation in the FinTech sector. This includes considering the potential for algorithmic bias, the need for data privacy and security, and the importance of ensuring that FinTech solutions are accessible and beneficial to all members of society. Acknowledging these limitations provides a balanced perspective and reinforces the value of the study while paving the way for future research. It demonstrates intellectual honesty and strengthens the credibility of the work. Conclusion This study has provided a comprehensive analysis of the multifaceted impact of FinTech and AI on the global financial sector, moving beyond a descriptive overview to identify key challenges, opportunities, and the critical role of regulatory frameworks in shaping the future of finance. Our analysis reveals that the rapid adoption of FinTech, while driving efficiency and expanding access to financial services, also introduces novel systemic risks and necessitates adaptable regulatory approaches. The geographic disparities in FinTech adoption highlight the importance of considering local contexts, technological infrastructure, and socio-economic conditions when formulating policy interventions. Specifically, our examination of electronic financial transactions underscores the persistent challenges posed by cross-border activities, decentralized systems, and cybersecurity threats. The increasing reliance on complex algorithms and data-driven decision-making in FinTech necessitates a renewed focus on transparency, accountability, and ethical considerations. The study findings suggest that effective regulatory frameworks must strike a delicate balance between fostering innovation and safeguarding financial stability, protecting consumers from potential harms, and promoting fair competition in the market. These frameworks should embrace a principles-based approach that allows for flexibility and adaptability, enabling them to keep pace with the rapidly evolving technological landscape. Furthermore, international cooperation is essential to address the cross-border challenges inherent in FinTech and to prevent regulatory arbitrage. The research highlights the crucial role of RegTech in enhancing regulatory compliance and risk management within the FinTech ecosystem. Investing in technological solutions that automate regulatory processes and improve data collection and analysis can significantly improve the efficiency and effectiveness of regulatory oversight. Additionally, fostering a culture of collaboration between regulators, industry stakeholders, and technology providers is essential to developing innovative RegTech solutions that meet the evolving needs of the financial sector. Ultimately, this study contributes to a more nuanced understanding of the transformative potential and inherent challenges of FinTech and AI in shaping the future of finance. The insights gleaned from this research have significant implications for policymakers, industry practitioners, and academics alike. By providing a robust empirical analysis and actionable recommendations, this work aims to inform the development of evidence-based policies that promote responsible innovation, enhance financial inclusion, and ensure the long-term stability and resilience of the global financial system. Future research should focus on evaluating the effectiveness of different regulatory approaches in promoting FinTech innovation while mitigating risks and exploring the ethical dimensions of AI in finance. Further, there is a need for longitudinal studies that track the long-term impacts of FinTech on financial stability, consumer welfare, and market competition. Only through a continued commitment to rigorous research and informed policymaking can we harness the full potential of FinTech to create a more inclusive, efficient, and resilient financial system for all. Bibliography: Arner, D. W., Barberis, J., Buckley, R. P. (2016). FinTech, RegTech, and the reconceptualization of financial regulation. Northwestern Journal of International Law & Business, 37; Bank for International Settlements. (2019). BigTech in finance: opportunities and risks; Bank for International Settlements. (2021). Fintech regulation: how to achieve a level playing field; Barefoot, J. A. (2020). The Future of Financial Regulation: The US Financial Innovation Bill. Journal of Financial Regulation and Compliance, 28 (3); Bouveret, A. (2018). Cyber risk for the financial sector: A framework for quantitative assessment. IMF Working Paper, 18(143); Brummer, C., Yadav, Y. (2019). Fintech and the innovation trilemma. Georgetown Law Journal, 107(2); Chen, Y., Bellavitis, C. (2020). Blockchain disruption and decentralized finance: The rise of decentralized business models. Journal of Business Venturing Insights, 13, e00151; Dahlberg, T., Guo, J., Ondrus, J. (2015). A critical review of mobile payment research. Electronic Commerce Research and Applications, 14 (5); (2021). RegTech Universe 2021; Donnelly, M. (2016). Payments in the digital market: Evaluating the contribution of Payment Services Directive II. Computer Law & Security Review, 32 (6); Eling, M., Lehmann, M. (2018). The impact of digitalization on the insurance value chain and the insurability of risks. The Geneva Papers on Risk and Insurance-Issues and Practice, 43 (3); (2019). EY Global FinTech Adoption Index 2019. Available at: <https://www.ey.com>; Feyen, E., Frost, J., Gambacorta, L., Natarajan, H. (2021). FinTech and the digital transformation of financial services: Implications for market structure and public policy; Financial Action Task Force. (2019). Guidance for a risk-based approach to virtual assets and virtual asset service providers. FATF, Paris; Financial Conduct Authority UK. (2015). Regulatory Sandbox; Financial Stability Board. (2019). FinTech and market structure in financial services; Financial Stability Board. (2022). FinTech and Market Structure in the COVID-19 Pandemic; Houben, R., Snyers, A. (2018). Cryptocurrencies and blockchain: Legal context and implications for financial crime, money laundering and tax evasion. European Parliament’s Special Committee on