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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). 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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. 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The effects of fiscal policy on economic growth in Algeria [Unpublished Ph.D. thesis, University of Maghnia-Tlemcen]; Kryeziu, A. (2016). The impact of macroeconomic factors on economic growth. European Scientific Journal, 12(7); 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); 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; 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); 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); 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. Future research will expand the sample, use a longitudinal approach, and explore additional factors like personality and external stressors, possibly incorporating qualitative methods. Competing Interests The author(s) has/have no competing interests to declare. References: 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). <doi.org/10.56734/ijahss.v5n4a3>; Conger, R. D., Conger, K. J., Martin, M. J. (2010). Socioeconomic status, family processes, and individual development. Journal of Marriage and Family, 72(3). <https://onlinelibrary.wiley.com/doi/10.1111/j.1741-3737.2010.00725.x>; Crouter, A. C., Booth, A. (2003). Children’s influence on family dynamics: The neglected side of family relationships. Mahwah, NJ: Lawrence Erlbaum Associates Publishers; Cummings, E. M., Taylor, L. K., Merrilees, C. E. (2020). 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Marital processes predictive of later dissolution: Behavior, physiology, and health. Journal of Personality and Social Psychology, 63(2). <doi.org/10.1037/0022-3514.63.2.221>; Kamo, Y. (1993). Determinants of marital satisfaction: A comparison of the United States and Japan. Journal of Social and Personal Relationships, 10(4). <doi.org/10.1177/0265407593104005>; 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). <doi.org/10.52534/msu-pp4.2023.57>; 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>; Markus, H. R., Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. 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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>; Taylor, Z. E., Conger, R. D. (2017). Promoting strengths and resilience in single-mother families. Child Development Perspectives, 11(2). <doi.org/10.1111/cdev.12741>; 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). <doi.org/10.1111/bjep.12551>; Thomas, K. W., Kilmann, R. H. (1974). Thomas-Kilmann Conflict Mode Instrument (TKI) [Database record]. APA PsycTests. <doi.org/10.1037/t02326-000>; 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>; 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.
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). The Rentier State in the Arab World. Arab Studies Quarterly, 9(4), pp. 383–398. Available at: <http://www.jstor.org/stable/41857943>; Yates, D. A. (1996). The Rentier State in Africa: Oil Rent Dependency and Neo-Colonialism In the Republic of Gabon. Africa World Press. Trenton: NJ.; Losman, D. L., pp. 427-445; Wilson, J., pp. 400-401. [17] El-Katiri, L. (2014). The Guardian State and its Economic Development Model. Journal of Development Studies, 50:1, pp. 22-34; Wilson, J. (2015). p. 405. [18] Di John, J. (2010). p. 79. [19] Hults, D. R. (2011). Petróleos de Venezuela, S.A. (PDVSA): from independence to subservience. 436, in D. G. Victor, D. R. Hults, & Thurber M. C. (eds). Oil and Governance: State-Owned Enterprises and the World Energy Supply. Cambridge University Press, pp. 418-477. [20] Hults, D. R. (2011). p. 437. [21] Noreng, O. (1994). National Oil Companies and Their Government Owners: The Politics of Interaction and Control. The Journal of Energy and Development, 198, Spring, Vol. 19, No. 2, pp. 197-226. [22] Di John, J. (2010). pp. 83-86. [23] Singh, J. M., Chen, G. C. (2018). State-owned enterprises and the political economy of state–state relations in the developing world. 1077, Third World Quarterly, 39:6, pp. 1077-1097. [24] Evans, P. (1995). Embedded Autonomy: States and Industrial Transformation. Princeton University Press: New Jersey, USA. [25] Styhre, A. (2019). p. 1. [26] Cuervo-Cazurro, A., Inkpen, A., Musacchio, A., Ramaswamy, K. (2014). Government as Owners: State-owned multinational companies. 923, Journal of International Business Studies, Vol. 45, August, pp. 919-942. [27] Mares, D. R., Altamarino, N. (2007). Venezeula’s PDVSA and World Energy Markets: Corporate Strategies and Political Factors Determining Its Behavior and Influence. The James Baker III Institute for Public Policy, Rice University, March, p. 15; Hertog, S. (2010). Defying the Resource Curse: Explaining Successful State-Owned Enterprises in Rentier States. 261, World Politics, Vol. 62, No. 2, April, pp. 261-301; 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>. [28] Rosales, A. (2016). Deepening Extractivism and Rentierism: China’s Role in Venezuela’s Bolivarian Developmental Model. 560, Canadian Journal of Development Studies, Vol. 37, Issue 4, 560-7, December. [29] SEC Filing. (2016). PDVSA: Petróleos de Venezuela, S.A. SEC, 128, Edgar Archives. Available at: <https://www.sec.gov/Archives/edgar/data/906424/000119312516712239/d171369dex99t3e.htm>. [30] CRS. (2021, April 28). Venezuela: Background and U.S. Relations, p. 2. Available at: <https://sgp.fas.org/crs/row/R44841.pdf>. [31] Lander, L., Lopez-Maya, M. (2002). Venezuela’s Oil Reform and Chavismo. 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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). 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). Doi: <https://doi.org/10.32479/ijeep.15108>; Blomquist, J., Westerlund, J. (2013). Testing slope homogeneity in large panels with serial correlation. Economics Letters, 121(3). Doi: <https://doi.org/10.1016/j.econlet.2013.09.012>; Breusch, T., Pagan, A. (1980). The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics. The Review of Economic Studies, 47(1). Doi: <https://doi.org/10.2307/2297111>; Canay, I. (2011). A simple approach to quantile regression for panel data. The Econometrics Journal, 14(3). Doi: <https://doi.org/10.1111/j.1368-423X.2011.00349.x>; 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). Doi: <http://dx.doi.org/10.19030/jabr.v32i1.9483>; Gómez-Loscos, A., Gadea, M., Montañés, A. (2012). Economic growth, inflation and oil shocks: are the 1970s coming back? Applied Economics, 44(35). Doi: <https://doi.org/10.1080/00036846.2011.591741>; Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1). Doi: <https://doi.org/10.1016/j.jmva.2004.05.006>; Koenker, R., Bassett Jr, G. (1978). Regression Quantiles. Econometrica, 46(1). Doi: <10.2307/1913643>; Machado, J., Silva, J. (2019). Quantiles via moments. Journal of Econometrics, 213(1). Doi: <https://doi.org/10.1016/j.jeconom.2019.04.009>; 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). Doi: <10.1257/mac.20190196>; Mamdouh, A. (2023). Oil price fluctuations and economic growth: the case of MENA countries. Review of Economics and Political Science, 8(5). Doi: <http://dx.doi.org/10.1108/REPS-12-2019-0162>; Marimoutou, V., Raggad, B., Trabelsi, A. (2009). Extreme Value Theory and Value at Risk: Application to oil market. Energy Economics, 31(4). Doi: <https://doi.org/10.1016/j.eneco.2009.02.005>; 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; Pesaran, M. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal Of Applied Econometrics, 22(2). Doi: <http://dx.doi.org/10.1002/jae.951>; 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>; 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). 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). Moderating effect of subordinates’ overall justice in the relationship between supervisors’ overall justice and supervisors’ affective organizational commitment. Journal of Management Development, 37(7), pp. 526–536. [18] Swalhi, A., Zgoulli, S., Hofaidhllaoui, M. (2017). The influence of organizational justice on job performance. Journal of Management Development, 36(4), pp. 542–559. [19] Abdullah, H. O., Al-Abrrow, H. (2023). Impact of perceived organisational justice, support and identity on workplace behaviour through job attitudes: verification in the role of LOC. International Journal of Organizational Analysis, 31(6), pp. 2645–2664. [20] Blau, P. (1964). Exchange and power in social life. Wiley. [21] Gouldner, A. W. (1960). The Norm of Reciprocity: A Preliminary Statement. American Sociological Review, 25(2), p. 161. [22] Blau, P. (1964). Exchange and power in social life. Wiley. [23] Wayne, S. J., Shore, L. M., Bommer, W. H., Tetrick, L. E. (2002). The role of fair treatment and rewards in perceptions of organizational support and leader-member exchange. Journal of Applied Psychology, 87(3), pp. 590–598. [24] Blau, P. (1964). Exchange and power in social life. Wiley. [25] Gouldner, A. W. (1960). The Norm of Reciprocity: A Preliminary Statement. American Sociological Review, 25(2), p. 161. [26] Jameel, A. S., Ahmad, A. R., Mousa, T. S. (2020). Organizational justice and job performance of academic staff at public universities in Iraq. Skyline Business Journal, 16(1). [27] Gouldner, A. W. (1960). The Norm of Reciprocity: A Preliminary Statement. American Sociological Review, 25(2), p. 161. [28] Swalhi, A., Zgoulli, S., Hofaidhllaoui, M. (2017). The influence of organizational justice on job performance. Journal of Management Development, 36(4), pp. 542–559. [29] Greenberg, J. (1990). Organizational justice: Yesterday, today, and tomorrow. Journal of Management, 16(2), pp. 399–432. [30] Swalhi, A., Zgoulli, S., Hofaidhllaoui, M. (2017). The influence of organizational justice on job performance. Journal of Management Development, 36(4), pp. 542–559. [31] Hosen, S., Hamzah, S. R., Arif Ismail, I., Noormi Alias, S., Faiq Abd Aziz, M., Rahman, M. M. (2024). Training &amp; development, career development, and organizational commitment as the predictor of work performance. Heliyon, 10(1), e23903. [32] 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. [33] Greenberg, J. (2001). Setting the Justice Agenda: Seven Unanswered Questions about “What, Why, and How”. Journal of Vocational Behavior, 58(2), pp. 210–219. [34] Abdullah, H. O., Al-Abrrow, H. (2023). Impact of perceived organisational justice, support and identity on workplace behaviour through job attitudes: verification in the role of LOC. International Journal of Organizational Analysis, 31(6), pp. 2645–2664. [35] Ibid. [36] Salam, A. (2020). Organizational justice as a predictor of organizational citizenship behaviour. International Business Education Journal, 13, pp. 29–42. [37] Ibid. [38] Greenberg, J., Colquitt, J. A. (2013). Handbook of organizational justice. Psychology Press. [39] Adams, J. S. (1965). Inequity In Social Exchange. Advances in Experimental Social Psychology. [40] Blau, P. (1964). Exchange and power in social life. Wiley. [41] Greenberg, J. (1990). Organizational justice: Yesterday, today, and tomorrow. Journal of Management, 16(2), pp. 399–432. [42] Bies, R. J. (2001). Interactional (in) justice: The sacred and the profane. Advances in organizational justice/Stanford University Press. [43] Colquitt, J. A. (2001). On the dimensionality of organizational justice: A construct validation of a measure. Journal of Applied Psychology, 68(3), pp. 386–399. [44] Greenberg, J. (1990). Organizational justice: Yesterday, today, and tomorrow. Journal of Management, 16(2), pp. 399–432. [45] Brockner, J., Ackerman, G., Greenberg, J., Gelfand, M. J., Francesco, A. M., Chen, Z. X., Leung, K., Bierbrauer, G., Gomez, C., Kirkman, B. L., Shapiro, D. (2001). Culture and Procedural Justice: The Influence of Power Distance on Reactions to Voice. Journal of Experimental Social Psychology, 37(4), pp. 300–315. [46] Greenberg, J., Colquitt, J. (2005). Handbook of Organizational Justice (Lawrence E). Mahwah NJ. [47] Imamoglu, S. Z., Ince, H., Turkcan, H., Atakay, B. (2019). The Effect of Organizational Justice and Organizational Commitment on Knowledge Sharing and Firm Performance. Procedia Computer Science, 158, pp. 899–906. [48] 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. [49] Jones, D. A., Martens, M. L. (2009). The mediating role of overall fairness and the moderating role of trust certainty in justice–criteria relationships: the formation and use of fairness heuristics in the workplace. Journal of Organizational Behavior, 30(8), pp. 1025–1051. [50] Kim, S. H., Laffranchini, G., Jeung, W. (2018). Moderating effect of subordinates’ overall justice in the relationship between supervisors’ overall justice and supervisors’ affective organizational commitment. Journal of Management Development, 37(7), pp. 526–536. [51] Rauf, A., Mahmood, H., Naveed, R. T., Yen, Y. Y. (2024). Modeling cynicism and organizational design on job performance: Mediation and moderation mechanism. Heliyon, 10(11), e32069. [52] Lind, E. A. (2001). Fairness heuristic theory: Justice judgments as pivotal cognitions in organizational relations (C. Stanford University Press, Stanford (ed.)). Advances in organizational justice/Stanford University Press. [53] Aryee, S., Walumbwa, F. O., Mondejar, R., Chu, C. W. L. (2015). Accounting for the Influence of Overall Justice on Job Performance: Integrating Self‐Determination and Social Exchange Theories. Journal of Management Studies, 52(2), pp. 231–252. [54] Jones, D. A., Martens, M. L. (2009). The mediating role of overall fairness and the moderating role of trust certainty in justice–criteria relationships: the formation and use of fairness heuristics in the workplace. Journal of Organizational Behavior, 30(8). [55] Lind, E. A. (2001). Fairness heuristic theory: Justice judgments as pivotal cognitions in organizational relations (C. Stanford University Press, Stanford (ed.)). Advances in organizational justice/Stanford University Press. [56] Ambrose, M. L., Schminke, M. (2009). The role of overall justice judgments in organizational justice research: A test of mediation. Journal of Applied Psychology, 94(2), pp. 491–500. [57] Meyer, J. P., Allen, N. J., Smith, C. A. (1993). Commitment to organizations and occupations: Extension and test of a three-component conceptualization. Journal of Applied Psychology, 78(4), pp. 538–551. [58] O’Reilly, C. A., Chatman, J. (1986). Organizational commitment and psychological attachment: The effects of compliance, identification, and internalization on prosocial behavior. Journal of Applied Psychology, 71(3). [59] 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. [60] Blau, P. (1964). Exchange and power in social life. Wiley. [61] Massoudi, A. H., Jameel, A. S., Ahmad, A. R. (2020). Stimulating Organizational Citizenship Behavior by Applying Organizational Commitment and Satisfaction. International Journal of Social Sciences and Economic Review, 02(02), pp. 20–27. [62] Karem, M. A., Jameel, A. S., Ahmad, A. R. (2019). The Impact of Organizational Justice Dimensions on Organizational Commitment among Bank Employees. International Journal of Psychosocial Rehabilitation, 23(02), pp. 502–513. [63] Yiing, L. H., Zaman, K., Ahmad, B., Yiing, L. H., Zaman, K., Ahmad, B. (2009). The moderating effects of organizational culture on the relationships between leadership behaviour and organizational commitment and between organizational commitment and job satisfaction and performance. [64] Abdullah, H. O., Al-Abrrow, H. (2023). Impact of perceived organisational justice, support and identity on workplace behaviour through job attitudes: verification in the role of LOC. International Journal of Organizational Analysis, 31(6), pp. 2645–2664. [65] 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. [66] Ibid. [67] Ibid. [68] Ibid. [69] Imamoglu, S. Z., Ince, H., Turkcan, H., Atakay, B. (2019). The Effect of Organizational Justice and Organizational Commitment on Knowledge Sharing and Firm Performance. Procedia Computer Science, 158, pp. 899–906. [70] 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. [71] Nazarian, A., Atkinson, P., Foroudi, P., Edirisinghe, D. (2020). Leaders ororganisations? Acomparison study of factors affecting organisational citizenship behaviour in independent hotels. International Journal of Contemporary Hospitality Management, 32(6), pp. 2055–2074. [72] Koopmans, L., Bernaards, C., Hildebrandt, V., van Buuren, S., van der Beek, A. J., de Vet, H. C. W. (2012). Development of an individual work performance questionnaire. International Journal of Productivity and Performance Management, 62(1), pp. 6–28. [73] Arab, H. R., Atan, T. (2018). Organizational justice and work outcomes in the Kurdistan Region of Iraq. Management Decision. [74] Sembiring, N., Nimran, U., Astuti, E. S., Utami, H. N. (2020). The effects of emotional intelligence and organizational justice on job satisfaction, caring climate, and criminal investigation officers’ performance. International Journal of Organizational Analysis, 28(5), pp. 1113–1130. [75] Swalhi, A., Zgoulli, S., Hofaidhllaoui, M. (2017). The influence of organizational justice on job performance. Journal of Management Development, 36(4), pp. 542–559. [76] Campbell, J. P., McHenry, J. J., Wise, L. L. (1990). Modeling job performance in a population of jobs. Personnel Psychology, 43(2), pp. 313–575. [77] Begley, T. M., Lee, C., Fang, Y., Li, J. (2002). Power distance as a moderator of the relationship between justice and employee outcomes in a sample of Chinese employees. Journal of Managerial Psychology, 17(8), pp. 692–711. [78] Rotundo, M., Sackett, P. R. (2002). 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The effects of emotional intelligence and organizational justice on job satisfaction, caring climate, and criminal investigation officers’ performance. International Journal of Organizational Analysis, 28(5), pp. 1113–1130. [89] Suliman, A., Kathairi, M. Al. (2013). Organizational justice, commitment and performance in developing countries: The case of the UAE. Employee Relations, 35(1), pp. 98–115. [90] Khaola, P., Coldwell, D. (2019). Explaining how leadership and justice influence employee innovative behaviours. European Journal of Innovation Management, 22(1), pp. 193–212. [91] Colquitt, J. A., Scott, B. A., Rodell, J. B., Long, D. M., Zapata, C. P., Conlon, D. E., Wesson, M. J. (2013). Justice at the millennium, a decade later: A meta-analytic test of social exchange and affect-based perspectives. Journal of Applied Psychology, 98(2), pp. 199–236. [92] Cohen-Charash, Y., Spector, P. E. (2001). The role of justice in organizations: A meta-analysis. 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Sustainability Reporting as an Opportunity to Improve Governance Reporting Practices
The concept of sustainable accounting has emerged as a result of the development of accounting over the past forty years. Two different approaches emerged: The first is the debate about accountability, based on a completely new accounting system and designed to strengthen the sustainability strategy; The second approach is a management perspective, which is related to many sustainability terms. It can therefore be considered an extension of conventional financial management accounting. The paper discusses the purpose of sustainability accounting, stages of development, and the possibility of implementing and using two of the most important standards in Georgian companies. Key considerations and responses to the use of standards in sustainability reporting regarding disclosures have been formulated. Based on European experience, Georgia has introduced international standards for sustainable development. The goal of sustainability reporting is to reduce the negative impacts of businesses on the environment and society. The main challenge is to standardize the process of preparing sustainability reports, ensuring their robustness and reliability. The introduction of standards is important and a priority for the sustainable development of local enterprises. The early adoption of these principles represents an opportunity for the country to improve its management reporting practices as stipulated in the Law on Accounting, Reporting, and Auditing of Georgia. Contribute to the creation of a more sustainable and competitive economic environment, which ultimately ensures the creation of a European business environment. The implementation of these standards will strengthen investor confidence and create opportunities for making informed decisions. Keywords: Sustainable reporting, IFRS standards, disclosure information, production practices, economic environment. Introduction Sustainability accounting issues have appeared in the accounting of various countries over the past half century. Accordingly, there is a significant challenge in Georgia today. Accounting based on sustainability reporting has passed significant milestones. Today, the use of sustainability accounting information in the management process of companies is increasing. Such information is important for making the right management decisions in companies. The goal of sustainability reporting is to reduce the negative impacts of businesses on the environment and society. The main challenge is to standardize the process of preparing sustainability reports, ensuring their robustness and reliability. The introduction of standards is important and a priority for the sustainable development of local enterprises. The early adoption of these principles represents an opportunity for the country to improve its management reporting practices as stipulated in the Law on Accounting, Reporting, and Auditing of Georgia. Contribute to the creation of a more sustainable and competitive economic environment, which ultimately ensures the creation of a European business environment. The implementation of these standards will strengthen investor confidence and create opportunities for making informed decisions. The research paper aims to improve governance reporting practices by applying international sustainability reporting standards. Investors will have the opportunity to obtain more complete, reliable, and comparable information; in turn, enterprises will receive a comprehensive picture for business model evaluation and development. The information disclosed in the sustainability report will be important for internal decision-making to create new policies that will impact the economic, environmental, and social factors of the enterprise. In turn, all of this will strengthen the development of the green economy in Georgia. The paper is based on qualitative research. The research used data from the Accounting, Reporting and Audit Supervision Service of Georgia, the Federation of Accountants and Auditors, IFRS Foundation, Sustainability Accounting Standards Board website materials. Results and Discussion Sustainability accounting as a subcategory of management accounting, and two different approaches Sustainability accounting is a subcategory of management accounting. The purpose of which is to use non-financial information about the activities of the enterprise for external stakeholders, creditors, and equity holders.[1] It differs from management accounting and is used to make internal decisions, create new policies, and influence the efficiency of the enterprise in economic, environmental, and social areas. According to the Global Reporting Initiative (GRI), corporate reporting on economic, social, and environmental performance is as necessary and time-consuming as financial reporting.[2] The concept of sustainable accounting has emerged from the development of accounting over the past forty years. Two different approaches emerged.[3] The first is the debate about accountability, based on a completely new accounting system and designed to strengthen the sustainability strategy. The second approach is a management perspective, which is related to multiple sustainability terms. It can therefore be considered an extension of conventional financial management accounting. Four main stages in the development of sustainability accounting Sustainability accounting is a rather complex process that can be divided into four stages. Stage 1: 1971-1980; Stage 2: 1981-1990; Stage 3: 1991-1995; Stage 4: from 1995 onwards. In the first stage- papers and empirical studies were published. Which contributed to the creation of social accounting models. The information was related to products and employees. The methodology was identical to financial accounting. Although several models were improved, the debate was not widespread. In the second stage - literature and research show how the field of social accounting has been refined, although interest in this field has shifted to environmental accounting. Empirical research has become more analytical, with social information replaced by a focus on environmental regulations as an alternative means of reducing environmental damage. At this stage, the development of training programs on social and environmental accounting issues has begun. Through the increasing use of conceptual frameworks, accounting standards, and legal provisions. In the third stage - environmental audit applications were developed to ensure transparency of environmental information. Environmental management systems and a regulatory framework were developed, which would influence the transparency of social and environmental accounting. The process of environmental regulation in the US, Canada, and Australia has progressed more rapidly than in Europe. At this stage, several manuals were issued and articles were published covering both social and environmental accounting issues. The role and purpose of sustainability and management accounting information has become an interesting object of study for the sustainable development of enterprises. The fourth stage - the initial period - is characterized by the approximately, this has led to the emergence of global and regional issues of management quality control. Since this period, special attention has been paid to accounting for environmental costs, which includes choosing suppliers whose views and practices regarding ecology are consistent with those of customers. It also refers to the costs of destroying waste products in the production process, after-sales service, and product withdrawal from the market. Environmental cost accounting provides support for a company’s environmental management initiatives.[4] The role of the International Federation of Accountants in sustainability accounting All of the above have led to the development of the accounting profession with international issues. Accounting literature has been published, focusing on sustainability accounting issues. Many international and national meetings are held on sustainability accounting issues.[5] The most developed form of sustainability accounting is environmental accounting. In 2002, at the World Summit on Sustainable Development, Robert Hugh Gray’s Sustainability Accounting Guidelines were published.[6] In recent years, interest in corporate sustainability accounting and reporting approaches has increased. Experts from international organizations argue that the sustainability aspects of accounting and reporting are of crucial importance in assessing the future development of enterprises. In this regard, the role of the International Federation of Accountants (IFAC) is important. Its goal is to promote the development of the accounting profession and harmonize it with standards. It has 167 member organizations in 127 countries and approximately two million accountants worldwide. To encourage professional accountants to incorporate sustainability into their accounting, the Prince of Wales created the Accounting for Sustainability Project in 2004.[7] The goal of sustainability accounting is to transition to sustainable business models and a sustainable economy. The popularity of sustainability has grown recently, with many companies already using new methods and techniques when publishing financial information. They provide external users with information about key activities and environmental impacts. This information helps suppliers, buyers, and government agencies understand how businesses are managing their resources so that they can achieve sustainable development. As a result of studying the issue, three areas of sustainability were identified: social, economic and environmental. Each of them depends on different factors.[8] That is why it is necessary to develop enterprises in the direction of environmental, social and governance processes. The role of the European Union in the development of sustainable development reporting and two international sustainability standards In 2022, the European Commission developed the Corporate Sustainability Reporting Directive (CSRD), which entered into force on January 5, 2023.[9] This directive replaced the previously existing Non-Financial Reporting Directive with updated wording and requirements. Preparing corporate sustainability reports for enterprises using relevant standards; It became mandatory for the 2024 reporting period, which will be submitted to local authorities starting in 2025. Georgia is actively working in this direction within the framework of European perspectives, to introduce best practices in the country. Two IFRS sustainability disclosure standards issued by the International Sustainability Standards Board (ISSB) in 2023 have already been translated into Georgian and published.[10] These are: IFRS S1- General requirements for financial disclosure on corporate sustainable development; IFRS S2- Climate-related disclosure information. Companies that must prepare a corporate sustainability report The new requirements will apply to up to 50,000 companies across the EU. According to the CSRD, companies must prepare a corporate sustainability report if they:[11] Representing “large” enterprises in the European Union (including banks, insurance companies, accountable enterprises, whose securities are admitted to trading on the stock exchange, and enterprises designated as SDP by local authorities); There are small and medium-sized enterprises on the EU-listed market; Enterprises that have a branch or subsidiary within the European Union. These companies are required to disclose information about how environmental and social issues affect the risks and challenges they face. They must also disclose information about the impact their business model has on people and the environment. As we mentioned, the European Commission has developed a directive on corporate sustainability reporting, which will replace the existing Non-Financial Reporting Directive. According to the new directive, the preparation of corporate sustainability reports using relevant standards will become mandatory for EU member states. Companies have many questions about this. Key considerations and feedback on the use of standards in sustainability reporting regarding disclosures A company that uses accounting standards will it be required to present the information disclosed in the sustainability report in accordance with IFRS standards? IFRS accounting standards apply to financial statements. It will not be mandatory, but it will be up to the company to decide whether companies in the jurisdiction will use IFRS standards to protect the information that is being disclosed in sustainable reporting. In addition, the company must make a separate statement stating that it has complied with all requirements for all information related to sustainable development. This information must be presented in accordance with sustainable reporting standards and must be consistent with any accounting principles.[12] Will IFRS standards for disclosure of information related to sustainable development be mandatory? The International Sustainable Development Standards Council does not have the authority to grant mandatory status to standards. However, companies can voluntarily choose to use them. Will the application of the standards proposed by the International Sustainable Development Standards Council begin gradually? A company is not required to present comparative information when first adopting a standard, but has the option to do so. This proposal will make it easier for the company to comply with the requirements and provide investors with sustainability-related information as quickly as possible. Will it be mandatory to report information related to sustainable development in a specific location, in a specific format, or a separate report? Financial information related to sustainable development must be part of a company’s general purpose financial statements. However, the company can provide information in different ways. The draft standards do not establish any specific structure. For example, in the form of a physical report, in a prescribed document format, as a tagged data file, or via a website. Some jurisdictions have specific formats or reporting requirements. For example, XBRL-based files or a report in PDF format.[13] If there is no such standard for disclosure of information related to sustainable development, which deals with the risks and opportunities associated with the sustainable development of a particular company, if so, what guidelines or requirements must this company comply with? The draft Common Requirements for Discussion provides companies with sources, which will help them identify appropriate risks and opportunities related to sustainable development and prepare information for disclosure, which will allow investors to assess the value of the enterprise. The company is advised to consider the requirements of the SASB standards, non-binding requirements of the International Sustainable Development Standards Council (for example, applying the CDSB principles to biodiversity disclosures), and standards developed by some other bodies. Most importantly, the standards that a company adopts should be designed to meet the information needs of investors. In addition, companies can also consider established practices in the industry. The climate-related requirements of the SASB standards are the basis for the climate-related project under consideration. Possible changes in requirements are expected. As a result of the proposed changes, some indicators will be updated to improve their international applicability; For the financial sector, requirements will be added regarding indicators related to funded and facilitated emissions. Also, if a company uses the proposals of the climate-related project under consideration, it will meet the TCFD recommendations.[14] Conclusion For Georgia to comply with the requirements of the European Union, the Accounting and Reporting Service plans to reflect the changes made to the regulatory directives and regulations in the legislation.[15] They will also develop sustainability reporting guidelines based on standards, research, share and implement international best practices, they will conduct training, disseminate information to raise awareness, and implement other socially beneficial activities. Currently, the International Standards Board (ISSB) plans to use two international standards for corporate sustainability reporting in enterprises. Through these standards, investors will have the opportunity to obtain more complete, reliable, and comparable information necessary to assess the value of an enterprise and manufacturers will get a more comprehensive picture for business model evaluation and development. In the future, I will continue to develop ideas on other risks, opportunities, and priorities related to sustainable development, which will be suitable for valuing the enterprise, as well as opinions on further improving industry requirements, based on the SASB standards. All of this will be an opportunity to strengthen the green economy. Bibliography: A brief description of the draft corporate sustainability reporting standard. (March 2022). IFRS® Sustainability Disclosure Standards. Accounting, Reporting and Audit Supervision Service. Available at: <https://saras.gov.ge/> (Last access:04.2025); Adams, W. (29-31 January 2006). The Future of Sustainability: Rethinking the Environment and Development in the Twenty-First Century; Report of the IUCN Eminent Thinkers Meeting. Atkinson, A., Kaplan, R., Matsumura, E.M., Young, S. (2009). Government Accounting, Georgian Herald Publishing House. European Sustainability Reporting Standards - ESRS. (13.01.2025). (Last Access: 03/04/2025); Global Reporting Initiative. Available at: <http://www.globalreporting.org> (Last access: 03.04.2025); IFRS Foundation. (2022). Available at: <https://www.ifrs.org/content/dam/ifrs/project/g eneral-sustainability-relateddisclosures/ georgian/georgian-s1-and-s2-edssnapshot- april-2022.pdf> (Last access: 03/04/2025); IFRS S2 Climate-related disclosures. Available at: <https://www.saras.gov.ge/ka/home/esrs>; International Federation of Accountants. Available at: https://www.ifac.org> (Last access: 03/04/2025); Kvantrishvili, N. (23.12.2024). Corporate Sustainability Reporting and Transparency in the Fight Against Corruption: A Business Perspective. Available at: <https://unglobalcompact.ge/sustainability-spotlight/korporaciuli-mdgradobis-angarishgeba-da-gamchvirvaloba-korufciastan-brdzolis-processhi-biznesis-perspeqtiva>. Ministry of Finance Accounting, Reporting and Audit Supervision Service. Strategy for the years 2023-2026. Available at: <https://www.saras.gov.ge/Content/files/SARAS_Strategy_2023-20262.pdf>. Slaper, T., Hall, T. (2011). The Triple Bottom Line: What Is It and How Does It Work? Indiana Business Review, Vol. 86, No. 1. Available at: <https://www.ibrc.indiana.edu/ibr/2011/spring/ahtml> (Last access: 03.04.2025); Sustainability Accounting Standards Board. Available at: <http://www.sasb.org> (Last access: 03/04/2025); Sustainability Reporting Update International Sustainability Reporting Bulletin 2025/01. (December 2024). Available at: <https://www.bdo.global/getmedia/5a181e3f-0a64-4dc2-be8b 98dcab4bb5eb/ISRB_2025_01_(final).pdf?ext=.pdf>; Footnotes [1] Accounting, Reporting and Audit Supervision Service. Available at: <https://saras.gov.ge/>. [2] Global Reporting Initiative. GRI. Available at: <http://www.globalreporting.org>. [3] Slaper, T., Hall, T. (2011). The Triple Bottom Line: What Is It and How Does It Work? Indiana Business Review, Vol. 86, No. 1. Available at: <https://www.ibrc.indiana.edu/ibr/2011/spring/a rticle2.html>. [4] Atkinson, A., Kaplan, R., Matsumura, E.M., Young, S. (2009). Government Accounting, Georgian Herald Publishing House, p.337. [5] Kvantrishvili, N. (23.12.2024). Corporate Sustainability Reporting and Transparency in the Fight Against Corruption: A Business Perspective. Available at: <https://unglobalcompact.ge/sustainability-spotlight/korporaciuli-mdgradobis-angarishgeba-da-gamchvirvaloba-korufciastan-brdzolis-processhi-biznesis-perspeqtiva>. [6] Sustainability Accounting Standards Board. Available at: <http://www.sasb.org>. [7] International Federation of Accountants. Available at: https://www.ifac.org>. [8] Adams, W. (29-31 January 2006). The Future of Sustainability: Rethinking the Environment and Development in the Twenty-First Century; Report of the IUCN Eminent Thinkers Meeting. [9] A brief description of the draft corporate sustainability reporting standard. (March 2022). IFRS® Sustainability Disclosure Standards. 10 IFRS Foundation. (2022). Available at: <https://www.ifrs.org/content/dam/ifrs/project/g eneral-sustainability-relateddisclosures/ georgian/georgian-s1-and-s2-edssnapshot- april-2022.pdf>. [11]A brief description of the draft corporate sustainability reporting standard. (March 2022). IFRS® Sustainability Disclosure Standards. [12] European Sustainability Reporting Standards - ESRS. (13.01.2025). [13] Sustainability Reporting Update International Sustainability Reporting Bulletin 2025/01. (December 2024). Available at: <https://www.bdo.global/getmedia/5a181e3f-0a64-4dc2-be8b 98dcab4bb5eb/ISRB_2025_01_(final).pdf?ext=.pdf>. [14] IFRS S2 Climate-related disclosures. Available at: <https://www.saras.gov.ge/ka/home/esrs>. [15] Ministry of Finance Accounting, Reporting and Audit Supervision Service. Strategy for the years 2023-2026. Available at: <https://www.saras.gov.ge/Content/files/SARAS_Strategy_2023-20262.pdf>.