Financial Crimes, Tax Evasion and Tax Avoidance; (2021). Cost of a Data Breach Report; International Monetary Fund. (2021). The Rise of Digital Money; Jenik, I., Lauer, K. (2017). Regulatory sandboxes and financial inclusion. Washington, DC: CGAP; Jung, D., Dorner, V., Weinhardt, C., Pusmaz, H. (2018). Designing a robo-advisor for risk-averse, low-budget consumers. Electronic Markets, 28 (3); Knight Capital Group incident: SEC. (2013). Administrative Proceeding File No. 3-15570; Lee, I., Shin, Y. J. (2018). Fintech: Ecosystem, business models, investment decisions, and challenges. Business Horizons, 61 (1); Mbama, C. I., Ezepue, P. O. (2018). Digital banking, customer experience and bank financial performance: UK customers’ perceptions. International Journal of Bank Marketing, 36 (2); Monehin, O., Okeke, J., Aina, O. (2022). Cross-border fintech regulation and regulatory challenges. Journal of Financial Regulation and Compliance, 30(1); (2018). G20/OECD Policy Guidance on Financial Consumer Protection Approaches in the Digital Age; Ozili, P. K. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4); Thakor, A. V. (2020). Fintech and banking: What do we know? Journal of Financial Intermediation, 41, 100833; World Bank Group. (2020). Global Experiences from Regulatory Sandboxes; Zetzsche, D. A., Preiner, C. (2018). Cross-Border Crowdfunding: Towards a Single Crowdlending and Crowdinvesting Market for Europe. European Business Organization Law Review, 19 (2); Zetzsche, D. A., Buckley, R. P., Arner, D. W., Barberis, J. N. (2017). From FinTech to TechFin: The regulatory challenges of data-driven finance. New York University Journal of Law and Business, 14(2). Footnotes [1] Mbama, C. I., Ezepue, P. O. (2018). Digital banking, customer experience and bank financial performance: UK customers’ perceptions. International Journal of Bank Marketing, 36 (2), pp. 230-255. [2] Ibid. [3] Ibid. [4] Dahlberg, T., Guo, J., Ondrus, J. (2015). A critical review of mobile payment research. Electronic Commerce Research and Applications, 14 (5), pp. 265-284. [5] EY. (2019). EY Global FinTech Adoption Index 2019. Available at: <https://www.ey.com>. [6] Dahlberg, T., Guo, J., Ondrus, J. (2015). A critical review of mobile payment research. Electronic Commerce Research and Applications, 14 (5), pp. 265-284. [7] Jung, D., Dorner, V., Weinhardt, C., Pusmaz, H. (2018). Designing a robo-advisor for risk-averse, low-budget consumers. Electronic Markets, 28 (3), pp. 367-380. [8] Eling, M., Lehmann, M. (2018). The impact of digitalization on the insurance value chain and the insurability of risks. The Geneva Papers on Risk and Insurance-Issues and Practice, 43 (3), pp. 359-396. [9] Thakor, A. V. (2020). Fintech and banking: What do we know? Journal of Financial Intermediation, 41, 100833. [10] Donnelly, M. (2016). Payments in the digital market: Evaluating the contribution of Payment Services Directive II. Computer Law & Security Review, 32 (6), pp. 827-839. [11] Jenik, I., Lauer, K. (2017). Regulatory sandboxes and financial inclusion. Washington, DC: CGAP. [12] Houben, R., Snyers, A. (2018). Cryptocurrencies and blockchain: Legal context and implications for financial crime, money laundering and tax evasion. European Parliament’s Special Committee on Financial Crimes, Tax Evasion and Tax Avoidance. [13] Barefoot, J. A. (2020). The Future of Financial Regulation: The US Financial Innovation Bill. Journal of Financial Regulation and Compliance, 28 (3), pp. 381-395. [14] Zetzsche, D. A., Preiner, C. (2018). Cross-Border Crowdfunding: Towards a Single Crowdlending and Crowdinvesting Market for Europe. European Business Organization Law Review, 19 (2), pp. 217-251. [15] Arner, D. W., Barberis, J., Buckley, R. P. (2016). FinTech, RegTech, and the reconceptualization of financial regulation. Northwestern Journal of International Law & Business, 37, p. 371. [16] Monehin, O., Okeke, J., Aina, O. (2022). Cross-border fintech regulation and regulatory challenges. Journal of Financial Regulation and Compliance, 30(1), pp. 101-118. [17] Chen, Y., Bellavitis, C. (2020). Blockchain disruption and decentralized finance: The rise of decentralized business models. Journal of Business Venturing Insights, 13, e00151. [18] Bouveret, A. (2018). Cyber risk for the financial sector: A framework for quantitative assessment. IMF Working Paper, 18(143). [19] Financial Action Task Force. (2019). Guidance for a risk-based approach to virtual assets and virtual asset service providers. FATF, Paris. [20] Arner, D. W., Barberis, J., Buckley, R. P. (2016). FinTech, RegTech, and the reconceptualization of financial regulation. Northwestern Journal of International Law & Business, 37, p. 371. [21] Ozili, P. K. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4), pp. 329-340. [22] Zetzsche, D. A., Buckley, R. P., Arner, D. W., Barberis, J. N. (2017). From FinTech to TechFin: The regulatory challenges of data-driven finance. New York University Journal of Law and Business, 14(2), pp. 393-446. [23] Brummer, C., Yadav, Y. (2019). Fintech and the innovation trilemma. Georgetown Law Journal, 107(2), pp. 235-307. [24] Knight Capital Group incident: SEC. (2013). Administrative Proceeding File No. 3-15570. [25] IBM. (2021). Cost of a Data Breach Report. [26] Bank for International Settlements. (2019). BigTech in finance: opportunities and risks. [27] International Monetary Fund. (2021). The Rise of Digital Money. [28] World Bank Group. (2020). Global Experiences from Regulatory Sandboxes. [29] Financial Conduct Authority UK. (2015). Regulatory Sandbox. [30] OECD. (2018). G20/OECD Policy Guidance on Financial Consumer Protection Approaches in the Digital Age. [31] Financial Stability Board. (2019). FinTech and market structure in financial services. [32] Bank for International Settlements. (2021). Fintech regulation: how to achieve a level playing field. [33] Deloitte. (2021). RegTech Universe 2021.
The Mediating Role of Organizational Commitment between Organizational Justice and Job Performance
The purpose of this study is to assess the mediating role of organizational commitment (OC) between organizational justice (OJ) and job performance (JP). The data was collected from 281 employees using a questionnaire approach. The data analysis used Smarts PLS for assessing the measurement and structure models. The results indicated that organizational commitment mediated the relationship between organizational justice and job performance. The results also showed that OJ has a significant impact on OC and JP, and OC significantly impacts JP. Managers must be familiar with the essential rules to improve job performance, organizational commitment, and organizational justice while also considering proper conduct. Furthermore, the necessary facilities for promoting professional advancement and training should be established to bolster banks’ current and future demands. The paper elucidates the conclusions and their limitations while also proposing avenues for further research. This study enhances the theoretical framework within organizational theory, organizational behavior, and psychological research, particularly concerning the Iraqi banking sector. However, the study advises banking industry managers to provide fairness and justice in the evaluation processes to improve employee commitment. Keywords: Organizational commitment, organizational justice, job performance, banks. Introduction Unlike in previous eras, human resources are perceived as essential to business efficiency.[1] In the past few years, academicians have debated the strategic significance of human resources (HR) in a world that is dominated by intellectual capital. The new narrative contradicts several study findings indicating that businesses frequently substitute human resources with alternative elements of production when expedient.[2] In most instances, human resources are perceived as a cost that should be reduced, particularly during challenging periods.[3] However, emerging trends provide some encouraging indications that a significant portion of this is undergoing rapid change. HR has transitioned from a cost center to a profit center. In specific sectors, such as technology, banking, services, and knowledge-based work systems, it is the sole primary resource, with others considered secondary.[4] The resource-based perspective posits that the organization’s strategic value is significantly influenced by its knowledge, skills, and abilities, making it unique.[5] Nowadays, organizations consider human resources essential for their continued operation. Consequently, they value their perceptions highly and respect their opinions.[6] Consequently, addressing the factors potentially affecting employees’ perceptions is essential. OJ and OC are two examples of such factors. OJ refers to individuals’ views of fairness in their treatment inside an organization. It is often examined to determine its impact on elements influencing organizational performance, such as OC.[7] Practitioners and scholars have paid more attention to the concept of justice and process in the workplace. The Staff will express their appreciation when they feel fairness exists in their workplace. HR managers are mainly concerned with the perception of justice, impartial organizational processes, and process impartiality.[8] It is frequently held that securing fair procedures within organizational justice frameworks can enhance employee commitment, productivity, and performance.[9] High job performance is predicated on equitable organizational practices, which include essential elements such as distributive, procedural, and interactional justice.[10] This study defines organizational justice as fair job duties at all organizational levels that are acceptable to all individuals. Employees may perceive these behaviors in terms of equity and organizational justice. Consequently, this study examines organizational justice as a critical prerequisite to assessing its influence on OC. Several studies have extensively examined organizational commitment.[11],[12] The extensive literature on organizational commitment indicates that it can lead to positive results for both employees and the organizations, including enhanced job performance, productivity, and commitment.[13],[14],[15] Consequently, organizations must prioritize organizational commitment as a significant individual concern, as it results in favorable outcomes in the workplace. However, several previous studies examined the Affective organizational commitment, such as,[16],[17],[18] and limited studies examined the overall organizational commitment,[19] particularly in Iraq. The purpose of this study is to find the impact of OJ on JP and the mediating role of OC. 1. Literature Review 1.1. Social exchange theory “Social exchange theory”, proposed by Blau in 1964,[20] offers a broad conceptual framework that justice researchers utilize to clarify the influence of individuals’ understanding of justice on JP, commitment, and other results at work. The concept of social exchange perception, initially formulated by Gouldner (1960)[21] and Blau (1964),[22] is the dominant framework used to elucidate the interactions between an organization and its staff. Wayne et al. (2002),[23] establish that workers’ favorable emotions are contingent upon their assessment of the company’s level of investment in them. This concept aligns with the principles of social exchange theory, which posits that exchanges are based on voluntary behaviors rather than formal contracts, in contrast to economic exchanges.[24] Gouldner (1960)[25] defines social exchange as a form of mutually satisfying interaction between both parties, characterized by the development of reciprocal behavior guided by a widely accepted moral standard. In this form of reciprocity, the exchange of reciprocal advantages, namely psychological benefits, helps to uphold a stable social order.[26] Put simply, when an organization shows kindness towards an employee, it develops a sense of duty for the worker to reciprocate with a positive action.