The Role of AI in Personalizing Travel Experiences and Enhancing Satisfaction Among Eco-Conscious Tourists in Algeria
This study examines the impact of AI-Driven Personalisation on traveller satisfaction and eco-conscious behavior among Algerian tourists. Data was collected from 160 Algerian travellers through a survey to understand how AI influences their travel experiences and environmental awareness. The results show a significant positive relationship between AI-Driven Personalisation and both traveller satisfaction and eco-conscious behavior. Personalization enhances travellers’ enjoyment by offering more relevant experiences and encourages more sustainable choices, such as eco-friendly accommodations and transportation. The study also identifies demographic factors that influence the effectiveness of AI personalization, including age and the use of specialized travel platforms. Younger travellers, who are more familiar with digital technologies, tend to benefit more from AI-driven recommendations compared to older tourists. These findings suggest that AI-Driven Personalisation can effectively promote sustainable tourism by improving traveller experiences and encouraging eco-friendly behaviors. Tourism providers can use AI to tailor suggestions to individual preferences, enhancing both the quality of the travel experience and the environmental impact. Future research should focus on the long-term effects of AI-Driven Personalisation, exploring its potential to shape future tourism trends and its broader impact on the industry. Keywords: AI-Driven Personalisation, eco-conscious behaviour, traveler satisfaction, Algeria. Introduction The tourism industry is one of the industry sectors affected by artificial intelligence.[1] This field is expected to transform various sectors and promoting both environmental sustainability and business success.[2] According to the United Nations Environment Programme (UNEP) and the World Tourism Organization (WTO), sustainable tourism is the “Tourism that takes full account of its current and future economic, social and environmental impacts, addressing the needs of visitors, the industry, the environment and host communities”.[3] Madjid et al. Emphasize that sustainable tourism requires a harmonious balance between environmental, economic, and social dimensions.[4] It also requires responsible behaviours from individuals.[5] The International Ecotourism Society (TIES) considers ecotourism as responsible travel to natural areas that protects the environment, improves the well-being of local residents, including interpretation and education. Education is meant to be inclusive of both staff and guests.[6] Eco-tourism, also known as responsible tourism, attempts to limit negative effects on the environment, support local people, and encourage cultural preservation.[7] Both statements highlight responsible tourism, which aims to reduce environmental damage, help local people, and protect cultural heritage. Education and active engagement from all stakeholders are critical for developing sustainability and cultural awareness in tourist activities. AI is rapidly being used across several service industries, such as travel and tourism, due to its great learning capacity, flexibility, and connectivity.[8] Several studies have explored the potential of AI in the travel industry. For instance, Vecchia et al. Investigated the use of AI-powered recommendation systems (RSs) where one or more attractions must be recommended to users based on preferences, contextual aspects, and various other limitations in a sustainable way.[9] Their findings demonstrated the effectiveness of AI in matching travellers with eco-friendly recommended systems that align with their interests. Similarly, Milton (2024)[10] investigated the role of AI in improving energy usage and waste management in hotels, demonstrating the potential for AI-driven solutions for reducing the environmental effects of the tourist industry. AI-driven solutions for enhancing energy efficiency and waste management in hotels directly contribute to the aims of sustainable tourism. AI promotes resource efficiency and minimizes waste, which aligns with sustainability values. This promotes an eco-friendly tourist company by preserving natural resources and limiting tourism’s negative environmental consequences, both of which are critical for the sector’s long-term sustainability. This study focuses on the use of AI-Driven Personalisation to improve the eco-conscious travel experience. The research will examine the possible benefits, challenges, and future trends of AI in this context. The main objective is to build a more sustainable and responsible tourism industry. Understanding AI’s role in supporting sustainable tourism and increasing visitor pleasure allows us to build ways for delivering personalized experiences that are consistent with environmental values. Research Problematic Based on the literature, we propose the following research question: How does AI-Driven Personalisation impact the satisfaction of the Algerian eco-conscious travellers? And if there is a significant impact, does this impact significantly vary across different demographic groups of Using Specialized platforms, Age, and Educational Level? Lastly, do the Daily green behaviours and public self-awareness moderate the relationship between AI-Driven Personalisation and traveller Eco-Consciousness Behaviour? To investigate these questions, we propose our conceptual framework: Conceptual framework Figure 1: Conceptual framework of the study Source: Proposed by the author The main objective in this research is to examine the potential for AI-Driven Personalisation to improve environmentally conscious travel experiences. This includes looking into the benefits, limitations, ethical concerns, and practical uses of AI in this context. The study’s focus is to provide a deep insight into how AI may be effectively utilized to promote sustainable tourism and develop customized experiences that are linked to traveller values and environmental objectives. Literature review and hypothesis development Understanding Eco-Conscious Travel: Eco-conscious travel, also known as green travel or eco-tourism, focuses specifically on the environmental sustainability of tourism within a destination landscape.[11] Thus, Eco-conscious travel is a form of tourism that strives to minimize the negative environmental effects of travel. In other words, it is a conscious effort to travel and take into consideration to preserve natural resources, protect cultural heritage, and support sustainable development. In their study by Sahabuddin et al. (2024),[12] they identify tourist satisfaction as a key factor influencing loyalty, environmentally responsible behaviour (ERB), and environmental commitment. The findings show that environmental value has a substantial effect on tourist satisfaction. Furthermore, visitor satisfaction is strongly correlated with tourist loyalty, ERB, and environmental commitment to the place or destination. Chen et al. (2023)[13] recommend that tourism destinations should maintain a conducive environment to develop tourist ERB, particularly when tourists exhibit a high level of public self-awareness. Previous studies have also shown that satisfactory AI services provide visitors with an exceptional trip experience and influence the benefits of tourism products.[14] In their study, Escobar-Farfán et al. (2024)[15] demonstrated that customers prefer brands relevant to their identity and enhance credibility and trust, favouring attitudes and behaviours that increase consumption. Travellers, like customers in general, like travel brands that reflect their character, values, and beliefs. When a brand shows relevance to a Traveller’s eco-conscious values, it increases confidence and credibility. This connection generates good sentiments toward the brand, resulting in improved pleasure with the travel experience, as Travellers feel understood and valued, which can lead to repeat bookings and loyalty. An Eco-conscious behaviour or Pro-environmental also known as the Eco-friendly tourist behaviour, happens when an individual tries to limit his/her negative effects on the natural environment and contribute to environmental conservation.[16] This behaviour is positively influenced by five emotions, as the Kvasova (2015) study found: extroversion, agreeableness, conscientiousness, neuroticism, openness. Other studies found that the Ecoconscious behaviour or Pro-environmental behaviour is positively influenced by situational factors such as tourism types or activities, personal emotions like awe and guilt, and individual motivation.[17] This individual motivation, as we supposed in our study it’s the Daily Green Behaviours and Public Self-Awareness as a mediator variable (DGB&PSA); these are the main supposed as a bridge between environmental attitude and eco-friendly behaviour. Studies investigated which generation is more widely known as the most eco-conscious generation, and they found that Generation Z is more accepting of eco-friendly travel.[18] In our study, we will focus on multiple generations from boomers to Generation Z, to know how age affects the eco-conscious behaviour of tourists. Also, the eco-friendly behaviour is affected positively by environmental and health concerns and service quality.[19] Successful AI-Driven Personalisation Initiatives in Eco-Tourism : Booking Platform (Netherlands 1996): With more than 610.9 million visits to its website,[20] the platform takes into consideration factors such as energy efficiency, waste reduction, and local impact to identify eco-friendly options. In October 2023, Booking.com announced its new initiatives around Sustainability.[21]com has integrated AI into its platform to recommend sustainable accommodations based on traveller preferences and location. These initiatives enhance the travellers’ experiences with AI-powered recommendations that help to find and book sustainable accommodations, contributing to increased demand for eco-friendly tourism. UK-based Skyscanner (UK 2003): this is a travel search engine that provides flights to hotels, and car hire and plan booking to many tourism destinations. Its main mission is to adopt the global transformation to modern and sustainable travel.[22] As a premier travel search platform with a 70 million monthly active user base and extensive global partnerships with about 1200 global partners. Skyscanner offers comprehensive flight data that closely aligns with booking trends.[23] Skyscanner has launched its app-exclusive Savvy Search tool, powered by OpenAI’s Chat GPT technology, to provide travellers with an easier way to plan their customized trips. Eco Tourism and AI status in Algeria: in the Strategic Tourism Development Plan (SDAT) 2025 for Algeria, this strategic plan aims to make tourism a pillar of the Algerian economy by capitalizing on the country’s diverse assets (cultural, natural, historical) and developing tourism products tailored to the expectations of domestic and international markets.[24] It aims essentially to make tourism a driving force of economic growth for Algeria by developing both domestic and international tourism, preserving the environment and cultural heritage, and improving the country’s international image. Furthermore, with more than 2 million km2 of surface and a rich relief made up of three major ensembles: the Tell in the north, the highlands and the Saharan Atlas in the centre, and the Sahara in the south.[25] Thus, ecotourism in Algeria offers a variety of activities, from exploring the Mediterranean coastline to venturing into the Saharan Atlas Mountains. Popular destinations include Tassili n’Ajjer National Park, Al Qal’a of Beni Hammad, Djémila, M’Zab Valley, Timgad, Tipasa, and Kasbah of Algiers, a UNESCO World Heritage Site known for its stunning historical and cultural places and diverse ecosystems.[26] Material and Methodology This study uses a quantitative research methodology to investigate and analyse the relationship between AI-Driven Personalisation and satisfaction among the Eco-Conscious Travellers in Algeria. A structured questionnaire was developed to collect data from tourists who have visited the different tourism destinations. The questionnaire included items measuring AI-Driven Personalisation (e.g., Destination Recommendations, Accommodation Recommendations, Activity Recommendations, etc.), Eco-Conscious Behaviour and Satisfaction of the travellers (e.g., Sustainable Travel Choices, Environmental Awareness, Responsible Consumption, etc.), and sociodemographic information (e.g., age, gender, monthly income). A convenience sampling method was used to recruit participants from tourists visiting the destination. A total of 160 respondents completed the survey and are ready to analysis. The target population for this study consists of Algerian tourists who have travelled inside and outside the country in the past 6 months. A convenience sampling method will be used to recruit participants from various regions across Algeria. Timeframe: The survey was open for replies from 12th August 2024 to 13th September 2024, which provided enough time for data collection. To investigate the relationships between the study variables, the obtained data were analysed using descriptive statistics and inferential statistics using SPSS Statistics 26. Firstly, we have to calculate and analyse the Cronbach’s Alpha. This is a measure of internal consistency; how closely related a number of items are as a group.[27] The coefficient has a range of 0 to 1. When an item’s alpha value is high, it suggests that it measures an underlying factor. That is a reliability/consistency test, not a statistical test, though. For our study, we found the results mentioned in Table 1. Table 1: Reliability Statistics. Source: Author’s explanation The reliability test refers to the consistency and accuracy of measurement. In this case, Cronbach’s alpha is used as a measure of internal consistency, indicating how well the items within each scale measure the same underlying construct Almquist et al., (2020). Therefore, the provided reliability statistics (Cronbach’s alpha over 0.60) in Table 1 indicate that the scales used to measure these constructs are generally reliable and provide a solid foundation for further analysis and interpretation of the research findings. Findings and Discussion: This part of the study included the results of the questionnaire forms distributed on the internet on Facebook, online Google Drive, email, and phone calls. To find out what the tourists’ satisfaction is regarding the role of AI-Driven Personalisation as a factor to enhance the EcoConsciousness of Algerian travellers. Respondent’s Demographics: The given data comprises 160 respondents’ demographic details. Table 2 provides a breakdown of the demographic and career characteristics of the respondents (n=160) involved in the study. Table 2: The respondents according to Source: Author’s explanation From the table above, the majority of respondents (58.1%) chose to travel within the country, while 41.9% travelled outside Algeria. The largest age group was 35-44 (38.8%), followed by 18-24 (28.1%). The sample was relatively balanced, with 41.9% male and 58.1% female respondents. A significant portion (48.8%) had a university-level education, followed by doctoral degrees (24.4%) and high school (26.9%). The most common income bracket was “more than 56,000” (34.4%), indicating a relatively high-income sample. The largest occupational group was “employed full-time” (39.4%), followed by self-employed (23.1%). A smaller proportion of respondents (16.9%) reported using specialized apps integrated with AI in their travels, while the majority (83.1%) did not; they use their recommendations from notifications generated based on their research. Descriptive statistics of factors The provided descriptive statistics we get from SPSS calculations summarize the responses to the questionnaire items across four dimensions: Daily green behaviours and public self-awareness, AI-Driven Personalisation, Eco-Conscious Behaviour, and Traveller Satisfaction. The statistics include the number of valid responses (N), mean values, and standard deviation for each item. Table 3: Measuring the traveller satisfaction and Eco-Consciousness Behaviour regarding the use of Source: Author’s explanation TABLE 4: DESCRIPTIVE ANALYSIS OF THE RESPONDENTS’ OPINIONS ACCORDING TO THE IMPACT OF AI-DRIVEN PERSONALISATION AS FACTOR IMPACT TRAVELLER SATISFACTION AND ECO-CONSCIOUSNESS BEHAVIOUR The results in Table 4, the mean values for all variables are relatively high, suggesting generally positive perceptions. And the standard deviation for all variables is moderate, indicating some variability in responses. Results also indicate that Eco-Conscious Behaviour is ranked highest, meaning that participants perceive it as having the greatest impact. And unlike Eco-Conscious Behaviour, AI-Driven Personalisation is ranked lowest, indicating a perceived lesser impact. Based on these results, we conclude that Eco-Conscious Behaviour is a crucial factor influencing traveller satisfaction. This highlights the importance of incorporating sustainability into travel experiences. On the other hand, while AI-Driven Personalisation is ranked lower, it still has a positive impact on traveller satisfaction. This suggests that personalized experiences can contribute to a more enjoyable trip, even if they are not the primary driver of satisfaction. Finally, the scale All Variables ranking suggests that the combination of all factors, including AI-Driven Personalisation, destination-based preferences, eco-conscious behaviour, and traveller satisfaction, has a significant impact on the overall travel experience. Hypotheses of the study test Hypothesis 1: There is a significant positive relationship between AI-Driven Personalisation and traveller Satisfaction and Eco-Consciousness Behaviour. Table 5 provides correlation coefficients between the main variables of the study: AI-Driven Personalisation, Eco-Conscious Behaviour, Traveller Satisfaction, and Scale All Variables. These coefficients indicate the strength and direction of the relationships between these variables. Table 5: The relationships between the main variables of the study Source: Author’s explanation Results found that A strong positive correlation of 0.831 exists between these two variables, supporting Hypothesis 1. This suggests that AI-Driven Personalisation is significantly associated with higher levels of traveller satisfaction. There is also a moderately strong positive correlation of 0.494 between AI-Driven Personalisation and Eco-Conscious Behaviour, further supporting Hypothesis 1. This indicates that personalized experiences can positively influence travellers’ eco-conscious behaviour. Also, we found a significant positive correlation of 0.669 observed between these two variables, suggesting that engaging in EcoConscious Behaviour can enhance traveller satisfaction. Overall, the results in Table 5 strongly support Hypothesis 1. “There is a significant positive relationship between AI-Driven Personalisation and traveller Satisfaction and EcoConsciousness Behaviour”. Hypothesis 2: Higher levels of AI-Driven Personalisation have a significant impact on traveller Satisfaction. Table 6 presents the results of an ANOVA (Analysis of Variance) test, which is used to determine whether there are significant differences between groups or models. In this case, the ANOVA is examining the relationship between AI-Driven Personalisation and Traveller Satisfaction. The ANOVA results in Table 6 provide strong evidence that AI-Driven Personalisation is a significant predictor of Traveller Satisfaction. The large F-statistic and highly significant p-value confirm that the model (including AI-Driven Personalisation) explains a significant amount of the variation in Traveller Satisfaction. This supports the findings from previous analyses and reinforces the importance of AI-Driven Personalisation in enhancing traveller experiences. Table 7 presents the coefficients for the regression model predicting Traveller Satisfaction based on AI-Driven Personalisation. These coefficients represent the standardized beta weights and their associated t-statistics and significance levels. Table 7: Table of Coefficients Source: The author based on SPSS results The results provide a standardized beta coefficient of 0.836 for AI-Driven Personalisation is relatively high, suggesting a strong positive relationship with Traveller Satisfaction. And, the t-statistic of 18,781 is extremely large, indicating that AI-Driven Personalisation is a highly significant predictor of Traveller Satisfaction. In conclusion, the results in Table 7 provide strong evidence that AI-Driven Personalisation is a significant and influential predictor of Traveller Satisfaction. The high beta coefficient and significant t-statistic demonstrate the substantial impact of personalized experiences on enhancing traveller satisfaction. Finally, the results from Table 6, and Table 7 consistently indicate a strong positive relationship between AI-Driven Personalisation and Traveller Satisfaction. The high correlation coefficient, significant F-statistic, and significant beta coefficient all point to the conclusion that higher levels of AI-Driven Personalisation are indeed significantly associated with increased traveller satisfaction. And, the hypothesis Hypothesis 2: Higher levels of AIDriven personalization significantly impact traveller Satisfaction” is supported. Hypothesis 3: Higher levels of AI-Driven Personalisation have a significant impact on Tourist Eco-Consciousness Behaviour Table 8 presents the model summary for a regression analysis where AI-Driven Personalisation is the predictor variable and Eco-Conscious Behavior is the outcome variable. Source: Author’s explanation Results shown in Table 8 provide strong evidence that AI-Driven Personalisation is a significant predictor of Eco-Conscious Behaviour. The large F-statistic and highly significant p-value confirm that the model (including AI-Driven Personalisation) explains a significant amount of the variation in Eco-Conscious Behaviour. This suggests that personalized experiences can play a role in influencing travellers’ eco-conscious behaviour. Table 9 presents the coefficients for the regression model predicting EcoConscious_Behaviour based on AI-Driven Personalisation. These coefficients represent the unstandardized and standardized beta weights, along with their associated t-statistics and significance levels. Source: Author’s explanation The coefficient of 0.473 indicates that for every one-unit increase in AI-Driven Personalisation, Eco-Conscious Behaviour increases by 0.473 units, holding other variables constant. And, the t-statistic of 7.147 is significantly large, indicating that AI-Driven Personalisation is a highly significant predictor of Eco-Conscious Behaviour, with the p-value of 0.000 being significantly less than 0.05, confirming the significance of AI-Driven Personalisation as a predictor. Hence, the results in Table 9 provide strong evidence that AIDriven Personalization is a significant and influential predictor of Eco-Conscious Behaviour. The positive coefficient and significant t-statistic demonstrate that personalized experiences can effectively encourage travellers to adopt more Eco-Conscious Behaviours. Finally, based on the results from Table 8 and Table 9, Hypothesis 3: Higher levels of AI-Driven Personalisation significantly impact Tourist Eco-Consciousness Behaviour is supported. Hypothesis 4: Higher levels of Eco-Consciousness Behaviour personalisation have a significant impact on Traveller Satisfaction. Table 10 presents the coefficients for a regression model predicting Traveler Satisfaction using Eco-Conscious Behaviour as the predictor variable. The coefficient of 0.703 indicates that for every one-unit increase in Eco-Conscious Behaviour, Traveler Satisfaction increases by 0.703 units, holding other variables constant. The beta coefficient of 0.669 suggests a moderately strong positive relationship between Eco-Conscious Behaviour and Traveler Satisfaction. The t-statistic of 11.307 is significantly large, indicating that Eco-Conscious Behaviour is a highly significant predictor of Traveler Satisfaction. While the p-value of 0.000 is significantly less than 0.05, confirming the significance of EcoConscious_Behaviour as a predictor The results in Table 10 provide strong evidence that Eco-Conscious Behaviour is a significant and influential predictor of Traveler Satisfaction. The positive coefficient and significant t-statistic demonstrate that engaging in eco-conscious behaviour can significantly enhance the overall travel experience. Table 10 presents the coefficients for a regression model predicting Traveler Satisfaction using Eco-Conscious Behaviour as the predictor variable. The coefficient of 0.703 indicates that for every one-unit increase in Eco-Conscious Behaviour, Traveler Satisfaction increases by 0.703 units, holding other variables constant. The t-statistic of 11.307 is significantly large, indicating that Eco-Conscious Behaviour is a highly significant predictor of Traveler Satisfaction. And, the p-value of 0.000 is significantly less than 0.05, confirming the significance of EcoConscious_Behaviour as a predictor. Source: Author’s explanation The results in Table 10 provide strong evidence that Eco-Conscious Behaviour is a significant and influential predictor of Traveler Satisfaction. The positive coefficient and significant t-statistic demonstrate that engaging in eco-conscious behaviour can significantly enhance the overall travel experience. Therefore, the hypothesis “Hypothesis 4: Higher levels of Eco-Consciousness Behaviour significantly impact Traveler Satisfaction” can be supported based on the provided results. Hypothesis 5: The impact of AI-Driven Personalisation significantly varies across different demographic groups of Using Specialized platforms, Age, and Educational Level. Table 11 presents the results of one-way ANOVAs to examine whether the impact of AIDriven Personalization varies across different demographic groups: Using Specialized Platforms, Age, and Educational Level. Source: Author’s explanation The F-statistic is 18,303 with a p-value of 0.000, indicating a significant difference in the impact of AI-Driven Personalisation across different groups using specialized platforms. The F-statistic is 7,601 with a p-value of 0.000, suggesting a significant difference in the impact of AI-Driven Personalisation across different age groups. Also, the F-statistic is 0.289 with a p-value of 0.749. This indicates that there is no significant difference in the impact of AIDriven Personalization across different educational levels. Accordingly, and based on the results, Hypothesis 5 is partially supported. The impact of AI-Driven Personalisation significantly varies across different groups using specialized platforms and different age groups, but does not vary significantly across different educational levels. Hypothesis 6: The impact of Eco-Consciousness significantly varies across different demographic groups of Age, Educational Level, and Gender. Table 12 presents the results of one-way ANOVAs to examine whether the impact of EcoConscious Behaviour varies across different demographic groups: Age, Educational Level, and Gender. The F-statistic is 17,218 with a p-value of 0.000, indicating a significant difference in the impact of Eco-Conscious Behaviour across different age groups. The F-statistic is 9,553 with a p-value of 0.000, suggesting a significant difference in the impact of Eco-Conscious Behaviour across different educational levels. The F-statistic is 3,301 with a p-value of 0.071. While this is marginally significant, it suggests a possible trend towards a difference in the impact of Eco-Conscious Behaviour across different gender groups. Source: The author based on SPSS results Based on the results, Hypothesis 6 is partially supported. The impact of Eco-Conscious Behaviour significantly varies across different age groups and educational levels, but there is only marginal evidence for a difference across gender groups. Hypothesis 7: The impact of Traveller Satisfaction significantly varies across different demographic groups of Age, Educational Level, and Gender. Table 13 presents the results of one-way ANOVAs to examine whether the impact of Traveler Satisfaction varies across different demographic groups: Age, Educational Level, and Gender. The F-statistic is 12,198 with a p-value of 0.000, indicating a significant difference in the impact of Traveler Satisfaction across different age groups. The F-statistic is 0.262 with a p-value of 0.770, suggesting no significant difference in the impact of Traveler Satisfaction across different educational levels. The F-statistic is 6,341 with a p-value of 0.013, indicating a significant difference in the impact of Traveler Satisfaction across different gender groups. Source: The author based on SPSS results Consequently, Hypothesis 7 is partially supported. The impact of Traveler Satisfaction significantly varies across different age groups and gender groups, but does not vary significantly across different educational levels. Hypothesis 8: The Daily green behaviours and public self-awareness will moderate the relationship between AI-Driven Personalisation and traveller Eco-Consciousness Behaviour. Table 14 presents the coefficients for a regression model predicting Eco-Conscious Behaviour, including AI-Driven Personalisation, DB_PS (a construct related to destination-based preferences and services), and their interaction term as predictors. The standardized beta coefficient of 0.392 for AI-Driven Personalisation is positive and significant, suggesting a direct positive relationship with Eco-Conscious Behaviour. The standardized beta coefficient of 0.152 for DB_PS is positive but not significant, indicating that while it has some influence on Eco-Conscious Behaviour, it’s not a strong predictor. Furthermore, the standardized beta coefficient of -0.150 for the interaction term (AI-Driven Personalisation * DB_PS) is negative and significant. This suggests that the relationship between AI-Driven Personalisation and Eco-Conscious Behaviour is moderated by DB_PS. Source: The author based on SPSS results Then, Hypothesis 8 is supported. The results indicate that the relationship between AIDriven Personalization and Eco-Conscious Behaviour is indeed moderated by DB_PS. Specifically, the positive impact of AI-Driven Personalisation on Eco-Conscious Behaviour is likely to be stronger when DB_PS is lower. Hypothesis 8 is supported. The results indicate that the relationship between AI-Driven Personalisation and Eco-Conscious Behaviour is indeed moderated by DB_PS. Specifically, the positive impact of AI-Driven Personalisation on Eco-Conscious Behaviour is likely to be stronger when DB_PS is lower. Figure 2: Interactions between AI-Driven Personalisation, Daily green behaviours, and Public self-awareness. Source: Slope visual analysis is generated using James Gaskin’s Excel StatTool (StatWiki, 2024) The moderation plot shown in Figure 2 confirms that Daily Green Behaviours and Public Self-Awareness indeed moderate the relationship between AI-Driven Personalisation and Traveler Eco-Consciousness Behaviour. This suggests that the effectiveness of AI-Driven Personalisation in promoting eco-conscious behaviour may depend on the individual traveller’s existing level of environmental awareness and engagement. Figure 3: Final conceptual framework. Source: The author based on SPSS results Conclusion This study aimed to investigate the impact of AI-Driven Personalisation on Traveler Satisfaction and Eco-Conscious Behaviour among Algerian travellers. Through a comprehensive analysis of survey data, several key findings have emerged. AI-Driven Personalisation and Traveler Satisfaction: Research indicates that AI-Driven Personalisation has a significant positive impact on traveller satisfaction. This indicates that personalized experiences enhance the overall travel experience for Algerian travellers. AI-Driven Personalisation and Eco-Conscious Behaviour: AI-Driven Personalisation was also shown to have a positive impact on Eco-Conscious Behaviour among travellers. This indicates that personalized experiences can support travellers to adopt more sustainable attitudes. Moderating Effects: The relationship between AI-Driven Personalisation and Eco-Conscious Behaviour was found to be moderated by Daily Green Behaviours and Public Self-awareness. The travellers with higher levels of environmental awareness and involvement exhibit eco-conscious behaviour when faced with personalized experiences. Demographic Variations: The impact of AI-Driven Personalisation and Eco-Conscious Behaviour varied through different demographic groups. Age and platform usage were found to influence the effectiveness of these factors. Finally, the findings of our study show that AI-Driven Personalisation can be a valuable tool to promote sustainable tourism and enhance traveller satisfaction. By personalizing experiences to travellers’ preferences and needs, tourism service providers can encourage travellers to adopt more eco-conscious behaviours and attitudes to ensure a positive and memorable journey. Challenges and Considerations While AI-Driven Personalisation offers significant potential impact on travellers’ satisfaction and eco-consciousness attitudes, it’s important to address several challenges, and tourism providers must take into account data privacy, ethical implications, technical limitations, and user acceptance. And the travel industry can harness the power of AI to promote sustainable tourism and create memorable experiences for travellers. Future Scope of Research The provided recommendations advocate for a comprehensive approach to AI-Driven Personalisation in eco-conscious travel. They suggest conducting long-term studies to assess its impact, developing ethical frameworks, ensuring scalability and affordability, considering cross-cultural perspectives, integrating with emerging technologies, fostering collaboration, and establishing global governance. By addressing these areas, the tourism industry can effectively leverage AI to promote sustainable practices while ensuring ethical and responsible travel experiences. Bibliography: Akter, S., Babu, M. M., Hani, U., Sultana, S., Bandara, R., & Grant, D. (2024). Unleashing the power of artificial intelligence for climate action in industrial markets; Industrial Marketing Management. Available at: <https://doi.org/10.1016/j.indmarman.2023.12.011>; Almquist, Y. B., Signild Kvart, Brännström, L. (2020). A practical guide to quantitative methods with SPSS. 3787995 Bytes. Available at: <https://doi.org/10.17045/STHLMUNI.10321829>; com Partners (Director). (2023, October 10). New & Next at Booking.com [Video recording]. 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Available at: <https://statwiki.gaskination.com/index.php?title=Main_Page; Su, L., Li, M., Wen, J., He, X. (2024). How do tourism activities and induced awe affect tourists’ pro-environmental behavior? Tourism Management, 106, 105002. Available at: <https://doi.org/10.1016/j.tourman.2024.105002>; (2015). What Is Ecotourism. The International Ecotourism Society. Available at: <https://ecotourism.org/what-is-ecotourism/>; UNEP & WTO. (2005). Making Tourism more Sustainable (United Nations). UNESCO World Heritage centre. (n.d.). World Heritage List. Available at: <https://whc.unesco.org/en/list> (Last access: 16.09.2024). Footnotes [1] Malik, S., Muhammad, K., Waheed, Y. (2024). Artificial intelligence and industrial applications - A revolution in modern industries. Ain Shams Engineering Journal, 15(9), 102886. Available at: <https://doi.org/10.1016/j.asej.2024.102886>. [2] Jorzik, P., Antonio, J. L., Kanbach, D. K., Kallmuenzer, A., Kraus, S. (2024). Sowing the seeds for sustainability: A business model innovation perspective on artificial intelligence in green technology startups. Technological Forecasting and Social Change, 208, 123653. Available at: <https://doi.org/10.1016/j.techfore.2024.123653>. [3] UNEP & WTO. (2005). Making Tourism more Sustainable (United Nations). [4] Majid, G. M., Tussyadiah, I., Kim, Y. R., Pal, A. (2023). Intelligent automation for sustainable tourism: A systematic review. Journal of Sustainable Tourism, 31(11), 2421– 2440. Available at: <https://doi.org/10.1080/09669582.2023.2246681>. [5] Chen, G., Peng, J. (2023). Promoting sustainable tourism destinations: Support and its role in tourist environmentally responsible behaviour. Environment, Development and Sustainability. Available at: <https://doi.org/10.1007/s10668-023-04095-y>. [6] TIES. (2015). What Is Ecotourism. The International Ecotourism Society. Available at: <https://ecotourism.org/what-is-ecotourism/>. [7] Kumar, P., Aggarwal, B., Kumar, V., Saini, H. (2024). Sustainable tourism progress: A 10-year bibliometric analysis. Cogent Social Sciences, 10(1), 2299614. Available at: <https://doi.org/10.1080/23311886.2023.2299614>. [8] Akter, S., Babu, M. M., Hani, U., Sultana, S., Bandara, R., Grant, D. (2024). Unleashing the power of artificial intelligence for climate action in industrial markets. [9] Dalla Vecchia, A., Migliorini, S., Quintarelli, E., Gambini, M., Belussi, A. (2024). Promoting sustainable tourism by recommending sequences of attractions with deep reinforcement learning. Information Technology & Tourism, 26(3), 449–484. Available at: <https://doi.org/10.1007/s40558-024-00288-x>. [10] Milton, D. T. (2024). Artificial Intelligence Transforming Hotel Gastronomy: An In-depth Review of AI-driven Innovations in Menu Design, Food Preparation, and Customer Interaction, with a Focus on Sustainability and Future Trends in the Hospitality Industry. International Journal for Multidimensional Research Perspectives, 2(3), Article 3. Available at: <https://doi.org/10.61877/ijmrp.v2i3.126>. [11] Ozcan, B., Bozoklu, S., Khan, D. (2021). Tourism Sector and Environmental Quality: Evidence from Top 20 Tourist Destinations. In D. Balsalobre-Lorente, O. M. Driha, & M. Shahbaz (Eds.), Strategies in Sustainable Tourism, Economic Growth and Clean Energy. Springer International Publishing, 39–66. Available at: <https://doi.org/10.1007/978-3-030-596750_3>. [12] Sahabuddin, M., Alam, Md. S., Nekmahmud, Md. (2024). How do perceived and environmental values influence tourist satisfaction, loyalty, and environmental awareness? Environment, Development and Sustainability. Available at: <https://doi.org/10.1007/s10668-024-050943>. [13] Chen, G., Peng, J. (2023). Promoting sustainable tourism destinations: Support and its role in tourist environmentally responsible behaviour. Environment, Development and Sustainability. Available at: <https://doi.org/10.1007/s10668-023-04095-y>. [14] Ku, E. C. S., Chen, C.-D. (2024). Artificial intelligence innovation of tourism businesses: From satisfied tourists to continued service usage intention. International Journal of Information Management, 76, 102757, Available at: <https://doi.org/10.1016/j.ijinfomgt.2024.102757>. [15] Escobar-Farfán, M., Cervera-Taulet, A., Schlesinger, W. (2024). Destination brand identity: Challenges, opportunities, and future research agenda. Cogent Social Sciences, 10(1), 2302803. Available at: <https://doi.org/10.1080/23311886.2024.2302803>. [16] Kvasova, O. (2015). The Big Five personality traits as antecedents of eco-friendly tourist behavior. Personality and Individual Differences, 83, 111–116. Available at: <https://doi.org/10.1016/j.paid.2015.04.011>. [17] Su, L., Li, M., Wen, J., He, X.2024. How do tourism activities and induced awe affect tourists’ pro-environmental behavior? Tourism Management, 106, 105002. Available at: <https://doi.org/10.1016/j.tourman.2024.105002>. [18] Ribeiro, M. A., Seyfi, S., Elhoushy, S., Woosnam, K. M., Patwardhan, V. (2023). Determinants of Generation Z pro-environmental travel behaviour: The moderating role of green consumption values. Journal of Sustainable Tourism. Scopus Available at: <https://doi.org/10.1080/09669582.2023.2230389>. [19] Sadiq, M., Adil, M., Paul, J. (2022). Eco-friendly hotel stay and environmental attitude: A value-attitude-behaviour perspective. International Journal of Hospitality Management, 100, 103094. Available at: <https://doi.org/10.1016/j.ijhm.2021.103094>. [20] Statista. (2024, July 12). Booking.com: Total website visits worldwide 2024. Statista. Available at: <https://www.statista.com/statistics/1294912/total-visits-to-booking-website/>. [21] Booking.com Partners (Director). (2023, October 10). New & Next at Booking com [Video recording]. Available at: <https://www.youtube.com/watch?v=_Jsdc7mZHg8>. [22] Skyscanner. (2023, December 15). Our commitment to net zero. Available at: <https://www.skyscanner.net/media/sustainability/our-commitment-to-net-zero>. [23] ForwardKeys. (2018, June 19). Skyscanner and ForwardKeys join forces to reveal the future of regional travel behaviour. Available at: <https://forwardkeys.com/skyscannerand-forwardkeys-join-forces-to-reveal-the-future-of-regional-travel-behaviour/>. [24] Mta.gov.dz. (2008). Le Schéma Directeur d’Aménagement Touristique 2030. Ministère de l’Aménagement du Territoire, de l’Environnement et du Tourisme. Available at: <https://www.mta.gov.dz/le-schema-directeur-damenagement-touristique-030/?lang=fr>. [25] Mta.gov.dz. (2023). Connaitre l’algerie. Available at: <https://www.mta.gov.dz/connaitrelalgerie/?lang=fr>. [26] UNESCO World Heritage centre. (n.d.). World Heritage List. UNESCO World Heritage Centre. Available at: <https://whc.unesco.org/en/list/> (Last access: 16.09.2024). [27] Almquist, Y. B., Signild K., Brännström, L. (2020). A practical guide to quantitative methods with SPSS. 3787995 Bytes. Available at: <https://doi.org/10.17045/STHLMUNI.10321829>.
Labour Market of Georgia: Overview and Anticipated Evolution
This study examines the trends and developments in Georgia’s labor market, with a primary focus on the period from 2013 to 2023. It is based on an analysis of current labor market conditions and relevant literature. The study identifies key drivers influencing the labor market, with particular emphasis on employers’ expectations. Notably, expanding digital access and the adaptation to advanced technologies are recognized as significant factors impacting the labor market. Additionally, the study outlines the most in-demand skills for the future workforce, which include creative and analytical thinking, technological literacy, systems thinking, expertise in artificial intelligence (AI) and big data, as well as competencies related to management, leadership, and cybersecurity. In the process of shaping future labor market policies, special attention is given to the influence of technological factors on the nature and roles of future work. The paper references studies that substantiate the growing impact of artificial intelligence on labor market dynamics. The conclusion emphasizes the necessity for coordinated approaches and strategies between labor market institutions and the education system to enhance labor market conditions and address existing and future skill mismatches. It is recommended that active labor market policies be grounded in a detailed and systematic study of anticipated labor market developments. Keywords: Future demands for skills and jobs, higher and self-employed, job creator macrotrends, employment and unemployment, drivers of changes. Introduction Reducing high unemployment rates and ensuring effective employment of the population requires the implementation of a comprehensive approach. To achieve these objectives, any policy, program, or project must involve a thorough study and analysis of the current state of the labor market. Furthermore, to ensure the desired outcomes, it is crucial to assess and forecast anticipated changes in the labor market. Addressing issues related to unemployment and employment of the population is complicated by the fact that numerous factors influence the labor market. Labor markets in developing countries exhibit a unique dynamism, and Georgia is no exception. For over three decades, the labor market in Georgia has been characterized by high unemployment rates and ineffective employment strategies. A significant recent factor that has dramatically impacted Georgia’s labor market is the COVID-19 pandemic. Although there have been some positive developments in reducing unemployment during the post-pandemic period, the labor market continues to face substantial challenges. Alongside a detailed study of the current situation, attention must be given to economic, technological, local, and global factors that may either exacerbate existing problems in Georgia’s labor market or, conversely, create new opportunities to improve labor market conditions. This is particularly relevant in the case of advanced technologies and digital work[1] platforms (Kvirkvaia, 2023). Therefore, it is crucial to conduct a comprehensive investigation into anticipated changes related to future skill requirements, labor market drivers, evolving workplace roles, strategies for preparing an adequate workforce, and other relevant factors. Methodology This study aims to analyze the current state of the labor market, with a focus on the factors influencing its dynamics and the directions of its changes. Utilizing the desk research method, the study draws upon official statistical data, publications from local and international organizations, and research conducted by both foreign and Georgian scholars. This comprehensive approach ensures an in-depth examination of the labor market dynamics and the various influences shaping its future. Additionally, the study incorporates findings from the report[2] on the development of skills forecasting in the labor market of Georgia, created in collaboration with Cambridge Econometrics and the Ministry of Economy and Sustainable Development of Georgia (MOESD) (Suta, et al., 2022). Special attention is given to the study results published by the World Economic Forum, which are related to ongoing processes in global labor markets. At the end of the paper, the research findings are summarized, and key conclusions are presented. This research serves as a foundational basis for a comprehensive study to be conducted on the labor market in the future. Overview of the Labor Market in Georgia To analyze the current state of the labor market, the most critical indicators are the unemployment and employment rates of the working-age population. Monitoring changes over time is also essential to identify trends within the labor market. It should be noted that official data on workforce indicators is based on established methodologies and adheres to international labor statistics practices. The methodologies and standards employed by the country’s official agency in workforce studies are of paramount importance, as modifications of these methodologies and standards can lead to significant variations in the reported indicators. A good example of this is the introduction of new standards by the International Labour Organization in Georgia in 2020, which were implemented by the National Statistics Office of Georgia (National Statistics Office of Georgia, 2025). This change led to notable alterations in workforce indicators. While the relevance of official statistical data warrants separate discussion, for this research, official statistical data, along with other materials, provide valuable insights into the current state of the labor market in Georgia. One particular useful set of statistical information is the official data on population and workforce indicators[3] for the last ten years (see Table 1). Table 1: Population and Labour Force Indicators* (thousand persons) Source: The table is compiled according to the data of the National Statistical Service of Georgia Among workforce indicators, the most significant are the dynamics of unemployment and employment levels over the past 10 years. According to official data, the lowest unemployment rate recorded between 2014 and 2023 occurred in 2023, while the highest rate was observed in 2014. It is noteworthy that, according to official data, unemployment has been steadily decreasing since 2014, except during the COVID-19 pandemic period. During the reporting period, the absolute number of unemployed individuals decreased by 112,000, and preliminary official data for the first three quarters of 2024 indicate that the number of unemployed individuals has decreased even further. The unemployment rate varies significantly across age groups (see Figure 1). For instance, in 2023, the unemployment rate among young people aged 20 to 24 was notably high, reaching 32 percent, which is nearly double the overall unemployment rate for the country in the same year. Additionally, unemployment rates were also elevated among the 25-29 and 30-34 age groups, both exceeding 20 percent. Figure 1 Source: National Statistical Service of Georgia Unemployment and employment data categorized by educational attainment level can provide valuable insights into the labor market. Typically, these statistics illustrate how different levels of education influence job prospects and employment stability. Data from 2020-2023 indicate that the highest unemployment rate by educational attainment level is observed among individuals with Primary or Lower Secondary level, followed by those with Upper Secondary level. Next is Vocational education graduates, and the lowest unemployment rate is among individuals with Higher education. According to official data, a positive correlation is confirmed between employment levels and educational attainment. From 2020 to 2023, it is evident that higher levels of education correspond to increased employment rates within the workforce. Furthermore, employment levels among young people also vary by gender. For example, in 2023, the employment rate for graduates aged 20 to 34 was 54.8 percent. Within this group, the employment rate for women was 50.4 percent, whereas for men it was nearly 59 percent. Over the past decade, the size of the workforce has remained relatively stable or has experienced a slight decline, with the participation rate being approximately 53 percent. During the same period, the number of individuals outside the labor force has also remained nearly constant. It can be assumed that the stagnation of both the labor force and those outside of it may be due to the low population growth rate and migration factors. Both phenomena are associated with numerous negative consequences for the population of Georgia. A positive development is the increase in the number of employed individuals by approximately 80,000, primarily attributed to the rise in hired employees. However, the increase in the number of employees was mainly due to the growth in the public sector workforce, which does not guarantee long-term effective employment. This is confirmed by the data from the National Statistics Office of Georgia (2025) on the distribution of employment by ownership forms,[4] which indicates that employment across all sectors generally increased by approximately 12% from 2014 to 2023, including about 27% in the public sector, while in other sectors only by about 7%. Despite a certain reduction, the number of self-employed people remains high (about 400 thousand). Likely, some of those self-employed individuals do not represent the actual employees or, at best, fall into the category of ineffective employees[5] (Kvirkvaia & Shengelia, 2024). Overall, the inefficiency of employment in Georgia is also reflected in the distribution of employees by type of economic activity, where the largest share is comprised of those employed in agriculture. Expected Changes in the Labor Market In the context of globalization, the labor market of any country, including Georgia, evolves under the influence of international processes and changes. Therefore, to study the expected changes and development directions in the labor market, it is beneficial to consider the findings from research conducted at both international and national levels. In this regard, the fourth edition of the Future of Jobs[6] report, published by the World Economic Forum (2023), holds significant importance. This edition is based on a survey conducted across 45 countries, including Georgia. These countries’ economies account for 88% of the global GDP. The research covered 27 industry clusters and 803 companies, employing over 11 million people in total. The survey includes questions about broad trends and technology developments, their impact on jobs and skills, and the strategies businesses plan to implement to transform their workforce. The results of the research are based on the expectations of the surveyed companies regarding future changes in the labor market. Since the demand for labor is derived from the demand for a firm’s output, changes in the labor market generally have a significant impact on businesses due to ongoing transformations. In terms of factors influencing business transformation, respondents in the Future of Jobs Report 2023 indicated that increased adoption of new and disruptive technologies, along with increased access to digital technologies, are likely to drive organizational change. These trends are expected to impact more than 86% of organizations surveyed. Among the factors driving changes within organizations, the broader application of Environmental, Social, and Governance (ESG) standards is also significant (80.6%). According to the respondents, the next most important trends in driving changes are macroeconomic trends, specifically the rising cost of living for consumers (74.9%) and slower global economic growth (73.0%). The report presents the surveyed organizations’ assessment of individual macrotrends as job creators over five years. According to their expectations, the highest percentage of respondents identifies the macrotrend of increased adoption of new and frontier technologies as the most significant job creator. However, a significant portion of respondents also classify the same macrotrend as a job displacer. Therefore, despite the positive net effect of the increased adoption of new and frontier technologies on job growth, more significant net job creators in the future are anticipated to be investments that facilitate the green transition of businesses, the broader application of ESG standards, and the localization of supply chains. In the World Economic Forum report, respondents from Georgia exhibit somewhat different expectations regarding job creators compared to the global perspective. For example, according to respondents from Georgia, the positive net effect (job creator minus job displacer) of the macrotrend of broadening digital access is 60%, whereas globally, the same indicator is almost half at 33.7%. Such differing expectations may be due to a relative lag in the adoption of digital technologies in Georgia compared to other countries. Nevertheless, Georgian respondents anticipate an increase in the utilization of digital technologies in the future and consider it a significant influencing factor on the labor market. The impact of technology on the labor market is particularly noteworthy among macrotrends, as understanding how technology impacts labor markets is critical for facilitating transitions from declining jobs to future employment opportunities. The majority of surveyed organizations (75% and more) anticipate the adoption of technologies such as digital platforms and apps, education and workforce development technologies, big-data analytics, cloud computing, encryption and cybersecurity, e-commerce and digital trade, artificial intelligence, and so on by 2027. In terms of the impact of technology on the labor market, particularly regarding job creation, the expectations for the next five years are almost identical both globally and in Georgia. Respondents from Georgia also consider e-commerce and digital trade, big-data analytics, distributed ledger technology (e.g., blockchain), encryption and cybersecurity, as well as digital platforms and apps, and so on, as significant job creators in the future. Regarding the anticipated creation of new jobs in the labor market, forecasts for the demand for green jobs are significant. Specifically, according to a recent estimate by the International Energy Agency[7] (IEA), a green-recovery scenario could result in an additional 3.5% growth in global GDP, alongside a net employment impact of 9 million new jobs created each year. Globally, the green transition could create 30 million jobs in clean energy, efficiency, and low-emission technologies by 2030. In order to adapt to future changes in the labor market, it is essential to identify the skills that will be increasingly in demand. More than half of the surveyed respondents recognize the basic skills whose importance is expected to rise between 2023-2027 (see table 3). Compared to the skills in demand in 2023, the importance of Creative and Analytical thinking will increase even more in the future. Table 2: Required skills (2023-2027) Authors elaboration. Source: World Economic Forum, Future of Jobs Survey 2023. When comparing the two fundamental skills, creative and analytical thinking, respondents indicate that the importance of creative thinking is expected to grow more significantly in the future than that of analytical thinking skills. Nevertheless, both skills rank at the top of the list of the most important competencies for their respective periods. Additionally, respondents anticipate an increase in the importance of skills such as artificial intelligence (AI) and big data, systems thinking, technological literacy, curiosity and lifelong learning, motivation, and self-awareness, among others. Forecasts regarding absolute job growth provide valuable insights. According to the Future of Jobs Report 2023, based on the study of 673 million employees using a global dataset of the International Labor Organization, the following forecasts are given regarding the absolute growth of jobs: Over the next five years (2023-2027), 69 million jobs will be created, and 83 million jobs will be lost. Thus, the study indicates a net loss of 14 million jobs, which constitutes 2% of the 673 million employees studied; According to the same study, the highest absolute job creation over the next five years is expected for Agricultural Equipment Operators, Heavy Truck and Bus Drivers, and Vocational Education Teachers. The greatest reduction in employment in absolute terms is expected for Data Entry Clerks, Administrative and Executive Secretaries, and Accounting, Bookkeeping, and Payroll Clerks. To forecast changes in the labor market, it is crucial to comprehend the evolving division of tasks performed by humans compared to those executed by machines and algorithms. According to the Future of Jobs 2023 report, organizations currently estimate that machines perform over one-third of all business-related tasks, while humans handle the remaining nearly two-thirds. Employers anticipate that automation will exceed 40% by 2027. The survey indicates that by 2027, 35% of reasoning and decision-making tasks and 65% of information and data processing tasks will be automated. Furthermore, the study indicates that 44% of workers’ skills are anticipated to become obsolete within the next five years, according to surveyed companies. Survey participants estimate that 60% of workers will require training by 2027. In response to these changes, companies plan to prioritize learning initiatives, on-the-job training, and process automation. Most companies expect to see a return on their investment in skills training within a year, whether through increased productivity, enhanced employee satisfaction, or greater role flexibility. In addition to the findings of the World Economic Forum’s research, numerous other papers and studies have highlighted the impact of technology on the labor market. Recent studies focusing on the short-term and long-term expectations regarding the impact of technologies, particularly artificial intelligence (AI), are particularly noteworthy. Regarding this, researchers (McRae et al., 2024) assert that “AI will create, not diminish, workforce opportunity”. A 2023 Gartner survey found that 22% of employees expected AI to replace their job within the next five years. Despite this anxiety, it is anticipated that, in the short to medium term, generative AI (GenAI) will not replace many jobs; rather, it will lead to the redesign of jobs to include new responsibilities, such as interacting with GenAI tools. “Gartner predicts that GenAI will be involved in 70% of text- and data-heavy tasks by 2025, up from less than 10% in 2023”.[8] Furthermore, the International Labour Organization (ILO, 2024)[9] has placed significant emphasis on the impact of artificial intelligence on the labor market in its 2024 report. The report states, “Many countries, including developing ones, have adopted policies to encourage the adoption of AI. However, in the current climate of geopolitical tensions, technological transfer seems to be facing intensifying barriers, which will hamper leapfrogging strategies in developing countries to harness the benefits of these digital technologies”. Researchers from Georgia (Abuselidze & Mamaladze, 2021) have dedicated a paper to examining the impact of artificial intelligence on the labor market and employment. According to their conclusion, “Artificial Intelligence can promote economic growth, create new jobs and employment. The destruction mechanism is a replacement effect, where new technology will replace old technology, and hence, changing old technology jobs will inevitably lead to unemployment. Technological advances will reduce costs and make resources more efficient”.[10] Alongside certain global trends, there are labor market drivers that are specific to particular countries or regions. For instance, a group of authors (Hodge et al., 2023)[11] asserts that “The US labor market has experienced significant changes since the turn of the century. Some of the most profound changes were driven by technology, others shaped by business, policy, and shifting social norms. Two enormous economic shocks, the Great Recession of 2007–2009 and the pandemic recession of 2020, also drove change in the economy and labor market. At the time of this writing, the Federal Reserve has been working to bring down inflation rates that reached a 40-year high last year. These major developments have transformed the nature of work and opportunities for American workers”. Based on the objectives of our research, among the recently published works and studies on the Georgian labor market, it is worth noting the report “Development of a Macroeconomic Skills Forecasting Model for Georgia” (Suta, et al., 2022). This report[12] was developed through a collaboration between the Ministry of Economy and Sustainable Development of Georgia and the international consulting company Cambridge Econometrics. Cambridge Econometrics was tasked with creating the skills forecasting model in close consultation with the National Bank and the National Statistics Office of Georgia. This document represents the first assessment of the future skills challenges facing the Georgian economy over the next five years (2022-2027). Based on the models developed within the framework of the work, a macroeconomic forecast is made in three key areas: the direction of labor demand (employment forecast by sector, occupation, and qualifications); the direction of labor supply (labor supply forecast by age, gender, and qualification); and replacement needs forecast by occupation. The models are constructed based on various assumptions. One such assumption is that by 2027, the working-age population (ages 15-64) will decrease by 12 thousand individuals. Under macroeconomic assumptions, starting in 2024, GDP growth is expected to remain stable at approximately 5% per year, with each major component of spending expected to grow at the same rate. According to this assumption, GDP is expected to increase by 30 percent by 2027 compared to 2022. Based on the sector growth estimates, the biggest sectors (for 2022-2027) are Agriculture, Manufacturing, Construction, Wholesale and Retail Trade, and Transport. Together, these five sectors are expected to account for nearly 60% of gross output. Over the forecast period (2022-2027), employment in Georgia is projected to grow at an average annual rate of 1.3%. In absolute terms, this translates to an expected increase of approximately 10,000 workers per year. By 2027, employment in Georgia is forecasted to reach 1.36 million people, representing a 6.9% growth compared to 2022. Most sectors are anticipated to experience employment growth during this period, except for agriculture, which is expected to decline by over 11,000 workers. Declines are also expected in manufacturing. The employment decrease in Agriculture and Manufacturing can be attributed primarily to the robust growth in labor productivity within these sectors. Notably, the largest absolute increase in employment is expected in Public Administration and Defense, Transport and Storage, and Education. Additionally, smaller sectors like Mining and Quarrying and Activities of Households as Employers are expected to exhibit strong percentage growth. The developed document contains critical information regarding the future labor market of Georgia, including anticipated job openings or vacancies. Two primary drivers of those directions are expansion demand* (resulting from changes in the size and structure of the economy); replacement demand (the need to replace people who may be leaving their current jobs). Forecasts of job openings are based on assumptions regarding changes in sectoral employment by occupation. Additionally, these forecasts consider trend analyses from countries similar to Georgia (such as Bulgaria and Romania), which have more readily available data, as well as expert estimates. The occupations considered are the nine ISCO 1-digit occupations (ILO, 2025).[13] According to the model developed in the report, in most occupations, replacement demand constitutes the majority of job openings. Overall, replacement demand and expansion demand are expected to account for 70% and 30% of job openings respectively (see figure 2). Productivity in the agriculture sector grows at a rate faster than output, the demand for Skilled Agricultural, Forestry, and Fishery Workers is expected to decrease, resulting in no anticipated job openings in that occupation. The occupations with the largest number of job openings coming from new jobs are Professionals and Service and sales workers, accounting for 25% and 21%, respectively, of total job openings. Furthermore, the Professionals category is where expansion demand accounts for the largest share of job openings (45%). The occupational structure of some sectors is kept unchanged due to a lack of evidence regarding potential future trends. As well as insufficient data on possible future trends. Figure 2: Job openings by broad occupational group, 2022-27 Source(s): Cambridge Econometrics. The paper outlines the expected labor supply based on age, gender, and qualification. It also compares labor demand by qualification to assess potential mismatches between skill supply and demand. Labor supply projections are based on population projections that do not consider any changes in labor force participation rates (by age and sex) for the period from 2022 to 2027. Consequently, the projected changes in labor supply are attributed solely to demographic shifts. The total labor force is expected to decline by approximately 66,000 individuals (2.5%) over the period from 2022 to 2027. The report compares the projected supply (labor force) and demand (employment) across various qualifications and illustrates the future supply available (i.e., supply minus demand). These forecasts indicate a potential shortage of highly* qualified workers in the medium term. Consequently, middle-skilled workers may occupy high-skilled positions, while low-skilled workers, whose supply is expected to increase-may occupy medium-skilled positions, potentially leading to a skills mismatch that can impact productivity. Conclusions Analysis of the existing statistical data on Georgia’s labor market shows that the overall unemployment rate, particularly among youth age groups, is significantly higher than the natural rate of unemployment. A positive development is that, according to official statistics, over the past 10 years, the number of employed individuals has increased, mainly due to a rise in the number of hired employees and a simultaneous decrease in the number of self-employed individuals. However, the number of self-employed individuals remains relatively high. Despite certain changes, the share of those employed in agriculture continues to be substantial. Regarding employment by sectors, over the past five years, the Georgian economy has experienced significantly higher percentage growth in the public sector compared to other sectors, which only provides a temporary alleviation of the unemployment problem. Looking ahead, a shortage of highly qualified labor coupled with a surplus of low-qualified labor is expected to emerge alongside a reduction of the labor force. This situation will exacerbate existing mismatches in the future labor market. In line with global processes, the primary factors influencing the development and changes in the Georgian labor market over the next five years will include expanding digital access, adaptation to modern advanced technologies, and projected economic growth. Additionally, other specific factors that will influence changes in Georgia’s labor market in the future include negative demographic and migration trends, as well as the prospect of joining EU structures etc. The Georgian labor market is expected to experience increased demand for the following skills: creative and analytical thinking, technological literacy, systems thinking, expertise in AI and big data, skills related to management, leadership, and cybersecurity. In developing labor market policies and programs in Georgia, it is essential to pay special attention to technological factors, such as artificial intelligence, which will influence not only the structure of employment but also the functions and roles performed by individuals in the workplace in the future. To ensure effective employment, the primary focus should shift from the public sector to fostering growth in the private sector, as the private sector is poised to play a crucial role in providing long-term, effective employment opportunities. Studying and forecasting the future development of the labor market should be prioritized as a pressing issue in the country. The primary users of labor market forecasts should be educational institutions (higher, professional, secondary). These institutions must provide an adequate labor market supply that aligns with the forecasted demand in a timely manner. Decision-makers at the public level should facilitate the alignment of skills demanded and supplied in the labor market. They should also support the study of future labor market development. This must be part of active labor market policy. To address the current and projected mismatches in the labor market in Georgia, labor market institutions and the education system should respond with a unified strategy and action plans to consider both global and local factors influencing the evolution of the labor market. To quickly adapt to changes in the labor market, private companies should develop a flexible system of on-site education and training, thereby reducing reliance on external sources of labor supply. Bibliography: Cambridge Econometrics (Belgium). Available at: <https://www.camecon.us> [Last Access: 01.12.2025]; European Training Foundation. (2021). The future of work: New forms of employment in the Eastern Partnership countries: Platform work. Turin: ETF. Available at: <https://www.etf.europa.eu/sites/default/files/2021-07/future_of_work_platform_work_in_eap_countries.pdf> [Last Access: 01.12.2025]; European Commission, Directorate-General for Employment, Social Affairs and Inclusion. (2021). Digital labour platforms in the EU: Mapping and business models: Final report. Publications Office. Available at: <https://data.europa.eu/doi/10.2767/224624> [Last Access: 01.12.2025]; Gartner, Inc. Available at: <https://www.gartner.com>; Hodge, N., Andreason, S., Van Horn, E. C. (2023). The labor market, then and now: The first two decades of the 21st century, part one. Available at: <https://doi.org/10.29338/wc2023-02>; Howson, K., Ferrari, F., Salem, N., Johnston, H., Katta, S., Heeks, R., Graham, M. (2022). Driving the digital value network: Economic geographies of global platform capitalism. Global Networks, 22(4). Available at: <https://doi.org/10.1111/glob.12358>; International Energy Agency. (2020). World Energy Outlook Special Report in collaboration with the International Monetary Fund. Available at: <https://iea.blob.core.windows.net/assets/c3de5e13-26e8-4e52-8a67-b97aba17f0a2/Sustainable_Recovery.pdf>; International Labour Organization. (2024). World Employment and Social Outlook. Available at: <https://doi.org/10.54394/HQAE1085>; International Labour Organization. (n.d.). International Standard Classification of Occupations (ISCO). Available at: <https://ilostat.ilo.org/methods/concepts-and-definitions/classification-occupation/> [Last Access: 01.12.2025]; Kvirkvaia, M. (2023). Digital work platforms in the modern labor market. In M. Kupiek & R. A. Brandmeier (eds.), The digital transformation of Georgia. Cham: Springer. Available at: <https://doi.org/10.1007/978-3-031-26451-1_1>; Kvirkvaia, M., Shengelia, M. (2024). Unemployment and Digital Labor Platforms in Georgia. European Scientific Journal, ESJ, 20(37). Available at: <https://doi.org/10.19044/esj.2024.v20n37p126>; Kvirkvaia, M., Kikutadze, V., Sikharulidze, D., Shaburishvili, S., Charaia, V. (2018). Study of factors affecting young people’s professional orientation in Georgia. Globalization and Business, 3(6). Available at: <https://doi.org/10.35945/gb.2018.06.035>; McRae, E. R., Aykens, P., Lowmaster, K., Shepp, J. (2024). 9 trends that will shape work in 2024 and beyond. Harvard Business Review. Available at: <https://hbr.org/2024/01/9-trends-that-will-shape-work-in-2024-and-beyond> [Last Access: 01.12.2025]; National Statistics Office of Georgia. (2025). Labour Force Indicators. Available at: <https://www.geostat.ge/en/modules/categories/683/Employment-Unemployment> [Last Access: 01.12.2025]; Suta, C.-M., Barbieri, L., Alexandri, E., Thoung, C., Barker, A. (2022). Development of a macroeconomic skills forecasting model for Georgia. Analysis of the labour market for the next 5 years. Cambridge Econometrics and the Ministry of Economy and Sustainable Development of Georgia. Available at: <https://www.lmis.gov.ge/Lmis/Lmis.Portal.Web/Handlers/GetFile.ashx?Type=Content&ID=2a982367-58a7-4744-93a5-14294b1ec451> [Last Access: 01.12.2025]; World Economic Forum. (2023). Future of Jobs Report 2023. Available at: <https://www3.weforum.org/docs/WEF_Future_of_Jobs_2023.pdf> [Last Access: 01.05.2025]. Footnotes [1] Kvirkvaia, M. (2023). Digital work platforms in the modern labor market. In M. Kupiek & R. A. Brandmeier (eds.), The digital transformation of Georgia, pp. 3-22. Cham: Springer. Available at <https://doi.org/10.1007/978-3-031-2641-1_1>. [2] Suta, C.-M., Barbieri, L., Alexandri, E., Thoung, C., Barker, A. (2022). Development of a macroeconomic skills forecasting model for Georgia. Analysis of the labour market for the next 5 years. Cambridge Econometrics and the Ministry of Economy and Sustainable Development of Georgia (MOESD). Available at: <https://www.lmis.gov.ge/Lmis/Lmis.Portal.Web/Handlers/GetFile.ashx?Type=Content&ID=2a982367-58a7-4744-93a5-14294b1ec451> [Last access: 01.12.2025]. [3] National Statistics Office of Georgia. (2025). Labour Force Indicators. Available at: <https://www.geostat.ge/en/modules/categories/683/Employment-Unemployment> [Last Access: 01.12.2025]. * Table 1 presents some labour indicators for the first three quarters of 2024 only, published by the Office for National Statistics during the study period. [4] National Statistics Office of Georgia. (2025). Labor Force Indicators. Available at: <https://www.geostat.ge/en/modules/categories/683/Employment-Unemployment> [Last Access: 01.12.2025]. [5] Kvirkvyaia, M., Shengelia, M. (2024). Unemployment and Digital Labor Platforms in Georgia. European Scientific Journal, ESJ, 20(37), p. 126. Available at: <https://doi.org/10.19044/esj.2024.v20n37p126>. [6] World Economic Forum. (2023). Future of Jobs Report 2023. Available at: <https://www3.weforum.org/docs/WEF_Future_of_Jobs_2023.pdf>. [Last Access: 01.05.2025]. [7] International Energy Agency. (2020). World Energy Outlook Special Report in collaboration with the International Monetary Fund. Available at: <https://iea.blob.core.windows.net/assets/c3de5e13-26e8-4e52-8a67-b97aba17f0a2/Sustainable_Recovery.pdf>. * Listed skills are ranked based on share of organizations surveyed which consider skills to be increasing in importance. [8] McRae, E. R., Aykens, P., Lowmaster, K., Shepp, J. (2024). 9 trends that will shape work in 2024 and beyond. Harvard Business Review. Available at: <https://hbr.org/2024/01/9-trends-that-will-shape-work-in-2024-and-beyond> [Last Access: 01.12.2025]. [9] International Labour Organization. (2024). World Employment and Social Outlook. Available at: <https://doi.org/10.54394/HQAE1085>. [10] Abuselidze, G., Mamaladze, L. (2021). The impact of artificial intelligence on employment before and during pandemic: A comparative analysis. J. Phys.: Conf. Ser. Available at: <https://iopscience.iop.org/article/10.1088/1742-6596/1840/1/012040>. [11] Hodge, N., Andreason, S., Van Horn, E. C. (2023). The labor market, then and now: The first two decades of the 21st century, part one. Available at: <https://doi.org/10.29338/wc2023-02>. [12] Suta, C.-M., Barbieri, L., Alexandri, E., Thoung, C., Barker, A. (2022). Development of a macroeconomic skills forecasting model for Georgia. Analysis of the labour market for the next 5 years. Cambridge Econometrics and the Ministry of Economy and Sustainable Development of Georgia (MOESD). Available at: <https://www.lmis.gov.ge/Lmis/Lmis.Portal.Web/Handlers/GetFile.ashx?Type=Content&ID=2a982367-58a7-4744-93a5-14294b1ec451> [Last Access: 01.12.2025]. * Expansion demand is calculated as employment in 2027 minus employment in 2022. Replacements is calculated as the total number of jobs where the person would need to be replaced over 2022-27. Total job openings is the sum between replacements and new/lost jobs. [13] International Labour Organization. (n.d.). International Standard Classification of Occupations (ISCO). Available at: <https://ilostat.ilo.org/methods/concepts-and-definitions/classification-occupation/> [Last Access: 01.12.2025]. * High- Doctor or equivalent; Master or equivalent; Bachelor or equivalent; Higher professional education or equivalent. Medium- Secondary general education (upper secondary); Vocational education on the base of secondary general education (except higher professional education); Vocational education without secondary general education. Low- Basic general education (lower secondary); Primary education; Pre-primary education; Has no education but can read and write; Illiterate.