[27],[28] Greenberg (1990)[29] suggests that justice can explain several organizational characteristics, such as attitudes and behavior. Within the corporate setting, justice is seen as a significant catalyst for trade or reciprocity. The employee’s thoughts of justice directly influence the quality of the link between them and the workplace. Based on the principles of reciprocity, individuals see the way they are viewed by other social entities as either positive or negative.[30] The “Social exchange theory” posits that by fulfilling individual’s emotional and social needs, organizations may enhance individual commitment to the organization’s purposes, hence resulting in improved job performance.[31] 1.2 Organizational justice “Organizational justice” refers to workers’ subjective evaluation of the fairness of their treatment inside the workplace. It is commonly investigated to determine its impact on other aspects that influence organizational performance, such as “organizational commitment and job satisfaction”.[32] According to Greenberg (2001),[33] justice in the workplace is related to positive and negative individual behaviours. Individuals assess the level of fairness in the operations and gains of organizations based on the effort they put in.[34] Within organizations, people regularly compare and evaluate themselves in relation to their colleagues. Therefore, the attitudes of these employees are formed based on their opinions of justice.[35],[36] Organizational justice is the beliefs and behaviors that determine whether individuals feel they have been treated fairly and equitably in terms of rewards in their employment. It also involves examining how these perceptions affect other results.[37] According to scholars Greenberg and Colquitt (2013),[38] when an employer treats its staff members fairly and is seen as fair by staff members, it increases the possibility of staff engaging in productive conduct that ultimately benefits the workplace. “Equity theory”[39] and “Social Exchange Theory (SET)” (Blau, 1964)[40] propose that individuals evaluate the worth of their association with an organization, taking into account the difficulties and advantages involved. This evaluation is influenced by the pay that they get from their job. There are different perspectives on the dimensions of organizational justice. Some argue that it has three types (“distributive, procedural and interactional”),[41] while others, such as Bies (2001)[42] and Colquitt (2001),[43] propose a fourth dimension called informational justice. Distributive justice is the subjective assessment of resource allocation by individuals in relation to their anticipated contributions and the outcomes they receive.[44] Procedural justice is the concept of fairness that staff members perceive in accordance with the workplace policies and procedures.[45] Interactional justice is the term used to describe the degree of equity that staff members perceive in their interpersonal interactions within the workplace.[46] Also, there is no broad agreement regarding organizational justice as a holistic or multidimensional construct. Previous studies examined organizational justice as a holistic construct,[47],[48],[49],[50],[51] based on the fairness heuristic theory, people in the workplace attend to overall justice besides the dimensions of justice.[52] Aryee et al. (2015)[53] maintained that justice could describe “the depth and richness” of individuals’ holistic justice experiences, which kinds of justice may not fully represent. They discovered that justice positively correlates with satisfaction and trust in the workplace. Jones and Martens (2009)[54] identified that justice is distinct from four categories of organizational justice “(distributive, procedural, interpersonal, and informational)” and is closely associated with emotional and organizational commitment. In conclusion, there is no consensus on whether justice is a multi-faceted or holistic concept. This paper’s premise is based on an adaptation of the justice heuristic theory argument by Lind (2001)[55] and Ambrose and Schminke (2009).[56] According to this theory, people’s perceptions of OJ are based on four different kinds of justice, and how people act and think is more important than any one kind of justice in shaping their overall perceptions of justice. So, rather than concentrating on specific forms of organizational justice, this paper explores how individuals perceive justice in general. 1.3 Organizational commitment Employee commitment is often seen as a crucial determinant of organizational productivity and performance.[57] O’Reilly and Chatman (1986)[58] indicated that OC constitutes a psychological connection or relationship between a person and the organization. Allen and Meyer (1996)[59] define OC as the psychological bond the staff members have towards an organization, which minimizes their inclination to leave the workplace. Organizational commitment, similar to organizational justice, is built on the social exchange theory, wherein staff members reciprocate favourable experiences from the organization.[60] Employees with a high degree of commitment will probably remain, maintain their association, and support the organization in attaining its objectives.[61] The term of OC has been associated with several characteristics within an organizational context, including OJ,[62] leadership.[63] Organizational commitment pertains to the loyalty of individuals towards their organizations. OC relies on the assessment of an individual’s perception of the quality of psychological contracts.[64] Organizational commitment consists of three main elements: “affective commitment, normative commitment, and continuance commitment”.[65] Affective commitment pertains to an organizational member’s emotional tie to the organization, namely the degree to which they desire membership and align with its objectives.[66] Normative commitment pertains to a member’s sense of moral responsibility to the organization, specifically the degree to which they believe they should remain affiliated.[67] Continuance commitment: pertains to the expenses associated with departing from the organization, encompassing the loss of perceived advantages and the challenges of securing an alternative job.[68] Several previous studies measured the OC as a single construct, such as.[69],[70],[71] 1.4 Job performance Job performance is a metric utilized in research within occupational environments.[72] Several kinds of research across disciplines, such as HRM, the health area, and industrial-organizational psychology, have investigated the determinants and consequences of employee JP. Job performance is a critical determinant in an organization that motivates all operations towards attaining organizational objectives.[73],[74] Subsequently, studies determined the concept of job performance to comprehend its intrinsic structure,[75] shifting from the prior emphasis on task performance or the adeptness with which individuals in the workplace execute fundamental or technical duties.[76] Research has established that job performance includes not just task performance but also surroundings and counterproductive work behaviour.[77],[78] Performance in the context refers to actions that facilitate achieving an organization’s social, psychological, and organizational objectives within which the technological core operates.[79] The income, career opportunities, psychological requirements, and well-being of individuals are significantly influenced by their job performance.[80] According to Guo et al. (2016),[81] there is a correlation between employees’ levels of alienation and the variety of jobs assigned to them, as well as the social behavior and culture of the business. 1.5 The impact of organizational justice on Job performance “Organizational justice” has been recognized as a crucial element in driving employee motivation and, thus, may play a significant role in establishing a competitive advantage within the service sector. Research indicates that the lack of justice within an organization may lead to detrimental consequences such as employee fatigue, the expression of negative emotions, inappropriate behavior, and poor performance.[82] Research indicates that a lack of organizational justice in the workplace can lead to undesirable outcomes such as fatigue and an increase in negative emotions and behaviors among employees, including poor performance.[83] Organizational justice is a critical feature inside organizations that significantly influences JP.[84] Various prior research studies have been undertaken to examine the impact of OJ on performance.[85],[86],[87],[88] Their study findings established that organizational justice exerts a substantial impact on performance. According to Suliman’s and Kathairi’s (2013)[89] study, it was shown that organizational justice does not have a substantial impact on employee performance. Additionally, people in the firm do not see justice as a determining factor for their performance. H1: OJ has a significant Impact on JP among bank employees. 1.6 The impact of organizational justice on organizational commitment One of the extensively studied linkages in management literature is the link between organizational justice and organizational commitment within the framework of social exchange theories. Based on SET, the norm of reciprocity suggests that employees are likely to respond to excellent or fair treatment from the organization or its management by demonstrating commitment to the organization.[90] OJ and OC are strongly interconnected and are often seen as indications of a social interaction.[91] Research on organizational justice often aims to determine its effects on other performance-influencing variables, such as employee commitment and work satisfaction, and staff members of the fairness of their treatment inside the organization.[92] It has been recognized as a crucial element in incentivizing individuals to succeed.[93] It may, therefore, be essential in establishing a competitive advantage in the field of service.[94] Consistent with this approach, research has generally shown that there is a positive relationship between organizational justice and organizational commitment.[95],[96],[97] H2: OJ has a significant Impact on OC among bank employees. 1.7 The impact of organizational commitment on Job Performance Organizational commitment enhances operations by influencing the work performance of individuals in different sectors.[98] Organizational commitment is a crucial aspect in improving workers’ performance to deliver optimal service in accordance with customers’ needs.[99],[100] Organizational commitment enhances organizations by influencing employees’ job performance at all levels in the finance, insurance, and health sectors.[101],[102] Arasanmi and Krishna (2019)[103] identified organizational commitment as key to increasing staff performance. Considering the fact that employee commitment to the organization correlates with job performance. Researchers have utilized several approaches to demonstrate a relationship between organizational commitment and job performance.[104],[105] Previous research has indicated a negative impact of organizational commitment on job performance.[106],[107] H3: OC has a significant Impact on OC among bank employees. 1.8 The mediating role of organizational commitment Individuals who consider decision-making procedures as unjust are anticipated to exhibit diminished organizational commitment and a decrease in their involvement in OC.[108] Organizational commitment mediates the relationship between the work environment and employee retention.[109] According to Swalhi et al. (2017),[110] effective commitment mediated the relationship between organizational justice and work performance among the SMEs. Organizational commitment was examined as a mediator between workplace spirituality and organizational performance, and the result reported that organizational commitment can play an important role as a mediator in the context of several industrial sectors in India.[111] a study conducted among hotel employees and choosing organizational commitment as a mediator between training and development, career development, and work performance, the findings showed organizational commitment significantly mediated the relationship among the mentioned variables.