Western Aspirations in Georgia’s Winemaking: Status and Prospects
Since its independence from the Soviet Union in 1991, Georgia has sought to revive its wine’s international reputation, diversify wine export destinations, and attract Western wine-loving tourists. Although much still needs to be done to decrease dependence on the Russian market and translate the aspirations into reality, Georgia has progressed in pivoting to the West. The country marketed as the Cradle of Wine has prioritized a Western orientation and holds the prospect of becoming a player in the global wine market. The recommendations provided in this paper are intended to solidify this prospect and break down barriers to entering Western wine and tourism markets. Effective promotion of Georgian wines, the cross-fertilization of wine production and wine and food tourism, and the development of domestic skills and international partnerships should go together with balancing various wine and tourist options. Export diversification should also involve complementing Georgian tradition with innovation, building on Western expertise and funding, and emphasizing premium-level wines, including natural wines. Keywords: Winemaking, Georgia, tourism, wine export. Introduction Georgia – a mountainous country between the Black and Caspian Seas, where Europe meets Asia – is now recognized as a place where wine has been made and celebrated continuously for the last 8000 years.[1] Multidisciplinary international research in archeology, paleoclimatology, chemistry, and biomolecular studies has provided the evidence behind this recognition. It was, however, a Westerner, Hugh Johnson, an English journalist, author, and wine expert, who first referred to Georgia as the Cradle of Wine in his authoritative book Vintage: The Story of Wine.[2] As Westerners were long fascinated with Georgia and interested in its wines, this paper aims to ascertain Western aspirations in Georgia’s winemaking, historically up to the present day, and to analyze the extent to which these aspirations have so far materialized. The Constitution formalized Georgia’s integration into the Euro-Atlantic networks as the country’s objective. It is, therefore, instructive to test the results of pivoting to the West by the wine and tourism sectors, which are central to Georgia’s economy. Wine is the country’s second most exported commodity.[3] Analysis of respective export data and an assessment of wine and food tourism can give a sense of Georgia’s progress in getting closer to the West. The paper also aims to explore the prospects of wine export diversification away from Russia as a risky traditional destination and provide recommendations for smooth and effective reorientation to the new Western markets. The employed research methods include desk research, analysis of Georgian national and international statistics, and the interviews conducted in May-June 2024 with Westerners working in Georgia’s wine industry, as well as Georgian nationals representing the wine business and government agencies. This paper builds on the previous research of Georgia’s winemaking in relation to global wine markets and international trade. Comparison of Georgia with traditional wine-exporting countries and the newcomers in the global wine business has led to an exploration of Georgia’s ability to break through and become a viable competitor.[4] In this regard, the work of Kym Anderson, an Australian economist who specializes in trade policy, is especially relevant to our analysis.[5] Given the attractiveness of the United States (US) large and prosperous consumer market, assessments of the prospects for Georgian wines to enter it and develop a favorable position are also of specific interest.[6] Analysis squarely focused on Georgia’s wine industry revealed its strengths, successes, and potential, suggesting its possible attractiveness to Western investors and producers.[7] As Georgia’s appeal calls for effective marketing of wine, the literature on this topic further informs the chances of the Western orientation of Georgian winemaking and wine exports. For example, it was demonstrated that storytelling as a marketing vehicle, including branding Georgia as the Cradle of Wine, can open new markets by linking the entrepreneurial process to Georgian culture.[8] Bridging winemaking with food and wine tourism was shown to be another strategic marketing tool for Georgia.[9] Vice versa, public relations tips on how to penetrate the Georgian market offered help to Westerners seeking business in Georgia. On a more general note, the exploration of the intersection of wine, society, and business in Georgia enriched the understanding of the national context as well as the influence of geopolitics on Georgia’s interactions with Russia and the West.[10] The paper is organized into six sections. Following the introduction, the second section traces Georgia’s Western aspirations from the international fame of the country’s 19th-century winemaking, through the post-Soviet revitalization of the wine industry, to the present-day targeting of Western markets, accounting for support from Western and international organizations. Russia’s 2006-2012 embargo on Georgian wine and the influence of the Russia-Ukraine war since 2022 are discussed as periods of the swings in Georgia’s trade flows that reinforce the need for wine export diversification. The third section addresses the challenges and opportunities of such diversification. It reveals Georgia’s persistent dependence on Russian demand for its wine. In contrast, it connects the opportunities for diversification away from Russia with the increase of Georgian wine exports to the US and the European Union (EU). The linkages between Georgia’s unique wine culture and wine and food tourism are the theme of the fourth section. Based on the interviews with Westerners working in Georgia’s wine business, the fifth section reports their assessments of the wine industry’s status and prospects. The concluding sixth section focuses on recommendations. Past and Present From the 19th-Century Fame to the Post-Soviet Reconstruction Westerners’ interest in Georgian winemaking traditions and their involvement in the country’s wine industry have roots in the 19th century. Prince Alexander Chavchavadze (1786-1846), a poet, Lieutenant-General, and businessman, introduced Western winemaking technology at his hereditary Tsinandali estate, thus contributing to Georgian wine’s fame in Europe (Prince, 2024). Prince Ivane Bagrationi-Mukhranbatoni (1811-1895) launched a “golden age” of Georgian winemaking by employing a French agronomist, importing the best foreign machinery and tools, and establishing an efficient European-style farm in his estate not far from Georgia’s capital Tbilisi.[11] Mukhranbatoni’s smart integration of Georgian traditions and Western innovation paid off. His “Mukhranuli” brand won a gold medal at the 1889 Paris Exposition Universelle.[12] During the first modern wave of globalization in the 19th century, Georgia managed to supply wines not only to the Russian Empire (to St. Petersburg, Moscow, Warsaw, and the Baltic nations), including the Russian imperial court, but also to Western Europe. Georgian wines received wide international recognition in European capitals, such as Paris and Vienna.[13] In the Soviet period (1921-91), Georgia found itself cut off from international markets and Western technologies and expertise. But following its independence in 1991, the country welcomed international investment and Western winemaking mastery. As an example, the Tsinandali complex associated with the name of Prince Chavchavadze has been, since 2008, under the patronage of the Silk Road Group, which is owned and run by Georgian and European partners.[14] The restoration of the decrepit palace and farm of Prince Mukhranbatoni led to the creation in 2010 of the joint-stock company Château Mukhrani, now owned by the Swedish businessman and founder of the Marussia Beverages Group, Frederick Paulsen.[15] Russia’s Wine Embargo as a Stimulus for Export Diversification Russo-Georgian post-Soviet relations have been marked by hostility and distrust, mostly caused by Russia’s support of the secessionist regions of Abkhazia and South Ossetia. In this atmosphere, in 2006, the Russian government introduced an embargo on Georgian wine under the pretext of its low safety and quality standards. Considering that Russia accounted at that time for 80 percent of Georgian wine exports, the losses from this embargo were extensive. Whereas the share of Georgia’s wine production volume that was exported grew rapidly between 2000-2005 to nearly 50 percent, it collapsed to just 7 percent by 2007.[16] Trading with the West—the European countries and the US—became Georgia’s primary objective in the post-Soviet period, especially during the years of Russia’s wine embargo. There are some achievements in this area. Georgia’s wine exports to the EU countries surged threefold during the decade of 2009-2018, have been expanding since then, and reached $31 million in 2023 (Graph 1). Similarly, Georgia’s wine exports to the US experienced significant growth. They increased 1.5 times from 2009 to 2018 and totaled $5.6 million in 2023 (Graph 2). Western Support for Winemaking in Georgia Western institutions are at the forefront of revitalizing Georgia’s winemaking. The USAID/Georgia’s Economic Security Program, implemented since 2006, has helped the Georgian government with the export of wine to the West, especially the US, and wine-related tourism. In partnership with the Wine Association of Georgia and the Wine Club, USAID supported multiple wineries to enable their readiness to accept tourists and trained wine guides.[17] USAID also partnered with the Georgian Orthodox Church and Badagoni Winery to create the Alaverdi Heritage Trail to increase international tourism.[18] Within the theme of “Unlocking Potential for Georgian Wine in US Markets”, the USAID Agriculture Program has supported small and medium-sized winemaking enterprises in terms of marketing and export. In collaboration with the US-based crowdsourced insights company Premise, USAID explored market trends and consumer preferences from three US markets: California, New York City, and Washington, D.C.[19] It also offered export grants and provided funding for wine degustation and trade missions, and fairs. Likewise, multilateral international organizations have entered Georgia’s wine scene. The World Bank’s Regional Development Project for Georgia has worked to improve infrastructure services and institutional capacity to support the development of a tourism-based economy and cultural heritage circuits in the winemaking Kakheti region. The World Bank has also sought to enhance the institutional capacity and performance of national institutions, such as the Georgia National Tourism Administration (GNTA) and the Agency for Culture Heritage Preservation of Georgia (ACHP).[20] Furthermore, the United Nations’ Food and Agriculture Organisation’s (FAO) “Inclusive Rural Development and Sustainable Agriculture” project has benefited winemaking among other agricultural segments.[21] The international efforts are in tune with the priority of the National Wine Agency (NWA) of Georgia, which is to market Georgian wines to the West, especially European countries and the US. The NWA organizes international exhibitions and presentations of wine, wine festivals, and the International Qvevri Competition, promoting the ancient Georgian method of using terra cotta urns buried in the ground for fermenting crushed grapes. It also participates in wine expos and fairs, supports exchanges among wine professionals across the world, and holds Ghvino (ღVino) Forums of America in collaboration with the America Georgia Business Council.[22] Russia-Ukraine War and its Implications for Georgia’s Wine Exports Following the onset of the Russia-Ukraine war in February 2022, Georgia’s economic dependence on Russia increased compared to previous years. In 2022, about 15 thousand Russian companies were registered in Georgia, 16 times more than the number in 2021. Georgian exports to Russia increased by 6.8%, and imports from Russia rose by 79%.[23] A recovery in tourism and a surge in immigration, financial inflows, and transit trade triggered by the war have boosted GDP growth and fiscal revenues. Although financial inflows sparked by the war have recently moderated, by early 2024, they remained above prewar levels, supporting a positive macroeconomic outlook.[24] Under these war-related economic conditions, Georgia’s dependence on the Russian market in terms of wine exports intensified.[25] In 2023, wine ranked first in the exports of Georgian goods to the Russian market, amounting to $168 million[26] and constituting a 29% increase from 2021. In contrast, wine exports to Ukraine declined by 42% in 2023, compared to 2021, and totaled $14 thousand, or 12 times less than respective exports to Russia (Graph 3). During the same period of 2021-2023, Georgian wine exports to the Commonwealth of Independent States (CIS), countries of the former Soviet Union that include Russia and its allies, increased by 13% and reached $203 million in value. The same exports to the member states of the Organisation for Economic Co-operation and Development (OECD), which is dominated by Western countries, increased by only 5% and reached the $43 million mark in 2023, which is four times less than exports to the CIS (Graph 4). Challenges and Opportunities of Wine Export Diversification Challenges According to a study conducted by the German Economic Team Georgia and ISET-PI, during the years of the Russian embargo (2006-2012), demand for Georgian wine in the EU and non-CIS countries was not able to replace the Russian market (Graph 5).[27] Some observers argued that the Russian embargo was a blessing rather than a curse for Georgia’s winemaking as it stimulated improvement in the quality of wine and diversification of the country’s exports. Most producers were, however, happy to see the ban lifted, which made wine exports to Russia rise substantially (Graph 6). Upon the end of the embargo in 2013, Georgia’s exports to Russia skyrocketed to an amount worth more than $111 million in 2014.[28] The same happened as a result of the Russia-Ukraine war, which propelled Georgia’s wine exports to Russia to an unprecedented value of $168 million.[29] Exports to the EU and US continue to be dwarfed by those to the CIS countries (Graph 7). Within the CIS, Russia remains the major importer of Georgian wines, up to 83% in 2023. Russia’s imports amounted to 60% of Georgia’s total wine exports in 2018 and increased to 65% in 2023, the highest figure since 2005.[30] Graph 7 Georgian Wine Exports (thousand USD) to the CIS Countries Compared to Exports to the EU and US (2019-2023) Source: External trade portal, 2024. The current export statistics suggest that much is still to be done to diversify Georgia’s wine exports away from Russia. Neighboring Russia is Georgia’s traditional market. This explains its large share of Georgia’s exports. The external circumstances have contributed to maintaining and even enlarging this share, compared to the previous years. Yet, Georgia’s wine exports no longer face an 80% dependence on the Russian market as before Russia’s wine embargo, and the developments since then have shown that the export quantity can be detrimental to wine quality. Therefore, entry into high-value Western markets with high-quality goods and products has been pushed to the top of Georgia’s agenda, which calls for increasing awareness of Georgian wines, reducing entry costs to new markets, and aligning the supply of particular wines with demand. Opportunities The swings in Georgia’s trade flows due to outside factors and difficulties in reorienting the country’s commerce toward the West do not mean that diversification of wine exports is a lost cause. The 2006-2012 embargo period remains a sore reminder of the urgency of strengthening trade relations with other countries, especially those in the West. At the same time, revenue from sales on the Russian market after the end of the embargo allowed for continuing improvements in Georgia’s wine industry.[31] The effect of the Russia-Ukraine war on Georgia’s economy has been waning, and although the high dependence of wine exports on the Russian market persists, the end of the war can bring changes. Prioritizing the US in Wine Export Diversification With support from Georgian government agencies and international organizations, the wine industry is pushing forward. Georgia attributes the utmost importance to the US as the two countries signed the US-Georgia Charter on Strategic Partnership (2009) and reaffirmed the Charter’s principles on its 10th anniversary (2019). Georgia and the US also signed a bilateral investment treaty and a bilateral trade and investment framework agreement.[32] There are also specific wine-related reasons for targeting the US market. The US tops the list of countries whose population drinks the most wine in terms of total volume, accounting for around 15% of the world’s total wine consumption.[33] According to Tamta Kvelaidze, Head of the Marketing & PR Department at the NWA, the agency prioritizes marketing Georgian wines to the US as the world’s largest wine consumer. The NWA has contractors in all markets; in the US, it is Colangelo & Partners, an integrated communications agency specializing in food, wine, and spirits, with offices in New York City and San Francisco.[34] The Teliani Valley company[35] one of Georgia’s largest wine producers, opened its office in the US, established its own distribution company and warehouse in California, and launched an extensive marketing campaign. If successful, Teliani Valley’s strategy can be replicated by other winemakers in Georgia.[36] Since 2013, the US market for Georgian wines has been one of the fastest growing and showed an almost eightfold increase in dollar terms and nearly sixfold expansion in volume.[37] Cooperation between Georgian and US wineries and educational visits to Georgia by members of the US Wine Lovers Club have sought to support this upward trajectory by raising awareness of Georgian wine.[38] To accurately assess the status and potential of Georgia’s exports to the US, different segments of the wine market should be considered. The recent worldwide trend, which is expected to continue, is “premiumization – the demise of non-premium wine and the emergence of commercial premium wine”. The volume of consumption of fine and commercial premium wines was projected to be about one-sixth higher, and the volume of non-premium wine slightly lower in 2025 than in 2016–2018.[39] The US market, one of the most affluent consumer markets, is deemed to be a high-value one for Georgian wine because of the comparatively high prices.[40] According to Zurab Mgvdliashvili, a co-founder of the Natural Wine Association of Georgia, the US is an almost single importer of the premium-segment natural wines produced by the 120 members of his association. Whereas in 2023, the overall annual export of Georgian wines reached 89.5 million liters or almost 120 million bottles,[41] the country’s export of natural wines counts in a couple of thousand bottles. Yet, the latter export can be more lucrative as a bottle of natural wine is four times more expensive than an average bottle.[42] Market research has revealed the following key obstacles faced by Georgian wine exporters in the US: high logistics costs, complex US legislation, limited awareness of Georgian wine, and copyright issues.[43] These are serious barriers, but they are not insurmountable. Julie A. Peterson, Managing Partner at the Marq Wine Group and a former NWA contractor, underscored and celebrated the impressive growth of Georgian wine exports to the US. “The challenge is to sustain this growth; the key is to keep traction”, advised Ms. Peterson.[44] Expanding to the EU In 2014, Georgia and the EU signed an Association Agreement, which included the Deep and Comprehensive Free Trade Agreement (DCFTA), allowing Georgian products to enter the EU market without customs duty.[45] The top importers of Georgian wine among EU members in 2023 were Poland, Germany, Latvia, and Lithuania (Graph 8). Poland consistently played a leading role: in 2023, it accounted for 49% of Georgian wine exports to the EU and was the second-top importer of Georgian wine in the world, although its 6% share was much smaller than the 65% share of Russia. In 2023, Germany overtook Latvia as the #2 EU importer of Georgian wine.[46] Graph 8 Top Importers of Georgian Wine (thousand USD) among EU Member Countries (2019-2023) Source: External trade portal, 2024. The NWA places Germany and Poland as the best candidates after the US for extensive marketing and export diversification.[47] According to the 2023 data, Germany was fourth in the world among countries whose population drinks the most wine and was the fifth in per capita wine consumption.[48] At the same time, Germany was ranked as the eighth-largest producer of wine in 2023.[49] Although France and Italy are top wine consumers after the US, Georgia hardly exports its wine to these countries, ranked in 2023 as first and second wine producers.[50] In contrast, Poland, which is known for vodka and beer but not wine, is a promising importer. Wine Culture as a Driver of Tourism Georgia is not only a wine country. It is also a land of exceptional natural beauty, a long and unique history, and an extraordinary landscape and ecological diversity. All these characteristics are attractive for tourism, but Georgia’s wine culture has emerged as the country’s leading promoter. “Tasting local cuisine and wine” was one of the most popular tourist activities, the second only after shopping, in 2022.[51] In 2023, it became the top activity, as 78.1% of international visitors cited it.[52] In 2022, the added value of Georgia’s tourism-related industries as a share of GDP increased from 6.7% to 7.2%. More than 20% of this value was driven by food and beverage services.[53] Tourism offers an opportunity to sell wine directly to consumers in wineries and plays a critical role in the advancement of local communities. Many rural producers in Georgia do not have distribution contracts enabling them to retail their wine. Therefore, the openness of their establishments for visitation, which typically includes tours, tastings, and opportunities to purchase beverages, is indispensable.[54] Similar to winemaking, tourism can generate secondary economic activity. Accounting for its effect on other sectors of the economy, it was estimated that in 2018, before the COVID-19 pandemic, 31.3% of Georgia’s GDP depended on the travel and tourism industry, including parks and transportation.[55] On average, tourism’s direct and indirect contribution to Georgia’s total economy is more than 25%, whereas this figure for the global economy is only about 7.5%.[56] Advertising Georgia as the Cradle of Wine and wine as a symbol of Georgian national identity has naturally connected wine production with wine and food tourism, and wine culture has become one of the drivers of global awareness of and interest in Georgia. In 2023, 7.1 million international travelers visited Georgia, and the country received a record $4.1 billion in tourism revenue.[57] The largest number of visitors (1.2 million) in 2023 was from Russia, amounting to 23.2% of the total number of visitors, followed by Turkey (21.4%) and Armenia (13.5%). Correspondingly, the citizens of Russia, Turkey, and Armenia made the most visits (Graph 9).[58] As is seen in Graph 10, compared to the largest shares of visits to Georgia from Russia and Turkey, the number of visits from the EU member countries has been small and has not yet returned to the pre-pandemic level. As for visits from “other countries”, a category that includes the US, their number has exceeded the pre-pandemic level in 2022 and increased further in 2023. The proportion of visits by EU visitors in the total number of visits to Georgia was 6% in 2023.[59] The International Visitor Surveys conducted by the GNTA at airport or land border checkpoints offer more detailed data. It turns out that both before the COVID-19 pandemic in 2019 and recently in 2023, Western visitors stayed substantially longer in Georgia than those from Turkey. For example, the average length of stay of US citizens was 10 nights in 2023, compared to 1.9 nights for visitors from Turkey. At the same time, US visitors stand out as higher spenders. Their average expenditures were almost twice as high in 2023 as spending by visitors from Poland and France.[60] Considering that a large share of visitors’ expenditures is consistently registered on served food and drinks, spending on wine consumption significantly increases the proceeds of tourism to Georgia.[61] These data reiterate the point about the difference between high-value and low-value economic activity. As Georgian wine exporters target markets in the US and other Western countries, the country’s tourist organizations are especially interested in visitors from these countries because of the expectations of higher returns. International tourism helps the Georgian wine sector and vice versa. Visitors touring wineries and buying directly from sellers drive higher demand for Georgian wine delivered to their home countries. Conversely, increased awareness of Georgian wine attracts more wine enthusiasts to visit the country. Westerners in Georgia’s Wine Business: Assessment of Industry’s Status and Prospects Looking beyond statistical data, the interviews conducted in May-June 2024 with Westerners working in Georgia’s wine industry revealed a buoyant mood about the country’s prospects in the global wine market.[62] “Georgia is extremely exceptional: it has a perfect story – amazing history, tradition, sustainable farming, and also good wines, including the natural ones”, stated Julie A. Peterson, a US consultant. This positive assessment was shared by Patrick Honnef, the Germany-born CEO of Château Mukhrani, who referred to a “renaissance of Georgian wine culture”: “Ten years ago, there was no wine agency, no national tourist administration, and no wine associations. Now there is a young generation that is better educated, the quality of wine is improving, and overall, it is a thrilling time”. Olivier Sauvage, a French businessman and consultant, agreed that “winemaking in Georgia has potential”, but also pointed to the challenges: the predominance of semi-sweet wines in Georgian exports, which are not favored by younger generations, and the lack of professionalism compared to the international level. He also highlighted the relatively high price of Georgian mass-produced wines, compared to the prices of international competitors, such as Spain or Chile. The reason behind the high price is small-scale production in Georgia and the large costs of supplies and logistics. Both Mr. Sauvage and Mr. Honnef also pointed to the constraints of land legislation, which allows foreigners to buy land only in cooperation with Georgian residents and thus limits the scale of wine production. The lack of foreign investment is another barrier. The question is what’s to be done to ensure further progress. “Wine is the number one value export of Georgia, it can transform the Georgian economy”, said Ms. Peterson, referring to the benefits of entering the US market with its 19 million consumers of wine. Georgian wines are sold on average for $5.15 a bottle in the US market and only for $2 a bottle in Russia; some wineries can sell for $9-$11 a bottle. As for skills, Mr. Honnef values his young Georgian staff hired fresh from the Agricultural University and the Technical University in Tbilisi, and also sees promise in interns attracted to work with him. There are study-abroad programs supported by universities, the EU, and USAID, which open opportunities, but more investment in travel, training, and international partnerships is needed. Georgia is proud of its winemaking tradition, but tradition must be balanced with and reinforced by international expertise. “Georgians need to learn, need innovation,” underscored Mr. Sauvage. Mr. Honnef was upbeat in this regard: “Today the new generation understands the global market and competition from abroad and seeks higher wine quality and new markets. Progress comes with open-mindedness and innovation”. Prioritizing Western markets means an increasing emphasis on premium-level wines. According to Ms. Peterson, “Georgia needs to make exceptional wines and to align the types of wines with trends in wine consumption”. Mr. Honnef agreed with the preferred focus of Georgia on premium-level wines but advocated gradual diversification of the types of wines (contingent on demand) and steady development of new markets, such as the US and Germany, while maintaining the traditional ones. Pivoting to the West – both in terms of wine exports and wine and food tourism – should offer increasing financial returns. It can also have a political impact. But as Georgia is determined to strengthen its international outreach, shifts should not be abrupt. “Georgia must stay on course but adjust every year. Marketing must be integrated with building logistics, skills, distribution, and sales – all components must work together. This country has all the ingredients for success and demonstrated progress; it just needs to stay the course, not slow the way forward”, emphasized Ms. Peterson. Conclusion Based on the findings of desk research and assessments, and suggestions of the interviewed Georgians and Western experts, the following conclusions and recommendations can be made. The wine industry is a priority sector of Georgia’s economy. Wine was the second most exported commodity in Georgia in both 2023 and the first half of 2024.[63] The rank of wine in Georgia’s exports has increased compared to 2018, when the wine industry was the fifth-largest export generator for the country.[64] The share of wine exports in Georgia’s GDP has been growing along with the GDP growth,[65] and the wine industry provides a multiplier effect on the economy as it is closely linked with its major sectors. Hence, mastering Western markets is worth pursuing, as every expansion of Georgian exports to the West is not merely a source of revenue but an engine of economic growth and social development. Effective marketing is imperative for positioning Georgian wines in the Western markets. As storytelling is an important marketing vehicle, Georgia’s story as the Cradle of Wine combines history and tradition and suggests continuity through sustainable farming. As “tasting local cuisine and wine” is one of the most popular tourist activities in Georgia, the cross-fertilization of wine production and wine and food tourism is beneficial for the national economy and global awareness of the country. Marketing should not, however, stand alone; it must be integrated into the entire system of wine production, tourism management, and skills development. It should also constantly improve, building on the successes of international partnerships and marketing campaigns and learning lessons from the operation of offices and distribution companies abroad. There is a consensus about the need to develop wine export markets beyond Russia and decrease dependence on Russia. However, the benefits of maintaining exports to Russia are also recognized. The same applies to balancing various tourist markets. Although pivoting to the West is expected to offer both economic and political advantages to Georgia, shifts in export and tourism strategies should be well-prepared and measured. Gradual diversification of the types of wines and steady development of new Western markets, such as the US and Germany, should go together with preserving the traditional ones. This gradual strategy is most feasible and beneficial. Georgian wine exporters face serious barriers in the West, ranging from high logistics costs to copyright issues and a mismatch between the types of wines produced and the global demand. Georgian mass-produced wines are also expensive, compared to the prices of international competitors, because of Georgia’s small scale of grape cultivation, the high costs of supplies, the constraints of land legislation, and the lack of foreign investment. To break down these barriers, it is crucial to complement Georgian tradition with innovation and to inject Western expertise and funding, both via private ventures and state and international assistance. To make Georgian wines viable in the global market, enhanced professionalism of winemakers, higher wine quality, and aligning the types of exported wines with wine consumption trends are essential. Given the characteristics of Georgia’s agriculture and winemaking, the country can hold a prominent position in niche markets in the world. As the recent worldwide trend is “premiumization”, Georgia is well-positioned to emphasize premium-level wines, including natural wines, in its production and exports. The US and Germany are the best among affluent high-value markets for the premiumization of Georgian exports and a focus on natural wines. In choosing major targets for export diversification, the recipient countries’ per-capita consumption of wine, the volume of their wine production, and the relative competitiveness of their wine industries should be considered. Similarly, attracting high-value tourists from the US and Germany can yield higher returns, including through visitors’ expenditures on wine. Bibliography: ge. (2024, April 26). Georgia, FAO sign new $4m project to boost sustainable agriculture, rural development. Available at: https://agenda.ge/en/news/2024/38857#gsc.tab=0; Anderson, K. (2009). Wine’s New World. Foreign Policy. Available at: https://foreignpolicy.com/2009/11/02/wines-new-world/; Anderson, K. (2012). Rural development in Georgia: what role for wine export growth? Wine Economics Research Centre Working Paper, 0112; Anderson, K. (2020). Is Georgia the next ‘new’ wine-exporting country? Chapter 13 in The international economics of wine. 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Index-based analysis of Georgian wine export’s competitiveness on a global market. International Journal of Agricultural Economics, 4(5). Available at: https://sciencepublishinggroup.com/article/10.11648/j.ijae.20190405.12. Footnotes [1] Maghradze, D., et al. (2016). Grape and wine culture in Georgia, the South Caucasus. 39th World Conference of Vine and Wine, BIO Web of Conferences 7 (03027); Lortkipanidze, D. (ed.). (2017). Georgia the cradle of viticulture. National Geographic Magazine - Georgia in collaboration with the Georgian National Museum. Available at: <https://nationalgeographic.ge/story/georgia-the-cradle-of-viticulture/>. [2] Gelashvili, A. (2024). The Revived Legend of Mukhrani. Sandro Books Publishing; Lordkipanidze, D. (ed.). (2017). Georgia the cradle of viticulture. National Geographic Magazine - Georgia in collaboration with the Georgian National Museum. Available at: <https://nationalgeographic.ge/story/georgia-the-cradle-of-viticulture/>. [3] National Statistics Office of Georgia. (2024). Exports by commodity groups (HS 2 digit level) in 2015-2024. Export. Available at: <https://www.geostat.ge/en/modules/categories/637/export>. [4] Zivzivadze, L., Taktakishvili, T. (2019). Index-based analysis of Georgian wine export’s competitiveness on a global market. International Journal of Agricultural Economics, 4(5), pp. 201-206. Available at: <https://sciencepublishinggroup.com/article/10.11648/j.ijae.20190405.12>. [5] Anderson, K. (2020). Is Georgia the next ‘new’ wine-exporting country? Chapter 13 in The international economics of wine. World Scientific Studies in International Economics, 73, pp. 311-346; Anderson, K. (2012). Rural development in Georgia: what role for wine export growth? Wine Economics Research Centre Working Paper, 0112; Anderson, K. (2009). Wine’s New World. Foreign Policy. Available at: <https://foreignpolicy.com/2009/11/02/wines-new-world/>. [6] Beyond the niche: the past, present & future of Georgian wine in the US market. (2021). Wines of Georgia. Available at: <https://winesgeorgia.com/wp-content/uploads/2021/08/Georgia-301-Virtual-Seminar-26-Aug-2021.pdf>; Georgian wine eyes USA market. (2021, September 23). Georgian Journal. Available at: <http://georgianamerica.com/eng/news/georgian_wine_eyes_usa_market_2744>. [7] Granik, L. (2019, July 29). Understanding the Georgian wine boom. Seven Fifty Daily. Available at: <https://daily.sevenfifty.com/understanding-the-georgian-wine-boom/>. [8] Rytkönen, P., Vigerland L., Borg, E. (2021). Tales of Georgian wine: storytelling in the Georgian wine industry. Journal of Wine Research, 32(2), pp. 117-133. [9] Marketing research of wine tourism sector in Georgia. (2014, December 20). International Business Development and Investment Promotion Center. [10] Tsereteli, M. (2018, December 7). Georgian wine and its narrative drive development. The Central Asia – Caucasus Analyst. Available at: <https://www.cacianalyst.org/publications/analytical-articles/item/13548-georgian-wine-and-its-narrative-drive-development.html>; Tsereteli, M., Oliker, O., Mankoff, J. (2019, January). Wine, society, and geopolitics. Center for Strategic and International Studies. Available at: <https://csis-website-prod.s3.amazonaws.com/s3fs-public/event/190307_Tsereteli_WineSociety_pageproofs5.pdf>. [11] Gelashvili, A. (2024). The Revived Legend of Mukhrani. Sandro Books Publishing. [12] Ibid. [13] Dinello, N. (2022). Centrality of winemaking in Georgia: from prehistoric age to present-day globalization. Journal of Wine Research, 33(3), pp. 123-145. [14] Tsinandali Estate Museum. (2024). Available at: <http://tsinandali.ge/en/museum/about-us>. [15] Gelashvili, A. (2024). The Revived Legend of Mukhrani. Sandro Books Publishing; World’s Best Vineyards. (2024). 47 Château Mukhrani, Mukhrani, Georgia. [16] Anderson, K. (2012). Rural development in Georgia: what role for wine export growth? Wine Economics Research Centre Working Paper, 0112. [17] USAID/Georgia’s Economic Security Program: Mid-Term Evaluation (2022, June). Final Report, pp. 33, 41, 43-44. Available at: <https://pdf.usaid.gov/pdf_docs/PA00ZGXC.pdf>. [18] USAID Economic Security Program. (2023, January 15). Quarterly report. Quarter 1 FY23: October – December 2022. Available at: <https://pdf.usaid.gov/pdf_docs/PA02122H.pdf>. [19] USAID Agriculture Program. (2023). Unlocking potential for Georgian wine in US markets. Cultivating New Frontiers in Agriculture (CNFA). [20] Georgia - regional development project. (2012, February 22). World Bank Group. [21] Agenda.ge. (2024, April 26). Georgia, FAO sign new $4m project to boost sustainable agriculture, rural development. Available at: <https://agenda.ge/en/news/2024/38857#gsc.tab=0>. [22] LEPL National Wine Agency. (2024). Available at: <https://wine.gov.ge/En/Page/mainactivities>. [23] Transparency International, Georgia. (2023, February 23). Georgia’s economic dependence on Russia: impact of the Russia-Ukraine war. [24] IMF Country Report No. 24/135. (2024, May). Georgia: 2024 article IV consultation—press release, staff report, and statement by the executive director for Georgia. [25] Transparency International, Georgia. (2023, February 23). Georgia’s economic dependence on Russia: impact of the Russia-Ukraine war. [26] Transparency International, Georgia. (2024, February 16). Georgia’s economic dependence on Russia: summary of 2023. [27] Von Cramon-Taubadel, S., Saha, D. (2015, May). Short-run risks and long-run challenges for wine production in Georgia. Policy Paper Series, German Economic Team Georgia and ISET Policy Institute, Berlin/Tbilisi, 7. [28] National Statistics Office of Georgia. (2024). External trade portal. Available at: <https://ex-trade.geostat.ge/en>. [29] Transparency International, Georgia. (2024, February 16). Georgia’s economic dependence on Russia: summary of 2023. [30] National Statistics Office of Georgia. (2024). External trade portal. Available at: <https://ex-trade.geostat.ge/en>; Transparency International, Georgia. (2024, February 16). Georgia’s economic dependence on Russia: summary of 2023. [31] Buckley, N. (2013, February 4). Georgian wine to flow as Russia lifts ban. Financial Times. Available at: <https://www.ft.com/content/13269432-6ee9-11e2-9ded-00144feab49a>; Sharkov, D. (2016, March 3). Russian imports of Georgian wine skyrocket after ban is lifted. Newsweek. Available at: <https://www.newsweek.com/russian-imports-georgian-wine-skyrocket-after-lifted-ban-434698>. [32] The Embassy of Georgia to the United States of America. (2021). High-level trade dialogue (HLTD). Available at: <https://georgiaembassyusa.org/bilateral-trade/>. [33] Mercer, C. (2023, May 24). Which countries drink the most wine? Ask Decanter. Decanter. Available at: <https://www.decanter.com/wine-news/which-countries-drink-the-most-wine-ask-decanter-456922/>. [34] Colangelo & Partners (2024). Available at: <https://www.colangelopr.com/>. [35] Teliani Valley. (2024). Available at: <https://www.telianivalley.com/en>. [36] Interview with Kvelaidze, T. (2024, June 3). [37] National Statistics Office of Georgia. (2024). External trade portal Available at: <https://ex-trade.geostat.ge/en>. [38] Gambashidze, D. (2023, July 31). Georgian wine is gearing up to strengthen its position in the US market. Forbes. [39] Anderson, K., Pinilla, V. (2021). Wine’s belated globalization, 1845–2025. AAEA Agricultural & Applied Economics Association – Wiley, pp. 750, 761-762. [40] Numbeo. (2024). Price rankings by country of bottle of wine (mid-range) (markets). Available at: <https://www.numbeo.com/cost-of-living/country_price_rankings?itemId=14>. [41] National Wine Agency of Georgia. Export of wine and alcoholic beverages. (2024, February 9). [42] Interview with Mgvdliashvili, Z. (2024, June 7). [43] Gambashidze, D. (2023, July 31). Georgian wine is gearing up to strengthen its position in the US market. Forbes. [44] Interview with Peterson, J. (2024, June 5). [45] Enterprise Georgia. (2024). Free trade regimes. [46] National Statistics Office of Georgia. (2024). External trade portal. Available at: <https://ex-trade.geostat.ge/en>. [47] Interview with Kvelaidze, T. (2024, June 3). [48] Mercer, C. (2023, May 24). Which countries drink the most wine? Ask Decanter. Decanter. Available at: <https://www.decanter.com/wine-news/which-countries-drink-the-most-wine-ask-decanter-456922/>. [49] World Population Review. (2024). Wine producing countries 2024. Available at: <https://worldpopulationreview.com/country-rankings/wine-producing-countries>. [50] Mercer, C. (2023, May 24). Which countries drink the most wine? Ask Decanter. Decanter. Available at: https://www.decanter.com/wine-news/which-countries-drink-the-most-wine-ask-decanter-456922/>; World Population Review. (2024). Wine producing countries 2024. Available at: <https://worldpopulationreview.com/country-rankings/wine-producing-countries>. [51] Georgian National Tourism Administration. (2023). Georgian tourism in figures: structure and industry data 2022. Available at: <https://gnta.ge/wp-content/uploads/2023/09/2022-eng-1.pdf>. [52] Georgian National Tourism Administration. (2024). Conducted Activities. International Visitors Survey. Available at: <https://gnta.ge/wp-content/uploads/2024/02/International-Visitor-Survey-2023.xlsx>. [53] Georgian National Tourism Administration. (2023). Georgian tourism in figures: structure and industry data 2022. Available at: <https://gnta.ge/wp-content/uploads/2023/09/2022-eng-1.pdf>. [54] Extension - University of Georgia. (2024). Georgia’s Alcoholic Beverage Industry 2024 Outlook. [55] Quinn, C. (2020, April 1). The tourism industry is in trouble. Foreign Policy. Available at: <https://foreignpolicy.com/2020/04/01/coronavirus-tourism-industry-worst-hit-countries-infographic/>. [56] Shamugia, E. (2023, October 17). Tourism: Georgia and the region. Forbes: Georgia. Available at: <https://forbes.ge/en/tourism-georgia-and-the-region/>. [57] Georgia National Tourism Administration. (2024, February 12). Record $4.1 billion in tourism revenue and 7.1 million international travelers - 2023 statistics. [58] National Statistics Office of Georgia. (2024). Inbound tourism statistics in Georgia. Available at: <https://www.geostat.ge/media/59934/Inbound-Tourism-Statistics---%282023-year%29.pdf>. [59] Ibid. [60] Georgia National Tourism Administration. (2024). International visitor survey 2015-2023. Available at: <https://gnta.ge/wp-content/uploads/2024/02/International-Visitor-Survey-2023.xlsx>. [61] Georgian National Tourism Administration. (2023). Georgian tourism in figures: structure and industry data 2022. Available at: <https://gnta.ge/wp-content/uploads/2023/09/2022-eng-1.pdf>; National Statistics Office of Georgia. (2024). Inbound tourism statistics in Georgia. <https://www.geostat.ge/media/59934/Inbound-Tourism-Statistics---%282023-year%29.pdf>. [62] Interviews with Honnef, P. (2024, May 24), Peterson, J. (2024, June 5), & Sauvage, O. (2024, May 5). [63] National Statistics Office of Georgia. (2024). Exports by commodity groups (HS 2 digit level) in 2015-2024. Export. Available at: <https://www.geostat.ge/en/modules/categories/637/export>. [64] Tsereteli, M. (2018, December 7). Georgian wine and its narrative drive development. The Central Asia – Caucasus Analyst. <https://www.cacianalyst.org/publications/analytical-articles/item/13548-georgian-wine-and-its-narrative-drive-development.html>. [65] Jmukhadze, N. (2022. August 1). The role and influence of wine export on the economic growth of Georgia. Forbes. Available at: <https://forbes.ge/en/ghvinis-eqsportis-roli-da-gavlena-saqarthvelos-ekonomikur-zrdaze/>.