[112] H4: OC mediates the relationship between OJ and JP among bank employees. Figure 1. The conceptual model 2. Methodology The study deployed the cross-sectional survey approach to examine the proposed hypotheses. The purpose of this work is to examine the mediating role of OC between OJ and JP in the context of the bank sector. The target population of this study is the employees of private banks located in the capital city of Iraq. Employees from five private banks represented the study sample; before beginning to collect the data, the researcher explained to the human resource department in each bank the purpose of this study and asked them for permission to collect the data. The study used a quantitative approach to collect data from private banks, using a self-administered questionnaire. The bank’s employees from different levels, such as managers, admins of the system and database, network officers, and information security officers, participants in this study. 281 valid questionnaires were analyzed in this study using SPSS and Smart-PLS, which is considered a premier software package for “partial least squares structural equation modeling” (PLS-SEM).[113] PLS-SEM, which emphasizes data prediction and is well-suited for explanatory models, is excellent for investigations that attempt to predict and elucidate outcome constructs.[114] It is also observed that PLS-SEM can be utilized to evaluate causal relationships in investigations characterized by limited sample sizes and insufficient theoretical backing. According to Herath and Rao (2009),[115] using validated instruments from previous work ensures the reliability of findings. The current study adapted the research items from earlier work to enhance the reliability of the results and reduce the issues related to reliability and validity. Table 1 shows the number of items and sources of each factor. The questionnaire was sent to four experts in the fields of business administration, human resources, and organization theory to assess its structure and questions; based on the experts’ feedback, some items have been reworded and modified. The questionnaire used a five-point Likert scale from “1 (strongly disagree) to 5 (strongly agree)”. Table 1. Instruments sources 3. Results The demographic information depicted in Table 2 shows that the majority of employees are men, 73%, and 27% are women, and this reflects the culture of the Governorate. Most of the employees were between 36 and 45 years old, 51%. Most of the employees hold bachelor’s degrees (75%), and working experience shows that most of the employees have between 5 to 10 years of experience (42%). Close to this, 32% have between 11 and 15 years of experience. Table 2 shows all the demographic information in detail. Table 2. Demographic information The data analyzed by Smart-PLS in this software should be conducted in two main runs. The first one should be a measurement model to examine reliability, validity, and convergent validity. The outer loading is the first indicator assessed to measure the model’s validity. Hair et al. (2019),[116] indicated that the values of each loading should be 0.708 and above are recommended. The results are shown in Table 3 and Figure 2. All the loadings above 0.708, except JP3, JP4, OC4, and OJ1, were lower than 0.70 and thus removed from the model to enhance the model’s validity. The reliability is assessed by Cronbach’s alpha and “Composite reliability” (CR) to confirm the internal consistency of each factor. The values should be 0.70 and above (Hair et al., 2019).[117] The values, as shown in Table 3, are all above the recommended value; thus, the model is reliable. The “Average variance extracted” (AVE) is assessed to examine the variance of factor items. The recommended AVE is 0.50 and above, which means that at least the factor explains 50 per cent of the variance, and it is the items. The value of each factor shown in Table 3 is between 0.604 OJ and 0.713 JP; thus, there is no issue with convergent validity. Table 3. Validity and reliability Discriminant validity The purpose of this step is to measure how empirically each factor is different from another factor in the proposed model. Fornell and Larcker (1981)[118] according to this criterion, each factor AVE should correlate with the same factor higher than another factor. Table 4 shows that each factor correlated with itself higher than others in columns and rows, with the value highlighted in bold font. Table 4. Fornell-Larcker criterion Note: OJ: Organizational justice; JP: Job performance; OC: Organizational commitment Henseler et al. (2015)[119] criticism of the previous methods and replacement with “heterotrait-monotrait” (HTMT) indicated if the HTMT value should be less than 0.9 and if the value is higher than 0.9, there is an issue in discriminant validity based on Table 5, all the HTMT values above 0.9, thus no issue in model discriminant. Table 5. HTMT Note: OJ: Organizational justice; JP: Job performance; OC: Organizational commitment Figure 2. Measurement model The second main step after assessing the measurement model is to use structural models to examine the proposed hypotheses. The first criterion in this step is to determine the collinearity of the model to ensure there are no biased results in the proposed model by VIF, According to Hair et al. (2019),[120] if the VIF values are above 5, this indicates there are issues in the collinearity among the model factors and the best value of VIF 3 and lower according to Table 6 all the VIF values between 1.662 OJ7 and OC5 3.713 which are less than 5 and most of the VIF value close to 3 and lower thus, there is no issue in model collinearity. Table 6. VIF After ensuring there are no issues in the model collinearity, the next step is to assess the coefficient of determination (R2) to measure the variance between the independent variables (IV) and dependent variable (DV) and examine the proposed model’s explanatory power. According to Hair et al. (2019),[121] the R2 values between 0.50 and 0.75 are moderate based on Figure 2 and Figure 3. The R2 of the current model is 0.628; thus, the R2 explains 62% between the IV and DV. The next criterion is to find the effect size F2 to measure the level of the IV’s effect on DV. According to Cohen (1988),[122] if the F2 is above 0.35, the effect is large; if it is between 0.15 and 0.35, the effect is medium; when the F2 is between 0.02 and 0.15, it is small; and if it is less than 0.02, there is no effect. Based on Table 7, the effect size of OC on JP and OJ on OC is 0.760 and 0.524, respectively, large, and the effect size of OJ on JP is 0.072, which is small. Table 7. Effect size (F2) Note: OJ: Organizational Justice; JP: Job Performance; OC: Organizational commitment The main analysis was run by bootstrapping with a 50000 subsample as recommended by Hair et al. (2019)[123] to reduce the error; the hypothesis results are reported in Table 8 and depicted in Figure 2. The direct effect proposed three hypotheses. All the proposed direct effect hypotheses are supported due to the T-statistics >1.96 and the P-value <0.05. The results indicate that OJ has a positive and significant impact on JP and OC. The p-value is 0.07 and 0.00 <0.05, respectively, and the T-statistics are 2.707 and 10.433 >1.96; thus, H1 and H2 are supported. Similarly, OC has a significant impact on JP with the p-value of 0.00 and the < 0.05 and the 9.312 >1.96; therefore, H3 was supported. The indirect effect showed that OC mediated the relationship between OJ and JP, with a p-value of 0.00 >0.05 and T-statistics of 6.534 >1.96; thus, H4 was supported. Table 8. Hypotheses results Note: OJ: Organizational Justice; JP: Job Performance; OC: Organizational commitment Figure 3. Structural model 4. Discussion Dedication is usually inherent among employees in a job. The HR occasionally seeks to assess commitment. The HR typically assesses aspects including motivation, organizational procedures and policies, work environment, and superior-subordinate interactions, while the current study measured the mediating role of OC between the OJ and JP in the context of Iraq. The current study reported that OJ significantly increased the JP; this result is in line with several previous studies’ results.[124],[125],[126] Organizational justice has a pivotal role in management directives. This indicates that for leaders to effectively realize their goal of exceeding performance standards, it is crucial to cultivate and maintain an objective perception of fairness in workplace processes and treatment among organizational members. This implies that firm personnel must be prepared to exert additional effort to attain the organization’s objectives, provided they cultivate and maintain a long-term perspective. Organizational justice can impact performance; hence, managers’ non-discriminatory attitudes in communication and interaction with employees can enhance work performance. The findings suggest that perceptions of justice influence employees’ propensity to reciprocate with enhanced performance and increased organizational commitment. According to the results presented here, individuals in Iraq place a higher value on the justice they receive from their supervisors and organizational representatives during processes and decision-making. According to the findings, the most important factors in recruiting high-performing and committed workers in Iraq are support, dignity, respect, and honesty. OJ shown in this study, significantly improved the OC; similar findings were reported in previous research.[127],[128],[129] The results indicate that respondents saw justice as a crucial element of organizational commitment. Ensuring that awards are equitable and transparent enhances the reputation of the business and its executives. A primary cause of discontent in many firms is employees’ perception of inequitable compensation allocation. The perception of equitable procedures reinforces the concept of just organizational practices and value systems. The foundational work suggests that managers should include adequate objectivity in rewards, potentially minimizing managerial discretion to secure employee commitment. This means the employees who recognized higher levels of justice in the workplace were more inclined to indicate increased levels of commitment. When employees see the justice for promotion, salary augmentation, transfer, termination, reward, and punishment as equitable, they are more inclined to willingly accept the judgments, regardless of whether the outcomes are advantageous. Employees who cultivate robust connections with the organization exhibit heightened commitment and concurrently get satisfaction from their profession. OC has a significant effect on JP. This result is consistent with previous results.[130],[131] The results indicate that employees committed to their organizations demonstrate conduct that benefits the organization. Consequently, ensuring that individuals inside organizations experience a sense of devotion to the organization is essential. This fosters a sense of belonging among employees, motivating them to enhance the organization’s market position. Given that the organization’s greatest asset is its personnel, any actions taken by them for the organization’s advantage would improve its worth. The study suggests that Banks in Iraq should enhance employee commitment. When employees are committed, their performance will improve and increase. The managers must cultivate a culture of good connections in the workplace to increase employee commitment. This will encourage employees’ emotional commitment to their workplace, hence improving their inventive problem-solving capabilities. The findings indicated a substantial mediating effect of organizational commitment on the connection between organizational justice and job performance among bank staff. The findings of this study are aligned with those of prior research[132],[133],[134] who reported similar findings. This study strengthens the legitimacy of prevalent ideas and certain academic results that employee commitment significantly promotes voluntary activities and fosters good perceptions of organizational justice and performance.