Asymmetric Effect of Monetary and Fiscal Policy Uncertainty on the Energy Transition: Evidence from the United States
This research attempts to investigate how uncertainty in fiscal policy (FPU) and monetary policy (MPU) affects the US energy transition. While previous literature took the total renewable energy consumption (REC) as an indicator for the energy transition, this study uses different renewable energies across different sources, including solar, hydropower, wind, and biomass. Then, the novel multivariate quantile on quantile regression (MQQR) approach and time-varying nonparametric quantile causality (TVNQC) methods were applied in the period from 2000 to 2023. The MQOQ findings demonstrate a robust asymmetry between MPU, FPU, and all renewable energy sources, where MPU has the biggest impact, meanwhile, biomass energy has the strongest relationship. This was affirmed by TVNQC, which reveals a significant time-varying causation impact of MPU and FPU on various renewable energy sources; however, the causality becomes weaker during periods of global economic uncertainty, such as the COVID-19 pandemic and the Russia-Ukraine war. These findings provide a new insight for policymakers for addressing the energy transition and sustainability challenges. Keywords: Monetary policy, fiscal policy, energy transition, renewable energy, quantile. Introduction Energy consumption served a crucial role in the expansion of different types of industries and the fast rise in the world economy ever since the start of the Industrial Revolution.[1] The bulk of this energy usage comes from polluting and non-renewable sources, it consequently caused an unheard-of increase in environmental degradation such as natural disasters, extreme weather events and greenhouse gases emissions,[2] With Carbon dioxide (CO2) represent the most significant component of greenhouse gases, making up the biggest proportion of their entire amount, where, the primary cause of the high CO2 emissions is the production and consumption of human’s activities.[3] Due to climate change and pollution consequences, the shift to renewable energy sources is rapidly gaining importance, whereas transitioning from one or a group of dominating energy resources to a different type is referred to as an “energy transition”. Historical instances include the use of coal instead of wood during the Industrial Revolution and the use of kerosene instead of whale oil in the late 1800s.[4] Meanwhile, the current energy transition is the move toward substituting fossil fuels, which have higher carbon footprints, with cleaner alternatives, notably wind, solar, and biomass energies. Nevertheless, it is uncommon to entirely replace a main source of energy transition by an alternate all at once, instead, this transition typically occurs progressively, beginning with a small percentage and increasing to attain a major portion of the energy consumption’s composition.[5] In recent years, the world began to take significant steps towards energy transition, especially after the Paris Climate Change Agreement, with a massive investment push in the renewable energy generation sector, yet not as fast as anticipated, despite the proven advantages of renewable energy.[6] Besides of relatively low cost of fossil fuels, there are a number of challenges that impede the advancement of renewable energy. As an instance, the high expense of installation, maintenance, and policy uncertainty.[7] In light of policy uncertainty, policymakers may shift their attention away from environmental sustainability toward other pressing challenges, which negatively affect the environmental restrictions. Furthermore, it’s reasonable for firms to anticipate laxer environmental regulations in an environment where a high degree of political uncertainty leads to a greater emphasis on economic goals.[8] One of the most significant policy uncertainties that the energy transition may encounter is economic policy uncertainty (EPU), which is defined as the degree of ambiguity around the government policies, especially those pertaining to monetary and fiscal policies, that could significantly affect the business environment.[9] Moreover, many research, proved that EPU have significant impacts on energy generation (e.g.; Shafiullah et al.;[10] Yi et al.;[11] Aslan et al.[12]), through price swings and a high reliance on foreign countries, additionally, the renewable energy generation and consumption proportions in a given economy could be influenced by government policies, such as subsidies and direct investment, which aim to improve the macroeconomic climate for energy supply, as both proportions increase due to the increased in energy sector investments. However, EPU has the potential to hinder renewable energy generation through price shocks and fossil fuel shortages. In contrast to other energy sources, the consumption of renewable energy is directly impacted by governmental policies, particularly monetary policy through its impacts on financial investments. Monetary policy can make it more difficult for investors to get financing and raise the initial cost of investing, as well as the bank lending channel, which rises in response to an increase in the money supply and consequently boosts investments. Given that investing in renewable energy is more expensive and riskier than conventional energy sources, it is extremely susceptible to changes in monetary policies.[13] Fiscal policy, on the other hand, is predicated on altering the level of the country’s tax base. Tight fiscal policies have the potential to deter investors, and capital provision would continue to be a barrier by increasing the investors’ access to capital costs. However, the renewable energy industry stands to benefit from the lax policies, which present a favorable investment opportunity.[14] Overall, monetary and fiscal policies are both directly and indirectly related to environmental quality, through their significant role in the mitigation of CO2 emissions and financing the world’s energy transition.[15] Furthermore, the renewable energy sector comprises the various categories of the energy sources, in each of which has its properties or behavior to policy measures, where recent studies have highlighted significant heterogeneities within these energy sectors (e.g. Jurasz et al.;[16] Liu et al.;[17] Sinha et al.[18]). Hence, it is important to recognize the heterogeneous nature of renewable energy sources when formulating policies, where understanding how policy uncertainties differentially impact various renewable energy sectors is critical for both policymakers and investors aiming to foster sustainable energy development. Additionally, tailored policy interventions that account for the distinct characteristics of each energy source can enhance the effectiveness of renewable energy policies and promote a more efficient transition to sustainable energy systems. Despite the growing literature on the nexus between policy uncertainty and renewable energy consumption, most existing studies tend to aggregate overall renewable energy consumption (REC) data, potentially overlooking the distinct dynamics present within individual energy sources. The research fills an important knowledge gap through separate analysis of renewable energy’s main consumption areas, including solar and hydropower and wind power, and biomass. Moreover, the complex interplay between monetary policy uncertainty (MPU) and fiscal policy uncertainty (FPU) and their effects on energy transition indicators has received limited academic attention. Most of the prior research focused on how policy uncertainty affected overall renewable energy consumption (REC), with limited attention to the asymmetric impact on various policies and how they affect energy transition. Hence, the current research looks at the effects of MPU and FPU on different types of renewable energy. The United States was selected for examination in this study, due to it is both the biggest economy and the second-highest carbon emitter in the world. Additionally, it ranks among the top countries in the world for the REC (Syed & Bouri, 2022), as it has come a long way in its energy transition, due to its significant development in the renewable energy sector. Yet, the REC makes around only 11.3% of total energy consumption. Additionally, the study also makes use of the novel multivariate quantile on quantile regression (MQQR) and time-varying nonparametric quantile causality (TVNQC) approaches. With these methodologies, the impact of MPU and FPU on each of the renewable energy segments is examined with a high degree of detail. These approaches offer more robust evidence on the heterogeneity of the impacts of monetary and fiscal uncertainties across the different sectors of energy by considering disaggregate renewable energy data and using quantile regression models, which goes much deeper into the nature of the energy transition, and reveals the unequal exposure and associated different vulnerabilities and resilience of those sectors dependent on solar, hydropower, wind and biomass consumption. Meanwhile, the time-varying analysis allows for the uncovering of the dynamic nature of these causal relationships, which can reveal how the strength and direction of policy impacts can shift significantly over different periods. Here is the structured overview of this paper: Section 2, summarizes the relevant literature on the subject. Section 3, details the study’s methodology and dataset, Section 4 contains the empirical results and associated discussions, and the final section offers some concluding comments and implications for policies. Literature Review The global energy transition has recently received more attention from researchers considering the urgent need to address climate change and promote sustainable development (e.g. Tian et al.;[19] Elshkaki;[20] Hassan et al.[21]). In the context of the U.S energy transition, the literature researchers have examined this subject from various perspectives over the years. Solomon & Krishna[22] compared the United States with France and Brazil in terms of sustainable energy transition. Unlike the success of France and Brazil in shifting from an oil-based transportation system to more sustainable alternatives, the U.S. was unable to transition from imported oil to a combination of locally produced energy sources. O’Connor & Cleveland[23] studied the U.S. energy transition by analyzing the patterns of the consumption of different energy sources. They reveal that, when traditional energy is taken into account, energy intensity in the United States from 1820 to 2010 shows a downward tendency, as opposed to the inverse U-shaped nexus observed when just commercial energy is taken into account. Stokes & Breetz[24] analyzed the impact of the politics of U.S. state and federal policy on energy transition, using a variety of renewable energy sectors. The finding shows that Similar trends can be observed in various industries: emerging technology is misappreciated or misinterpreted, high-energy costs present windows of opportunity for legislation, Policies are gradually expanded once they are enacted, and growing political intrigue is a result of established technology’s danger to the status quo. The study of Mayer[25] investigated whether community economic identity, elite political affiliation, and ideological cues raise the support for energy transition in multiple U.S. states. Study findings indicate that local policymakers who see fossil fuels as relevant to their area are more likely to back the energy transition, although community economic identities centered around renewable energy sources might not increase endorsement. Surprisingly, elite partisan cues did not affect opinions of the energy transition, while party membership was a strong predictor. Karapin[26] analyzed several eras of renewable energy policymaking at the federal and state levels. A detrimental impact of federalism was found on national policies pertaining to the U.S energy transition, given the way its federalist institutions combine with polarization within the parties and a robust fossil fuel sector domestically. Similarly, Roemer & Haggerty[27] evaluated how state and federal policy in the United States West’s rural coal communities facilitate or impede transition planning. It is discovered that Coal areas are shown to be more unpredictable due to the absence of a national energy transition program, leading to the emergence of two separate and divergent policy pathways at the state level. Hammond & Brady[28] analyzed how critical minerals affect the U.S. energy transition using greenhouse gas emissions. They found that the availability of critical minerals will not allow for the green energy transition, and that the price of these commodities will drive up the cost of green energy; moreover, the U.S. government will persist in obstructing any agreement on a clear strategy to promote domestic mineral production. Hincapie-Ossa et al[29] assessed the county-level economic vulnerability to U.S. energy transition, using a machine learning method. The results show that counties with a high concentration of coal mining have a notably lower capacity to handle economic hardship. Using a multivariate quantile on quantile regression, Usman et al[30] examined how residential energy use affects U.S energy transition policies. The findings show that the clean electricity transition across quantiles is positively impacted by household energy-related efficiency. Despite the existence of literature that covered the effect of EPU on U.S. energy transition (e.g., Nakhli et al.;[31] Ayhan et al.;[32] Husain et al.;[33]). The literature is still limited in terms of monetary and fiscal policies on REC. Sohail et al[34] investigated asymmetry between MPU and both REC and non-REC, using a nonlinear-ARDL model. The findings show that whereas reduced MPU has a considerable positive impact on U.S. REC, yet, MPU’s measurement has negligible effects over the short and long terms. While it has short- and long-term negative effects on non-REC, when there is increasing U.S. monetary policy uncertainty. Jamil et al[35] used the ARDL approach to analyze the effect of MPU, FPU, and trade policy uncertainty on the U.S. energy transition. They found that whereas FPU increases the generation of renewable energy, MPU decreases it both in the short and long terms. Furthermore, the production of renewable energy is unaffected by trade policy uncertainties. Hashmi et al[36] studied the relationships between U.S monetary policy and REC. The results show that expansionary monetary policy encourages REC in both the long- and short-term and vice versa. Additionally, monetary policy has a rather large impact in the short term. By applying the STIRPAT approach, Sun et al.[37] examined how monetary and fiscal policy affected the G7 nations’ REC. The empirical findings indicate that the increased fiscal policy contributes significantly to REC. Where Bildirici et al[38] analyzed the U.S. monetary and fiscal policy causal impact on CO2 emissions as an indicator of U.S. energy transition using a nonlinear bootstrapping ARDL to generalize the nonlinear bootstrapping Granger causality test. The results reveal that monetary and fiscal policy exhibit an asymmetrical impact in both the short and long run. While the contractionary or expansionary effects of fiscal measures raise CO2 emissions, the expansion of monetary policies drives down CO2 emissions. In general, the prior research regarding the effects of MPU and FPU on REC that we highlight in this paper has provided mixed findings, where REC has often been considered a single variety. Meanwhile, looking at the evolution of renewables specifically, the market for renewable energy sources is quite diverse, which means that the market for one source may react differently to changes in policy compared to another source. On the other hand, while some studies have begun to address these issues, there is a clear need for further research employing advanced econometric techniques such as multivariate quantile on quantile regression and time-varying nonparametric quantile causality, that can capture both the asymmetric and dynamic nature of policies impacts across various quantiles of different sources of REC. Addressing this gap would provide a more granular understanding of how distinct facets of policy uncertainty shape the energy transition practically in the U.S., ultimately offering more precise insights for policymakers and investors. Methodology 2.1. Data Table 1: Descriptive statistics Note: * stands for P<0.01. Source: Author’s research in R-studio. The research dataset contains different renewable energy consumption of the four main sources, obtained from U.S. Energy Information Administration, namely, solar (SLR), hydropower (HDR), wind (WND), and biomass (BIO), all measured in Trillion BTU. In addition to the Monetary Policy Uncertainty index (MPU) and Fiscal Policy Uncertainty index (FPU), collected from Federal Reserve Economic Data. Monthly data was used for all variables within the U.S., in the period from January 2000 to November 2023, with 287 Observations, as displayed in Table 10. 2.2. Empirical methods 2.2.1. MQOQ method The study analyzed the asymmetric effect of MPU and FPU on REC as a proxy for energy transition by applying the MQQR approach, which was employed in many recent studies about renewable energy (e.g., Sinha et al;[39] Abbas et al;[40] Usman et al.[41]). This approach is considered an extension of Sim & Zhou’s[42] quantile on quantile regression (QQR), which functions in a bivariate frame and provides a combination of nonparametric estimation and quantile regression. Nevertheless, there’s a possibility that this approach will suffer from omitted series bias. Meanwhile, MQOQ approach enables to examination of the standalone impact of each variable after controlling for confounding factors, by evaluating the dependent and independent variables’ quantiles. With Y as the dependent variable and X1, X2 ... Xn as the independent variables, the MQQR model for the Y and X relationship across different quantiles (0,05-0,95) can be described as follows: Where: represent the quantiles of X1, X2 ... Xn respectively, indicates the quantile of Y, and is the error with a zero –quantile. Since the QQR method relies on the bandwidth size being appropriately picked, we will next set it to 0.05 for our MQQR models. 2.2.2. TVNQC method Following Adebayo,[43] this study uses the time-varying nonparametric quantile causality (TVNQC) method presented by Olasehinde-Williams et al. (2023), which uses the time-varying nonparametric quantile causality (NQC) approach of Balcilar et al. (2016) in rolling sub-sample windows to analyze the study’s dependent and independent variables’ dynamic causal relationship. This method offers a more comprehensive view of the causal quantile effect among the study variables and exhibits greater robustness against errors of misspecification (Mouffok & Mouffok[44]). Results and Discussion 3.1. Unit root and nonlinear tests Firstly, we ascertain the variables’ levels of stationarity using Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) as two distinct unit root tests in order to obtaining accurate results. According to the findings of the tests listed in Table 2, the null hypothesis can be rejected in the level series at the 1% level of significance, except for SLR and WND, where their stationarity can be confirmed at the 5% level of significance. Table 2: Unit root tests Note: L, FD, * and ** stand for level, first difference, P<0.01, and P<0.05, respectively. Source: Author’s research in R-studio Brock et al.[45] BDS test is employed to assess nonlinearity of the study variables. Based on the results of Table 3, the null hypothesis of linearity for all the variables is rejected, as such, there is a nonlinear tendency in SLR, HDR, WND, BIO, MPU and FPU. Table 3: BDS tests Note: * stands for P<0.01. Source: Author’s research in R-studio 3.2. MQQR results Figure 1: MQQR plots of the impact of MPU and FPU on SLR Source: Author’s research in MATLAB Figure 1 presents the slope coefficient estimates of the impact of the τth quantile of MPU in the presence of FPU and of FPU in the presence of MPU on the quantile of SLR at various values of δ and τ. According to Figure 2 (a), MPU has a positive impact on SLR at the low quantiles of MPU (0.23 to 0.43) and the high quantiles of SLR (0.66 to 0.90). This finding suggests that when the level of MPU is relatively low, any increase in uncertainty may actually coincide with or even promote higher levels of solar energy consumption, perhaps reflecting a scenario where low uncertainty encourages investment in renewable energy projects at times when the solar sector is already performing strongly. Conversely, when the analysis shifts to the higher MPU, it has a negative impact on SLR at the high quantiles of MPU (0.80 to 0.90) and the medium and high quantiles of SLR (0.66 to 0.90). This inversion could indicate that when monetary policy uncertainty is elevated, it dampens solar energy investments or adoption, especially in segments of the market that are otherwise robust, possibly due to risk aversion or tighter credit conditions affecting capital-intensive renewable projects. In addition. Figure 2 (b) shows that at the low and medium quantiles of FPU (0.05 to 0.50), the impact of FPU on SLR is negative at low and medium quantiles of SLR (0.05 to 0.52) and positive at the high quantiles of SLR (0.57 to 0.90). This pattern might suggest that, under relatively stable fiscal conditions, increases in uncertainty can have a dual character, suppressing solar energy consumption when the sector is underperforming but stimulating it when the sector is already in a high-consumption phase, potentially due to strategic adjustments by market participants who perceive uncertainty as a signal to capitalize on favorable conditions. While at the high quantiles of FPU (0.71 to 0.90), the impact of FPU on SLR is positive at the low and medium quantiles of SLR (0.05 to 0.61) and negative at the high quantiles of SLR (0.76 to 0.90). This reversal could imply that under conditions of high fiscal uncertainty, lower-performing segments of the solar energy market might experience a boost, possibly due to government interventions or reallocation of resources—while the sectors already enjoying high levels of solar consumption become adversely affected, perhaps due to market saturation or increased competition for limited fiscal support. The findings confirm the previous studies (e.g., Sohail et al.;[46] Khan & Su;[47] Liu et al.[48]). Figure 2: MQQR plots of the impact of MPU and FPU on HDR Source: Author’s research in MATLAB Figure 2 shows the slope coefficient estimates of the impact of the τth quantile of MPU in the presence of FPU and of FPU in the presence of MPU on the quantile of HDR at various values of δ and τ. From Figure 3 (a), we note that the HDR was positively impacted by MPU at all quantile levels of MPU (0.19 to 0.90) and the medium quantiles of HDR (0.47 to 0.71). This suggests that during periods of medium hydropower consumption, increases in MPU are associated with enhanced HDR activity. One interpretation of this finding is that, under moderate levels of hydropower usage, monetary uncertainty might encourage a reallocation of capital towards renewable energy investments, thereby bolstering hydropower initiatives. Also, it was negatively impacted by MPU at the low and high quantiles of HDR (0.14 to 0.42; 0.76 to 0.90). This could be indicative of scenarios where either a low base level of hydropower consumption or an already saturated market becomes more vulnerable to the destabilizing effects of monetary uncertainty. In low-consumption settings, even modest uncertainty might deter further investment, while in high-consumption scenarios, the added uncertainty might constrain additional expansion by heightening risk perceptions among investors. In Figure 3 (b), MPU has a positive impact on HDR at the low and high quantiles of MPU (0.05 to 0.33, 0.61 to 0.90) and the low and high quantiles of HDR (0.05 to 0.42, 0.76 to 0.90). This positive relationship may imply that in conditions of relatively low or very high fiscal uncertainty, perhaps hydropower consumption benefits through targeted policy measures or compensatory investments that offset uncertainty. Meanwhile, it has a negative impact on HDR at the medium quantiles of MPU (0.38 to 0.71) and SLR (0.47 to 0.71). This negative impact at moderate levels might signal that during periods of middling fiscal uncertainty, the market experiences conflicting signals that lead to hesitancy or misallocation of resources, thereby stifling hydropower development. These results are consistent with prior studies (e.g., Xue et al.;[49] Yi et al.;[50] Dai et al. 2025[51]). Figure 3: MQQR plots of the impact of MPU and FPU on WND Source: Author’s research in MATLAB Figure 3 presents the slope coefficient estimates of the impact of the τth quantile of MPU in the presence of FPU and of FPU in the presence of MPU on the quantile of WND at various values of δ and τ. Figure 4 (a) shows that at the medium quantiles of WND (0.51 to 0.57), the impact of MPU on WND is positive. This suggests that under moderate levels of WND, an increase in MPU might spur investment or operational activity in wind energy. This could be interpreted as market participants perceiving moderate uncertainty as a precursor to potential corrective actions or policy adjustments that might benefit the wind energy sector. Yet, the impact becomes negative at the low quantiles of WND (0.05 to 0.41) and at the medium and high quantiles of MPU (0.47 to 0.90), indicating that when wind energy consumption is already at a subdued level or medium to high level of MPU, any increase in monetary uncertainty may exacerbate investor hesitancy or reduce the flow of capital necessary for growth in the sector. Meanwhile, the impact of FPU on WND at the all-quantiles levels of FPU and WND is positive, with the highest and most significant impact at the high quantiles of FPU (0.80 to 0.90) and the low quantiles of WND (0.05 to 0.19), as shown in Figure 4 (b). the consistently positive impact across all quantiles suggests that fiscal policy uncertainty may catalyze enhancing wind energy consumption, potentially by fostering a reallocation of resources towards more sustainable and economically viable energy alternatives in times of fiscal unpredictability, which minimize the shifting to non-renewable alternatives and support the investment in wind energy than other renewable sources (Johnston & Yang;[52] Chen[53]). Figure 4: MQQR plots of the impact of MPU and FPU on BIO Source: Author’s research in MATLAB Figure 4 demonstrates the slope coefficient estimates of the impact of the τth quantile of MPU in the presence of FPU and of FPU in the presence of MPU on the quantile of BIO at various values of δ and τ. Figure 5 (a) outcomes show that MPU has a negative impact on BIO at the all quantiles levels of MPU (0.05 to 0.90) and the low and high quantiles of BIO (0.05 to 0.47; 0.61 to 0.71) This suggests that when biomass consumption is either relatively low or within a specific high range, increased monetary uncertainty tends to depress investment or operational activities in the biomass sector. It is conceivable that in these segments, heightened MPU exacerbates risk aversion among investors or signals tighter credit conditions, thus leading to reduced capital flows into biomass projects. While the relationship reverses at the medium and high quantiles of BIO (0.66 to 0.71, 0.76 to 0.90). This implies that when the biomass consumption is high, increased monetary uncertainty might spur a reallocation of resources or foster a competitive environment that benefits the biomass sector. This positive effect could be interpreted as market participants perceiving uncertainty as an opportunity to shift investments towards biomass, possibly due to its relative resilience or because of supportive measures that come into play during periods of heightened monetary instability. Figure 5 (b) affirms that at the low quantiles of FPU (0.05 to 0.41), suggesting that even in relatively stable fiscal environments, the increases in FPU can have a dampening effect on biomass consumption when the sector is already underperforming. The impact of FPU on BIO is positive at medium and high quantiles of BIO (0.42 to 0.90) and it’s negative at the low quantiles of BIO (0.05 to 0.42). This hints that when biomass consumption is more robust, the increases in fiscal uncertainty may be associated with proactive adjustments, while in more uncertain fiscal settings, even the lower-performing BIO might benefit from targeted fiscal interventions or a rebalancing of resource allocation. For the low medium and high quantiles of FPU (0.41 to 0.90), the impact of FPU on BIO is positive at low quantiles of BIO (0.05 to 0.42) and it’s negative at the medium and high quantiles of BIO (0.42 to 0.90), which implies that for the periods that already exhibiting higher levels of biomass consumption, increased fiscal uncertainty may hinder further growth, possibly due to market saturation or the adverse effects of broader economic instability. These outcomes are in line with past studies (e.g., Zhang & Razzaq;[54] Qamruzzaman et al.[55]). Overall, the MPU and FPU have an asymmetric relationship with different U.S REC sources at the majority of combinations of quantiles. In particular, MPU exerts the most pronounced and multifaceted influence on the U.S. energy transition, where MPU tends to have substantial positive or negative impacts on REC depending on the prevailing market conditions. Meanwhile, FPU also affects these energy sources, yet its effects are generally less dramatic than those of MPU. Moreover, biomass energy consistently shows the strongest relationship with both MPU and FPU. 3.3. TVNQC results The study applies the time-varying nonparametric quantile causality (TVNQC) to determine the causal influence of MPU and FPU on SLR, HDR, WND, and BIO in the US, using a rolling window size of 3 years. Figure 5 presents the time-varying causal impact of MPU on SLR, HDR, WND, and BIO. We note that the time-varying causality between MPU and renewable energies consumption is concentrated at the all-quantiles levels (0.10 to 0.90). This wide distribution indicates that the effect of MPU permeates nearly all levels of renewable energy consumption, reflecting the pervasive nature of monetary uncertainty across different market conditions. Notably, the causality exhibits significant temporal variation, with marked intensification during the 2005-2009 and 2011-2015 periods. These intervals likely coincide with episodes of heightened macroeconomic turbulence, such as the global financial crisis and subsequent recovery phases, when fluctuations in monetary policy were more pronounced and, as a result, had a stronger spillover effect on investment decisions and operational activities within the renewable energy sector. Conversely, the period from 2020 to 2023 shows a weakened causal relationship, suggesting that recent developments, including shifts in the global economic environment, changes in policy frameworks, or evolving market conditions, have mitigated the influence of monetary policy uncertainty on renewable energy investments. Furthermore, SLR emerges as the most sensitive to MPU fluctuations, displaying the highest level of causality. This pronounced sensitivity could be attributed to the capital-intensive nature of solar projects and the sector’s reliance on rapidly evolving technological and financial conditions, which make it more reactive to shifts in monetary policy. On the other hand, HDR shows the lowest causality with MPU, suggesting a relative insensitivity that might stem from the mature, long-term infrastructure characteristic of hydropower projects, which are typically less vulnerable to short-term monetary fluctuations. This confirms the prior research (e.g., Lu et al.;[56] Li et al.;[57] Wang et al.[58]). Figure 5: TVNQC plots of causal impact of MPU on SLR, HDR, WND, and BIO. Source: Author’s research in R-studio Figure 6 shows the time-varying causal impact of FPU on SLR, HDR, WND, and BIO. The results display that the time-varying causality between FPU and renewable energies consumption is appearing at the low, medium, and high quantiles (0.15 to 0.80). This broad range implies that fiscal policy uncertainty does not solely affect extremely low or high consumption levels; rather, its impact is distributed across the entire consumption spectrum. However, the causality is not static over time. Instead, it exhibits clear temporal fluctuations, with pronounced periods of stronger causality during 2011–2015 and again in 2017–2019. These intervals may correspond to periods when fiscal policy was undergoing significant shifts or when macroeconomic conditions heightened fiscal risks, thereby exerting more substantial influence on investment decisions and consumption patterns within the renewable energy sectors. Meanwhile, the period from 2020 to 2023 is characterized by a relatively weaker causal linkage, possibly reflecting the sensitivity of the causal nexus between FPU and REC to the changes in policy responses, market destabilization, global economic crisis, and rising geopolitical risks. Among the four energy types, BIO exhibits the strongest causal relationship with FPU, suggesting that fluctuations in fiscal uncertainty are most keenly felt in the biomass sector. This heightened sensitivity may be due to the capital-intensive and policy-dependent nature of biomass investments, where fiscal signals play a critical role in driving financing decisions and operational adjustments. In contrast, SLR shows the weakest causal connection with FPU, indicating that the solar sector might be less vulnerable to fiscal uncertainty, potentially due to more diversified financing structures, technological advancements, or stronger policy support that cushions against fiscal fluctuations. These findings coincide with past studies research (e.g., Su et al.;[59] Wang et al.;[60] Zhao et al.[61]) Figure 6: TVNQC plots of the impact of FPU on SLR, HDR, WND, and BIO. Source: Author’s research in R-studio Conclusion The present research delves into the asymmetric impact of monetary and fiscal policy uncertainty on energy transition in the United States, using U.S renewable energy consumption from solar, hydropower, wind and biomass as proxy US energy transition, with monthly data spanning from January 2000 to November 2023, by applying the multivariate quantile on quantile approach (MQOQ) and time-varying nonparametric quantile causality (TVNQC) approaches. The MQOQ results show that U.S. monetary and fiscal policy uncertainty indexes have a significant asymmetric impact on different renewable energy consumption, where the monetary policy uncertainty index has the bigger impact, while renewable energy consumption from biomass has the strongest relationship with monetary and fiscal policy uncertainty indexes than the author’s sources. The TVNQC outcomes reveals a strong time-varying causality of U.S. monetary and fiscal policy uncertainty indexes with all renewable energies consumption sources, except for the period of covid-19 and Russia-Ukraine war (2020-2023), whereas biomass source shows a stronger causality with US monetary and fiscal policy uncertainty indexes respectively than the author renewable energies sources. The implications of this result are crucial for policymakers and investors involved in shaping transformation plans in the U.S. energy sector. First, policymakers should design tailored incentives for each sector. For example, targeted subsidies or tax credits could be implemented for solar projects during periods of high monetary uncertainty, while biomass sectors might benefit more from direct fiscal support, as well as adopting frameworks that can adjust monetary and fiscal measures in real time based on market conditions. Additionally, the dynamic causal nexus between policy uncertainty and renewable energy consumption can help authorities design policies that are more resilient during economic stress and capitalize on periods of stability. Moreover, by tailoring interventions to both the sector and the prevailing economic conditions, policymakers can better support long-term investments in renewable energy. Second, investors should diversify their investments across different renewable energy sectors can help to mitigate risks associated with policy fluctuations, also adjust their strategies in anticipation of future turbulent periods by increasing hedging measures or reallocating assets to more resilient sectors. Furthermore, by implementing flexible and dynamic strategies, investors can take advantage of both uncertain and certain periods to invest in renewable energy and capitalize on the entire energy transition. Even though the current study advances the understanding of how monetary and fiscal policy uncertainty affects the US energy transition, some limitations need to be acknowledged. For example, the analysis is focused mainly on the United States and a specific set of renewable energy sources. Future research could extend the analysis by generalizing the findings a cross-country framework or using sector-specific renewable energy consumption. 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Sustainability Disclosure, CEO Duality, and Ownership Concentration: Evidence from Georgia
This study examines the determinants of corporate sustainability disclosure in Georgia, emphasizing the influence of CEO duality and ownership concentration. The absence of significant external demand for sustainability information and a robust regulatory framework often limits the voluntary release of such information. This research utilizes a sustainability disclosure scorecard developed in accordance with the EU Corporate Sustainability Reporting Directive, encompassing key environmental, social, and governance dimensions. Analyzing annual reports from all listed companies in Georgia from 2018 to 2021 through descriptive statistics and hierarchical multiple regression, findings highlight that board chair/CEO role duality and concentrated ownership significantly undermine sustainability disclosure. Specifically, CEO duality adversely affects social and governance metrics, while concentrated ownership primarily diminishes environmental transparency. These insights enhance understanding of the factors influencing corporate sustainability disclosure in emerging economies. The findings of this study may also provide valuable implications for local policymakers, who could use this information to develop more detailed and rigorous draft laws concerning sustainability disclosure requirements. Keywords: Sustainability disclosure, ESG, determinants, ownership structure, corporate governance, emerging market. Introduction It has long been recognized that business is about more than just making money, and corporate sustainability disclosure plays a significant role in enabling firms to communicate and engage with stakeholders.[1] Therefore, society in general and capital providers in particular are increasingly interested in corporate sustainability disclosure to satisfy their demand for corporate sustainability performance.[2] Previous research has extensively explored the drivers of sustainability disclosure, yet the prevailing insights predominantly emerge from markets with strong external legitimacy and agency pressures on sustainability. The generalizability of these findings to developing economies, which are marked by distinct institutional and socio-economic contexts, remains questionable.[3] In such markets, corporate disclosure practices are shaped by comparatively weaker sustainability pressures due to underdeveloped capital markets and limited influence of non-governmental organizations, media, civil society, consumer advocates, and activists. Moreover, these economies often display reduced legitimacy aspirations and lack the robust enforcement mechanisms and corporate governance frameworks necessary to protect human and environmental rights.[4] Recognized conventional drivers of sustainability disclosure include firm size, which indicates a company’s resource capabilities, and industry sensitivity, which reflects the influence of stringent regulations.[5] The impact of other factors, such as ownership structure and corporate governance mechanisms, presents a more mixed picture.[6] For instance, dispersed ownership may encourage managerial commitment to sustainability disclosure as a strategy to reduce agency conflicts. Similarly, the separation of CEO and board chair roles, which reduces the concentration of power in the CEO, is linked to greater accountability and possibly more comprehensive sustainability disclosures.[7] These governance structures create internal pressures that can drive management to prioritize sustainability initiatives. This study investigates the drivers of corporate sustainability disclosure among publicly listed companies in Georgia, a developing economy characterized by passive capital markets and modest media scrutiny.[8] According to the Law of Georgia on Accounting, Reporting, and Auditing (2016) (Article 7),[9] public interest entities employing over 500 individuals are required to report key non-financial indicators, including those related to environmental, social, employment, human rights, anti-corruption, and bribery issues, starting from 2018. Additionally, the evolving corporate governance landscape and significant ownership concentration in Georgia present a unique context for examining the effects of ownership structure and CEO duality on the extent of corporate sustainability disclosures.[10] By presenting empirical evidence from a largely underexplored, developing economy, this study contributes to the sustainability disclosure literature. Unlike research focused on developed markets with robust legitimacy pressures, our findings suggest that in settings characterized by underperforming capital markets and minimal external demand for sustainability disclosures, corporate governance mechanisms play a crucial role. This paper not only provides a comprehensive conceptual framework for understanding the primary literature on sustainability disclosure, its origins, theoretical perspectives, and methodologies, but also aligns its approach with the EU’s Corporate Sustainability Reporting Directive (CSRD), laying the groundwork for future research replication. From a regulatory perspective, our results offer valuable insights for local regulators by evaluating the adoption levels and drivers of sustainability disclosure, informing ongoing discussions, and guiding future amendments to the accounting law to enforce stricter sustainability standards. The next section outlines the theoretical background, the institutional framework of Georgia, and our hypotheses. Section 3 details the data and methodology, Section 4 presents the results, and Section 5 provides the conclusion and discussion. Theoretical Background and Hypotheses 1.1 Theoretical lens and conceptual framework Corporate sustainability disclosure is a tool for communication between corporate managers and a wide range of external stakeholders: investors and other capital providers, the general public, civil society, professional associations, NGOs, regulators, employees, etc. In line with this complexity, the field uses a wide range of theories: resource-based,[11] legitimacy,[12] agency,[13] stakeholder,[14] signaling,[15] and voluntary disclosure,[16] among others. Due to the complementary and often overlapping nature of these theories, a more extensive understanding of sustainability disclosure practices is possible using a multi-theory lens to explain firms’ willingness to engage in sustainability disclosure.[17] Sustainability disclosure’s theoretical framework is conceptualized in Figure 1. Figure 1. Conceptual framework for sustainability disclosure (author’s own) Socio-political sustainability disclosure stream. The literature on corporate sustainability disclosure can be divided into two streams: socio-political and economic streams. The socio-political stream follows the corporate social responsibility (CSR) path and perceives the general public as the primary user of sustainability information, viewing environmental and social disclosure through the lens of the role of information in the organization-society dialogue, arguing that firms tend to disclose voluntarily to “legitimize” their activities and thus change public perception of the firm. A strong reputation in the social arena is thought to attract high-quality employees and reduce transaction costs (e.g., by reducing employee turnover) and distributional conflicts (e.g., by disclosure on the firm’s practices in terms of diversity, equal pay, fair trade conditions, etc.). By enabling a firm to attract more competent, capable, and productive human capital, build brand loyalty, and broaden the customer base, firms are said to be able to achieve sounder financial performance.[18] The socio-political stream uses the lenses of legitimacy and stakeholder theories, whereby ﬁrms are willing to voluntarily engage in sustainability disclosure to, first, legitimize their maneuvers and, second, balance the expectations of various stakeholders. Legitimacy theory is perhaps the most widely used theory in the field. Developed in the organizational theory era, it argues that public and societal pressures lead to environmental and social disclosures aimed at gaining social legitimacy. According to this framework, a firm’s value system is congruent and aligned with society’s expectations. Stakeholder theory has a more specific focus on a particular group of stakeholders, suggesting that firms disclose information even when not required to meet stakeholder expectations. Sustainability disclosure in this case is a tool through which firms communicate with external stakeholders to gain attractiveness and ensure sustainable performance.[19] The applicability of legitimacy and stakeholder theories is often tested by examining the importance of firm size and industry sensitivity as drivers of sustainability disclosure. These theories argue that legitimacy reasons are more visible for larger firms and those operating in environmentally sensitive sectors. Larger firms are subject to greater external public pressure, and sustainability disclosure helps these firms maintain a “social contract” and successfully attract resources. Similarly, environmentally sensitive firms, such as those in the mining, fossil fuel, oil, and coal sectors, face greater risks associated with environmental damage due to their propensity for carbon and other emissions.[20] Economic sustainability disclosure stream. The economic stream builds on the information asymmetry problem embedded in the agency theory, with a focus on investor/capital market orientation. Information asymmetry between managers and shareholders is a product of insiders’ higher awareness of the firm’s fundamentals compared to outsiders. To balance such asymmetry, managers voluntarily disclose sustainability information as a source of communication with the external parties.[21] This literature stream branches into agency and signaling theories. Agency theory suggests that because quantifiable and objective (i.e., “hard”) sustainability disclosure requires the use of sound management control systems to identify, measure, and report this information, such behavior is associated with increased and real economic production costs that only successful firms are likely to be willing to incur. Disclosing information about a firm’s environmental and social technologies, processes, practices, and performance may not only be commercially sensitive but may also entail regulatory, contractual, reputational, and opportunity costs. For example, the provision of objective sustainability information verifies a firm’s potential future (and current) actions or commitments, thereby reducing the management’s discretionary capacity and increasing costs. As such, firms with better financial performance should be more willing, ready, and able to incur such costs by providing more extensive sustainability disclosures.[22] Instead, signaling theory suggests that managers disclose sustainability data to send a positive signal about the ﬁrm’s performance. Thus, firms with better environmental and social performance are more likely to voluntarily disclose sustainability data to differentiate themselves from their competitors and ultimately gain a competitive advantage by improving their market position.[23] Under agency theory, scholars use financial leverage and ownership structure measures, arguing that more leveraged firms, as well as those owned by a broad range of owners, are subject to greater external pressures and therefore act more responsibly and disclose more information. As for signaling theory, scholars use liquidity and profitability measures, suggesting that “only” those firms with sound financial performance diligently disclose costly sustainability data.[24] 1.2 The context of Georgia Demand for corporate (non)financial information in Georgia is limited. Georgia’s capital markets are only able to exert meaningful pressure on managers’ reporting diligence at a low level.[25] Moreover, the media and NGO sectors are associated with limited resources and high levels of political partisanship,[26] making them less likely to alter legitimacy aspirations.[27] The Law of Georgia on Accounting, Reporting and Audit (2016) addresses non-financial disclosure, albeit superficially. Article 7 of the law requires that the management reports of the largest (“Category I” entities, as defined by the Law) Georgian public interest entities (PIEs) with an average number of employees exceeding 500 during the reporting period should include key non-financial information on the “development, performance, position and impact of the company’s activities with respect to environmental, social, employment matters, human rights, anti-corruption and bribery issues”. The largest PIEs have been required to file their sustainability information since 1 October 2018. All other entities are not required to file such information, and there is no direct (e.g., tax) benefit for them to do so.[28] The Law of Georgia on Entrepreneurs was improved in 2021. By filling the gaps regarding supervisory board members, shareholder rights, meeting procedures, fiduciary duties, and capital reduction provisions, the awareness of corporate governance is increasing, but it will take time and patience to build a valid corporate governance culture. The board is a two-tier system that includes the supervisory board (board of directors) and the management board. Securities issuers are required to include a corporate governance report with a statement on compliance, internal control, risk management systems, and shareholder rights. The banks’ code, additionally, requires the governance of ESG-related components, including board discussions to address ESG risks and disclosures.[29] Local companies are closely held by the owners, with board members often bypassed and decisions made directly between management and controlling shareholders. For example, the largest direct owner of securities issuers owns more than 90% of the capital, indicating a high degree of ownership concentration. Effective enforcement and compliance practices are needed to instill the values and awareness of effective corporate governance among corporate actors. Companies tend to disclose only at a level that is sufficient for compliance, and little effort is made to go beyond the basic requirements. A mechanism that would further incentivize healthy corporate governance is lacking. Shareholder (including minority) rights are relatively well protected on paper, but in practice, there are more concerns (e.g., in terms of related party transactions). In addition, in situations involving complex transactions or where simple arm’s length comparisons are not possible, supervisory boards may find it difficult to maintain objectivity due to the influence of controlling shareholders. There are instances where supervisory board members appear to put the company’s interests first in the absence of clear obligations to protect shareholder interests. The average number of supervisory board members among PIEs is around 5.1, while almost half show no evidence of female representation.[30] Overall, considering the existing external demand for information,[31], [32] alongside the development and enforcement of regulatory frameworks, the corporate sustainability environment in Georgia is not yet poised for effective sustainability disclosure. 1.3 Hypothesis development Ownership concentration. Ownership structure can have a significant impact on sustainability disclosure. Under the ownership structure, we focus on ownership concentration. An increase in the dispersion of ownership can lead to an increase in information asymmetries, which in turn can lead to more frequent conflicts of interest between management and stakeholders. Disclosure on environmental and social issues can play an important role in managing such agency conflicts. As corporate ownership becomes more widely dispersed, stakeholder demands for “extracurricular” corporate activities become more diverse. In contrast, firms with concentrated ownership have fewer incentives to disclose sustainability information, as they can obtain the required information directly from the firm.[33] In addition, more concentrated ownership, ceteris paribus, may be a proxy for the public’s passive interest in the firm. Limited public interest, and thus limited external pressure, can only weakly motivate corporate managers to activate their inclinations toward social and environmental concern. In response to these increased demands, management is likely to disclose environmental information directly rather than communicating it separately to each investor.[34] Consequently, it is reasonable to expect that firms with more dispersed ownership will disclose a greater amount of corporate sustainability information. Therefore, we posit: H1: Ownership concentration negatively affects corporate sustainability disclosure in Georgia. CEO duality. As investors continue to ask for better information on how companies manage sustainability, corporate governance is seen as the foundation for building a firm’s sustainability disclosure habits. Corporate governance is a system that deals with the effectiveness of relationships between the board of directors, shareholders, stakeholders, and management. A sound corporate governance system focused on sustainability should help companies identify material sustainability information that enables them to properly consider the risks and opportunities related to sustainability issues and make strategic decisions. The effectiveness of corporate governance is important in markets with weak legal frameworks, as it can serve as an effective substitute for mandatory sustainability disclosure. Accordingly, the literature suggests that firms with strong corporate governance are likely to be more responsible and demonstrate higher levels of social and environmental responsibility.[35] Scholars argue that regulators may be better served by focusing on improving corporate governance quality (rather than mandatory sustainability disclosure) as a way to increase CSR disclosure.[36] As such, boards of directors should (and do) prioritize the firm’s environmental performance because it is expected to be positively related to shareholder wealth and other non-financial benefits.[37] Under corporate governance, we refer to CEO duality, namely, when the CEO also chairs the board. CEO duality implies a lack of distinction between decision control and decision management.[38] While evidence of the impact of CEO duality on voluntary disclosure is mixed, we suggest that CEO duality reduces overall accountability, resulting in less sustainability transparency. CEO duality can be detrimental to shareholder interests because a powerful CEO can override the necessary checks and balances within the organization.[39] Combining the CEO and board chair roles reduces conflicts of interest, in turn reducing accountability pressures. In contrast, when the roles are separated, the chair has the ability and motivation to create an environment where other board members can contribute effectively, leading to board independence. As such, CEO duality inhibits open and honest discussions about the firm’s performance. Therefore, we posit: H2: CEO duality negatively affects corporate sustainability disclosure in Georgia. Method We examine all Georgian public companies granted this status for the fiscal year 2021. These companies are allowed to publicly issue their shares on the local capital market. In addition, we expanded the sample to include companies that voluntarily expressed interest in participating in the Best Annual Reporting and Transparency Award (BARTA). In this way, we cover the entire population of listed companies and a significant portion of the largest Georgian companies that are likely to report at least some sustainability information. The financial variables were manually extracted from the annual reports of the sampled firms, which we retrieved from the official website of the Ministry of Finance of Georgia (https://reportal.ge/en). The analysis covers the period 2018–2021. After eliminating observations with missing data, the final sample consists of 36 firms and 140 firm-year observations. Our objective is to identify the drivers of corporate sustainability disclosure. In line with the literature, we construct a sustainability disclosure scorecard based on the EU’s CSRD (2022, Article 19b), which is aligned with the generally accepted framework and guiding principles of the Global Reporting Initiative (GRI).[40], [41] Our sustainability disclosure scorecard includes general parameters and ESG indicators. General attributes focus on report content and presentation, covering regulatory basis, conciseness, reliability, completeness, consistency, and comparability. For instance, the regulatory basis assesses whether reports follow international frameworks. The environmental dimension evaluates corporate interactions with nature, including climate change mitigation, water and marine issues, resource efficiency, circular economy, air pollution, and biodiversity. The social dimension addresses diversity, equality, and workplace safety, covering equal opportunities (gender equality, pay equity, inclusion of people with disabilities, training), working conditions (wages, job security, social dialogue, work-life balance, safe work environments), and respect for human rights. The governance aspect assesses management’s role in sustainability, business ethics (anti-corruption, anti-bribery), political engagement (lobbying), stakeholder relationships (payment practices), and internal control systems for disclosure (CSRD, 2022). We build a sustainability disclosure scorecard by manually going through the annual reports of each company and coding the content according to the sustainability disclosure scorecard. We code the relevant sections and sentences of each company’s annual reports for each year, paying attention to the use of graphic illustrations, as recommended by the CSRD framework. We analyze 140 annual reports, classifying the text of each report according to its thematic content: a) whether the disclosure states a certain approach (e.g., a support for gender balance) at the policy level, b) whether concrete actions are shown that supports the stated policy (e.g., more women hired in the most recent recruitment to achieve the stated gender balance goal), and c) whether the final result (e.g., the “right” gender balance between men and women in the workforce) has been achieved and disclosed (at all levels of management). We used this classification for each of the aforementioned ESG sustainability disclosure indicators. We also considered linguistic attributes, such as the semantic nature of the information provided, and distinguished text units by type of measure, such as non-quantitative (e.g., support for climate change action) and quantitative (e.g., support for climate change action following the Paris Agreement threshold of 1.5ºC of global warming).[42] To ensure the consistency and reliability of the classification procedure, we conducted a pre-test to verify the authors’ coding rules and approaches. We also re-tested the comparability of our results with the BARTA award scores for companies that participated in the competition. The coefficient of agreement, and thus the ratio of pairwise inter-judge agreement to total pairwise judgments, is above acceptable levels in both cases. Our model incorporates the two commonly used independent variables: firm size (log of total assets)[43] and industry sensitivity (real estate, construction, and the financial sector).[44] Our variables of interest are ownership concentration (% of capital owned by the largest shareholder)[45] and CEO duality (dummy variable for CEO role duality that takes the value 1 if the CEO and board chair are the same person, and 0 otherwise).[46] In addition, we use some control variables that have been reported to be significant in driving sustainability disclosure in emerging economies, including regulation (a dummy variable for mandatory disclosure that takes value 1 for firms subject to mandatory sustainability disclosure according to the 2016 Law of Georgia, and 0 otherwise),[47] foreign ownership (dummy variable that takes value 1 if a firm is owned by a foreign shareholder, and 0 otherwise),[48] financial leverage (total liabilities over total assets),[49] profitability (net income over total revenues; with alternative values such as ROA and ROE),[50] Big 4 (a dummy variable that takes value 1 if a report was audited by one of the Big 4, and 0 otherwise), and language (a dummy variable that takes value 1 if the annual report was prepared both in Georgian and English, and 0 otherwise).[51] Results and Analysis 3.1 Descriptive statistics Table I presents descriptive statistics of the sustainability scorecard and financial variables for Georgian listed companies. The average sustainability score stands at 34%, highlighting relatively low disclosure practices compared to EU standards.[52] Notably, 22 observations (16%) completely lack sustainability information. Despite a nascent regulatory framework, certain foreign-listed entities, particularly banks, demonstrate robust reporting, adhering to international standards like the TCFD and disclosing comprehensive greenhouse gas emissions data. The sustainability disclosure scorecard reveals an uneven emphasis across its dimensions, with the general criterion achieving the highest average at 10.3 points out of 25. This reflects a trade-off between conciseness and completeness, where efforts to provide thorough information might result in lower conciseness scores. The ESG pillars show varying levels of reporting depth: environmental issues scored the lowest at 7 points, governance at 7.7, and social issues at 9.5. Environmental disclosures are sparse, with 40% of reports omitting this data entirely, though some engagement in resource use and recycling is noted. Social sustainability metrics are more consistently addressed, with similar scores across their sub-pillars. However, while companies often express a commitment to human rights and gender equality, actual reporting on relevant KPIs and detailed statistics on gender balance in leadership remains scarce and skewed. In one of the cases, although gender balance is postulated as a high priority, the figures show a female-to-male ratio of 4 to 1. Gender balance is often interpreted as having no less than 50% female employees, but the same does not apply to males. In the governance dimension, Georgian companies fare better in areas like anti-corruption, bribery, customer relations, and internal control mechanisms; however, there is a notable lack of disclosure concerning political engagements and lobbying. This omission is particularly evident among major financial institutions with alleged political affiliations, suggesting a deliberate avoidance of disclosing such sensitive connections. Moreover, risk mitigation committees rarely address sustainability issues like climate change, except in the largest internationally listed banks. Table I. Descriptive statistics of sustainability disclosure scorecard and financial variables Notes: SUST_Score stands for a sustainability score that varies between 0 and 100 and incorporates general attributes and ESG metrics of the sustainability disclosure. SIZE is given in 1,000 GEL (3 GEL = 1 USD). SIZE, PROF, and LEV are winsorized at 5%. N=140. Table I (Part B) details the financial characteristics of the sample, encompassing profitability, firm size, and leverage. The average profitability is 6%, with a median of 9%, indicating some variability in financial performance among the firms. The distribution of total assets, measured in thousands of Georgian Lari (GEL), is highly skewed: while the mean assets amount to GEL 1,202 million, influenced by large banks, the 75th percentile firm holds considerably less, at GEL 488 million. This skewness reflects the disproportionate impact of a few large entities on the sample’s average. The financial leverage across the firms is substantial yet typical for the sector, with total liabilities averaging 68% of total assets, displaying a normal distribution across the dataset. A descriptive table (un-tabulated) drops down the sustainability disclosure score by industry and year. The dataset includes four primary industry groups: finance (39 observations), construction and real estate (22), manufacturing (32), and a diverse “other” category (47 observations), encompassing sectors like healthcare, electricity, accommodation, retail, and transport. Sustainability disclosure varies significantly across industries. The finance sector leads with a score of 49 out of 100, reflecting its pivotal economic role and stringent regulatory oversight. The environmentally sensitive construction and real estate sector scores 40, outperforming finance in environmental reporting. Manufacturing lags with an average sustainability score of only 12. The “other” sectors achieve a score of 35. Yearly data shows little variation, with scores slightly increasing from an average of 32-33 points in 2018-2019 to 36-37 in 2020-2021. Sustainability practices, once reported, tend to persist in subsequent reports, exemplified by repeated mentions of initiatives like the Green Box campaign. Pearson correlations (un-tabulated) highlight associations between the model variables. The SUST_Score strongly correlates with its components (r > 0.88, p < 0.01) and general attributes (r = 0.97, p < 0.01). It also has significant correlations with firm size (r = 0.70), industry sensitivity (r = 0.38), mandatory disclosure (r = 0.38), CEO duality (r = -0.47), Big 4 (r = 0.37), and reporting language (r = 0.24), all at p < 0.01. No association is found between firm profitability and sustainability levels. Variance Inflation Factors (VIFs) remain below 2, confirming no multicollinearity concerns. 3.2 Regression analysis Table II presents the results of the OLS fixed effects regressions on the determinants of sustainability disclosure. The regression for sustainability disclosure (SUST Score) (column 1) is accompanied by the regressions for the sustainability pillars: general (GEN Score) and ESG (ENV Score, SOCL Score, and GOV Score) (columns 2-5). The adjusted R-squared of the SUST Score model is 58%, implying good power in explaining the variation of the sustainability scorecard data points around their mean. The power of the model is higher compared to similar studies conducted in emerging markets.[53] The hierarchical model regressions show that firm size (SIZE_log: β = 0.08, p < 0.01) and industry dummy (IND_SENSITIVITY: β = 0.08, p < 0.1) are the main drivers of sustainability disclosure. They alone can explain 54% of the variation of the sustainability scorecard around its mean. Larger companies and those operating in more regulated sectors provide significantly more sustainability information than their counterparts. Larger firms, and hence with more resources, are more likely to disclose more scrupulous sustainability information, which is consistent with legitimacy theory. Size is a significant variable (p < 0.01) in all five regressions. Larger firms tend to disclose more on all four pillars: general, environmental, social, and governance. Including the variables of interest increases the adjusted R-squared of the model, but only by 2%. Table II. Determinants of sustainability disclosure. Control variables include: mandatory model of reporting, profitability, financial leverage, Big4 dummy, financial report language dummy, foreign ownership, and board diversity. Notes: t statistics in parentheses; *** p < 0.01; ** p < 0.05; * p < 0.10. VIF highest value = 2.14. Observing the coefficients of the variables of interest, we note that the results support both H1 and H2. Ownership concentration (%_LARGEST_OWNER: β = -0.12, p < 0.1) and CEO duality (CEO_DUALITY: β = -0.08, p < 0.05) both have a negative impact on sustainability disclosure. This implies that companies with more concentrated ownership are likely to exert weaker controlling mechanisms, reducing transparency and accountability, and therefore tend to provide less detailed sustainability disclosure information. Similarly, companies where CEOs simultaneously serve as board members and key decision-makers are also inclined to provide less comprehensive sustainability disclosures, likely due to reduced oversight and checks on management. These findings align with prior studies, which suggest that dispersed ownership and independent board structures contribute to more robust sustainability reporting practices. Conclusion, Discussion, and Limitations This study investigates the role of CEO duality and ownership concentration on corporate sustainability disclosure in the context of Georgia. Based on 140 unique firm-year observations of the largest (listed) Georgian companies, our findings suggest a relatively limited prevalence of sustainability disclosure among firms listed on the Georgian capital market compared to more developed contexts.[54] The observed low level of sustainability disclosure is likely due to limited resources and a scarce awareness of the importance of sustainability disclosure as a tool for communicating with external stakeholders. In the context of the pillars of sustainability disclosure, there is a comparatively stronger emphasis on social issues, while environmental issues receive relatively less attention. This finding is consistent with studies conducted in emerging markets, suggesting that firms in developing contexts often struggle to address both social and environmental dimensions simultaneously.[55] Limited resources coupled with the costs associated with sustainability disclosure appear to force firms in developing economies into a trade-off between the two dimensions. As a result, the social pillar tends to receive more disclosure, as there is greater public awareness and direct interest in working conditions, wages, workplace safety, and gender equality. This contrasts with the relatively indirect and distant perceptions of climate change. Societal focus in developing economies is often on short- and medium-term goals related to basic human needs, rather than the more future-oriented “premium” goals related to environmental protection, which tend to come to the fore only after immediate needs have been met.[56] At the multivariate level, we show that firm size and industry sensitivity are the main drivers of sustainability disclosure, consistent with prior studies.[57] In a developing context with limited external demand, we show that it is the mandatory nature and thus the regulatory burden that pushes firms to engage in socially and environmentally responsible behavior. Aligning with our hypotheses, we show that ownership concentration and corporate governance mechanisms play a significant role in the propensity of firms to report on sustainability. Our analysis also suggests that those firms with a more dispersed ownership structure and separate CEO/chair roles report more on sustainability issues. These findings are consistent with the existing literature, which suggests that ownership dispersion positively impacts the extent of sustainability disclosure.[58] Furthermore, our study supports previous research that has found a negative impact of CEO duality on the extent of sustainability disclosure.[59] Better sustainability disclosure practices can be achieved not only by strengthening external demand for sustainability issues but also by improving internal corporate governance mechanisms. The local regulator can play an important role in improving the sustainability disclosure practices in Georgia. The current regulatory framework for non-financial disclosure is general and does not specify the details, format, and order of sustainability disclosure. With the development of the European Sustainability Reporting Standards, it is hoped that the next draft of the Accounting Law of Georgia will more specifically define the sustainability disclosure requirements. Nevertheless, our study has some limitations. First, despite the detailed manual content analysis of the firm’s annual reports, it is difficult to assess whether the results can be generalized to the Georgian population or beyond. Our analysis considers four consecutive years (2018–2021), and the sample of the largest Georgian firms may not provide a holistic picture of sustainability disclosure in Georgia. Beyond listed companies (as is the case for Category III and IV companies), sustainability disclosure is likely to be even less common. Future research could extend our study using different samples to test our findings. Second, measuring the quality of sustainability disclosure by quantifying the notional information provided may be biased because codification is susceptible to the subjectivity of the context and the measurer. We evaluated all companies using the same matrix, with equal weighting given to the “general” and ESG components. It may be the case that for a group of companies, reporting on certain sustainability elements may be less relevant due to the nature of their operations. In addition, different ESG components in the matrix have different numbers of elements, but the same weight (25%) is assigned to each, resulting in an unbalanced score if the scorer assigns the lower points with less consideration and the higher points with more rigor. We compared our findings to the BARTA award results, and the analysis does not reveal any material differences. The comparative analysis across companies and sectors also remains valid. Finally, our models capture some potentially important determinants of sustainability disclosure, with explanatory power often exceeding 50%. Nevertheless, future studies could attempt to measure and include variables such as media coverage/reach, sustainability awareness, and so forth, at the firm level. Bibliography: Ali, W., Frynas, J. G., Mahmood, Z. (2017). 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A resource-based perspective on corporate environmental performance and profitability. Academy of management Journal, 40(3); Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3); Stacchezzini, R., Melloni, G., Lai, A. (2016). Sustainability management and reporting: the role of integrated reporting for communicating corporate sustainability management. Journal of Cleaner Production, 136(November); Verrecchia, R. E. (2001). Essays on disclosure. Journal of accounting and economics, 32(1-3); World Bank. (2021). Georgia Corporate Governance Report on the Observance of Standards and Codes. Available at: <https://openknowledge.worldbank.org/server/api/core/bitstreams/100d9e33-fbd4-5086-a6c5-8c7d600ab360/content>. Footnotes [1] De Villiers, C., Venter, E. R., Hsiao, P. C. K. (2017). Integrated reporting: background, measurement issues, approaches and an agenda for future research. Accounting & Finance, 57(4), pp. 937-959. [2] Pirveli, E., Ortiz-Martínez, E., Marín-Hernández, S., Thompson, P. (2025). Influencing sustainability: the role of lobbyist characteristics in shaping the EU’s Corporate Sustainability Reporting Directive. Sustainability Accounting, Management and Policy Journal, 16(2), pp. 415-442. [3] Qiu, Y., Shaukat, A., Tharyan, R. (2016). Environmental and social disclosures: Link with corporate financial performance. The British Accounting Review, 48(1), pp. 102-116. [4] Kuzey, C., & Uyar, A. (2017). Determinants of sustainability reporting and its impact on firm value: Evidence from the emerging market of Turkey. Journal of Cleaner Production, 143(February), pp. 27-39. [5] Kolsi, M. C., Attayah, O. F. (2018). Environmental policy disclosures and sustainable development: Determinants, measure and impact on firm value for ADX listed companies. Corporate social responsibility and environmental management, 25(5), pp. 807-818. [6] Ismail, A. M., Latiff, I. H. M. (2019). Board diversity and corporate sustainability practices: Evidence on environmental, social and governance (ESG) reporting. International Journal of Financial Research, 10(3), pp. 31-50. [7] Hamad, S., Draz, M. U., Lai, F.-W. (2020). The impact of corporate governance and sustainability reporting on integrated reporting: A conceptual framework. Sage Open, 10(2), pp. 1-15. [8] Pirveli, E., Zimmermann, J. (2015). Time-series properties of earnings: the case of georgian stock exchange. Journal of Business and Policy Research, 10(1), pp. 70-96. [9] Law of Georgia on Accounting, Reporting and Auditing, (2016). Available at: <https://saras.gov.ge/Content/files/bugaltruli-agricxvis-angarishgebis-da-auditis-shesaxeb-kanoni.pdf>. [10] World Bank. (2021). Georgia Corporate Governance Report on the Observance of Standards and Codes. Available at: <https://openknowledge.worldbank.org/server/api/core/bitstreams/100d9e33-fbd4-5086-a6c5-8c7d600ab360/content>. [11] Russo, M. V., Fouts, P. A. (1997). A resource-based perspective on corporate environmental performance and profitability. Academy of management Journal, 40(3), pp. 534-559. [12] Gray, R., Kouhy, R., Lavers, S. (1995). Corporate social and environmental reporting. Accounting, Auditing & Accountability Journal, 8(8), pp. 47-77. [13] Jensen, M. C., Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of financial economics, 3(4), pp. 305-360. [14] Freeman, R. E., Harrison, J. S., Wicks, A. C., Parmar, B. L., De Colle, S. (2010). Stakeholder theory: The state of the art. Cambridge University Press. [15] Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), pp. 355-374. Available at: <https://www.jstor.org/stable/1882010>. [16] Verrecchia, R. E. (2001). Essays on disclosure. Journal of accounting and economics, 32(1-3), pp. 97-180. [17] Fernando, S., Lawrence, S. (2014). A theoretical framework for CSR practices: Integrating legitimacy theory, stakeholder theory and institutional theory. Journal of Theoretical Accounting Research, 10(1), pp. 149-178. [18] Cormier, D., Ledoux, M. J., Magnan, M. (2011). The informational contribution of social and environmental disclosures for investors. Management Decision, 49(8), pp. 1276-1304. [19] Desai, R. (2022). Determinants of corporate carbon disclosure: A step towards sustainability reporting. Borsa Istanbul Review, 22(5), pp. 886-896. [20] Kumar, P., Firoz, M. (2018). Impact of carbon emissions on cost of debt-evidence from India. Managerial Finance, 44(12), pp. 1401-1417. [21] Healy, P. M., Palepu, K. G. (2001). Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature. Journal of accounting and economics, 31(1-3), pp. 405-440. [22] Brammer, S., Pavelin, S. (2008). Factors influencing the quality of corporate environmental disclosure. Business Strategy and the Environment, 17(2), pp. 120-136. [23] Ben-Amar, W., Chang, M., McIlkenny, P. (2017). Board gender diversity and corporate response to sustainability initiatives: Evidence from the carbon disclosure project. Journal of business ethics, 142(2), pp. 369-383. [24] Ali, W., Frynas, J. G., Mahmood, Z. (2017). Determinants of corporate social responsibility (CSR) disclosure in developed and developing countries: A literature review. Corporate social responsibility and environmental management, 24(4), pp. 273-294. [25] Pirveli, E. (2020). Earnings persistence and predictability within the emerging economy of Georgia. Journal of Financial Reporting and Accounting, 18(3), pp. 563-589. [26] Foundation, E. (2021). Georgia Media Landscape Assessment. Available at: <https://epfound.ge/static/file/202206134459-media-good-governance.-09.06.22.pdf>. [27] Pirveli, E., Thompson, P. (2022). ESG Indicators of Sustainability Reporting in Emerging Georgia: Application Levels, Determinants and the Impact. 5th International Conference on Applied Research in Management, Economics and Accounting, Barcelona, Spain. [28] Pirveli, E. (2024). Corporate disclosure timing under IFRS: the case of emerging Georgia. Journal of Financial Reporting and Accounting, 22(5), pp. 1253-1283. [29] World Bank. (2021). Georgia Corporate Governance Report on the Observance of Standards and Codes. Available at: <https://openknowledge.worldbank.org/server/api/core/bitstreams/100d9e33-fbd4-5086-a6c5-8c7d600ab360/content>. [30] Ibid. [31] Pirveli, E. (2014). Accounting quality in Georgia: Theoretical overview and development of predictions. International Journal of Business and Social Science (USA), 5(3), pp. 283-293. [32] Pirveli, E. (2020). Earnings persistence and predictability within the emerging economy of Georgia. Journal of Financial Reporting and Accounting, 18(3), pp. 563-589. [33] Ruhnke, K., Gabriel, A. (2013). Determinants of voluntary assurance on sustainability reports: an empirical analysis. Journal of Business Economics, 83(9), pp. 1063-1091. [34] Cormier, D., Magnan, M. (1999). Corporate environmental disclosure strategies: determinants, costs and benefits. Journal of Accounting, Auditing & Finance, 14(4), pp. 429-451. [35] Haniffa, R. M., Cooke, T. E. (2005). The impact of culture and governance on corporate social reporting. Journal of Accounting and Public Policy, 24(5), pp. 391-430. [36] Chan, M. C., Watson, J., & Woodliff, D. (2014). Corporate governance quality and CSR disclosures. Journal of Business Ethics, 125(September), pp. 59-73. [37] De Villiers, C., Naiker, V., Van Staden, C. J. (2011). The effect of board characteristics on firm environmental performance. Journal of Management, 37(6), pp. 1636-1663. [38] Fama, E. F., Jensen, M. C. (1983). Separation of ownership and control. The journal of law and Economics, 26(2), pp. 301-325. [39] Cheng, E. C., Courtenay, S. M. (2006). Board composition, regulatory regime and voluntary disclosure. The international journal of accounting, 41(3), pp. 262-289. [40] Orazalin, N., Mahmood, M. (2020). Determinants of GRI-based sustainability reporting: evidence from an emerging economy. Journal of Accounting in Emerging Economies, 10(1), pp. 140-164. [41] Pirveli, E., Thompson, P. (2022). ESG Indicators of Sustainability Reporting in Emerging Georgia: Application Levels, Determinants and the Impact. 5th International Conference on Applied Research in Management, Economics and Accounting, Barcelona, Spain. [42] Stacchezzini, R., Melloni, G., Lai, A. (2016). Sustainability management and reporting: the role of integrated reporting for communicating corporate sustainability management. Journal of Cleaner Production, 136(November), pp. 102-110. [43] Kolsi, M. C., Attayah, O. F. (2018). Environmental policy disclosures and sustainable development: Determinants, measure and impact on firm value for ADX listed companies. Corporate social responsibility and environmental management, 25(5), pp. 807-818. [44] Hassan, A., Elamer, A. A., Fletcher, M., Sobhan, N. (2020). Voluntary assurance of sustainability reporting: Evidence from an emerging economy. Accounting Research Journal, 33(2), pp. 391-410. [45] Faisal, F., Situmorang, L. S., Achmad, T., Prastiwi, A. (2020). The role of government regulations in enhancing corporate social responsibility disclosure and firm value. The Journal of Asian Finance, Economics and Business (JAFEB), 7(8), pp. 509-518. [46] Hamad, S., Draz, M. U., Lai, F.-W. (2020). The impact of corporate governance and sustainability reporting on integrated reporting: A conceptual framework. Sage Open, 10(2), pp. 1-15. [47] Faisal, F., Situmorang, L. S., Achmad, T., Prastiwi, A. (2020). The role of government regulations in enhancing corporate social responsibility disclosure and firm value. The Journal of Asian Finance, Economics and Business (JAFEB), 7(8), pp. 509-518. [48] Matuszak, Ł., Różańska, E. (2020). Online corporate social responsibility (CSR) disclosure in the banking industry: evidence from Poland. Social Responsibility Journal, 16(8), pp. 1191-1214. [49] Li, D., Huang, M., Ren, S., Chen, X., Ning, L. (2018). Environmental legitimacy, green innovation, and corporate carbon disclosure: Evidence from CDP China 100. Journal of business ethics, 150, pp. 1089-1104. [50] Masoud, N., Vij, A. (2021). The effect of mandatory CSR disclosure on firms: empirical evidence from UAE. International Journal of Sustainable Engineering, 14(3), pp. 378-389. [51] Orazalin, N., Mahmood, M. (2020). Determinants of GRI-based sustainability reporting: evidence from an emerging economy. Journal of Accounting in Emerging Economies, 10(1), pp. 140-164. [52] Gatti, L., Seele, P. (2014). Evidence for the prevalence of the sustainability concept in European corporate responsibility reporting. Sustainability Science, 9(May), pp. 89-102. [53] Desai, R. (2022). Determinants of corporate carbon disclosure: A step towards sustainability reporting. Borsa Istanbul Review, 22(5), 886-896. [54] Gatti, L., Seele, P. (2014). Evidence for the prevalence of the sustainability concept in European corporate responsibility reporting. Sustainability Science, 9(May), pp. 89-102. [55] Ching, H. Y., Gerab, F., Toste, T. H. (2017). The quality of sustainability reports and corporate financial performance: Evidence from Brazilian listed companies. Sage Open, 7(2), 2158244017712027. [56] Belal, A. R., Cooper, S. M., Khan, N. A. (2015). Corporate environmental responsibility and accountability: what chance in vulnerable Bangladesh? Critical Perspectives on Accounting, 33(December), pp. 44-58. [57] Bhatia, A., Tuli, S. (2017). Corporate attributes affecting sustainability reporting: an Indian perspective. International Journal of Law and Management, 59(3), pp. 322-340. [58] Matuszak, Ł., Różańska, E. (2020). Online corporate social responsibility (CSR) disclosure in the banking industry: evidence from Poland. Social Responsibility Journal, 16(8), pp. 1191-1214. [59] Lassoued, N., Khanchel, I. (2023). Voluntary CSR disclosure and CEO narcissism: the moderating role of CEO duality and board gender diversity. Review of Managerial Science, 17(3), pp. 1075-1123.
Hofstede’s National Cultural Dimensions in the Managerial Context (Case study)
Efficient management is crucial for organizational development, considering the diverse national cultures worldwide. Solid empirical and theoretical knowledge exists globally to study cultural dimensions’ role in this context. However, findings cannot be generalized to every culture, including Georgia, without local research on values and characteristics. This study aimed to identify Georgian society’s cultural dimensions, influenced by both Western and Eastern elements due to its unique geographical position and context. Understanding these dimensions is essential for effective human resource management and cross-cultural cooperation in organizations, facilitating successful business activities. The literature review highlights how national culture impacts management practices, citing studies by various scholars. The research employed Hofstede’s cultural dimensions framework, updated with insights from five major Georgian cities, using quantitative methods to ensure representative findings. Comparing the dimensional scores of cultural orientations of Polish culture studied similarities and differences, driven by shared history and regional proximity. The study’s innovative approach addresses gaps in empirical cross-cultural management research in Georgia, offering recommendations for leadership and HR management in local organizations. Hypotheses were formulated and tested using self-administered surveys and SPSS software, confirming Georgia’s individualistic tendencies and moderate long-term orientation. Differences between educational levels and national comparisons with Poland were also explored, revealing insights into cultural orientations. Limitations consider studying only two dimensions and five cities in the country. Keywords: Hofstede’s cultural dimensions, individualism vs collectivism, short-long term orientation, management. Introduction This research aimed to explore Georgia’s unique cultural dimensions, shaped by both Western and Eastern influences, to inform effective human resource management and cross-cultural cooperation. The literature review discusses how national culture impacts management, referencing studies by different authors. Using Hofstede’s[1] cultural dimensions framework, the study conducted a quantitative analysis in five major Georgian cities. It compared Georgian cultural traits with Polish culture, identifying both similarities and differences due to shared history and regional context. The study offers new insights into Georgia’s cultural orientations, with findings on individualism and long-term orientation, and explores the impact of education levels. However, it is limited by its focus on just two cultural dimensions and five cities. Literature Review Hofstede’s Cross-Cultural Model Welzel and colleagues[2] identified three key factors driving cultural change: socioeconomic shifts, value changes, and political institutions. Socioeconomic changes include technological innovation, improved health and life expectancy, higher income, better education, and increased access to information. The second factor is market expansion, while the third involves political institutions, particularly efforts to enhance democracy. To understand Georgian culture, it’s important to consider these influences from the country’s recent past. Hofstede and Bond[3] introduced the concept of “Long-term versus short-term orientation” based on the Chinese Value Survey (CVS). The study compared students from 23 countries to highlight these cultural differences. The Implications of National Culture in Management Tarhini and colleagues[4] highlight the reciprocal influence between culture and organizational processes, where culture impacts business practices and vice versa. A diverse environment is seen as a valuable opportunity in business.[5] It was suggested that HR practices are shaped by managers’ perceptions of workers and tasks,[6],[7] which are, in turn, influenced by their cultural orientation.[8] Additionally, it was emphasized that the concepts of self and personality, linked to individualistic cultures, play a key role in branding and advertising.[9] In collectivist societies, self-identity is shaped by the social context, with behavior varying according to the situation.[10] Marketers use various strategies to build loyalty among current and potential customers, with branding often incorporating personality, especially in individualistic cultures. Hofstede and colleagues noted that long-term-oriented traders focus on building lasting relationships and partnerships based on trust, while those with short-term orientation prefer more immediate, transactional interactions. People from individualistic cultures aim to fulfill their potential. Plim and his colleagues found that individualism, long-term focus, and indulgence are key cultural factors that support national innovation.[11] Polish Cultural Orientation Poland’s shared Communist past likely influenced its long-term versus short-term orientation. However, according to Hofstede’s Insights, Polish society now has a moderately individualistic orientation (55) and an intermediate score (47) for Flexibility vs. Monumentalism (FLX/MON). Poland’s geographical location, surrounded by Western individualistic countries, also plays a role in shaping its cultural orientation. Factors Influencing on Georgian Culture Georgian historian Giorgi Anchabadze presents the significant influence of Soviet rule on Georgia’s cultural and economic development. During the period from 1801 to 1878, Georgia was under Russian imperial control, freedom of speech was suppressed, and harsh punishments on dissenters were imposed. Despite attempts at independence, Georgia fell under Soviet rule, where private property was abolished, industries nationalized, and dissenters persecuted. The Soviet era brought industrialization, collectivization of agriculture, and cultural suppression, stifling artistic expression and limiting economic opportunities. The collapse of the Soviet Union in 1991 resulted in economic downturns across former member states, including Georgia, marking a significant shift in its socio-economic landscape. In conclusion, the literature suggests that in this context, competition in the market was not prioritized, quantity outweighed quality, and there were limited development opportunities across all fields. Hence, the system upheld collectivistic values in Georgian society.[12] Ganesan views investment as a key indicator of long-term orientation,[13] while investing in education is considered as crucial for productivity and well-being. Although quality education doesn’t guarantee employment or full potential, it increases the chances of success. There is a high demand for higher education, as many students apply for National Unified Exams each year. Additionally, in Georgia’s banking sector, various types of savings deposits are offered to help customers save for the future, with different durations and modest returns, illustrating another example of long-term orientation.[14] As Georgia transitioned from socialism to capitalism, individuals gained the right to own businesses and private property, reflecting a shift toward Western values. The country joined international organizations, including the Council of Europe,[15] World Trade Organization.[16] Former President Eduard Shevardnadze expressed interest in joining NATO[17] and the European Union.[18] The Georgian population strives to get close to European Union and Western values. Notably, a geographical factor of the country can potentially influence neighboring countries. Specifically, Russia scored 56 in FLX/MON and 57 in Individualism/Collectivism. The score is intermediate but above 50. If we go through the previous (2017-2021) and current (2022-2030) Strategic plans of the Ministry of Education and Science of Georgia, Internationalization is a key strategy in higher and professional education, emphasizing the importance of becoming more globally oriented rather than ethnocentric. Methodoloy Minkov and Hofstede used data from the World Values Survey to redefine Long-Term Orientation. Their subsequent work, particularly the study by Minkov introduced an updated dimension named Monumentalism-Flexumity. The following model classifies nations into Monumentalist cultures, prevalent in regions like the Middle East and Africa, which emphasize mutual assistance and reputation, and Flexumility cultures, which prioritize flexibility and adaptability.[19] The study considered applying a quantitative approach to generalize findings across a population, ensuring precision through statistical analysis of substantial raw data obtained from respondents. This analysis aimed to identify the indices of several cultural dimensions.[20] Validation of the Model The model, widely used by authors at Hofstede’s Insights Center, has been utilized to conduct in more than 54 national cultures, using a revised framework by Michael Minkov[21]. Calculating scores for dimensions was performed through regression analysis. In our study, regression analysis was applied alongside published indices from other countries provided by Hofstede’s Insights Center.[22] Research Instrument In the framework of the study, we utilized an instrument about cultural values provided by the Hofstede Research Center. The survey was meticulously formed by specialized groups, including psychologists. It comprised 102 items on a three-level scale, covering topics related to culture, personality, consumer behavior, and demographic information. The use of forced-choice items enabled precise measurement of concept intensity compared to free-choice items. The instrument was translated into the local language and back to verify accuracy, and each item was contextualized to ensure semantic equivalence. The research sample consisted of individuals with at least a high school education, evenly split between genders. Research Design of Study N1 The sample for the following study was randomly selected from five major cities to ensure equal opportunity for potential respondents to participate. This approach, grounded in both empirical and theoretical frameworks, aimed for a representative sampling method. The questionnaire was distributed in two stages to reach the desired number of responses, considering past low response rates with lengthy questionnaires. Initially sent to 630 individuals, 122 incomplete responses were excluded, resulting in a 75% response rate from 472 participants who completed all questions. Cross-checking questions helped filter out illogical responses, yielding data from 468 respondents, balanced. Research Design of Study N2 Focused on understanding Georgians’ past experiences, this study calculates scores for IND/COL and LO/ST Orientation. Applying to Hofstede’s Insights Research Center’s precise sampling methodology, data was analyzed from respondents with higher education levels. This approach allows for comparison of aggregated means and scores from previous studies with a larger sample of 200 respondents, comprising 111 females and 89 males, distributed across Tbilisi (59), Kutaisi (46), Batumi (29), Rustavi (39), and Zugdidi (27). This research also incorporates comparing Georgian cultural indices of Ind/Coll and FlX/MON with those of Polish society. The selection of Poland is justified by its geographical proximity to Georgia and shared historical influence, characterized by collectivistic values and short-term orientation similar to Georgia. The following survey was employed to gather data from both nations, facilitating direct comparison. Research Findings Findings of Study N1 According to the obtained data from all age groups, the calibrated equation yielded a score of approximately 59.45 for the Individualism/Collectivism (IND/COLL) dimension in Georgian society, whereas the regression analysis indicated a score of approximately 54.05. This suggests that Georgian culture leans towards individualism. Conversely, on the Flexumility/Monumentalism (FLX/MON) dimension, Georgia scored lower with a calibrated score of approximately 17.66 and a regression-based score of 57.4, indicating a long-term-oriented culture. In summary, the study confirms the first and second hypotheses that Georgian culture is both individualistic and long-term oriented. Despite potential deviations attributed to the research instrument, the general orientation remains consistent, albeit potentially slightly lower in score. Findings of Study N2 In both samples, Georgian society demonstrated consistent tendencies towards individualism and long-term orientation. Despite the small differences, the IND scores were 54.05 and 54.9, and the LTO scores were 57.4 and 57.9. In conclusion, it is anticipated that Georgian society needs certain time and generational change to increase scores in the following dimensions. A shift towards Western values is expected among younger people with modern education and less Soviet influence. Research Findings of Study N3 Despite differences among nations, comparing cultural orientations based on two dimensions through scores provides interesting insights. Using aggregated mean data from Hofstede’s Insights Research Center, we rescaled and converted cultural scores to a 0-100 scale, applying regression analysis to evaluate each orientation’s level. It’s notable that, for cross-cultural comparisons, we utilized scores from a smaller sample (the individuals with only high school education) similar to other countries. In terms of scores, Poland got around 55.72 on the scale for IND/COLL and around 47.12 for FLX/MOM. The scores underline Polish culture’s higher level of individualism compared to Georgian society, while Polish scores for Flexumility-Monumentalism were lower than those for Georgia. Polish society exhibited higher individualism scores than Georgian society. However, Georgian culture showed higher scores for Long-Term Orientation (LTO). Figure 1 – Comparative scores. Source: Author’s research The differences in the Flexumility dimension may stem from factors such as social desirability bias, varying sample sizes, and data being collected at different times. Research limitatins Every study has limitations. Scholars agree that larger sample sizes lead to more accurate representations of the general population, so expanding the sample size in each city could be a focus for future research. Additionally, including more cities would provide a more accurate evaluation of cultural dimensions at the national level. The current model does not analyze other dimensions based on survey data, so we cannot confirm the existence of dimensions like power distance or indulgence vs. restraint. We hope future research will develop a more comprehensive model with relevant items for analysis. It was emphasized that nations may not be the best unit of analysis for cultural differences, as countries often contain various subcultures. They also noted that culture is dynamic and evolving due to globalization, technology, and other challenges. Therefore, it’s important to periodically study cultural dimensions to maintain up-to-date knowledge for future development.[23] Conclusion The study underscores the critical importance of examining national cultural orientations across various domains. The theoretical framework highlighted in the research underscores how cultural dimensions significantly impact organizational behavior and related fields. In addressing the empirical gap within the Georgian cultural context, this research employed a meticulous methodology encompassing diverse target groups and precise sample selection. By calculating dimensional scores from two distinct samples, the study revealed insights into the lingering influence of the Soviet experience on older generations. The findings, derived from both smaller and comparative analyses with over 50 other national cultures studied by Hofstede’s Insights Research Center, yielded compelling results, particularly in the comparison of Georgian and Polish cultures. The hypotheses concerning Individualism orientation were substantiated, with intermediate scores. Similarly, the acceptance of Georgian society’s Long-Term Orientation aligns with the study’s expectations despite some non-significant variables in regression analysis. Surprisingly, Polish culture exhibited a lower score in Long-Term Orientation compared to Georgian culture while demonstrating a higher Individualism orientation. Despite its limitations, this study holds implications for organizational contexts in Georgia. The theoretical foundation offers robust insights into cultural dimensions’ role in organizational development. Generalizable findings at the national level can inform management practices, ensuring organizational alignment with cultural preferences. Recommendations for managing individualistic orientations include promoting fairness, involving employees in decision-making, implementing formal job appraisal systems, offering motivating rewards, granting autonomy, and providing developmental opportunities. Team-building efforts should be prioritized for tasks requiring collective effort among individuals with the following orientation. Lastly, management should engage in ongoing dialogue regarding long-term organizational goals and invest in employee professional development to support long-term employment. Flexibility in managing human resources across Georgian and Polish societies is crucial. In conclusion, this study and its insights into cultural orientations offer valuable guidance for scholars and managers navigating organizational development challenges. Bibliography: Anchabadze, G. (2005). History of Georgia: A short sketch. Caucasian House; Aycan, Z., Kanungo, R. N., Sinha, J. P. (1999). Organizational Culture and Human Resource Management Practices: The Model of Culture Fit. Journal of Cross-Cultural Psychology. <https://doi.org/10.1177/0022022199030004002>; Buller, P. F., McEvoy, G. M. (2012). Strategy, Human Resource Management and Performance: Sharpening Line of Sight. Human Resource Management Review, 22(1); Ganesan, S. (1994). Determinants of Long-Term Orientation in Buyer-Seller Relationships. Journal of Marketing, 58(2). Retrieved from <https://doi.org/10.1177/002224299405800201>; Hofstede, G., Bond, M. (1988). The Confucius connection: From cultural roots to economic growth. Organizational Dinamics, Elsevier, 16(4); Hofstede, G. (2011). Dimensionalizing cultures: the Hofstede model in context Online Readings Psychology and Culture., 2 (1) (2011). International Association for Cross-Cultural Psychology, 2(1); Hofstede’s Insights. (n.d.). Retrieved March 30, 2022, from <https://hi.hofstede-insights.com/about-geert-hofstede>; Lenartowicz, T., Roth, K. (2001). Does subculture within a country matter? A cross-cultural study of motivational domains and business performance in Brazil. Journal of International Business Studies, 32(2). doi:10.1057/palgrave.ji; Ludviga, I. (2009). Measuring Cultural Diversity: Methodological Approach and Practical Implications; Assessment in Latvian. The International Journal of Diversity in Organisations, Communities and Nations, 9(3); Markus, H. (1991). Culture and the self: implications for cognition, emotion and motivation. Research Gate, 98(6); Minkov, M., Hofstede, G. (2012) Hofstede’s Fifth Dimension: New Evidence from the World Values Survey. Journal of Cross-Cultural Psychology, 43. http://dx.doi.org/10.1177/0022022110388567 Minkov, M. (2018). A revision of Hofstede’s model of national culture: Old evidence and new data from 56 countries. Cross-Cultural and Strategic Management, 25(2); Minkov, M. (2018b). What values and traits do parents teach their children? New data from 54 countries. Comparative Sociology, 17(2); Mooij, M. D. (2015, January). The Hofstede Model Application to Global Branding and Advertising Strategy and Research. International Journal of Advertising, 29(1); Prim, A. L., Filho, L. S., Luiz, C., Zamur, G. A. (2017, June). The Relationship Between National Culture Dimensions and Degree of Innovation. International Journal of Innovation Management, 21(3). Tarhini, A., Hone, K., Liu, X., Tarhini, T. (2016). Examining the Moderating Effect of Individual-level Cultural values on Users’ Acceptance of E-learning in Developing Countries: A Structural Equation Modeling of an extended Technology Acceptance Model. Interactive Learning Environments. <https://doi.org/10.1080/10494820.2016.1183183>; Weisbrod, B. A. (1996). Education and Investment in Human Capital. Journal of Political Economy, 70(5). Retrieved from <https://www.journals.uchicago.edu/doi/abs/10.1086/258728>; Welzel, C., Inglehart, R., & Klingemann, H.-D. (2003). The theory of human development and the development of human theory. Political Psychology, 24(3). <https://doi.org/10.1111/1475-6765.00086>; Council of Europe. Georgia. Council of Europe, accessed June 26, 2022. <https://www.coe.int/en/web/portal/georgia>. World Trade Organization. Georgia and the WTO: Accessions. World Trade Organization, accessed December 21, 2021. <https://www.wto.org/english/thewto_e/acc_e/a1_georgia_e.htm>. InfoCenter of the Government of Georgia. NATO and Georgia: History. InfoCenter, accessed December 21, 2021. <https://infocenter.gov.ge/en/nato-georgia/nato-georgia-history/>. Ministry of Foreign Affairs of Georgia. Georgia–European Union Relations: Key Events Chronology. Ministry of Foreign Affairs of Georgia, accessed December 25, 2021. <https://mfa.gov.ge/en/european-union/903144-saqartvelo-evrokavshiris-urtiertobebis-mnishvnelovani-movlenebis-qronologia>. Footnotes [1] Hofstede, G. (2011). Dimensionalizing cultures: The Hofstede model in context. Online Readings in Psychology and Culture, 2(1). International Association for Cross-Cultural Psychology [2] Welzel, C., Inglehart, R. Klingemann, H. D. (2003). The Theory of Human Development and the Development of Human Theory, Political Psychology 24(3), pp. 493–511. <https://doi.org/10.1111/1475-6765.00086>. [3] Hofstede, G., Bond, M. (1988). The Confucius Connection: From Cultural Roots to Economic Growth. Organizational Dynamics 16(4), pp. 5–21. [4] Tarhini, A., Hone, K., Liu, X., Tarhini, T. (2016). Examining the Moderating Effect of Individual-Level Cultural Values on Users’ Acceptance of E-Learning in Developing Countries: A Structural Equation Modeling of an Extended Technology Acceptance Model. Interactive Learning Environments. <https://doi.org/10.1080/10494820.2016.1183183>. [5] Ludviga, I. (2009). Measuring Cultural Diversity: Methodological Approach and Practical Implications; Assessment in Latvian. The International Journal of Diversity in Organisations, Communities and Nations 9(3), pp. 67–78. [6] Aycan, Z., Kanungo, R. N., Sinha, J. P. (1999). Organizational Culture and Human Resource Management Practices: The Model of Culture Fit. Journal of Cross-Cultural Psychology. <https://doi.org/10.1177/0022022199030004002>. [7] Buller, P. F., McEvoy, G. M. (2012). Strategy, Human Resource Management and Performance: Sharpening Line of Sight. Human Resource Management Review 22(1), pp. 43–56. [8] Hofstede, G., Bond, M. (1988). The Confucius Connection: From Cultural Roots to Economic Growth. Organizational Dynamics 16(4), pp. 5–21. [9] Mooij, M. D. (2015). The Hofstede Model Application to Global Branding and Advertising Strategy and Research. International Journal of Advertising 29(1), pp. 84–110. [10] Markus, H. (1991). Culture and the Self: Implications for Cognition, Emotion, and Motivation. Research Gate 98(6), pp. 224–246. [11] Prim, A. L., Filho, L. S., Luiz, C., Zamur, G. A. (2017). The Relationship Between National Culture Dimensions and Degree of Innovation. International Journal of Innovation Management, 21(3), pp. 5-8. [12] Anchabadze, G. (2005). History of Georgia: A short sketch. Caucasian House. [13] Ganesan, S. (1994). Determinants of Long-Term Orientation in Buyer-Seller Relationships. Journal of Marketing 58(2), pp. 1–19. <https://doi.org/10.1177/002224299405800201>. [14] Weisbrod, B. A. (1996). Education and Investment in Human Capital. Journal of Political Economy 70, no. 5. <https://www.journals.uchicago.edu/doi/abs/10.1086/258728>. [15] Council of Europe. Georgia. Council of Europe, accessed June 26, 2022 <https://www.coe.int/en/web/portal/georgia>. [16] World Trade Organization. Georgia and the WTO: Accessions. World Trade Organization, accessed December 21, 2021. <https://www.wto.org/english/thewto_e/acc_e/a1_georgia_e.htm>. [17] InfoCenter of the Government of Georgia. NATO and Georgia: History. InfoCenter, accessed December 21, 2021. <https://infocenter.gov.ge/en/nato-georgia/nato-georgia-history/>. [18] Ministry of Foreign Affairs of Georgia. Georgia–European Union Relations: Key Events Chronology. Ministry of Foreign Affairs of Georgia, accessed December 25, 2021. <https://mfa.gov.ge/en/european-union/903144-saqartvelo-evrokavshiris-urtiertobebis-mnishvnelovani-movlenebis-qronologia>. [19] Minkov, M., Hofstede, G. (2012). Hofstede’s fifth dimension: New evidence from the World Values Survey. Journal of Cross-Cultural Psychology, 43, pp. 2–14. <https://doi.org/10.1177/0022022110388567>. [20] Minkov, M. (2018). A revision of Hofstede’s Model of National Culture: Old Evidence and New Data from 56 Countries. Cross-Cultural and Strategic Management 25(2), pp. 231–256. [21] Minkov, M. (2018b). What values and traits do parents teach their children? New data from 54 countries. Comparative Sociology, 17(2) [22] Hofstede’s Insights. (n.d.). About Geert Hofstede. Retrieved March 30, 2022, from https://hi.hofstede-insights.com/about-geert-hofstede [23] Lenartowicz, T., Roth, K. (2001). Does Subculture Within a Country Matter? A Cross-Cultural Study of Motivational Domains and Business Performance in Brazil. Journal of International Business Studies 32(2), pp. 269–279. <https://doi.org/10.1057/palgrave.ji>.