[135],[136] Consequently, workplace decision-makers seeking to encourage pro-organizational behaviors among workers should provide cognitive and organizational resources to enhance employee commitment to their positions. 5. Theoretical Contributions and Practical Implications This study enhances the theoretical framework within HR, organizational behavior, and psychological research, particularly concerning the Iraqi banking sector. The banking industry in Iraq has a significant power gap, characterized by hierarchical organizational structures where authority is predominantly concentrated in the higher echelons. Employees advocate for justice from the upper echelons to the lower levels. Furthermore, incorporating fairness and equality into performance processes within the banking sector is essential for fostering contented and dedicated bank employees and facilitating favorable banking results. This study investigates the mediating role of organizational commitment in the relationship between organizational justice and job performance, contributing significantly to the literature on performance and organizational justice within a unique environment. The study advises banking industry managers to provide fairness and justice in the evaluation processes to improve employee commitment. To accomplish this, managers should provide sufficient knowledge of the methods and procedures of work performance exercises, enabling employees to comprehend and feel committed to their roles. During the assessment of job performance, the managers or leaders should pay attention to the employee’s respect and dignity; they should ensure justice and equity during the assessment of job performance. Managers must ensure equitable distribution of performance assessment results to foster a sense of responsibility among employees and encourage them to commit more diligently to the bank’s best interests. 6. Limitations and Future Recommendations The study has several limitations; nonetheless, it also offers recommendations for future research endeavors. The present study was conducted within Iraq’s banking sector, raising concerns regarding generalizability. Consequently, the findings cannot be extrapolated to other sectors. However, this study was performed in the banking industry; thus, the same approach may be utilized in many industries to assess the influence of relationships. Nevertheless, the inclusion of personnel from many industries reveals emerging patterns. The present study examined the influence of organizational commitment as a mediating variable; however, other pertinent aspects, such as organizational citizenship behavior, may affect the link between organizational justice and job performance. It will be intriguing to examine the link using various intervening factors. Conclusion This study’s findings provide new perspectives into the interaction between individuals and the workplace, highlighting the roles of justice views, commitments, and performance. The results of the current study and other empirical research confirmed that a high level of justice and commitment leads to an effective strategy for managers to improve job performance and competitive standing. Consequently, the current results reinforce most of the previous work’s conclusion that organizational justice significantly influences individual commitment and performance. 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Footnotes [1] Jehanzeb, K., Mohanty, J. (2019). The mediating role of organizational commitment between organizational justice and organizational citizenship behavior. Personnel Review, 49(2), pp. 445–468. [2] Snell, S. A., Shadur, M. A., Wright, P. M. (2005). Human Resources Strategy. In The Blackwell Handbook of Strategic Management, Wiley, pp. 631–653. [3] Gill, C. (2018). Don’t know, don’t care: An exploration of evidence based knowledge and practice in human resource management. Human Resource Management Review, 28(2), pp. 103–115. [4] Jehanzeb, K., Mohanty, J. (2019). The mediating role of organizational commitment between organizational justice and organizational citizenship behavior. Personnel Review, 49(2), pp. 445–468. [5] Boon, C., Boselie, J. P., Dietz, G. (2005). Commonalities and contradictions in research on human resource management and performance. Human Resource Management, 15(3), pp. 67–94. [6] Salam, A. (2020). Organizational justice as a predictor of organizational citizenship behaviour. International Business Education Journal, 13, pp. 29–42. [7] Cohen-Charash, Y., Spector, P. E. (2001). The role of justice in organizations: A meta-analysis. Organizational Behavior and Human Decision Processes, 86(2), pp. 278–321. [8] Salam, A. (2020). Organizational justice as a predictor of organizational citizenship behaviour. International Business Education Journal, 13, 29–42. [9] Ibid. [10] Greenberg, J., Colquitt, J. A. (2013). Handbook of organizational justice. Psychology Press. [11] Allen, N. J., Meyer, J. P. (1996). Affective, continuance, and normative commitment to the organization: An examination of construct validity. Journal of Vocational Behavior, 49(3), pp. 252-276. [12] Meyer, J. P., Smith, C. A. (2000). HRM Practices and Organizational Commitment: Test of a Mediation Model. Canadian Journal of Administrative Sciences / Revue Canadienne Des Sciences de l’Administration, 17(4), pp. 319–331. [13] Jameel, A. S., Mahmood, Y. N., Jwmaa, S. J. (2020). Organizational Justice and Organizational Commitment among Secondary School teachers. Cihan University-Erbil Journal of Humanities and Social Sciences, 4(1), pp. 1–6. Available: <https://doi.org/10.24086/cuejhss.vol4n1y2020.pp1-6c>. [14] Meyer, J. P., Allen, N. J. (1997). Commitment in the workplace: Theory, research, and application. Sage. [15] Ohana, M., Meyer, M. (2016). Distributive justice and affective commitment in nonprofit organizations. Employee Relations, 38(6), pp. 841–858. [16] Jiang, Z. (2015). The relationship between justice and commitment: the moderation of trust. Asia-Pacific Journal of Business Administration, 7(1), pp. 73–88. [17] Kim, S. H., Laffranchini, G., Jeung, W. (2018). 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