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Enhancing Tourism in the South Caucasus through Coopetition
This article explores the concept of “coopetition” as a strategic approach for enhancing tourism development in the South Caucasus region, comprising Armenia, Azerbaijan, and Georgia. The region holds significant tourism potential but faces infrastructure gaps, limited awareness, safety standards, and accessibility. Additionally, political instability, including the Armenia-Azerbaijan conflict and the ongoing occupation of Georgian territories by Russia, has hindered growth. Fortunately, recent peace efforts between Azerbaijan and Armenia offer opportunities for collaborative tourism initiatives, potentially boosting economic stability. Through an assessment of tourism intelligence, competitiveness, and regional dynamics, the study identifies key areas where these countries can both compete and cooperate to attract high-value tourists. Coopetition offers a strategy for enhancing the region’s competitiveness through joint marketing, shared tourist routes, and improved cross-border infrastructure while also allowing each country to utilize its unique strengths in niche tourism products. At the same time, coopetition also poses risks, such as unequal benefit distribution and coordination challenges in aligning policies, among other issues. The analysis concludes that by balancing competition with strategic cooperation, the South Caucasus countries can boost regional tourism, attract high-value visitor segments, strengthen their global market position, and contribute to lasting peace in the region. Keywords: Tourism Policy, Coopetition, South Caucasus Region. Introduction The Caucasus region, often hailed as the cradle of European civilization, stands at the crossroads of Europe and Asia, serving as a vital cultural and geographical corridor. This unique positioning has profoundly influenced the societies within the South Caucasus—comprising Georgia, Armenia, and Azerbaijan—leading to a rich fusion of European and Asian cultural elements. Renowned for its natural beauty and cultural heritage, the South Caucasus offers an array of diverse tourism products that attract anyone in the world. The historical development of tourism in the region reflects its strategic geopolitical location and abundant resources. Early tourism initiatives were influenced by foreign expertise, particularly from Europe, which provided crucial recommendations on safety standards and infrastructure development. Although technological advancements have reshaped the tourism landscape, many of the challenges from the early tourism period, such as inadequate safety standards, poor infrastructure, limited advertising, and restricted accessibility, persist today, continuing to hamper the region’s full tourism potential.[1] Addressing these challenges through collaborative efforts among the three countries, with support from European partners, could enhance the region’s tourism potential and facilitate sustainable growth. A 2017 study examining the relationship between tourism competitiveness factors and performance in Azerbaijan, Georgia, and Armenia from 2007 to 2015 found that Azerbaijan led in tourism performance, primarily due to its oil and gas revenues. Furthermore, the study identified the Human, Cultural, Natural Resources Index as the most significant contributor to competitiveness, highlighting the need for enhanced regional cooperation and sectoral development to strengthen tourism in the South Caucasus.[2] The instability and conflicts have significantly undermined tourism development in the region. Georgia continues to grapple with the effects of its two conflict zones occupied by Russia, while the dispute between Armenia and Azerbaijan over the Karabakh region has severely impacted tourism flows. Additionally, the Russia-Ukraine conflict, despite being geographically distant, has further harmed the region’s image among long-haul tourists unfamiliar with the Caucasus region.[3] Recent developments, such as conflict resolution efforts between Armenia and Azerbaijan, suggest a more favorable environment for collaborative initiatives. Tourism, with its potential to boost employment, balance of payments, reduce poverty, and many other economic variables, could also serve as a tool for peacebuilding, helping to address political and economic challenges and fostering long-term stability in the South Caucasus. Environmental risks also pose a significant threat. The mountainous terrain, while a tourist attraction, exposes the region to natural disasters, necessitating advanced disaster management strategies. In Georgia, where 54% of the land is mountainous, natural processes have caused extensive damage to the tourism sector and related industries.[4] Natural disasters can also be linked to global warming. The country’s geographic and climatic traits make it susceptible to various calamities, such as floods, droughts, storms, landslides, mudslides, and avalanches.[5] Collaboration between countries on disaster management and climate adaptation strategies is essential, as limited resources make regional cooperation crucial for enhancing the safety of both residents and tourists. Despite these obstacles, the governments of Georgia, Armenia, and Azerbaijan recognize tourism as a critical driver of economic development. They are increasingly focusing on promoting their unique attractions, including wine regions, mountain landscapes, ancient monasteries, and cultural heritage, to attract high-value visitors from Europe, the U.S., and other global markets. However, the region remains heavily reliant on tourists from the post-Soviet states. Barriers to reaching high-value markets include limited financial resources, low international visibility, and the economic and political limitations of the region’s small nations. This paper examines the concept of ‘coopetition’—a blend of competition and cooperation—as a potential strategy to enhance the region’s appeal, focusing on perspectives such as the motives of coopetition and its determinants, as well as its potential positive and negative outcomes for the three tourism destinations. Previous research indicates that tourism destinations with high market commonality tend to form stronger business associations, fostering robust coopetition networks, while those with low commonality rely more on long-term firm strategies.[6] Destinations also tend to benefit from factors like interdependence, complementarity, shared goals, and geographical proximity, which make coopetition relationships more viable.[7] A long-term vision for tourism, along with strengthened associations or other collaborative frameworks among Azerbaijan, Armenia, and Georgia, could enable these countries to effectively use coopetition for mutual benefits. Given their shared tourism products, including cultural heritage and natural landscapes, such collaboration could significantly boost their competitive advantage in the global tourism market. The study will analyze the tourism product commonalities, target markets, and long-term visions of the three South Caucasus countries by assessing policy documents, national statistics, UNWTO data, and the World Economic Forum’s Travel and Tourism Competitiveness Index. Finally, it will identify areas where cooperation can maximize benefits and mitigate potential risks associated with coopetition. Tourism Policy and Product Commonalities in the South Caucasus Region Attracting both high-value and responsible tourists in the region requires effective policy and strategic planning, which are essential but proved to be insufficient. Policymakers, planning officials, and stakeholders of the three countries must recognize emerging trends and implement coordinated measures that promote sustainable growth and high-quality tourism offerings, benefiting both visitors and local communities. Tourism policy in this study is broadly defined to encompass marketing, planning, and sustainability. It refers to a framework of actions, guidelines, directives, and principles that guide the development of tourism within an ethical context.[8] These policies, whether legislative, administrative, or judicial, shape the growth and development of the tourism sector. They are often embedded in official documents, reflecting a nation’s vision for tourism planning, product development, marketing, and sustainable practices.[9] This chapter analyzes the strategic documents of Georgia, Armenia, and Azerbaijan to gain insights into each country’s tourism policy, highlighting the potential for regional collaboration. Georgia is currently transitioning from its 2015-2025 Tourism Strategy to a new plan that is expected to extend until 2035. This new strategy aims to integrate tourism and marketing strategies into a single, comprehensive document—moving away from the previous approach where strategic and marketing goals were addressed separately. The 2015-2025 strategy, developed with World Bank support, emphasized balanced growth through aligning resources and stakeholder needs, with a strong focus on attracting high-value tourists. Specifically, the 2025 Strategy vision positioned Georgia as a year-round, high-quality tourist destination renowned for its cultural and natural heritage, exceptional hospitality, and world-class services. Key investments targeted infrastructure, education, and the promotion of unique Georgian experiences, aiming to enhance global competitiveness.[10] To complement the strategic approach, Georgia’s marketing strategy identified three core tourism products: wine and gastronomy, nature and adventure, and cultural heritage. These focus areas were selected based on competitive analysis and emerging global trends, which highlighted demand for these experiences. Other segments such as health and wellness, city breaks, MICE tourism, and coastal tourism also play a significant role, ensuring diverse offerings for identified target markets.[11] Armenia’s tourism policy, outlined in the “Tourism Doing Business – Investing in Armenia” publication, emphasizes the country’s appeal through its cultural heritage, scenic landscapes, and niche tourism offerings like cultural, adventure, and gastronomy tourism. The document highlights the government’s pro-investment stance, underscored by infrastructure upgrades and the influx of international hotel chains. It argues that the Government Programme 2021-2026 in Armenia aims to attract 2.5 million international visitors through increased direct flights, enhanced visa regulations, and improved global visibility. On the other hand, the Tourism Committee’s 2025-2029 Strategy focuses on balanced regional growth, improved service quality, and developing Destination Management Organizations (DMOs) to diversify tourism products, including agritourism and specialized gastronomy tourism. Furthermore, Armenia promotes underdeveloped regions like Syunik, Vayots Dzor, Gyumri, and Dilijan to expand its tourism offerings beyond the capital. Moreover, strategic initiatives such as the “Armenia, The Hidden Track” campaign aim to attract high-value tourists, increase spending, and showcase the country’s cultural and natural appeal globally.[12] Azerbaijan’s 2023-2026 Tourism Strategy serves as a roadmap for aligning tourism development with broader national socio-economic goals. The strategy emphasizes sustainability, regional development, and competitiveness through a nine-pillar model, with the Azerbaijan Tourism Board (ATB) playing a key role, particularly since the launch of a new country brand in 2018 aimed at repositioning Azerbaijan as a sustainable tourism destination. On the other hand, Product development initiatives center around providing authentic and immersive experiences in nature, culture, and wellness. This includes the creation of cultural heritage routes, the design of recreational zones, and a focus on sustainable tourism that respects local communities. The overarching goal is to position Azerbaijan as a competitive, year-round destination offering diverse and high-quality tourism experiences.[13] Georgia, Armenia, and Azerbaijan share similar goals in their tourism strategies, such as attracting high-value tourists, improving service quality, and promoting regional development. Analyzing their policies reveals shared priorities like sustainable growth, investment in tourism infrastructure, and marketing strategies that emphasize cultural heritage and unique experiences. These commonalities in vision present opportunities for cooperation. The South Caucasus Counties can utilize their complementary tourism products and develop joint marketing campaigns, cross-border tourism offerings, and coordinated standards that enhance the South Caucasus’ appeal as a regional destination. These efforts can amplify the positive effects of regional tourism growth. Tourism Intelligence and Trends in the South Caucasus: A Comparative Analysis of Armenia, Azerbaijan, and Georgia The assessment of tourism statistics across Armenia, Azerbaijan, and Georgia reveals substantial disparities in data collection, methodology, and availability, complicating direct comparisons. Georgia leads in terms of data accessibility and clarity, providing a comprehensive range of tourism-related statistical indicators. Its tourism intelligence includes four Tourism Satellite Account (TSA) tables, offering a detailed picture of the sector’s demand side economic impact. However, Georgia’s statistical system lacks specific information about organized tourism, which would enhance its understanding of tourism dynamics. Azerbaijan, in contrast, covers both organized and non-organized tourism but offers a limited set of variables. Moreover, the absence of a TSA and insufficient methodological explanations weaken the overall reliability of its data. Armenia lags in terms of tourism research, having only recently reintroduced the International Visitor Survey in 2023 after an 11-year gap. Its data dissemination is also hindered by methodological inconsistencies and a lack of detailed explanations. Despite these differences, an analysis of the available common variables reveals important insights into the region’s tourism trends. The period from 2014 to 2023 highlights the steady pre-pandemic growth of international tourist arrivals in all three countries, followed by a sharp decline in 2020 due to the COVID-19 pandemic. By 2019, Georgia had established itself as the top destination in the region, attracting over 5 million tourist trips. Azerbaijan followed with approximately 2.9 million, while Armenia saw 1.9 million tourist trips. The pandemic resulted in significant reductions in tourist arrivals—Armenia (-81%), Azerbaijan (-82%), and Georgia (-79%). However, by 2023, Armenia had demonstrated strong resilience, surpassing pre-pandemic levels with a 22% increase in arrivals compared to 2019. Georgia also showed a solid recovery, reaching 4.67 million tourist arrivals, while Azerbaijan struggled to regain momentum, with only 1.40 million tourist trips due to continued land border restrictions. Figure 1: International Tourist Arrivals in South Caucasus Countries 2014-2023 (mln) Source: World Tourism Organization (2024), ‘UN Tourism Data Dashboard’, UN Tourism, Madrid, available online: <https://www.unwto.org/tourism-data/global- and-regional-tourism-performance>. Examining the purpose of international visits to South Caucasus Countries provides insight into the visitor segment structure in each country. Azerbaijan stands out, with 66.9% of its international visitors arriving for holiday, leisure, and recreation purposes, positioning it as a strong leisure tourism destination. Georgia follows with 52.3%, showcasing its diverse recreational offerings, while Armenia trails with 43.1%, suggesting a need for more aggressive marketing strategies to enhance its appeal in this segment. In contrast, Armenia leads in the “Visiting Friends and Relatives” (VFR) category, with 30.1% of its visitors motivated by familial ties, compared to Georgia (20.4%) and Azerbaijan (17.2%). This highlights the role of the Armenian diaspora in driving tourism. Meanwhile, Azerbaijan leads in business travel, with 11.0% of visitors arriving for professional reasons, positioning itself as an emerging business hub in the region, followed by Armenia (8.4%) and Georgia (6.8%). Figure 2: International Visitor Trips by Purpose of Visit to South Caucasus Countries in 2023 Source: National Statistics Office of Georgia, State Statistical Committee of the Republic of Azerbaijan, & Statistical Committee of the Republic of Armenia. Russia is the dominant source market for all three countries, accounting for half of the arrivals in Armenia, 36% in Azerbaijan, and 23% in Georgia. This heavy reliance on Russian tourists underscores the need for diversified source markets to mitigate potential economic risks. Armenia’s second-largest source market is Georgia (11%), reflecting the close ties between the two neighbors. In contrast, Azerbaijan attracts a broader range of visitors, with Türkiye (10%) and India (8%) being key contributors, demonstrating its appeal beyond the immediate region. Georgia’s strong connections with neighboring countries, especially Türkiye and Armenia, further emphasize its role as a regional tourism hub within the South Caucasus. Figure 3: Source Markets of South Caucasus Countries Source: World Tourism Organization (2024), ‘UN Tourism Data Dashboard’, UN Tourism, Madrid, available online: <https://www.unwto.org/tourism-data/global- and-regional-tourism-performance>. The analysis of international travel receipts from 2014 to 2023 reveals significant trends in the economic impact of tourism in Armenia, Azerbaijan, and Georgia, closely correlating with data on international tourist arrivals and source markets. Armenia’s receipts increased from $1.0 billion in 2014 to $3.0 billion in 2023, reflecting a robust recovery that aligns with its strong visitor numbers, particularly from Russia, which accounts for 50% of arrivals. In contrast, Azerbaijan’s receipts peaked at $2.7 billion in 2016 but experienced volatility, dropping to $0.3 billion in 2021 before recovering to $1.5 billion in 2023. This decline can be attributed to the limited international tourism activity during the pandemic and subsequent restrictions despite the country having a strong domestic tourism market. Georgia, consistently the leader in tourist arrivals, demonstrated a significant increase in receipts from $1.8 billion in 2014 to $4.1 billion in 2023, which correlates with its high volume of arrivals, particularly from Russia, Türkiye, and Gulf countries. Figure 4: International Travel Receipts 2014-2023 (Bln) Source: World Tourism Organization (2024), ‘UN Tourism Data Dashboard’, UN Tourism, Madrid, available online: <https://www.unwto.org/tourism-data/global- and-regional-tourism-performance>. The four-quadrant graph[14] illustrates the relationship between the average length of stay and the average daily expenditure for visitors in the South Caucasus countries. The vertical axis represents the average length of stay, which is 8.4 days across the region, while the horizontal axis shows the average daily expenditure, calculated at 142 USD. The product of these two values gives the average total expenditure per visitor in the South Caucasus, amounting to 872 USD. A key pattern observed from the graph is that the further east a country is located, the longer the average stay of international visitors. Armenia, positioned furthest east among the South Caucasus countries, has the longest average stay, with visitors staying 15.3 days. Conversely, Azerbaijan, located to the north, sees much shorter stays, averaging only 4.5 days. Georgia falls between these two extremes, with an average stay of 5.4 days. This suggests that visitors tend to spend more time in Armenia despite the relatively low daily expenditure there. The unusually long stays of visitors to Armenia require further research, as this may be attributed to methodological differences or the characteristics of the VFR (Visiting Friends and Relatives) segment, which tends to stay for longer periods. On the other hand, the graph shows that countries located further north tend to have higher daily expenditures. Azerbaijan stands out with the highest average daily expenditure of 225.8 USD, significantly exceeding the regional average. This can be attributed to the fact that only air travelers are allowed to cross the border, which tends to generate higher expenditures in the country. Georgia also sees relatively high spending, with visitors spending an average of 147.8 USD per day. Armenia, despite having the longest stay, shows the lowest daily expenditure, with visitors spending only 51.9 USD per day. The size of the circles in the graph indicates the total expenditure per visitor, combining both the length of stay and daily spending. Azerbaijan, despite the short average length of stay, sees a relatively high total expenditure per visitor. Georgia, with a moderate length of stay and daily expenditure, shows a total expenditure per visitor close to Armenia’s at 798 USD and 795 USD, respectively. Although Armenia has a longer stay, the lower daily expenditure results in a total expenditure that is comparable to Georgia. The diagram below shows that Azerbaijan attracts higher-spending visitors who stay for shorter periods, while Armenia attracts visitors who stay longer but spend less per day. Georgia falls in between, balancing moderate stays with moderate spending. Figure 5: Four Quadrant Diagram of South Caucasus Countries: Expenditure per day & Average Length of Stay Source: National Statistics Office of Georgia, State Statistical Committee of the Republic of Azerbaijan, & Statistical Committee of the Republic of Armenia. The diagram was constructed using Flourish. In summary, the assessment of tourism intelligence across Armenia, Azerbaijan, and Georgia underscores both the challenges and opportunities for each country. A key challenge that needs to be addressed through coordination is the methodological differences in tourism research. While methodological differences hinder direct comparability, the analysis of common variables reveals important trends in tourism arrivals, receipts, and visitor expenditure patterns. Georgia leads in terms of overall arrivals and revenue, Armenia shows resilience in its post-pandemic recovery, and Azerbaijan attracts high-spending visitors in the region but faces challenges in fully regaining its pre-pandemic momentum due to the border closure. Furthermore, the dominance of Russian tourists as a common source market reflects a shared reliance on this demographic. This presents both opportunities and risks, as fluctuations in Russian outbound tourism could significantly impact all three countries. Therefore, diversifying tourism is crucial for long-term stability, and this can be achieved through cooperation among the tourism sectors in the South Caucasus region. Competitiveness among the South Caucasus Countries The indicators provided by the World Economic Forum reveal a range of performances in Armenia, Azerbaijan, and Georgia, highlighting both strengths and areas for improvement in their tourism sectors.[15] Armenia, ranked 72nd in the Travel and Tourism Development Index (TDDI), leads the region in prioritization of travel and tourism (4.8) and demand sustainability (4.7), reflecting strong governmental commitment and resilient tourism demand. The country also performs well in safety and security (5.6) and health and hygiene (5.8). However, challenges persist in the business environment (4.0) and ICT readiness (5.0). Furthermore, Weak infrastructure, particularly in air transport (3.1) and tourist services and infrastructure (2.8), combined with underutilized natural (2.3), cultural (1.5), and non-leisure resources (1.5), limit Armenia’s full tourism potential. Azerbaijan, ranked 56th, leads the region in price competitiveness (5.8) and socioeconomic impact (4.4), positioning it relatively as a cost-effective destination in the region while demonstrating stronger contributions of tourism to its broader economy. Its scores in health and hygiene (5.5) and safety and security (5.3) remain reliable, ensuring a safe and stable environment for visitors. Nevertheless, Azerbaijan faces significant challenges in tourist services and infrastructure (2.8), natural resources (1.8), and non-leisure resources (1.5). Although it is the leader in cultural resources, its score remains low overall (2.5), signaling the need for improvement. These weaknesses reflect underdeveloped tourism infrastructure and limited utilization of the country’s natural and cultural assets, emphasizing the need for strategic investment to strengthen these areas and enhance its overall tourism offering. Georgia, ranked 45th, leads the region in several indicators, particularly excelling in safety and security (6.2) and openness to travel and tourism (4.5) compared to other South Caucasus countries. The country also demonstrates relatively strong performance in the business environment (4.9), ICT readiness (5.5), and air transport infrastructure (3.4). However, like Armenia and Azerbaijan, Georgia faces challenges in its tourist services and infrastructure(3.5). Its natural and cultural resources, along with non-leisure resources, while slightly better than those of its neighbors, remain low (2.1, 1.8, 1.6), highlighting the need for more focused efforts to fully utilize these assets. Figure 6: Heat MAP Travel and Tourism Development Index of South Caucasus Countries 2024 Source: World Economic Forum. (2024). Travel & Tourism Development Index 2024. World Economic Forum. Available online: <https://www.weforum.org/publications/travel-tourism-development-index-2024/interactive-data-and-economy-profiles-afaa00a59c>. In summary, tourism competitiveness shows a mixed performance across Armenia, Azerbaijan, and Georgia, each with unique strengths and challenges. Armenia demonstrates strong governmental commitment to tourism, excelling in safety, security, and demand sustainability but struggling with weak infrastructure and underutilized natural and cultural resources. Azerbaijan leads in price competitiveness and tourism’s socioeconomic impact but faces significant gaps in tourist services and resource utilization. Georgia, though leading in safety, openness, and business environment, shares similar challenges in infrastructure and resource development. To unlock their full potential, all three countries must address these infrastructural and resource-related weaknesses through targeted policies and investment, which could significantly boost the region’s overall tourism appeal. Cooperation and Competition in the South Caucasus Region The above analysis shows that the three countries are well-suited for a coopetition strategy. However, the question remains: Does coopetition have only positive effects, or could it also present challenges and risks for the three countries? Although the positive effects are evident—such as increased regional visibility, enhanced visitor experiences, access to new markets, and international support for regional cooperation and peacebuilding efforts—coopetition can also present challenges. Balancing cooperation and competition can be costly and complex, especially in terms of resource allocation. There may be an unequal distribution of benefits if one country has a more developed tourism infrastructure. Additionally, coordination challenges in aligning priorities, policies, and resources across the three countries may arise. To maximize the positive effects of coopetition and mitigate the negative ones, it is crucial to clearly distinguish the areas of cooperation and competition. Each country can use its unique strengths to compete for tourists at the company level while collaborating at the government level to enhance the region’s overall tourism appeal. As Schiavone and Simoni noted, cooperation occurs when companies complement one another to create a market while still competing for market share. In other words, the three countries can collaborate to attract high-value tourists yet still compete for their market share.[16] The South Caucasus countries have already made significant strides in promoting their unique attractions and competing in the tourism market. Each nation has developed a strong focus on cultural heritage, adventure tourism, and gastronomy, emphasizing its strengths to attract a wide range of visitors. Table 1: Potential Competitive and Cooperative Activities Competition Cooperation Cultural Heritage: Each country highlights its unique cultural and historical assets Joint Marketing and Intelligence Sharing: Develop unified marketing campaigns to promote the South Caucasus as a multi-country destination, while also sharing tourism statistical insights and addressing methodological differences in tourism research. Adventure Tourism: Promote unique landscapes and adventure activities Shared Tourist Routes: Create cross-border cultural and heritage routes linking major UNESCO and historical sites. Gastronomy: Focus on unique wine, national dishes and culinary experiences Infrastructure Development: Collaborate on transportation links and facilities to improve regional accessibility and ease of travel. National Branding: Each country develops its own branding and marketing strategies to attract different tourist segments. Safety and Crisis Management: Coordinate on regional safety protocols, Climate Change Adaptation Strategies and emergency response strategies to enhance tourism security. Events and Festivals: Promote country-specific cultural events, music, arts, and festivals to attract tourists (e.g., Tbilisi Open Air, Yerevan Jazz Festival, Baku Formula 1). Sustainable Tourism Initiatives: Joint efforts to promote eco-tourism, conservation, and responsible tourism practices. To unlock the full potential of the region, these countries can now move towards greater cooperation. By working together on joint marketing efforts, they can present the South Caucasus as a unified and diverse destination that offers a seamless travel experience. Shared tourist routes connecting key cultural and historical sites across the region can offer a more comprehensive experience for visitors. Improving cross-border infrastructure and coordinating safety and crisis management measures will also make travel more accessible and secure. Additionally, collaborative efforts in sustainable tourism can ensure the protection of natural resources, attracting environmentally conscious travelers and fostering long-term growth in the region. Conclusion The South Caucasus region, encompassing Armenia, Azerbaijan, and Georgia, presents a dynamic yet complex tourism landscape shaped by unique strengths, challenges, and evolving trends. The analysis of tourism intelligence and competitiveness across these countries highlights significant disparities in data collection, market performance, and infrastructure quality. Armenia has demonstrated resilience in its tourism sector, capitalizing on its rich cultural heritage and natural landscapes to drive growth. The Government Programme 2021-2026 aims to attract 2.5 million international visitors by enhancing direct flights and improving visa regulations. Its focus on promoting niche offerings like agritourism and specialized gastronomy tourism, alongside initiatives like “Armenia, The Hidden Track,” aims to increase spending and broaden the country’s appeal to high-value tourists. The emphasis on regional development seeks to spread the benefits of tourism more evenly, particularly in underdeveloped areas, aligning with sustainable tourism practices. Azerbaijan has positioned itself as a destination for high-spending visitors through its strong international connectivity and a focus on providing immersive experiences in culture and wellness. The 2023-2026 Tourism Strategy promotes sustainability and regional development through a nine-pillar model, emphasizing the creation of cultural heritage routes and recreational zones. However, Azerbaijan faces challenges in regaining pre-pandemic momentum, underscoring the need to balance leisure and business tourism while enhancing its cultural offerings. Georgia has emerged as a regional leader in tourism, offering a relatively strong business environment, comprehensive data accessibility, and the highest international tourist arrivals. However, it shares common challenges with its neighbors, including underdeveloped tourism infrastructure and reliance on a narrow range of source markets, particularly Russia. Georgia is transitioning from its 2015-2025 Tourism Strategy to a new plan that integrates tourism and marketing strategies into a cohesive framework. The focus on sustainable tourism development aims to attract high-value tourists while addressing infrastructure needs and utilizing unique experiences, such as its rich wine and gastronomy scene. Georgia’s marketing strategy highlights core tourism products and emphasizes the importance of diverse offerings, ensuring its competitiveness in the region. The concept of coopetition—a blend of cooperation and competition—emerges as a vital strategy for Armenia, Azerbaijan, and Georgia to navigate their shared challenges and enhance their collective tourism appeal. Fostering collaboration enables these countries to develop joint marketing campaigns, create cross-border tourist routes, and establish coordinated standards that strengthen the South Caucasus’ image as a regional destination. This approach allows each country to retain its unique identity while benefiting from shared resources and experiences. Coopetition offers an opportunity for these nations to address common challenges such as underdeveloped infrastructure and reliance on narrow source markets. Pooling resources for infrastructure development, promoting joint tourism products, and using each other’s strengths in cultural, natural, and gastronomic offerings can help Armenia, Azerbaijan, and Georgia create a more attractive and sustainable tourism environment. Additionally, coopetition can facilitate tourism data sharing among these countries, enabling them to respond effectively to global tourism trends and challenges. Collaborative efforts could lead to improved service quality, enhanced visitor experiences, and increased competitiveness in attracting high-value tourists. Bibliography: Azerbaijan Tourism Board & State Tourism Agency of the Republic of Azerbaijan. (2023). Azerbaijan Tourism Strategy 2023-2026. <https://www.tourism.gov.az>; Bregadze, G. (2023). Assessing the value chain impacts of the Ukraine war on the tourism industry of Georgia. Globalization and Business, 8(15); Bregadze, G. (2023). Climate change impacts on the tourism industry in Georgia. Globalization and Business, 8(16); Chim-Miki, A. F., da Costa, R. A., Okumus, F. (2024). Investigating the strategic role of business associations in willingness toward tourism coopetition. Current Issues in Tourism. <https://doi.org/10.1080/13683500.2024.2333910>; Davituliani, T., Azmaiparashvili, M. (2023). Ecological safety of Georgian tourism. Globalization and Business, 16. <https://doi.org/10.35945/gb.2023.16.007>; Della Corte, V., Sciarelli, M. (2012). Can coopetition be a source of competitive advantage for strategic networks? Corporate Ownership & Control, 9(3). <https://doi.org/10.22495/cocv9i3c3art5>; Dwyer, L., Forsyth, P., Dwyer, W. (2020). Tourism economics and policy (2nd, Aspects of Tourism Texts, Vol. 5). Channel View Publications; Edgell, D. L., Sr., Swanson, J. R. (2019). Tourism policy and planning: Yesterday, today, and tomorrow (3rd). Routledge; Georgian National Tourism Administration. (2019). Guideline for planning inbound tourism business (4th). Georgian National Tourism Administration. <https://gnta.ge/ge/publication/guideline/>; Gee, C. Y., Fayos-Solá, E., World Tourism Organization, WTO Education Network. (1997). International tourism: A global perspective (1st). World Tourism Organization; Kantarci, K., Başaran, M. A., Özyurt, P. M. (2017). A comparative research on South Caucasus countries’ tourism performances and competitiveness factors. In Proceedings of the International Scientific Conference; Schiavone, F., Simoni, M. (2011). An experience-based view of co-opetition in R&D networks. European Journal of Innovation Management, 14(2). <https://doi.org/10.1108/14601061111124867>; Tamarashvili, T. (2023). Aspects of tourism development in the South Caucasus: Past and present. Iakob Gogebashvili State University. <https://doi.org/10.52340/idw.2023.71>; World Bank. (2015). Tourism strategy 2015-2025: Sustainable tourism development plan. World Bank Group; World Economic Forum. (2024). Travel & tourism development index 2024: Insight report. World Economic Forum; World Tourism Organization. (2024). Tourism Doing Business – Investing in Armenia. UN Tourism. <https://doi.org/10.18111/9789284425785>. Footnotes [1] Tamarashvili, T. (2023). Aspects of tourism development in the South Caucasus: Past and present. Iakob Gogebashvili State University, 480-487. <https://doi.org/10.52340/idw.2023.7>. [2] Kantarci, K., Başaran, M. A., Özyurt, P. M. (2017). A comparative research on South Caucasus countries’ tourism performances and competitiveness factors. In Proceedings of the International Scientific Conference, 303-313. [3] Bregadze, G. (2023). Assessing the value chain impacts of the Ukraine war on the tourism industry of Georgia. Globalization and Business, 8(15), 65–75. [4] Davituliani, T., Azmaiparashvili, M. (2023). Ecological safety of Georgian tourism. Globalization and Business, 16, 69–70. <https://doi.org/10.35945/gb.2023.16.007>. [5] Bregadze, G. (2023). Climate change impacts on the tourism industry in Georgia. Globalization and Business, 8(16), 60. [6] Chim-Miki, A. F., da Costa, R. A., Okumus, F. (2024). Investigating the strategic role of business associations in willingness toward tourism coopetition. Current Issues in Tourism, 1–18. <https://doi.org/10.1080/13683500.2024.2333910>. [7] Della Corte, V., Sciarelli, M. (2012). Can coopetition be source of competitive advantage for strategic networks? Corporate Ownership & Control, 9(3), 355. <https://doi.org/10.22495/cocv9i3c3art5>. [8] Edgell, D. L., Sr., Swanson, J. R. (2019). Tourism policy and planning: Yesterday, today, and tomorrow (3rd ed., 12). Routledge. [9] Gee, C. Y., Fayos-Solá, E., World Tourism Organization, WTO Education Network. (1997). International tourism: A global perspective (1st ed.). World Tourism Organization, 305. [10] World Bank. (2015). Tourism strategy 2015-2025: Sustainable tourism development plan. World Bank Group, 4-26. [11] Georgian National Tourism Administration. (2019). Guideline for planning inbound tourism business (4th edition). Georgian National Tourism Administration, 51. <https://gnta.ge/ge/publication/guideline/>. [12] World Tourism Organization. (2024). Tourism Doing Business – Investing in Armenia. UN Tourism, 1-28. <https://doi.org/10.18111/9789284425785>. [13] Azerbaijan Tourism Board & State Tourism Agency of the Republic of Azerbaijan. (2023). Azerbaijan Tourism Strategy 2023-2026, 3-18. <https://www.tourism.gov.az>. [14] Dwyer, L., Forsyth, P., & Dwyer, W. (2020). Tourism economics and policy (2nd ed., Aspects of Tourism Texts, Vol. 5, 282). Channel View Publications. [15] World Economic Forum. (2024). Travel & tourism development index 2024: Insight report. World Economic Forum, 37. [16] Schiavone, F., Simoni, M. (2011). An experience-based view of co-opetition in R&D networks. European Journal of Innovation Management, 14(2), 145. <https://doi.org/10.1108/14601061111124867>.
Determinants of E-Learning Adoption by the Student in Algeria:A Structural Equation Modelling Approach
Although previous studies have confirmed the importance of e-learning systems for both students and teachers, the level of adoption of such systems in Algeria is still low. This paper aims to determine the factors influencing the adoption and use of e-learning by Algerian students. A theoretical model was proposed based on the Unified Theory of Acceptance and Use of Technology and the Technology Acceptance Model. To assess the proposed model, a survey was conducted on 300 students in Algeria, and the data were analyzed using structural equation modeling. In the end, the findings indicate that perceived usefulness and perceived ease of use significantly positively influence behavioral intention. In turn, behavioral intention influencese-learning adoption. The results also emphasize how facilitating conditions have a strong and significant impact on the adoption of e-learning. Overall, the findings shed light on the factors that influence Algerian students’ adoption of e-learning, providing clear benefits to universities in their efforts to improve their e-learning systems and student satisfaction. Keywords: E-learning, Technology Acceptance Model, Structural Equation Modeling, Student, Algeria. Introduction The rapid growth of information technology (IT) and the usage of innovative technologies has resulted in new modes of learning and teaching. E-learning is becoming common in today’s classrooms. According to El-Hussein and Cronje, e-learning is the application of wireless technology and portable mobile devices’ ubiquitous communication capabilities and user-friendly interfaces in formal learning processes. E-learning offers various benefits for the student; it enables students to continue their academic activities and obtain crucial information without being constrained by space or time. Moreover, the e-learning system is important in educational places for distance education; students can retain the educational information and materials well while saving a lot of time compared to traditional face-to-face learning. Despite its potential benefits, e-learning is still a major challenge since technology for learning may be badly embraced, terminated, or refused by learners. Thus, the adoption of e-learning remains an interesting topic for researchers. In Algeria, the country worked to digitize the higher education sector by providing educational digital platforms and platforms such as the Moodle platform and the Progress platform to keep pace with global trends and improve the educational process. However, despite the advantages offered by the distance education process to students, Algerian e-learning adoption is still in its early stages. Therefore, it would seem beneficial to comprehend the key elements affecting students’ adoption and utilization of online learning. Many researchers attempted to determine the factors affecting e-learning adoption and use based on theories and models of technology acceptance, such as the unified theory of acceptance and use of technology (UTAUT) and the technology acceptance model (TAM).Their findings demonstrate various factors explaining the higher rate of e-learning adoption, including facilitating conditions, perceived ease of use, and perceived usefulness. However, there is no universal agreement on the factors that influence e-learning adoption, and the findings differ depending on context, place, and time. Furthermore, the question has not been extensively examined in the context of Algeria. Thus, this paper aims to investigate the crucial factors affecting e-learning adoption by students in Algeria. For this paper, the following research question was addressed: What are the factors influencing the adoption of e-learning by students in Algeria? The remainder of this paper is presented as follows: Section one presents the literature review. Section two proposes the conceptual framework. Section three explains the research methodology of the study. Section four presents the results. Section five discusses the results and provides the academic and managerial Implications. Finally, section six concludes our work. Literature Review E-learning, additionally referred to as electronic learning or online learning, is the utilization of electronic technology as well as digital media to enhance education and learning. It includes the sharing of educational content, resources, and interactive activities through various digital platforms, such as computers, mobile devices, and the Internet. In e-learning, learners can access educational materials, participate in online courses, interact with instructors and peers, complete assessments, and receive feedback using digital tools and technologies. E-learning provides flexibility in terms of time and location, allowing learners to engage in educational activities at their own pace and from anywhere with an internet connection. The concept of e-learning encompasses a wide range of approaches and technologies, including online courses, virtual classrooms, educational apps, multimedia resources, simulations, gamified learning experiences, and learning management systems (LMS) that facilitate course administration and delivery. E-learning offers several advantages, such as accessibility, convenience, self-paced learning, personalized instruction, and the ability to reach a global audience. It is used in various educational settings, including schools, universities, professional training programs, and lifelong learning initiatives. In addition, e-learning platforms often facilitate communication and collaboration among learners. Discussion forums, chat features, and collaborative tools enable learners to connect with peers, engage in group projects, and share knowledge and experiences. This fosters a sense of community and encourages peer learning. Based on the technology acceptance theories, several researchers have tried to examine the factors affecting the adoption and use of e-learning, in the first study, Abdullah and Ward investigated the effect of TAM variables in the context of the adoption of e-learning and performed a quantitative meta-analysis of 107 papers. The findings indicated that computer anxiety, self-efficacy, and experience are the most important factors affecting perceived ease of use and perceived usefulness of e-learning adoption. In the second study, Jameel et al.examine the factors that affect the intention to use e-learning in Iraq based on the UTAUT. The data of 187 responses were analyzed using the structural equation modeling. The results found that performance expectancy, effort expectancy, and facilitating conditions raised the willingness to use e-learning and had a significant and positive effect on the intention to use e-learning. In another study, Twum et al. explored the factors that influence the intention to use E-learning during the COVID-19 pandemic using the unified theory of acceptance and use of technology 2. The data were collected from 617 university students and were analyzed using partial least squares structural equation modeling. The results indicated that personal innovativeness, perceived financial cost, performance expectancy, and hedonic motivation have a significant impact on behavioral intention to use E-learning. Finally, Hunde et al. examined the factors affecting students’ behavioral intention to use e-learning in Ethiopia. Structural equation modeling analyses were used on 637 responses from health science students to test the hypotheses. The findings showed that effort expectancy and facilitating conditions have a significant impact on the behavioral intention to use e-learning by the student. In the end, and even if these studies provide some understanding of the interactions that can occur between students and their e-learning acceptance and use, there is still some knowledge gap in developing countries, and it seems essential to conduct more studies. Indeed, little research exists regarding the adoption of e-learning in North African or Middle Eastern nations, including Algeria. Conceptual Model To determine the factors that influence Algerian students’acceptance of e-learning, an integrated conceptual model based on the TAM and the UTAUT was constructed (Figure 1). Over the past two decades, the TAM was most commonly utilizedby information technology researchers and had accumulated large empirical support. Therefore, the research model proposed in this study contains all factors adopted by TAM. Nevertheless, this model ignoresseveral crucial theoretical constructs, and it does not reflect the variety of user constraints. Then, we based on UTAUT in addition to the TAM, Therefore, we adopt the facilitating conditions from the UTAUT. Figure 1. Research model Perceived Ease of Use Perceived Ease of Use (PEOU): The extent to which an individual perceives that using technology is easy and needs the least effort. In the context of e-learning, perceived ease of use relates to how learners believe the user interface and overall usability of e-learning platforms.previous studies have found that perceived ease of use has a significant effect on consumers’ intention to use and adopt e-learning.Consequently, the first hypothesis is as follows: H1: Perceived ease of use positively influences behavioralintention to adopt e-learning. Perceived Usefulness: Perceived Usefulness (PU) is the level to which a person believes that utilizing new technology would improve their efficiency and performance. In the e-learning area, PU describes how learners believe e-learning resources and platforms can contribute to their learning outcomes, such as improving knowledge acquisition or skills development. Several studies indicated that PU positively affects behavior intention to use e-learning. Thus, the second hypothesis is: H2: Perceived usefulness positively influences behavioral intention to adopt e-learning. Behavioural Intention to Adopt e-learning: According to Davis et al., behavioral intention (BI) is a measure of a person’s readiness to adopt new technologies. Theories and models of technology acceptance found that intention is the most powerful influencing factor in the adoption of technology. E-learning prior studies cite behavioral intention as a key factor influencing the adoption of e-learning. As a result, this research puts forth the following hypothesis: H3. The behavioral intention will positively influence students’adoption of e-learning. Facilitating Conditions: Facilitating Conditions (FC) represents a measure of which individuals think that the required resources, support, and infrastructure are available to enable the use of technology. According to prior studies, FC provides an important influence in the adoption of e-learning.Therefore, the fourth hypothesis is formulated as follows: H4. Facilitating conditions will positively influence students’ e-learning adoption. Methods and Materials ​The empirical study was conducted on a sample of the students in Algeria. The survey method was used to test the hypotheses becauseit is the mostcommon method of collecting data on constructs connected with behavioral theories. Regarding the measurement, as shown in Table 1, the instruments (items) were derived from previous research, and their reliability and validity have been proven. Items in this paper were rated using a 5-point Likert scale. (1=strongly disagreed; 5=strongly agreed). Table 1. Measurement scales Factor Number of questions E-learning adoption 3 items Behavioural intention to adopt e-learning 3 items Perceived ease of use 4 items Perceived usefulness 3 items Facilitating conditions 3 items This study’s hypotheses were investigated using Covariance-Based Structural Equation Modelling (CB-SEM). The data analysis was completed in two stages. The first stage entailed conducting a reliability and validity analysis with SPSS (version 22) to determine the stability and consistency of the assessed items. The second phase was testing the study assumptions using AMOS (version 22). Sample Characteristics A total of Three hundred (300) valid questionnaires were collected. Table 2 shows that respondents consisted of 174 males (58%) and 126 females (42%). Their age ranged from 19 to more than 29 years, with 55.3% being 19-24 years and 42% being 25-29 years. Table 2. Demographic Analysis Variable Response’s choice Frequency Per cent Gender Male 174 58% Female 126 42% Age 19-24 years 166 55.3% 25-29 years 126 42% 25+ years 8 2.7% Results The Measurement Model To examine the reliability and validity of the items, the constructswere assessed using Cronbach’s alpha. According to Table 3’s findings, all of the variables have values higher than the 0.70 cut-off point. This shows a sufficient level of internal consistency in the measurement model. We conducted a confirmatory factor analysis (CFA) to ensure sufficient levels of construct validity, reliability, and model fitness. Table 3 illustrates that all factor loading values (λ), which ranged from 071 to 0.97, are significant and above the suggested criterion of 0.50. Structural Model Goodness-Of-Fit Indicators The values of the goodness of fit indices in Table 4 appeared that the structural model is an excellent fit for the data (Hair et al. 2010, 96) [35]. Table 3. Reliability and Validity Test Variable Notation Items li (α) Cronbach e-learning adoption Adoption A1 A2 A3 0.92 0.95 0.84 0.938 Behavioural intention BI BI1 BI2 BI3 0.96 0.97 0.84 0.944 Perceived ease of use PEU PEU1 PEU2 PEU3 PEU4 0.71 0.77 0.90 0.77 0.863 Perceived usefulness PU PU1 PU2 PU3 0.85 0.88 0.91 0.910 Facilitating conditions FC FC1 FC2 FC3 0.83 0.89 0.84 0.891 Source: Prepared by researcher based on the outputs of AMOS and SPSS Table 4. Goodness-of-Fit Indicators Indicator Value RMSEA 0.07 IFI 0.94 RFI 0.91 CFI 0.94 TLI 0.92 NFI 0.92 CMIN/DF 2.15 Source: Prepared by researcher based on the outputs of AMOS Coefficient of Determination (R2): The research yielded highly satisfactory R2 values for the endogenous components. To be precise, Table 5 estimates this coefficient as follows: 42.3% for e-learning adoption and 40.5% for behavioral intention. Table 5. Coefficient of Determination (R2) Construct R square Adoption 0.405 BI 0.423 Source: Prepared by researcher based on the outputs of AMOS Hypothesis Test: Figure 2 and Table 6 indicate the findings of the structural equation analysis. The results validate the positive impact of perceived usefulness and perceived ease of use on behavioral intention to use and adopt e-learning (b=0.0.326, p<0.001; b=0.538, p<0.001). Therefore, H1 and H2 are supported. In addition, behavioral intentions (b=0.481, p<0.001) and facilitating conditions (b=0.373, p<0.001) have both a significant and positive influence on the adoption of e-learning. Therefore, H3 and H4 are supported. Table 6. Structural Model Results and Hypothesis Testing Hypothesis Estimate SE CR Inference H1: PEU → BI 0.326*** 0.073 4.461 Supported H2: PU → BI 0.538*** 0.085 6.295 Supported H3: BI → Adoption 0.481*** 0.051 9.359 Supported H4: FC → Adoption 0.373*** 0.051 7.365 Supported ***p < 0.001 Source: Prepared by researcher based on the outputs of AMOS Figure 2. Structural Model Discussion To identify the factors affecting students’ use and adoption of e-learning in Algeria, we suggested a research framework that combined TAM components (PEOU, PU, and BI) with FC from the UTAUT element. Four hypotheses were addressed by this model. We used the questionnaire-based survey approach and the CB-SEM method of data analysis to test the suggested model and hypotheses. First, the study’s findings provide strong support for our hypothesis; the R square of 40.5% was higher than the suggested threshold of 40%. This indicates that the model has a high predictive value and considerable explanatory power. We have been able to improve the TAM model’s prediction capacity by using FC. According to a study by Mubuke et al., 48.6% of the variation in the use of e-learning was explained by conducive conditions. Second, the results also indicate that PU and PEOU are positively associated with behavioral intention to adopt e-learning. Thus, as long as individuals perceive that the use of e-learning platforms is free of effort and facilitates their studies, their intention to use and adopt e-learning is increased. Therefore, the findings validated our original relationship with the TAM. This is consistent with the literature regarding e-learning adoption., Finally, the findings found that behavioral intention and facilitating conditions determine the adoption of e-learning. This suggests that students will use and adopt e-learning if they desire to use these technologies and believe that the resources and support services are available. These findings are consistent with the overall literature on technology adoption, in which behavioral intention and conducive conditions have always been important determinants in the acceptance of technological advancements. The findings are also consistent with earlier e-learning research. Academic Implications This study makes significant scholarly contributions to the body of knowledge regarding the acceptance and use of technology. First, it examined the factors that influence e-learning in Algeria using the TAM and UTAUT models, which were established in Western culture, to explain a similar behavior in a non-western (Arabic) culture and confirm and extend the results of Mailizar et al. to the case of e-learning. As a result, the study adds to the contextual implications of the TAM and UTAUT models used in Algeria, a developing country case study. In the Algerian context, there are a limited number of e-learning adoption studies. The findings of this study will contribute to a general understanding of the factors that affect the adoption and use of e-learning in Algeria. Second, the study used the models and theories, which were created in an organizational context, to study an individual user behavior type (e-learning). Managerial Implications This study presents several managerial implications for fostering a stronger relationship between universities and e-learning users. One key finding is the exploration of students’ adoption of e-learning. Understanding their behavior toward e-learning use can assist universities in crafting strategies that encourage engagement with these platforms. Specifically, Algerian universities can leverage these insights to enhance the promotion of e-learning initiatives. The study highlights that perceived ease of use and perceived usefulness are critical factors influencing e-learning adoption in Algeria. To increase adoption rates, universities should design user-friendly e-learning platforms and provide clear instructions for their use. Moreover, creating compelling promotional campaigns that emphasize the benefits and opportunities offered by e-learning can motivate students to explore these platforms further. Additionally, the research reveals that facilitating conditions significantly impact e-learning adoption, underscoring the need for robust support resources and accessible services. Therefore, improving the infrastructure, such as enhancing internet access and ensuring smooth connectivity, is essential for Algerian universities aiming to attract more students to e-learning platforms. Conclusion This study examines the key factors influencing students’ adoption and use of e-learning in Algeria. A research model was created by integrating elements from both the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). To test the proposed hypotheses, a survey involving 300 Algerian students was conducted, and the data were analyzed using structural equation modeling. The results showed that students’behavioral intention to adopt e-learning is significantly and positively influenced by perceived usefulness and ease of use. Additionally, both behavioral intention and facilitating conditions play a crucial role in shaping e-learning adoption and usage. Bibliography: 1. Abdullah, F., Ward, R. (2016). Developing a general extended technology acceptance model for e-learning (GETAMEL) by analyzing commonly used external factors. Computers in Human Behavior, 56; 2. Alassafi, M. O. (2022). E-learning intention material using TAM: A case study. Materials Today: Proceedings, 61; 3. Alblooshi, S., Hamid, N. A. (2021). The role of Unified Theory of Acceptance and Use of Technology in e-learning adoption in higher education institutions in the UAE. IBIMA Business Review; 4. Alfalah, A. A. (2023). 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Informatics in Medicine Unlocked, 36, 101154; 13. Jameel, A. S., Karem, M. A., & Ahmad, A. R. (2022). Behavioral intention to use e-learning among academic staff during the COVID-19 pandemic based on the UTAUT model. In Proceedings of International Conference on Emerging Technologies and Intelligent Systems: ICETIS 2021. Springer International Publishing; 14. Kline, R. B. (Ed.). (2011). Principles and practice of structural equation modeling. The Guilford Press; 15. Mailizar, M., Burg, D., Maulina, S. (2021). Examining university students’ behavioral intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Education and Information Technologies, 26(6); 16. Mehta, A., Morris, N. P., Swinnerton, B., Homer, M. (2019). The influence of values on e-learning adoption. Computers & Education, 141, 103617; 17. Mubuke, F., Kutosi Masaba, A., Ogenmungu, C., Mayoka Kituyi, G. (2017). 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Using the UTAUT, personal innovativeness, and perceived financial cost to examine student’s intention to use e-learning. Journal of Science and Technology Policy Management, 13(3); 23. Venkatesh, V., Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2); 24. Venkatesh, V., Davis, G. B., Davis, F. D., Morris, M. G. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3); 25. Zhu, M., Sari, A., Lee, M. M. (2018). A systematic review of research methods and topics of the empirical MOOC literature (2014–2016). Internet and Higher Education, 37(January). <https://doi.org/10.1016/j.iheduc.2018.01.002>; 26. Zhuang, Y., Ma, H., Xie, H., Leung, A. C. M., Hancke, G. P., Wang, F. L. (2017). When innovation meets evolution: An extensive study of emerging e-learning technologies for higher education in Hong Kong. In Emerging Technologies for Education: First International Symposium, SETE 2016, Held in Conjunction with ICWL 2016, Rome, Italy, October 26-29, 2016, Revised Selected Papers 1. Springer International Publishing. ​ Footnotes [1] El-Hussein, M. O. M., Cronje, J. C. (2010). Defining mobile learning in the higher education landscape. Journal of educational technology & society, 13(3), 13. [2] Hunde, M. K., Demsash, A. W., Walle, A. D. (2023). Behavioral intention to use e-learning and its associated factors among health science students in Mettu University, southwest Ethiopia: Using modified UTAUT model. Informatics in Medicine Unlocked, 36, 105. [3] Alassafi, M. O. (2022). E-learning intention material using TAM: A case study. Materials Today: Proceedings, 61, 875. [4] Mehta, A., Morris, N. P., Swinnerton, B., Homer, M. (2019). The influence of values on E-learning adoption. Computers & Education, 141, 113. [5] Zhu, M., Sari, A., Lee, M. M. (2018). A systematic review of research methods and topics of the empirical MOOC literature (2014–2016). The Internet and Higher Education, 37, 35. [6] Alfalah, A. A. (2023). Factors influencing students’ adoption and use of mobile learning management systems (m-LMSs): A quantitative study of Saudi Arabia. International Journal of Information Management Data Insights, 3(1), 120. [7] Alassafi, M. O. (2022). E-learning intention material using TAM: A case study. Materials Today: Proceedings, 61, 875. [8] Dinh, L. P., Nguyen, T. T. (2023). Convenient and comfortable, yet limited in many ways: advantages and disadvantages of online learning during the COVID-19 pandemic from perspectives of social work students in Vietnam. Asia Pacific Journal of Social Work and Development, 33(3), 196. [9] Zhuang, Y., Ma, H., Xie, H., Leung, A. C. M., Hancke, G. P., Wang, F. L. (2017). When innovation meets evolution: An extensive study of emerging e-learning technologies for higher education in Hong Kong. In Emerging Technologies for Education: First International Symposium, SETE 2016, Held in Conjunction with ICWL 2016, Rome, Italy, October 26-29, 2016, Revised Selected Papers 1, Springer International Publishing, 579. [10] Tayebinik, M., Puteh, M. (2013). Blended Learning or E-learning? arXiv preprint arXiv, 1310. [11] Abdullah, F., Ward, R. (2016). Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analyzing commonly used external factors. Computers in human behavior, 56, 238-256. [12] Jameel, A. S., Karem, M. A., Ahmad, A. R. (2022). Behavioral intention to use e-learning among academic staff during the COVID-19 pandemic based on the UTAUT model. In Proceedings of International Conference on Emerging Technologies and Intelligent Systems: ICETIS 2021. Springer International Publishing, 1, 187-196. [13] Twum, K. K., Ofori, D., Keney, G., Korang-Yeboah, B. (2022). Using the UTAUT, personal innovativeness and perceived financial cost to examine student’s intention to use E-learning. Journal of Science and Technology Policy Management, 13(3), 713-737. [14] Hunde, M. K., Demsash, A. W., Walle, A. D. (2023). Behavioral intention to use e-learning and its associated factors among health science students in Mettu University, southwest Ethiopia: Using modified UTAUT model. Informatics in Medicine Unlocked, 36, 101154. [15] Abdullah, F., Ward, R. (2016). Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analyzing commonly used external factors. Computers in human behavior, 56, 248. [16] Olushola, T., Abiola, J. O. (2017). The efficacy of technology acceptance model: A review of applicable theoretical models in information technology researches. Journal of research in business and management, 4(11), 76. [17] Davis, F. D. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 984, 995. [18] Bailey, D. R., Almusharraf, N., Almusharraf, A. (2022). Video conferencing in the e-learning context: explaining learning outcome with the technology acceptance model. Education and Information Technologies, 27(6), 7685. [19] Humida, T., Al Mamun, M. H., Keikhosrokiani, P. (2022). Predicting behavioral intention to use e-learning system: A case study in Begum Rokeya University, Rangpur, Bangladesh. Education and information technologies, 27(2), 2256. [20] Davis, F. D. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35 (8), 996. [21] Revythi, A., Tselios, N. (2019). Extension of technology acceptance model by using system usability scale to assess behavioral intention to use e-learning. Education and Information Technologies, 24, 2351. [22] Davis, F. D. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35 (8), 990. [23] Venkatesh, V., Morris, M. G., Davis, G. B., Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 433. [24] Ali, M., Raza, S. A., Qazi, W., Puah, C. H. (2018). Assessing e-learning system in higher education institutes: Evidence from structural equation modeling. Interactive Technology and Smart Education, 15(1), 67. [25] Alblooshi, S., Abdul Hamid, N. A. B. (2021). The role of the unified theory of acceptance and use of technology in e-learning adoption in higher education institutions in the UAE. IBIMA Business Review, 1(26), 13. [26] Venkatesh, V., Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 314. [27] Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford publications, 105. [28] Black, W. C., Babin, B. J., Anderson, R. E. (2010). Multivariate data analysis: A global perspective. Pearson, 115. [29] Straub, D., Boudreau, M. C., Gefen, D. (2004). Validation guidelines for IS positivist research. Communications of the Association for Information Systems, 13(1), 36. [30] Mubuke, F., Kutosi Masaba, A., Ogenmungu, C., Mayoka Kituyi, G. (2017). Examining the Effect of Facilitating Conditions as an imperative input in enhancing the intention to use Mobile Learning systems in Universities, 341. [31] Revythi, A., Tselios, N. (2019). Extension of technology acceptance model by using system usability scale to assess behavioral intention to use e-learning. Education and Information Technologies, 24, 2350. [32] Bailey, D. R., Almusharraf, N., Almusharraf, A. (2022). Video conferencing in the e-learning context: explaining learning outcome with the technology acceptance model. Education and Information Technologies, 27(6), 7690. [33] Venkatesh, V., Morris, M. G., Davis, G. B., Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 460. [34] Alblooshi, S., Abdul Hamid, N. A. B. (2021). The role of the unified theory of acceptance and use of technology in e-learning adoption in higher education institutions in the UAE. IBIMA Business Review, 1(26), 12. [35] Mailizar, M., Burg, D., Maulina, S. (2021). Examining university students’ behavioral intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Education and information technologies, 26(6), 7057-7077.
Bayesian Networks for Migration, International Remittances, Trade, Foreign Direct Investments, Inflation, Real Interest Rate and Employment in Georgia
Migration has long been a topic of interest in Georgia, given its small economy, population, and unique history and culture. The main objective of this study is to examine the factors affecting emigration and immigration in Georgia and identify the dependencies among various macroeconomic variables, such as international remittances, trade, foreign direct investment (FDI), inflation, real interest rates, and employment. Using data spanning from 2002 to 2023, the study applies a machine learning technique, specifically Bayesian Networks, to analyze these relationships. The findings are discussed, and conclusions are drawn, along with recommendations for both the government and researchers for further exploration. To our knowledge, this is the first study to apply the Bayesian Network algorithm to investigate these dynamics in Georgia, filling an important research gap. The results indicate that both immigration and emigration are affected by remittances paid, with emigration also being dependent on employment. It was found that remittances received and exports are directly influenced by remittances paid, while imports are affected by both exports and employment. Additionally, remittances received are directly dependent on imports, and the real interest rate is influenced by both imports and inflation (CPI). FDI is shown to be dependent on inflation, imports, and remittances received. Furthermore, both emigration and immigration are dependent on exports, imports, and remittances received, with immigration also exhibiting a dependency on FDI. Keywords: Emigration, Immigration, Bayesian Networks, Machin Learning, Remittances. Introduction Migration has been a long-standing topic for Georgia. As a small country with a limited population and economy, the country faces challenges due to emigration, particularly the brain drain - the loss of skilled workers and professionals - which hinders its development. On the other hand, immigration, particularly of skilled workers, is beneficial for the country and, therefore, also a subject of interest. Machine learning is evolving quickly and has become a crucial component in diverse fields such as economics, medicine, and business. Virtually every sector now depends on data, and harnessing it effectively holds the potential to address a wide range of challenges across these domains. However, research applying data science techniques in economics and business remains limited for Georgia. Importantly, no studies currently employ machine learning techniques, such as Bayesian Networks, to examine the potential causes of migration and explore the relationships between macroeconomic variables like FDI, international trade, remittances, inflation, interest rates, and employment in Georgia. Therefore, another central aim of this research is to create a base for future research for Georgia and inspire others to apply various data science techniques in investigating different economic topics. Georgia is a developing country with a GDP per capita (PPP) of $22,247 and a population of 3.7 million as of 2023.[1] Given its relatively small population compared to many other countries, migration has long been a topic of interest in Georgia. As shown in Graph 1, both emigration (the number of people leaving the country) and immigration (the number of people arriving in Georgia) have had an increasing trend since 2002, with a notable increase in both trends in 2022. In 2023, the number of emigrants comprised 245,064, while the number of immigrants was 205,857. Graph 1. Emigration (EMI) and Immigration (IMM) in Georgia (2002-2023) Source: The National Statistics Office of Georgia <www.geostat.ge> Analyzing migration by citizenship is also a valuable approach. As shown in Graph 2, the majority of migrants are Georgian citizens, followed by individuals from Russia, Turkey, Ukraine, India, and Azerbaijan. The largest group of migrants falls within the age range of 15-64, followed by those in the 0-14 and 65+ age groups.[2] Thus, the largest group of migrants is the working-age population. Graph 2. Emigrants (EMI) and Immigrants (IMM) by Citizenship (2023) Source: The National Statistics Office of Georgia <www.geostat.ge> As previously noted, Georgia is a developing country with relatively low productivity, making the size of its workforce and the level of economic activity crucial factors for growth. This research aims to identify the potential causes of migration and explore the relationships among various macroeconomic variables. Specifically, the objective of this study is to examine the dependence between migration and other macroeconomic factors, including international remittances, trade, foreign direct investment (FDI), inflation, real interest rates, and employment, as well as to investigate the interdependencies among these variables. To achieve this, the study applies the machine learning algorithm, specifically Bayesian Networks, which are probabilistic graphical models, to detect complex relationships between the variables. The first task was to select relevant variables, followed by building appropriate models and ultimately analyzing and interpreting the results. The structure of the study includes a literature review, an overview of the data, methodology, and a presentation of the results for emigration and immigration separately. The study concludes with a discussion of the findings and provides recommendations for both the government and future researchers. The research is done in R programming language. Literature Review While numerous studies have examined migration in Georgia, most focus on emigration, with only a few exploring the underlying causes of migration. Even fewer studies have utilized statistical analysis, and almost none have employed machine learning approaches. Kharaishvili, E. et al. (2017) investigated the causes of labor and educational migration, as well as challenges related to youth unemployment by age and gender, particularly in Georgia’s agricultural sector. The study identified high poverty levels, underdeveloped infrastructure, and limited access to healthcare and other public services as the primary drivers of migration. It suggested that the government should develop policies to create employment opportunities for youth, especially in rural areas.[3] Zangurashvili, M. (2020) explored the causes of youth emigration from Georgia, concluding that the key factors affecting it were distrust of state institutions, the lack of an employment policy for new job seekers, an unpromising labor market, nepotism, and low wages in an unfair work environment.[4] Mihi-Ramirez, A. et al. (2020) examined the relationship between emigration, immigration, foreign direct investment (FDI), international remittances, and trade in Spain, using a Mixed Linear Model (MLM) for the period from 1998 to 2016. Their findings revealed that the effects of imports, exports, and FDI on migration were significant. They also found that remittances sent had a significant effect on immigration, while both remittances sent and received impacted emigration.[5] Tchanidze, K. et al. (2021) analyzed the impact of migration on Georgia’s labor market. Their findings indicated that young people often emigrate in search of better living conditions. Many from rural areas leave the country illegally, bypassing efforts to settle in urban centers. To address this, the study recommended that the government should create job opportunities for both highly educated individuals and those without higher education.[6] Karkashadze, N. et al. (2021) examined migration causes in Georgia and concluded that limited employment opportunities and low wages were the main reasons for emigration. The study also highlighted that many people emigrate abroad to pursue education. Additionally, the COVID-19 pandemic significantly affected migration patterns, with many leaving the country afterward. The study suggested that to reduce emigration, the government should increase investment, enhance public spending to create jobs, and ensure that social insurance programs are effectively integrated into the labor market.[7] Data Overview The data presented in this study are 10 macroeconomic variables for Georgia for 22 years between 2002-2023. The data doesn’t have missing values, and the sources of the data are the National Statistics Office of Georgia and The World Bank’s Data - The World’s Development Indicators. Detailed information about the data is presented in Table 1. Table 1: Macroeconomic Variables Included in the Model IMM Immigration to Georgia. Source: The National Statistics Office of Georgia EMI Emigration from Georgia. Source: The National Statistics Office of Georgia FDI Foreign Direct Investment net inflow current (current US$)- BOP. Source: The World Bank REMR Personal remittances, received (current US$). Source: The World Bank REMP Personal remittances, paid (current US$). Source: The World Bank IMP Imports of goods and services (current US$). Source: The World Bank EXP Exports of goods and services (current US$). Source: The World Bank CPI Inflation, consumer prices (annual %). Source: The World Bank EMPL Employment to population ratio, 15+, total (%) (modeled ILO estimate). Source: The World Bank RIR Real interest rate (%). Source: The World Bank Source: The National Statistics Office of Georgia <www.geostat.ge> The World Bank <https://data.worldbank.org/> Over the past 22 years, Georgia has experienced several significant economic and political events. These include the Rose Revolution in 2003 when the “National Movement” came to power; the Russian-Georgian war in 2008; a change in government in 2012, when the “Georgian Dream” party assumed office; the Russian economic crisis in 2015, which also impacted Georgia’s economy; the onset of the COVID-19 pandemic in 2020; and the Russia-Ukraine war which started in 2022. Graph 3 presents the time series of Georgia’s macroeconomic variables from 2002 to 2023. The trends in emigration (EMI) and immigration (IMM) were relatively stable over the years. However, both variables saw a significant surge in 2022, with even greater increases observed in 2023. Graph 3. Time Series of the Variables (2002-2023) Source: The National Statistics Office of Georgia <www.geostat.ge> The World Bank <https://data.worldbank.org/> Remittances received (REMR) experienced a significant decline in 2015, primarily due to the economic crisis in Russia at that time. Since the majority of remittances to Georgia originated from Russia, the downturn in Russia’s economic activity had a direct impact on remittances received in Georgia (Blouchoutzi, A. et al., 2023).[8] Remittances paid (REMP) followed an upward trend over the years but saw a notable decrease in 2009, following the Russia-Georgia war, and again in 2020 during the COVID-19 pandemic. Foreign Direct Investment (FDI) showed some fluctuations over the years but generally followed an upward trajectory. Exports (EXP) and imports (IMP) also exhibited an increasing trend, though both experienced a sharp decline in 2009 after the Russia-Georgia war, in 2015-2016 during Russia’s economic crisis, and in 2022 when the Russia-Ukraine war began. The employment-to-population ratio (EMPL) fluctuated over the years, with a significant decline in 2009 following the Russia-Georgia conflict. Inflation (CPI) and the real interest rate (RIR) both exhibited fluctuations throughout the period. While CPI had a constant trend across the years, RIR showed a downward trend. Methodology The Bayesian Networks Bayesian networks are graphical models that represent the joint probability distribution of a set of variables and detect dependence between them. In the networks, nodes correspond to the variables, while arrows indicate probabilistic dependencies between them. The structure of the network is a directed acyclic graph (DAG), meaning there are no cycles or circular dependencies between variables. The DAG facilitates the factorization of the global probability distribution into local distributions through the Markov property (Scutari, M. 2009).[9] More specifically: For discrete variables: For continuous variables: The term refers to the parents of the random variable - , which depends on their respective parents. Bayesian networks utilize a two-step process: first, the algorithm learns the structure of the DAG, and then it estimates the local distributions of the random variables, conditioned on their parent variables (Scutari, M. 2009). There are three main types of Bayesian networks: Discrete, where all variables are discrete; Continuous, where all variables are continuous; and Mixed, which involves both continuous and discrete variables. 4.2 The Structure Learning Algorithms, Blacklist and Whitelist When the structure of a Directed Acyclic Graph (DAG) is unknown, it can be determined using two main types of algorithms: constraint-based and score-based algorithms. Constraint-based algorithms use conditional independence tests to evaluate the probabilistic relationships between variables and construct the DAG. These algorithms detect conditional dependencies among variables, are more effective with large datasets, and are computationally more efficient. Some common functions within constraint-based algorithms include Grow-Shrink (GS), Incremental Association (IAMB), Fast Incremental Association (Fast.IAMB), Interleaved Incremental Association (Inter.IAMB), and Max-Min Parents and Children (MMPC). Each of these methods employs slightly different techniques to identify conditional dependencies between variables (Scutari, M. 2009). Score-based algorithms, on the other hand, assess the fit of the DAG by assigning a score to each network structure and optimizing it using algorithms such as hill-climbing or tabu search. (Scutari, M. 2009). By maximizing the score, these algorithms aim to identify the best network structure. While score-based methods can perform better with smaller datasets, they tend to be more computationally expensive due to the large search space. Given that the dataset in this study is relatively small, first, a score-based algorithm, specifically hill-climbing (HC), was applied. However, the Bayesian networks did not fully capture the dependencies among several variables. To address this, the conditional independence test was used to assess the conditional dependencies of these variables, particularly using the ci.test function. When the data is categorical, in the ci.test, the mutual information test is applied for ordered factors, the Jonckheere-Terpstra test, and for continuous variables, the linear correlation. Since the data in this study is continuous, in the ci.test, the linear correlation test was applied. In the context of the ci.test, the null hypothesis ( ) asserts that the variables are conditionally independent. If the p-value is less than the significance level, the null hypothesis is rejected in favor of the alternative hypothesis ( , which states that there is conditional dependence between the variables. If there is prior knowledge regarding relationships between variables, this can be incorporated into the Bayesian Network through whitelist or blacklist arguments. Relationships that are whitelisted will be included in the model, while relationships marked as blacklisted will be excluded. If a relationship is both whitelisted and blacklisted, it will be treated as whitelisted and will not be counted as blacklisted (Scutari, M. 2009). This study only blacklisted the arc and did not whitelist it to avoid excessive intervention and artificial results. Results Emigration and All Other Macroeconomic Variables In the first scenario, the primary objective was to identify the variables that influence emigration and, after that, the relationships among all other variables, such as remittances, trade, interest rate, inflation, FDI, and employment. Since emigration is the key variable, the arc from emigration to trade, employment, interest rate, inflation, FDI, and remittances was blacklisted to prevent any direct arrows from emigration to these variables. Graph 4 illustrates the results from the Directed Acyclic Graph (DAG), highlighting the relationships among the macroeconomic variables. As shown in Graph 6, remittances received are directly influenced by remittances paid. Emigration is affected by both remittances paid and employment. Exports are directly dependent on remittances paid, while imports are influenced by exports. FDI depends on remittances received, imports, and inflation (CPI). Additionally, FDI indirectly depends on remittances paid and exports through imports. Finally, the real interest rate is influenced by both imports and inflation (CPI). Graph 4. DAG for Emigration and All Other Macroeconomic Variables Source: Author’s research in R-studio The DAG did not capture the dependency between emigration and other macroeconomic variables, apart from remittances paid and employment. Therefore, the missing relationships were examined using the conditional independence (CI) test. As shown in Table 2, emigration and imports are dependent, as the p-value is less than 0.05 at the 95% significance level. Table 2. CI Test for Emigration and Import Source: Author’s research in R-studio Table 3 presents the results of the conditional independence test for emigration and exports. The findings indicate that emigration and exports are dependent, as the p-value is less than 0.05. Table 3. CI Test for Emigration and Export Source: Author’s research in R-studio The test results also revealed that emigration and remittances received are dependent, with a p-value of 0.0001. The was not rejected for the other variables. The p-values for emigration and variables such as FDI, CPI, and RIR ranged between 0.05 and 0.9, indicating that no significant relationships were detected between them. 5.2 Immigration and All Other Macroeconomic Variables In the second scenario, the primary variable is immigration, and the objective is to identify the factors that influence immigration and explore how other macroeconomic variables, such as remittances, trade, interest rates, inflation, FDI, and employment, interact with each other. As in the first scenario, the arc from immigration to the other variables was excluded to prevent any direct arrows from immigration to these variables since the focus is on the variables that affect immigration. Graph 5 illustrates the Directed Acyclic Graph (DAG), which shows the dependencies between the variables. As depicted in Graph 5, immigration directly depends on remittances paid, which is the only variable in the DAG influencing immigration. The relationships between the other variables in this scenario are consistent with those in the first scenario. Specifically, remittances received and exports are directly dependent on remittances paid. Imports depend on exports and employment, while remittances received are directly dependent on imports. Finally, FDI is influenced by remittances received, imports, and inflation (CPI), and the real interest rate is dependent on both imports and inflation (CPI). Graph 5. DAG for Immigration and All Other Macroeconomic Variables Source: Author’s research results in R-studio Similar to the first scenario, the DAG did not capture the dependency between immigration and all other macroeconomic variables, except for remittances paid. Therefore, the missing relationships were examined using the conditional independence (CI) test. As shown in Table 4, immigration and imports are dependent, as the p-value is less than the significance level of 0.05. Table 4. CI Test for Immigration and Import Source: Author’s research results in R-studio Table 5 presents the results of the conditional independence test for immigration and FDI. The findings show that immigration and FDI are dependent, as the p-value is below the significance level of 0.05. Table 5. CI Test for Immigration and FDI Source: Author’s research results in R-studio The test results also indicated that immigration and exports, as well as immigration and remittances received, are dependent, with p-values of 2.55E-08 and 0.0039, respectively. The hypothesis was not rejected for the other variables. Specifically, the p-values for immigration and other variables, such as CPI and RIR, ranged from 0.5 to 0.8, indicating that no significant relationships were identified between them. Discussion of Results Bayesian networks show the dependencies between variables but do not necessarily indicate causation. Identifying cause-and-effect relationships requires further investigation; however, this section will still discuss the associations and potential cause-and-effect relationships that may exist between these variables. Both immigration and emigration are dependent on remittances paid. Remittances paid can affect immigration by providing financial incentives in the recipient country. If remittances paid from a particular country are high, it may make that country more attractive to foreigners, encouraging them to migrate there. The relationship between remittances paid and emigration should be more indirect. A decline in remittances sent abroad could be a result of an economic downturn, which, in turn, may push people to leave the country in search of better opportunities elsewhere. Emigration is closely linked to employment in Georgia, where limited employment opportunities are one of the primary reasons for emigration to another country. For both scenarios, the relationships between the macroeconomic variables are largely consistent. In both cases, remittances received are directly dependent on remittances paid. During an economic downturn, people may reduce the amount they remit while simultaneously asking for financial support from abroad, which can lead to an increase in remittances received. Exports are directly dependent on remittances paid. This relationship is more complex, as an increase in remittances paid can stimulate the economy in the recipient country, boosting consumption. This, in turn, can lead to higher demand for imports, thereby increasing exports from the sending country. Imports are directly related to exports, as the revenue generated from exports typically funds the imports. Imports are also directly dependent on employment since higher employment can lead to greater income and consumption, which usually increases imports. Remittances received are directly dependent on imports, though the relationship can be more indirect and complex. Imports can affect economic conditions, employment, consumption patterns, and inflation, all of which can influence the need for financial support from abroad. If imports cause higher living costs, they may indirectly lead to an increase in remittances received. This relationship is complex and can be shaped by factors such as wage disparities, economic policies, and migration patterns. FDI and remittances received are dependent, as remittances can help stimulate the economy in the recipient country, making it a more attractive destination for foreign direct investment. The real interest rate and imports are also dependent, albeit indirectly. Imports can affect the real interest rate through various channels, such as inflation, economic growth, and exchange rates. If an increase in imports leads to higher inflation, the central bank may raise nominal interest rates, which in turn would raise the real interest rate. The real interest rate and CPI (consumer price index) are also directly dependent, as inflation is a key factor in determining real interest rates. Since real interest rates are calculated by subtracting inflation from nominal interest rates, the relationship is clear. Finally, FDI directly depends on inflation. High inflation can create uncertainty in the economy, discouraging foreign investment. Generally, there is a negative relationship between FDI and CPI, as higher inflation tends to deter investment. Conclusion This study explored the relationships among migration, international remittances, trade, foreign direct investment (FDI), inflation, interest rates, and employment by employing the machine learning technique of Bayesian Networks. The primary focus was on emigration and immigration and the factors influencing these phenomena. The Bayesian Network models were constructed with emigration and immigration as the key variables of interest, starting with emigration as the primary variable and then addressing immigration. The results indicated that both immigration and emigration are dependent on remittances paid, with emigration also being dependent on employment. Remittances received were found to be directly influenced by remittances paid, exports were dependent on remittances paid, and imports were influenced by both exports and employment. Additionally, remittances received were found to be directly dependent on imports, while the real interest rate was influenced by both imports and inflation (CPI). FDI was found to be dependent on inflation (CPI). Moreover, both emigration and immigration were dependent on exports, imports, and remittances received, with immigration also showing a dependency on FDI. These findings align with previous research on the relationships between migration, imports, exports, FDI, and remittances. Additionally, they support the notion that employment-related issues are a significant driver of emigration, as highlighted by numerous studies. Georgia’s small economy and limited labor market diversity contribute to the lack of job opportunities, especially for younger workers. Furthermore, low remuneration in nearly all sectors exacerbates the problem. To address these issues, the government should focus on attracting more international companies and FDI in the country, improving the education system, and enhancing skills development to meet labor market demands. Employment is a multifaceted issue influenced by factors such as economic growth, political stability, and overall economic stability - areas that require significant improvement in Georgia. While this study tried to explore the associations and potential cause-and-effect relationships between the variables, Bayesian Networks primarily highlight dependencies but not necessarily causal links. Therefore, further research is needed to clarify causation. Specifically, the interesting findings from this study - such as the dependencies between remittances received and imports, FDI and remittances received, and the real interest rate and imports—warrant further investigation. Additionally, the relationship between migration, exports, imports, and FDI should be explored further to better understand cause-and-effect relationships and provide more comprehensive explanations. Bibliography: Blouchoutzi, A., Pedi, R. (2023). In-betweenness and Migration Interdependence: Lessons from Georgia, Moldova, and Ukraine. Studia Europejskie-Studies in European Affairs, 27(1); Karkashadze, N., Ukleba, S. (2021). Unemployment and migration in Georgia at the modern stage. FBIM Transactions, 9(2); Kharaishvili, E., Chavleishvili, M., Lobzhanidze, M., Damenia, N., Sagareishvili, N. (2017). Problems of youth employment in agricultural sector of Georgia and causes of migration. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 11(10); Mihi-Ramirez, A., Sobieraj, J., Garcia-Rodriguez, Y. (2020). Interaction of foreign direct investment, international trade, and remittances with emigration and immigration. Transformations in Business & Economics, 19(2A); Scutari, M. (2009). Learning Bayesian networks with the bnlearn R package. arXiv preprint arXiv:0908.3817; Tchanidze, K., Katsadze, I. (2021). The Study of Migration Influence on the Labor Market Structure and Employment in Georgia. Georgian Maritime Scientific Journal, 1(1); The National Statistics Office of Georgia www.geostat.ge [Last Access: 11.29.2024]; The World Bank. <https://data.worldbank.org/> [Last Access: 11.29.2024]; Zangurashvili, M. (2020). The main reasons for migration of young educated people from Georgia (Doctoral dissertation, Masarykova Univerzita). Footnotes [1] The World Bank. <https://data.worldbank.org/> [Last Access: 11.29.2024]. [2] The National Statistics Office of Georgia. <www.geostat.ge> [Last Access: 11.29.2024]. [3] Kharaishvili, E., Chavleishvili, M., Lobzhanidze, M., Damenia, N., Sagareishvili, N. (2017). Problems of youth employment in agricultural sector of Georgia and causes of migration. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 11(10), 2116-2121. [4] Zangurashvili, M. (2020). The main reasons for migration of young educated people from Georgia (Doctoral dissertation, Masarykova Univerzita). [5] Mihi-Ramirez, A., Sobieraj, J., Garcia-Rodriguez, Y. (2020). Interaction of Foreign Direct Investment, International Trade and Remittances with Emigration and Immigration. Transformations in Business & Economics, 19(2A), 42-59. [6] Tchanidze, K., Katsadze, I. (2021). The Study of Migration Influence on the Labor Market Structure and Employment in Georgia. Georgian Maritime Scientific Journal, 1(1), 87-96. [7] Karkashadze, N., Ukleba, S. (2021). Unemployment and Migration in Georgia at the Modern Stage. FBIM Transactions, 9(2). [8] Blouchoutzi, A., Pedi, R. (2023). In-betweenness and Migration Interdependence: Lessons from Georgia, Moldova, and Ukraine. Studia Europejskie-Studies in European Affairs, 27(1), 127-148. [9] Scutari, M. (2009). Learning Bayesian networks with the bnlearn R package. arXiv preprint arXiv:0908.3817.
Forms of state intervention in the health sector
Any economic activity is rarely free from state intervention. State interventions mainly cover the following aspects: supply, distribution, and regulation of goods or services. State interventions in the health sector cover the same aspects. The state regulates the medical market to prevent market defects. It affects the distribution of resources by developing special rules and instructions. Antimonopoly legislation is such a mechanism of regulation. The paper discusses various mechanisms of state intervention in the health sector, including taxes and subsidies, public health care, transfer programs, and regulation. Their goal is to influence the distribution of resources and revenues in the health sector. Much of the government intervention in the health sector is aimed at reducing costs in the industry. These regulations restrict entry into the medical market, limit the industry’s inappropriate expansion, and control prices. Some regulations also try to improve the quality of treatment. Licensing of medical personnel is the best example of quality control and improvement. Keywords: state intervention, regulation, public health, taxes, subsidies. Introduction The state provides a significant portion of health care services through state hospitals (or other state health care providers) and programs. The provision of health services and social insurance programs are important means of redistributing income from high-income groups to low-income ones or from the healthy to the elderly. The regulatory role of the state is carried out through various government agencies that affect almost all sectors of the economy and individual employees. The state can use various mechanisms to influence the distribution of resources and income. The main instruments in the health sector are taxes and subsidies, public health provision, transfer programs, and regulation. The paper discusses various mechanisms of state intervention in the health sector, including taxes and subsidies, public health care, transfer programs, and regulation. Their goal is to influence the distribution of resources and revenues in the health sector. Taxes and Subsidies When positive externalities arise as a result of the consumption of goods, the competitive market is inefficient. For example, the use of vaccines against infectious diseases causes beneficial external effects for society. If the good or service has significant external benefits, a subsidy can be used to increase the efficiency of market outcomes. At this point, it doesn’t matter whether the producers are subsidized or the consumers. In either case, a consumer or producer subsidy lowers the market price and increases consumption. In the US, the government provides tax subsidies (benefits) when employers purchase private insurance for their employees, which promotes greater coverage of the insured population.[1] When a product generates external costs, a tax can be imposed to reduce the consumption of that product. For example, the consumption of goods such as tobacco and alcohol causes harmful (negative) externalities, the marginal external cost must be added to the marginal private cost to determine effective solutions.[2] To reduce the consumption of such goods, it is recommended to increase the price. The tax or subsidy problem is related to determining the appropriate rate. Changing tax or subsidy rates is not a simple political process, and the market cannot always indicate the appropriate rate. Public Provision Public supply of a product is another approach to market failure. Public provision of health care is a complex process that requires answering three main economic questions (what? how? and for whom?). The question “what” is related to the types of health services, their quantity, and quality. The question “how?” It is related to how the state provides health services, whether the state can provide the services itself or contract with the private sector to solve the problem. The question “Who?” Regarding the financing and distribution of the service: will the program be of universal use, or will it be targeted only at certain groups? The financing mechanism has a significant impact on the resources raised in health care and the likely distribution - from rich to poor and from young to old.[3] Public provision is particularly useful for pure public goods. When there are significant externalities, and it is difficult or inefficient to exclude certain potential customers, public provision may be the best answer. Even if private firms can profitably produce a product demanded by consumers, the use of prices for such products is undesirable. For example, private research firms can profitably conduct certain public health research by disseminating the results only to organizations that pay for access to it. However, this approach is ineffective because very few people will gain access to the research. The value of research is not diminished if it is shared more widely. State provision does not necessarily mean state production. For example, medical research has many characteristics of public goods. Medical research is carried out by both government employees and independent scientists, private researchers employed by government-funded research foundations. Another example of state provision is medical assistance for the poor, which aims to improve the health of low-income citizens. Both state and private hospitals and clinics, which are financed by state programs, provide medical services to them. Transfer Programs Cash transfer programs are usually intended to achieve social equity by redistributing income in such a way that recipients are free to choose how to spend their income.[4] Social protection for the elderly, the poor, and the disabled is an example of this. Cash transfers for the poor include temporary assistance to needy families. In-kind transfers are also a redistribution of income, the main purpose of which is to increase the consumption of specific goods or services by the recipient. Important types of transfers include food assistance programs and housing. Regulation The state regulates the medical market to prevent market defects. It affects the distribution of resources by developing special rules and instructions. Antimonopoly legislation is such a mechanism of regulation. Regulation of the healthcare market by the state may take many forms: licensing laws, restrictions on entering the medical market, and regulation of the price, quality, and volume of medical services. In special cases, the state can completely prohibit the production of any goods or any activity. For example, the production and consumption of drugs (narcotics) in an illegal way.[5] In general, the state regulates the form of goods and determines the terms of production and consumption of goods. Licensing Licensing is seen as protecting citizens from fraudulent or unsafe healthcare providers. Licensing has a “good side” (improving quality) and a “bad side” (limiting market entry and competition). Licensing usually refers to the labor resources needed to provide health care and the medical organizations themselves that provide health care services. Licensing covers healthcare professionals. In the regular market, farmers are not licensed, although the food they produce is crucial to human life. People who manufacture cars are not licensed either. However, airline pilots and taxi drivers are required to be licensed. Licensing is considered a safety and quality improvement regulation mechanism and includes the following conditions: The quality of individual resources (e.g., doctors and nurses) varies significantly; Low-quality resources lead to poor results; Enterprises that produce goods or services cannot or do not want to measure the quality of their labor resources (firms are liable for damages caused by their employees); The customer does not have complete information about the quality of goods or services; Because medical care is tailored to the patient, it is difficult to exchange it. However, the use of defective goods or services may endanger the consumer. In the medical market, it is difficult for consumers to assess the quality of the service provided because the results of the treatment performed with each patient are different.[6] Sometimes, people’s health can improve even with minimal or unsatisfactory medical care. However, not infrequently, people’s health can deteriorate or become fatal even with the best medical care. Different professional qualifications of different doctors should also be taken into account. The user tries to find out if the doctor is “good”, but the conclusion is problematic. Does a “good” health result guarantee that the doctor is “good”? (No, the doctor may just be lucky.) Does a “bad” health outcome guarantee that the doctor is “bad”? (No; maybe it was a fluke of nature, despite the best service.). Sometimes, the user tries to extract information from a very limited number of events or may have no information at all. From a statistical point of view, the problem is that when one is trying to judge whether a doctor is “good” or “bad,” random information can override existing opinion. This explains why some doctors who lose their licenses can compile a list of patients who attest to their good professional qualities, even in the process of revoking their licenses. Through licensing, we can obtain two types of quality information. First of all, we get information about the level of education of the licensed person. For example, it can also test the surgeon’s knowledge of the indications and proper procedures for surgery. On the other hand, licensing authorities can collect information about poor treatment outcomes of individual doctors. By doing so, licensing authorities have a much greater ability to evaluate medical personnel, allowing for a much faster identification of a physician’s competency than any patient or physician. Voluntary Quality Certification Medical service quality certification is also carried out by private organizations. These organizations perform two functions. Firstly, they have certain training programs in their specialties, and secondly, they conduct special examinations to obtain a quality certificate. Typically, before being eligible to take the exam, a physician must complete a certified training program, namely a residency in an appropriate medical specialty (e.g., surgery, cardiology, family medicine) conducted at university hospitals. Some of these narrow specialty programs require additional specialized training beyond residency. For example, you can become licensed as a pediatrician after a three-year residency, but a narrow specialty in neonatology requires an additional three years of training. Voluntary quality certification has certain advantages over mandatory licensing. First, the voluntary “Council” is more in line with the principles of competition, as it lacks state coercion. Second, councils have created different levels of quality indicators that provide the market with more quality information than a single quality license can provide.[7] Voluntary certification, like mandatory licensing, has its problems. The first question that arises is related to the quality of the certifier. That is, it may be difficult for individual patients to understand the essence and meaning of certification. The second question that arises is the ability of the certification body to restrict entry into the specialty. An organization that achieves a very strong position in the market in terms of quality certification can acquire the ability to restrict market entry. Also, some medical specialty boards may limit the number of approved residencies statewide, which may limit the number of practitioners in a given specialty. In addition to the quality certification of doctors, dentists, nurses, and other medical personnel, it is important to certify medical organizations that cover a wide range of their activities. As a result of the certification of medical organizations, specific reports are developed, where specific notes are mentioned. Another important issue arises when considering quality certification in healthcare markets. How does certification affect consumers’ incentives to seek out providers that provide services at a relatively low cost? In many markets, low price means low quality, which is often true. When quality is inherently difficult to measure, sellers may misrepresent “high quality” to inflate prices. Evaluation of the quality of the activity of the medical service provider promotes competition in the medical field.[8] In the medical market, which is essentially monopolistic competition, customer search is important.[9] However, when consumers cannot judge quality, searching for a lower-cost provider is a challenge. Thus, quality assessment through licensing and certification can promote competition. Consumers use quality information to select providers. There are three types of quality data in the healthcare market: provider competency certification (licensing), compliance with desired protocols (e.g., adherence to the vaccination schedule, percentage of patients vaccinated against influenza), and actual outcome information (e.g., patient mortality following complicated surgery). Regulation mainly involves licensing. The latter two are usually provided to the public by some organization or agency, and the user is then free to react to such information. It is convenient for patients to use such indicators of quality assessment, which evaluate the results of treatment. For example, patients are known to choose cardiac surgeons with low mortality rates. Unfortunately, as with any type of information, mortality rates are difficult to collect and analyze. The greatest difficulty is associated with comorbidities treated by different providers. Physicians and reputable hospitals (e.g., academic medical centers) may attract—by direct patient selection or referral from their primary care physician—patients with high rates of comorbidity. It is expected that such patients may develop a higher mortality rate as a result of surgery than in less complicated patients. As a result, in the field of surgery, along with the general indicators of mortality, other indicators that take into account the patient’s risk are used.[10], [11] Many countries operate national “rating agencies” that provide quality scores for hospitals and nursing homes.[12] Nursing homes can be evaluated by indicators such as fractures, frequency of bedsores, etc. Hospital quality measurement tools are much more complex due to patient heterogeneity and varying rates of comorbidities. The following indicators are used to measure outcomes: 1. Direct outcome indicators, which include mortality rates and hospital readmission rates within 30 days; 2. Measurable indicators of the process, for example, taking the necessary medicines at the appropriate time; (3) patient satisfaction survey; (4) frequency of use of imaging, aimed at limiting the overuse of imaging studies. Quality assessment of nursing homes primarily involves measuring immediate outcomes (e.g., bedridden rates, rates of malnutrition or dehydration, rates of falls and fractures, etc.). Certificate of Need U.S. healthcare markets have been subject to a completely different type of regulation for decades - namely, restrictions on the construction of new facilities to prevent hospital overuse. These regulations restrict the construction of new hospital beds (or the purchase of expensive hospital equipment) without prior approval from the state. The makers of such laws try to determine how many hospital beds (and perhaps how many magnetic resonance imaging (MRI) units, etc.) are needed in a given geographic area. Only after that, they will issue a construction permit for a new facility. Because of this basic logic, these rules are called Certificate of Need. In the US, until 1974, the Certificate of Need had an advisory purpose. In 1974, the National Health Planning and Resource Development Act was passed. In 1986, President Ronald Reagan repealed the 1974 law that required states to use certificates of need. Since then, about a quarter of states have completely repealed their certificate of need laws, although about three-quarters still retain them in some form. States that continue to use a certificate of need focus more on outpatient facilities than hospitals. The Certificate of Need rules attempt to assess the need for medical facilities and control entry into the medical market to eliminate excess capital investment and thereby make the industry work more efficiently. The area of ​​greatest focus of the Certificate of Need laws is nursing homes, in which all states have a significant financial interest in the states’ share of the costs of the Medicaid program.[13] The purpose of regulating the certificate of need is to prevent “excessive entry” into the medical market and to reduce production costs. However, the analysis of the effect of the certificate of need is not so simple. If the certificate of need rules limit the capital investment of a hospital that wants to provide more services than the number of resources allows, the hospital has the option to use the same capital investment for other resources (e.g., intensive nursing services to treat more patients). Consequently, the ultimate effect of the Certificate of Need Act is mixed. In an environment of monopolistic competition, entry restrictions have the potential to reduce the average cost of production in an industry. However, defects in the manufacturing process increase production costs. Studies have shown that the certificate of need limits the increase of beds. Conclusion Much of the government intervention in the health sector is aimed at reducing costs in the industry. These regulations restrict entry into the medical market and limit the inappropriate expansion of the industry, as well as control prices. Some regulations also try to improve the quality of treatment. Licensing of medical personnel is the best example of quality control and improvement. Considering the above, it is necessary to expand the research on the economic analysis of regulation in the health sector. Bibliography: Chand, M., Armstrong, T., Britton, G., Nash, G. F. (2007). How and why do we measure surgical risk? Journal of the Royal Society of Medicine, 100(11). <https://doi.org/10.1177/014107680710001113>; Della Guardia, A., Lake, M., Schnitzer, P. (2022). Selective inclusion in cash transfer programs: Unintended consequences for social cohesion. World Development, 157, 105922. <https://doi.org/10.1016/j.worlddev.2022.105922>; Griffith, R., O’Connell, M., Smith, K. (2022). Price floors and externality correction. The Economic Journal, 132(646). <https://doi.org/10.1093/ej/ueac011>; Mwachofi, A., & Al-Assaf, A. F. (2011). Health care market deviations from the ideal market. Sultan Qaboos University Medical Journal, 11(3); Paley, D. (2017). State power and the enforcement of prohibition in Mexico. Mexican Law Review, 10(1); Rahman, M., Galarraga, O., Zinn, J. S., Grabowski, D. C., Mor, V. (2016). The impact of certificate-of-need laws on nursing home and home health care expenditures. Medical Care Research and Review, 73(1). <https://doi.org/10.1177/1077558715597161>; Rivers, P. A., & Glover, S. H. (2008). Health care competition, strategic mission, and patient satisfaction: Research model and propositions. Journal of Health Organization and Management, 22(6). <https://doi.org/10.1108/14777260810916597>; Shaw, C. D., Groene, O., Botje, D., Sunol, R., Kutryba, B., Klazinga, N., Bruneau, C., Hammer, A., Wang, A., Arah, O. A., Wagner, C., DUQuE Project Consortium. (2014). The effect of certification and accreditation on quality management in four clinical services in 73 European hospitals. International Journal for Quality in Health Care, 26(Suppl 1). <https://doi.org/10.1093/intqhc/mzu023>; Sixma, H. J., Kerssens, J. J., Campen, C. V., Peters, L. (1998). Quality of care from the patients’ perspective: From theoretical concept to a new measuring instrument. Health Expectations, 1(2). <https://doi.org/10.1046/j.1369-6513.1998.00004.x>; Tai, T. W. C., Mattie, A., Miller, S. M., Yawson, R. M. (2023). An examination of Leapfrog safety measures and Magnet designation. Journal of Healthcare Risk Management, 42(3-4). <https://doi.org/10.1002/jhrm.21533>; Tandon, A., & Reddy, K. S. (2021). Redistribution and the health financing transition. Journal of Global Health, 11, 16002. <https://doi.org/10.7189/jogh.11.16001>; Vaid, S., Bell, T., Grim, R., Ahuja, V. (2012). Predicting risk of death in general surgery patients based on preoperative variables using American College of Surgeons National Surgical Quality Improvement Program data. Perm Journal, 16(4). <https://doi.org/10.7812/TPP/12-019>; Weinmeyer, R. M., McHugh, M., Coates, E., Bassett, S., O’Dwyer, L. C. (2022). Employer-led strategies to improve the value of health spending: A systematic review. Journal of Occupational and Environmental Medicine, 64(3). <https://doi.org/10.1097/JOM.0000000000002395>. Footnotes [1] Weinmeyer, R. M., McHugh, M., Coates, E., Bassett, S., & O’Dwyer, L. C. (2022). Employer-led strategies to improve the value of health spending: A systematic review. Journal of Occupational and Environmental Medicine, 64(3), 218-225. <https://doi.org/10.1097/JOM.0000000000002395>. [2] Griffith, R., O’Connell, M., & Smith, K. (2022). Price floors and externality correction. The Economic Journal, 132(646), 2273–2289. <https://doi.org/10.1093/ej/ueac011>. [3] Tandon, A., Reddy, K. S. (2021). Redistribution and the health financing transition. Journal of Global Health, 11, 16002. <https://doi.org/10.7189/jogh.11.16001>. [4] Della Guardia, A., Lake, M., Schnitzer, P. (2022). Selective inclusion in cash transfer programs: Unintended consequences for social cohesion. World Development, 157, 105922 <https://doi.org/10.1016/j.worlddev.2022.105922>. [5] Paley, D. (2017). State power and the enforcement of prohibition in Mexico. Mexican Law Review, 10(1), 3-20. [6] Sixma, H. J., Kerssens, J. J., Campen, C. V., & Peters, L. (1998). Quality of care from the patients’ perspective: From theoretical concept to a new measuring instrument. Health Expectations, 1(2), 82-95. <https://doi.org/10.1046/j.1369-6513.1998.00004.x>. [7] Shaw, C. D., Groene, O., Botje, D., Sunol, R., Kutryba, B., Klazinga, N., Bruneau, C., Hammer, A., Wang, A., Arah, O. A., Wagner, C., DUQuE Project Consortium. (2014). The effect of certification and accreditation on quality management in four clinical services in 73 European hospitals. International Journal for Quality in Health Care, 26(Suppl 1), 100-107. <https://doi.org/10.1093/intqhc/mzu023>. [8] Rivers, P. A., Glover, S. H. (2008). Health care competition, strategic mission, and patient satisfaction: Research model and propositions. Journal of Health Organization and Management, 22(6), 627-641. <https://doi.org/10.1108/14777260810916597> [9] Mwachofi, A., & Al-Assaf, A. F. (2011). Health care market deviations from the ideal market. Sultan Qaboos University Medical Journal, 11(3), 328-337. [10] Vaid, S., Bell, T., Grim, R., Ahuja, V. (2012). Predicting risk of death in general surgery patients on the basis of preoperative variables using American College of Surgeons National Surgical Quality Improvement Program data. Perm Journal, 16(4), 10-17. <https://doi.org/10.7812/TPP/12-019> [11] Chand, M., Armstrong, T., Britton, G., Nash, G. F. (2007). How and why do we measure surgical risk? Journal of the Royal Society of Medicine, 100(11), 508-512. <https://doi.org/10.1177/014107680710001113>. [12] Tai, T. W. C., Mattie, A., Miller, S. M., Yawson, R. M. (2023). An examination of Leapfrog safety measures and Magnet designation. Journal of Healthcare Risk Management, 42(3-4), 21-29. <https://doi.org/10.1002/jhrm.21533>. [13] Rahman, M., Galarraga, O., Zinn, J. S., Grabowski, D. C., Mor, V. (2016). The impact of certificate-of-need laws on nursing home and home health care expenditures. Medical Care Research and Review, 73(1), 85-105. <https://doi.org/10.1177/1077558715597161>.
The Impact of Industry 4.0 in The Conditions of Globalization: An Overview of Logistics Companies Originating from Turkiye
The main purpose of this study is to investigate the impact of Industry 4.0 technologies on the survival and competitiveness of logistics companies based in Turkiye, a developing country, within the global landscape. From a qualitative study perspective, it aims to elucidate the positive and negative effects of Industry 4.0 applications on the logistics sector while also discussing recommendations to mitigate or eliminate these negative impacts. Based on the results of the semi-structured interview analysis, it can be asserted that the positive impacts of Industry 4.0 applications increase proportionally with the scale of a firm. Besides, if the R&D investments are enhanced in the logistics industry operating in Turkiye, it is expected that the negative effects will be more likely to be mitigated. According to findings from interviews, the preliminary anticipated effect of Industry 4.0 applications on the logistics sector is improved efficiency, while the primary barrier to its adoption is identified as the inadequacy of infrastructure and education. Keywords: industry 4.0, logistic sector, developing countries, globalization. Introduction The advent of the fourth industrial revolution, also called Industry 4.0, characterized by the integration of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), robotics, and big data analytics, has significantly transformed various sectors worldwide.[1] Particularly, one of these sectors, logistics, has experienced profound changes as Industry 4.0 offers potential benefits such as increased operational efficiency, improved supply chain management, and increased global competitiveness. In an era of globalization, where economies are increasingly interconnected, these technological advancements are essential for maintaining competitive advantage.[2] As an important developing country, Turkiye, with a strategic geographical location, plays a crucial role in international logistics and trade. The country’s logistics sector serves as a vital bridge between Europe, Asia, and the Middle East, making it a key player in global supply chains. Nonetheless, the adoption of Industry 4.0 technologies in logistics companies originating from Turkiye brings with it both significant opportunities and significant challenges.[3] This study aims to investigate the impact of Industry 4.0 on Turkish logistics companies. Using a qualitative research approach, specifically through semi-structured interviews with key industry stakeholders, this research aims to provide a comprehensive understanding of how technological developments associated with Industry 4.0 are impacting the industry. The study will examine both the positive and negative effects of Industry 4.0 applications, highlighting the factors that facilitate or impede their adoption.[4] Similar to the literature, findings suggest that larger firms tend to benefit more from Industry 4.0 applications due to their greater resources and scalability.[5] Conversely, smaller firms may face significant barriers, including inadequate infrastructure and a lack of specialized education and training.[6] Additionally, increased investments in research and development (R&D) in the logistics sector are expected to alleviate some of the negative impacts and create a more conducive environment for technology adoption.[7] So, this study aims to provide valuable insights and recommendations for logistics companies in Turkiye, helping them navigate the complexities of Industry 4.0 and enhance their global competitiveness. Through a detailed analysis of the current state of the industry and the challenges faced, this research will contribute to a broader understanding of the impact of Industry 4.0 on logistics in developing countries.[8] Literature Review The concept of “Industry 4.0” originated from the 2011 Hannover Fair in Germany and represents the fourth industrial revolution characterized by the integration of advanced digital technologies into manufacturing and service industries.[9] The revolution paradigm aims to provide uninterrupted connection and automation in processes with mainly the principles of Cyber-Physical Systems (CPS), Internet of Things (IoT), and Smart Factory principles.[10] The key components of Industry 4.0 include horizontal integration across value chains, vertical integration within production systems, and end-to-end digital integration of engineering processes.[11] These dimensions enable real-time data exchange, predictive maintenance, and agile manufacturing capabilities.[12] Despite its existing and potential benefits, such as improved efficiency, personalization, and sustainability, the adoption of Industry 4.0 is not without its challenges. The high cost of technology implementation, the need for a skilled workforce, and cybersecurity-related concerns are being struggled, especially by small and medium-sized enterprises (SMEs). The literature emphasizes the significance of interoperability, scalability, and adaptive organizational structures as critical factors for successful deployment.[13] In the logistics sector, Industry 4.0 technologies play a crucial role in enhancing operational efficiency and competitiveness in a global area. Especially the integration of IoT, Artificial Intelligence (AI), and big data analytics in logistics processes enables real-time tracking, improved inventory management, and optimized supply chain operations.[14] Various studies in the literature have shown that these advancements are particularly beneficial in developing countries like Turkiye, where strategic geographical positioning facilitates global trade connectivity.[15] However, the adoption of Industry 4.0 in the logistics sector also faces significant challenges. Infrastructure limitations, lack of technological awareness, and insufficient workforce skills are the main challenges and obstacles, especially for small-scale logistics companies. To overcome these obstacles and take full advantage of the benefits of Industry 4.0, it is crucial to invest in research and development (R&D) and targeted training programs.[16] The relationship between globalization and Industry 4.0 is also a critical area of study. Industry 4.0 technologies improve global supply chain integration and facilitate more efficient international trade by reducing costs and improving responsiveness to market demands.[17] This is particularly significant for countries like Turkiye, where logistics plays a vital role in connecting Europe, Asia, and the Middle East. While Industry 4.0 promises transformative advances in manufacturing and service sectors worldwide, ongoing research efforts are crucial to overcome implementation challenges, optimize technological integration, and foster inclusive economic growth in the age of digital transformation. Methodology The study explores the impact of Industry 4.0 technologies on the survival and competitiveness of logistics companies originating from Turkiye within the context of globalization. The research questions are: What are the primary impacts of Industry 4.0 technologies on the operational efficiency and competitiveness of logistics companies originating from Turkiye? What are the key challenges and barriers faced by Turkish logistics companies in adopting Industry 4.0 technologies? What strategies can be recommended to enhance the adoption and integration of Industry 4.0 technologies in the Turkish logistics sector? A semi-structured interview method was used for the qualitative design approach. The primary data were collected through interview questions with key stakeholders in the Turkish logistics industry. These stakeholders included executives and managers from a range of logistics companies and industry experts familiar with Industry 4.0 applications. A purposive sampling technique was employed to determine 20 interviewees who have at least 5 years of experience in the logistics sector. Participants were selected to represent companies of a wide range of sizes, from small and medium-sized businesses (SMEs) to large-scale corporations. Interviews were conducted via online platforms depending on the availability and time preference of the participants. Each interview lasted between 35 and 50 minutes and was recorded audio and video with the consent of the participants. Data Analysis A thematic analysis procedure was used to analyze the interview data, complete with key tables summarizing the findings. This approach was chosen for its effectiveness in identifying, analyzing, and reporting patterns/themes in qualitative data. The stages of the thematic analysis procedure are as follows: Transcription: To ensure accuracy, all interviews were transcribed verbatim. Familiarity: The researcher became familiar with the data by reading the transcripts multiple times. Coding: Initial codes were created by identifying important expressions and concepts related to the research questions. Theme Development: Codes were grouped into broader themes that formed the core of the data. Themes were reviewed and refined multiple times to ensure they accurately reflected the data. Interpretation: The themes created were interpreted in the context of the research questions and existing literature to draw meaningful conclusions. Findings As a result of the thematic analysis of the interview data, several important findings emerged regarding the impact of Industry 4.0 technological transformation on Turkish logistics companies. These findings are summarized below and supported by relevant tables. Positive Impacts of Industry 4.0 Industry 4.0 technologies have created many positive changes in the logistics sector in Turkiye, mainly increasing operational efficiency and competitiveness. The main positive effects identified, their descriptions from interviews, and their frequencies are shown in Table 1. Table 1. Positive Impacts of Industry 4.0 Impact Description Frequency of Mention Real-Time Tracking Providing advanced real-time tracking of shipments and assets 18 Inventory Management Increasing accuracy and efficiency in managing inventory levels 15 Supply Chain Optimization Improving coordination and optimization of supply chain operations 14 Cost Reduction Reducing operational costs due to automation and efficiency improvements 12 Barriers to Adoption of Industry 4.0 Despite the many benefits it provides, it has been determined that there are various obstacles to the adoption of Industry 4.0 technologies, especially for small companies. The main barriers to adoption, their descriptions from interviews, and frequencies are shown in Table 2. Table 2. Barriers to the Adoption of Industry 4.0 Barrier Description Frequency of mention Inadequate Infrastructure Lack of technological infrastructure required 17 Workforce and Training Lack of skilled workforce and training programs 14 High Initial Investment Costs Significant amount of capital required for initial implementation 12 Cybersecurity Concerns Risks related to data security and privacy 11 Differences Based on Company Scale The impact of Industry 4.0 digital transformation and technologies varies significantly between large companies and SMEs. While larger companies benefit more from these technologies due to greater resource allocation and scalability, SMEs face more significant challenges. The frequencies of positive impacts and barriers that large companies and SMEs mentioned in the interviews are shown in Table 3. Table 3. Differences based on company scale Company Size Positive Impacts (frequency) Barriers (frequency) Large Firms 23 9 SME’s 14 17 The Role of R&D Investments Increasing investments in research and development (R&D) were found to play an important role in reducing the negative effects and barriers of Industry 4.0 technologies. R&D investments foster innovation and better integration and help create a more conducive environment for technology adoption. The main aspects highlight the role of research and development investments in the successful adoption and implementation of Industry 4.0 technologies in the Turkish logistics sector, their descriptions from interviews and frequencies are shown in Table 4. Table 4. The Role of R&D Investments Aspect Description Frequency of Mention Innovation Encouraging the development of new technologies and solutions 14 Integration Improving existing operations and make more efficient 11 Mitigation of Negative Impacts and Barriers Helping reduce the negative impacts of technology adoption 9 Discussion The integration of Industry 4.0 technologies into Turkish logistics companies presents a complex scenario affected by various opportunities and challenges. Based on semi-structured interviews with various industry experts and company representatives, various important information has been revealed that sheds light on the current status and future potential of Industry 4.0 in the Turkish logistics sector.[18] One of the key drivers of the adoption of Industry 4.0 technologies and an important finding of this study is the increase in strategic and operational efficiency offered by this digital transformation. Various technological applications based on Industry 4.0, such as IoT, artificial intelligence, and big data analytics, enable real-time tracking of shipments and improved inventory management. These technologies also optimize supply chain operations. In this way, operations become easier, and costs are significantly reduced by minimizing manual interventions and errors. While large companies are motivated by strategic advantages such as improved decision-making capabilities, increased efficiency, and increased customer satisfaction, operational benefits such as reduced costs, increased productivity, and better resource management are of particular interest to SMEs.[19] These motivations are consistent with findings in the literature highlighting the various benefits of Industry 4.0 for different types of organizations. Despite these many potential benefits, numerous challenges may prevent the widespread adoption of Industry 4.0 technologies.[20] In the study, a lack of technical skills and expertise was identified as one of the main obstacles. This issue is well documented in the literature, where the lack of skilled labour is often cited as a significant barrier to digital transformation. The relatively slow adaptation of the education system in Turkiye to the demands of Industry 4.0 further aggravates this problem and results in the workforce not being sufficiently prepared for the complexity of new technologies. Financial constraints create a significant challenge, especially for SMEs.[21] The high initial costs of purchasing Industry 4.0 technologies can be a prohibitive constraint, and uncertainty about return on investment can further discourage companies from making these investments. This financial hesitation creates a common theme in the literature that emphasizes the need for significant capital and the risks associated with uncertain outcomes. Organizational resistance to change is another significant barrier to adoption. Many companies have already established traditional ways of working and are resistant to adopting new technologies. This resistance is mostly due to the lack of understanding of the benefits of Industry 4.0 and the fear of being laid off due to the automation to be installed.[22] To overcome this resistance, companies need to create effective change management strategies and clear communication about the long-term benefits of digital transformation. The interviews also reveal the critical role of government support and policy frameworks in facilitating the adoption of Industry 4.0. In countries with well-developed Industry 4.0 systems, government policies are effective in providing the necessary infrastructure, financial incentives, and training programs to support digital transformation. In Turkiye, stronger government intervention is needed to address gaps in infrastructure, provide financial support to SMEs, and support training initiatives focused on Industry 4.0 skills. Intercompany collaboration and information sharing emerged as another important factor. Industry 4.0 transformation is not an isolated effort but a collaborative process involving multiple stakeholders, including technology providers, educational institutions, and industry consortiums.[23] Knowledge exchange and partnership platforms can help companies overcome the challenges of digital transformation.[24] These findings from our semi-structured interviews are consistent with the broader literature on Industry 4.0, which highlights the interaction between technological, financial, and organizational factors in shaping the adoption environment. For instance, Sony and Naik (2020) identified the increasing complexity of production and logistics networks as a major hurdle that requires advanced data analytics and process integration technologies. Briefly, while Industry 4.0 offers significant opportunities for Turkish logistics companies, realizing its full potential requires overcoming many fundamental challenges. A multifaceted approach that includes investment in skills development, financial support mechanisms, organizational change management, and improved collaboration among stakeholders is essential. By overcoming these challenges and barriers, Turkish logistics companies can benefit from Industry 4.0 technologies to achieve sustainable competitive advantage and operational excellence. Conclusion and Implications The transition to Industry 4.0 presents a dual spectrum of opportunities and challenges that impact its adoption in different types of organizations. This research focused on the specific conditions of Turkish logistics companies, revealing critical insights into the factors driving and inhibiting the adoption of Industry 4.0 technologies. For large companies, strategic opportunities such as increased efficiency, increased competitiveness, and innovation potential encourage adoption. SMEs, on the other hand, are motivated by operational benefits such as reducing costs and increasing efficiency. The main challenge hindering the adoption of Industry 4.0 is the lack of technical skills and expertise, which are vital for the successful implementation and management of new technologies. Financial constraints, such as high initial investment costs and uncertainty regarding returns, further complicate the adoption process. Organizational resistance to change due to traditional working methods and fear of dismissal also poses a significant obstacle. Overcoming these challenges requires a multifaceted approach. For large companies, it is important to continually invest in employee training to develop the necessary technical expertise. SMEs will be able to benefit from government support through financial incentives and grants to reduce initial investment pressure. It will be very beneficial for companies if policymakers focus on developing comprehensive digital strategies that support the adoption of Industry 4.0, including clear guidelines and frameworks. It is crucial to promote a culture of innovation and digital literacy in organizations. This includes technical training and raising awareness about the strategic importance of digital transformation. Collaboration and information sharing between companies can also help overcome the challenges of digital transformation. While Industry 4.0 offers significant opportunities to Turkish logistics companies, realizing its full potential requires overcoming many fundamental barriers. A comprehensive approach that includes investment in skills development, financial support mechanisms, organizational change management, and improved collaboration between stakeholders is essential. By overcoming these problems, Turkish logistics companies can benefit from Industry 4.0 technologies to achieve sustainable competitive advantage and operational excellence. Bibliography: Bag, S., Gupta, S., Kumar, S. (2021). Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development. International Journal of Production Economics, 231, 107844. <https://doi.org/10.1016/j.ijpe.2020.107844>; Bag, S., Telukdarie, A., Pretorius, J. H. C., Gupta, S. (2021). Industry 4.0 and supply chain sustainability: Framework and future research directions. Benchmarking: An International Journal, 28(5). <https://doi.org/10.1108/BIJ-03-2018-0056>; Ben-Daya, M., Hassini, E., Bahroun, Z. (2019). Internet of things and supply chain management: A literature review. International Journal of Production Research, 57(15–16). <https://doi.org/10.1080/00207543.2017.1402140>; Büyüközkan, G., Göçer, F. (2018). Digital supply chain: Literature review and a proposed framework for future research. Computers in Industry, 97. <https://doi.org/10.1016/j.compind.2018.02.010>; Frank, A. G., Dalenogare, L. S., Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210. <https://doi.org/10.1016/j.ijpe.2019.01.004>; Gilchrist, A. (2016). Industry 4.0. Apress. <https://doi.org/10.1007/978-1-4842-2047-4>; Hofmann, E., Rüsch, M. (2017). Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, 89. <https://doi.org/10.1016/j.compind.2017.04.002>; Hermann, M., Pentek, T., Otto, B. (2016). Design principles for Industrie 4.0 scenarios. 2016 49th Hawaii International Conference on System Sciences (HICSS). <https://doi.org/10.1109/HICSS.2016.488>; Kamble, S. S., Gunasekaran, A., Gawankar, S. A. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection, 117. <https://doi.org/10.1016/j.psep.2018.05.009>; Liao, Y., Deschamps, F., Loures, E. de F. R., Ramos, L. F. P. (2017). Past, present and future of Industry 4.0—A systematic literature review and research agenda proposal. International Journal of Production Research, 55(12). <https://doi.org/10.1080/00207543.2017.1308576>; Luthra, S., Mangla, S. K. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117. <https://doi.org/10.1016/j.psep.2018.04.018>; Phuyal, S., Bista, D., Bista, R. (2020). Challenges, opportunities and future directions of smart manufacturing: A state of the art review. Sustainable Futures, 2, 100023. <https://doi.org/10.1016/j.sftr.2020.100023>; Rüßmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., & Harnisch, M. (2015). Industry 4.0: The future of productivity and growth in manufacturing industries. Boston consulting group, 9(1), 54-89. Salkin, C., Oner, M., Ustundag, A., Cevikcan, E. (2018). A conceptual framework for Industry 4.0. In A. Ustundag & E. Cevikcan (Eds.), Industry 4.0: Managing the digital transformation. Springer International Publishing. <https://doi.org/10.1007/978-3-319-57870-5_1>; Sony, M., Naik, S. (2020). Key ingredients for evaluating Industry 4.0 readiness for organizations: A literature review. Benchmarking: An International Journal, 27(7). <https://doi.org/10.1108/BIJ-09-2018-0284>; Strange, R., Zucchella, A. (2017). Industry 4.0, global value chains and international business. Multinational Business Review, 25(3). <https://doi.org/10.1108/MBR-05-2017-0028>. Tatoglu, E., Bayraktar, E., Golgeci, I., Koh, S. C. L., Demirbag, M., Zaim, S. (2016). How do supply chain management and information systems practices influence operational performance? Evidence from emerging country SMEs. International Journal of Logistics Research and Applications, 19(3). <https://doi.org/10.1080/13675567.2015.1065802>; Vogel-Heuser, B., Hess, D. (2016). Guest editorial industry 4.0–Prerequisites and visions. IEEE Transactions on Automation Science and Engineering, 13(2). <https://doi.org/10.1109/TASE.2016.2523639>. Footnotes [1]Gilchrist, A. (2016). Industry 4.0. Apress, 195. [2] Büyüközkan, G., Göçer, F. (2018). Digital Supply Chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 174. [3] Luthra, S., Mangla, S. K. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117, 169. [4] Tatoglu, E., Bayraktar, E., Golgeci, I., Koh, S. C. L., Demirbag, M., Zaim, S. (2016). How do supply chain management and information systems practices influence operational performance? Evidence from emerging country SMEs. International Journal of Logistics Research and Applications, 19(3), 188. [5] Sony, M., Naik, S. (2020). Key ingredients for evaluating Industry 4.0 readiness for organizations: A literature review. Benchmarking: An International Journal, 27(7), 2214. [6] Ben-Daya, M., Hassini, E., Bahroun, Z. (2019). Internet of things and supply chain management: A literature review. International Journal of Production Research, 57(15–16), 4720. [7] Strange, R., Zucchella, A. (2017). Industry 4.0, global value chains and international business. Multinational Business Review, 25(3), 175. [8] Phuyal, S., Bista, D., Bista, R. (2020). Challenges, Opportunities and Future Directions of Smart Manufacturing: A State of Art Review. Sustainable Futures, 2, 100023, 4. [9] Bag, S., Gupta, S., Kumar, S. (2021). Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development. International Journal of Production Economics, 231, 107844, 10. [10] Rüßmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Harnisch, M. (2015). Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries, 3. [11] Hermann, M., Pentek, T., Otto, B. (2016). Design Principles for Industrie 4.0 Scenarios. 2016 49th Hawaii International Conference on System Sciences (HICSS), 3930. [12] Ustundag, A., Cevikcan, E., Salkin, C., Oner, M., Ustundag, A., & Cevikcan, E. (2018). A conceptual framework for Industry 4.0. Industry 4.0: managing the digital transformation, 17. [13] Frank, A. G., Dalenogare, L. S., Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 18. [14] Luthra, S., Mangla, S. K. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117, 169. [15] Liao, Y., Deschamps, F., Loures, E. de F. R., Ramos, L. F. P. (2017). Past, present and future of Industry 4.0—A systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), 3610. [16] Vogel-Heuser, B., Hess, D. (2016). Guest Editorial Industry 4.0–Prerequisites and Visions. IEEE Transactions on Automation Science and Engineering, 13(2), 411–413. IEEE Transactions on Automation Science and Engineering, 5. [17] Strange, R., Zucchella, A. (2017). Industry 4.0, global value chains and international business. Multinational Business Review, 25(3), 178. [18] Hofmann, E., Rüsch, M. (2017). Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, 89, 25. [19] Vogel-Heuser, B., Hess, D. (2016). Guest editorial industry 4.0–Prerequisites and visions. IEEE Transactions on Automation Science and Engineering, 13(2). 412. [20] Liao, Y., Deschamps, F., Loures, E. de F. R., Ramos, L. F. P. (2017). Past, present and future of Industry 4.0—A systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), 3612. [21] Phuyal, S., Bista, D., Bista, R. (2020). Challenges, opportunities and future directions of smart manufacturing: A state of the art review. Sustainable Futures, 2, 100023, 8. [22] Rüßmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., &amp; Harnisch, M. (2015). Industry 4.0: The future of productivity and growth in manufacturing industries. Boston consulting group, 9(1), 62. [23] Bag, S., Telukdarie, A., Pretorius, J. C., & Gupta, S. (2021). Industry 4.0 and supply chain sustainability: framework and future research directions. Benchmarking: An International Journal, 28(5), 1430. [24] Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2018). Sustainable Industry 4.0 framework: A systematic literature review identifying the current trends and future perspectives. Process safety and environmental protection, 117, 412.
Is Winemaking Central to Georgia’s Economy?
Based on the primary data and review of secondary sources, this paper argues that wine is more than a symbol of Georgia; it is a foundation of the country’s economy and social life. The article also looks beyond the direct current statistics of the formal economy and considers the indirect economic impact, trends, and potential, an assessment of winemaking and wine-related tourism points to these sectors as a business priority for Georgia and an important economic and social development vehicle. The study also highlights the potential risks associated with climate change, including increased heat stress, drought, altered growing seasons, and other relatively minor obstacles. The paper identifies specific grapevine cultivars that may be particularly vulnerable to these challenges and explores adaptation strategies to mitigate their negative effects. The results of this study offer valuable insights for Georgian winemakers and policymakers to ensure the sustainability of the country’s wine industry in the face of a changing climate. Keywords: Georgia, Wine Economy, Tourism, Subsidy. Introduction The Centrality of Winemaking in Georgia’s History and Culture Georgia’s history and culture are inseparable from winemaking. The 8,000-year-old Qvevri method of using terra cotta urns buried in the ground for fermenting crushed grapes is evidence of Georgia’s uniqueness as the birthplace of winemaking. Having originated in 6000 BC, winemaking spread from the Caucasus west to the eastern Mediterranean from 2500 BC and to the north into much of Europe by 400 AD. Regarding the language, the Georgian word ghvino (wine) was probably the origin of the Latin term vino, considering that Georgia was allied with the Latin Roman Empire from the 1st century BC to the 4th century AD. On an even deeper level, viticulture and winemaking are integral to the Georgian Orthodox religion, whose major symbol is the “Grapevine Cross”. The 6th-century Jvari Monastery in Mtskheta – the continuous religious center of Georgia – has a painting of the Virgin Mary holding grapes for Christ as a child. The country’s church architecture and paintings use the vine leaf as one of the most distinctive motives. Reinforcing the centrality of winemaking in Georgia’s customs, through centuries, wine has had a special meaning as a unifier of people and a source of social cohesion. The traditional supra feast has bonded people via collective experiences of toasting, singing, and dancing, while hospitality is part of the national character.[1] Despite the greater profitability of other agriproducts (for instance, watermelons), Georgia favors winemaking. The social, cultural, and religious prominence of winemaking begs the question of whether it is equally central to Georgia’s economy. If winemaking is vital for the economy, to what extent is it important for its current condition and further development? Wine Exports and Georgia’s Gross Domestic Product (GDP) The value of Georgian wine exports was $259 million in 2023, making the industry the second-largest export generator for the country (Graph 1). Adding other alcoholic beverages to “wine of fresh grapes” brought 2023 exports in this combined category to $457 million.[2] In January-June 2024, “wine of fresh grapes” comprised 5.5% of the country’s total exports and was the second most exported commodity after motor cars, which accounted for 32.8% of (re)exports. Together with the category of “spirituous beverages”, wine and other alcoholic exports amounted to 10.2% of the country’s total exports[3] (see Graph 2). Graph 1. Major commodity positions by exports, million USD Source: National Statistics Office of Georgia.[4] Graph 2. Share of major commodity positions by exports in January-June 2024* * Revised data will be published on November 15, 2024 Source: National Statistics Office of Georgia.[5] The high rank of wine in Georgia’s exports implies its importance, but it is largely due to the country’s lack of promising export options and low export diversification. More than 50% of the total exports are made up of only five commodity positions: motor cars, wine of fresh grapes, ferroalloys, spirituous beverages, and precious metal ores and concentrates. In the first six months of 2024, Georgia exported 54.5 million liters of wine worth $156.7 million to 61 countries. The exports figure meant a 26% increase over the same period of 2023, while revenues increased by 24%.[6] In Russia’s wine imports, Georgian wine amounted in 2022 to 19% in US dollar terms, while its share in top wine importer countries was negligible.[7] The 2024 remarkable upswing in Georgia’s wine exports was especially notable in exports to Russia, which increased 74% in the first quarter of the year compared to the same period of 2023, accounting for $65 million in value.[8] Despite serious efforts to diversify exports of wine, Russia remains the main destination of Georgian wine, reaching 65% of the overall 2023 exports in this sector, the highest figure since 2005.[9] Russia ranked second among Georgia’s commercial partners in the first quarter of 2024, while Turkey ranked first.[10] As shown in Graph 3, the share of wine exports in Georgia’s GDP has been growing along with the GDP growth in 2015-2021.[11] The country’s GDP has continued to increase since 2021. It showed an 11% growth in 2022 and a 7.5% growth in 2023 and reached 80.2 billion GEL (or $30.5 billion) in 2023 (Graph 3). The share of wine exports in the GDP in 2023 equaled 0.85% and was more than 1.50% if spirituous beverages were considered.* Compared to 0.64% in 2015,[12] these figures signal a significant increase over the 8 years. Graph 3. Wine exports and GDP, 2015-2023 Source: Forbes.[13] Wine is the main source of income for several regions in Georgia. It also enhances the economic and social welfare of local communities. In Kakheti, winemaking is the dominant sector and a crucial source of employment. In 2013, around 65–70% of all vineyards in Georgia were concentrated in the Kakheti region, which has many family-run wine cellars representing small and mid-sized wineries.[14] While 16.4% of the labor force was unemployed in 2023 at the national level, this figure was lower – 12% – in Kakheti.[15] There are also wineries in many other areas, including Racha, Shida Kartli, Kvemo Kartli, Imereti, Samegrelo, Guria, Samtskhe-Javakheti, and Ajara. Georgia’s rugged and mountainous landscape limits the availability of arable acreage, and the overwhelming majority of households own less than two hectares of agricultural land. Only 4.8% of households own two to five hectares of land, and 1.5% own more than five hectares. As over 40% of Georgia’s population lives in rural areas, agriculture, including the cultivation of grapevines, offers an important safety net through small-scale village-type farming.[16] Georgia’s formal wine production sector attracted, on average, 0.8% of directly employed people (approximately 5,000 people) from 2011-2019. As for total employment in the sector, it is estimated to be around 100 thousand people. The latter estimate includes self-employed people and those working in the broader winemaking cluster on distribution, sales, trade, mechanization, chemical treatment of vines, transportation, and other auxiliary tasks. The average monthly remuneration of employees in the winemaking sector amounted to 1,046 GEL (or 371 dollars) in 2019, having increased by about 11.5% annually between 2011 and 2019. It constituted 93% of the country’s average salary in 2019.[17] Given Georgia’s unemployment rate of 16.4% in 2023,[18] informal or complementary employment in winemaking makes a difference in rural areas. The size of Georgia’s informal economy is estimated to be 46.5% of GDP,[19] which represents $40.4 billion at the GDP (PPP) level. While the nominal 2023 GDP of Georgia in current prices was $30.5 billion, it was more than double, $86.8 billion, accounting for purchasing power parity (PPP), which makes this indicator comparable across countries.[20] State Promotion and Subsidies of Winemaking The National Wine Agency (NWA) of Georgia implements an extensive program to promote Georgia’s winemaking. The state budget of this program in 2024 was set at 16 million GEL (or almost $6 million), which is 2 million GEL ($740 thousand) higher than the figure for 2023.[21] The NWA does not promote wine exports to Russia, which are already extensive. It prioritizes marketing Georgian wine in the USA, Great Britain, Germany, Poland, the Baltic states, China, South Korea, and Japan. In these countries, the contractor companies of the NWA hold a variety of events to increase the export potential of Georgian wine. Wine exhibitions, festivals, and other events are also held throughout Georgia to raise the potential of the wine industry and wine-related tourism in the domestic and international markets. Furthermore, the Government of Georgia supports national winemaking through two types of subsidies. Direct subsidies entail cash payments to producers per kilogram of grapes. As for indirect subsidies, they encourage state-owned companies to purchase grapes from farmers. After a temporary decline of the subsidiary scheme in 2017-2019, spending on the wine sector resumed with a new force in 2020 (Graph 4). In 2021, the government’s spending on the wine sector increased by 44%, compared to 2020, with the largest share (90%) going to grape subsidies.[22] In 2022, the government continued to subsidize the grape harvest, allocating about 150 million GEL ($54.2 million) for this purpose and emphasizing the purchase and processing of specific grape varieties from the Kakheti region.[23] Graph 4. Grape Production and Government Spending on the Wine Sector Source: Free Network.[24] Some analysts question the effectiveness of direct subsidies to producers of grapes. The significance of the promotion of Georgian wine exports suggests the need to prioritize subsidizing the marketing of wine in foreign markets to help winemakers enter international trade networks, especially in European and other strategic countries.[25] Other proposals for useful government interventions include ensuring producers’ adherence to food safety standards to improve the quality of grapes and wine and providing high-quality extension services, including advice and technical support, to benefit the sustainable, long-term growth of the wine sector.[26] Food and Wine Tourism Wine-related tourism is not a modern phenomenon. There is evidence of wine tourism in ancient Egypt, Greece, and China going back to the Tang dynasty (618-907 AD) (This Day in Wine History, 2022).[27] The modern wine tourism industry is believed to have been born in California in the 1970s. Mondavi Winery was one of the first wineries to welcome guests for tastings, launching the popularity of winery tours in the USA. In the 1980s, wine tourism spread outside the Americas to become common in Italy, France, South Africa, and other countries The United Nations World Tourism Organization (UNWTO) held its 1st Global Conference on Wine Tourism in Kakheti, Georgia, in September 2016. This inaugural event attracted more than 200 participants from almost 50 countries.[28] The latest, 7th UNWTO Global Conference on Wine Tourism took place in November 2023 in Spain’s winemaking region La Rioja under the theme of “Inclusive, sustainable and digital wine tourism: Building stronger territorial cohesion”. The conference aimed to identify ways to make wine tourism an enabler of a more sustainable, inclusive, and resilient future for communities.[29] The section on wine and food of the 2018 strategy of the Georgian National Tourism Administration blended the themes of the country’s cultural heritage and unique wine and cuisine. It called for the promotion of Georgia as “the Cradle of Wine”, identification of wine routes/trails in the Kakheti and Imereti regions, and the development of wine- and food-related services and festivities. To differentiate Georgia from competitor destinations, the strategy proposed aspiring for an “emotional connection” with the country’s visitors/tourists around authentic, engaging, and unique experiences.[30] Following the inevitable decline of Georgia’s tourism industry as well as the entire economy during the COVID-19 pandemic,[31] also known as the coronomic crisis,[32] the years 2022 and 2023 saw an impressive recovery. In 2023, revenues from international tourism exceeded the 2019 level by 26.2% or $856.7 million and the 2022 data by 17.3% or $608.7 million. In 2023, 7.1 million international travelers visited Georgia, which amounted to a 75.6% recovery in numbers from the pre-pandemic period. As a result, the country received a record $4.1 billion in tourism revenue.[33] The largest number of visitors (1.2 million) in 2023 was from Russia, amounting to 23.2% of the total number of visitors, followed by Turkey (21.4%) and Armenia (13.5%). Correspondingly, the citizens of Russia, Turkey, and Armenia made the most visits (Graph 5).[34] Graph 5. Distribution of the number of visits made by inbound visitors by the country of citizenship Source: National Statistics Office of Georgia.[35] The expenditures during the 2023 visits were 20.5% higher compared to the previous year’s record.[36] For this paper, it is important to highlight the share of food and drinks in the overall expenditures. In 2022, the largest share of visitors’ expenditures was registered on served food and drinks (33.2% of total expenses) and accommodation (31% of total expenses).[37] “Tasting local cuisine and wine” was one of the most popular tourist activities – the second only after shopping – in 2022 (Graph 6). In 2023, the share of food and drinks decreased to 21.6%, while accommodation and shopping were the main expenditure categories (Graph 7). Graph 6. Popular tourist activities Source: Georgian National Tourism Administration.[38] Graph 7. Distribution of the expenditure spent by inbound visitors by expenditure categories in 2023* Expenditure (Million USD) % Average Expenditure Per Visit (USD) Accommodation 1793 36.4 291 Shopping 1152 23.4 186 Foods and Drinks 1065 21.3 172 Holiday, Leisure, Recreation, Culture and Sporting Activities 495 10 80 Local Transport 359 7.3 58 Other Expenditures 62 1.3 10 Total Expenditure 4945 100 797 Source: National Statistics Office of Georgia.[39] *Official average exchange rate for 2023 was taken at 1$ = 2.6279 GEL How important is the tourism sector for the economy? Worldwide, in 2022, the Travel and Tourism sector contributed 7.6% to global GDP, constituting an increase of 22% from 2021, though 23% below the 2019 pre-pandemic level.[40] In the same year in Georgia, the added value of tourism-related industries as a share of GDP increased from 6.7% to 7.2%. More than 20% of this value was driven by food and beverage services.[41] In 2023, the world’s Travel and Tourism sector contributed 9.1% to the global GDP and added 27 million new jobs.[42] Wine-related tourism is essential for the development of winemaking regions of Georgia to support well-established and also startup companies as well as households. In 2023, the visits to the wine-making regions of Kakheti, Imereti, Samtske-Javakheti, and Kvemo Kartli comprised 20% of the total visits to Georgia.[43] The ability to sell wine directly to consumers in wineries plays a critical role in the growth and development of Georgia’s beverage industry as well as the advancement of local communities. Many rural producers in Georgia do not have distribution contracts enabling them to retail their wine. Therefore, the openness of their establishments for visitation, which typically includes tours, tastings, and opportunities to purchase beverages, is indispensable.[44] Given a dramatic increase in the number of wineries registering for commercial production – from 80 in 2006 to an estimated 2,400 in 2023[45] – these wineries can serve as the lifeblood of regional tourism and the rural economy. Close to one-half of the Georgian population is still employed in agriculture, while this sector accounted for 7-8% of GDP in 2014-2023,[46] and 98% of farm workers are considered self-employed practicing subsistence agriculture.[47] Since human capital in the rural economy remains largely untapped, it can be mobilized to participate in both winemaking and wine and food tourism offerings. Overall Impact of Winemaking and Wine Tourism If we consider only direct statistics on Georgia’s winemaking, the impact of this sector appears moderate, if not small. Because mountains occupy 65% of Georgia’s territory,[48] opportunities for large-scale agriculture are limited, and small-scale village-type farming and winemaking are predominant. Even though wine exports in Georgia have been growing, they comprised only 5.5% of the country’s total exports in January–June 2024.[49] They also do not contribute much to the country’s GDP: 0.85% or about 1.50%, if considering spirituous beverages, according to the 2023 statistics.** “Agriculture, forestry, and fishing” – a category that includes vine-growing – added only 6.9% to the GDP (Graph 8), and winemaking is subsidized by the government. Graph 8. GDP structure 2023, % Source: National Statistics Office of Georgia.[50] However, it is important to look beyond current data about the formal economy and focus on trends and potential, also with the help of modern financial technologies.[51], [52] Wine was the second most exported commodity in Georgia in both 2023 and the first half of 2024.[53] The rank of wine in Georgia’s exports had increased compared to 2018 when the wine industry was the fifth-largest export generator for the country.[54] The share of wine exports in Georgia’s GDP has been growing along with the GDP growth,[55] and it is increasingly important for regional development in terms of both economic growth and employment. It is also notable that detailed statistics on GDP reflect the formal economy, whereas data on the informal economy is scarce, thus underrepresenting trends in village-type winemaking. Compared to other major commodity positions, such as “motor cars” and “ferroalloys”, winemaking has greater potential. Georgia does not produce cars but rather reexports them,[56] the country’s mining industry has been in decline since Georgia’s independence from the Soviet Union, and the ferroalloys market has experienced a crisis.[57] Wine is a more promising export option than the alternatives, considering the country’s climate, terrain, and soil; culture and long history of winemaking; and economic performance and prospects. Moreover, past manufacturing and mining showed negative environmental impacts that would contradict interest in marketing Georgia as a beautiful place and a “Cradle of Wine”. Learning from the world’s top winemaking regions, the wine industry not only contributes significantly to the export and GDP but also provides a multiplier effect on the economy. This point can be proven by the example of California, which is known as “the world’s great wine state”, accounts for 87% of US wine production and, if it were an independent nation, would be the world’s fourth wine-producing country behind Italy, France, and Spain.[58] California’s wine industry generates close to $88.12 billion in total economic activity that embraces farming, banking, accounting, manufacturing, packaging, transportation, printing, and advertising. It directly employs as many as 256 thousand people; creates an additional 116 thousand jobs in supplier and ancillary industries; and produces $8.45 billion in tax revenues on the local, state, and national levels (Exhibit 1).[59] Exhibit 1. What’s Wine Worth? 2022 California Economic Impact Study Wine Producers Jobs Annual Wages (Bln $) Tourism Visits Tourist Expenditures (Bln $) Total Taxes (Bln $) Federal Taxes (Bln $) State and Local Taxes (Bln $) 4 795 513 738 32.05 25 215 863 8.56 8.45 5.42 3.03 Total Impact – 88.12 billion USD Source: The National Association of American Wineries.[60] The 2022 economic impact study of California’s wine industry also corroborates a strong linkage between winemaking and tourism. California’s “wine country” generates more than 25 million tourist visits and $8.56 billion in annual tourism expenditures, benefiting local economies and tax bases.[61] This evidence brings us to a brief discussion of the overall impact of Georgia’s tourism sector. As noted above, in 2022, Georgia received $3.5 billion from incoming tourism, and the share of tourism in Georgia’s GDP was 7.2% – almost on par with the worldwide 7.6% contribution of the Travel and Tourism sector to the global GDP.[62] In 2023, revenue from tourism increased to $4.1 billion,[63] which amounted to 13.4% of the $30.5 billion GDP.[64] The 13.4% figure was higher than the 9.1% contribution of the world’s Travel and Tourism sector to the global GDP in 2023.[65] Before the COVID-19 pandemic in 2019, the Georgian travel and tourism industry represented 25% of the total GDP, and this industry supported 482 thousand jobs (equivalent to more than one in every four jobs).[66] The comparison of the 2023 and 2019 data suggests that Georgia’s tourism has not yet fully recovered from the economic crisis caused by a health emergency and that the upward trend in the advancement of this sector is likely to continue. Considering 7.1 million visitors to Georgia in 2023,[67], the average country’s revenue per visitor in the same year was $577.[68] For comparison, in France, the country with the highest number of international tourist arrivals worldwide, the average revenue per visitor in 2023[69] – the year that saw a record number of arrivals at 100 million[70] and a record revenue of €69 billion or $75 billion – was $750.*** Thus, even though Georgia is a much less known tourist destination than France, the country’s capacity to generate revenue from tourism is substantial in relative terms. While the added value of Georgia’s tourism as a share of GDP increased in 2022 compared to 2021, more than 20% of this value was driven by food and beverage services.[71] Although the share of food and drinks decreased to third place in the visitors’ expenditures in 2023, compared to 2022, when this share occupied the top position, “tasting local cuisine and wine” remains one of the most popular tourist activities. This reveals the cross-fertilization of winemaking and food and wine tourism, which especially benefits winemaking regions of Georgia, increases awareness of the country across the world and boosts its economic and social development. In the international context, as well as in Georgia, winemaking can generate secondary economic activity. Winemaking is closely linked with major sectors of the economy: agriculture (grape growing), wine production (grape processing into wine and other alcoholic drinks), transportation (of grapes and wine), marketing of wine, and businesses associated with wine and food tourism (hotels, restaurants, events planning, supermarkets, and shops). Reversely, tourism affects and bolsters other sectors of the economy. In 2018, before the COVID-19 pandemic, 31.3% of Georgia’s GDP depended on the travel and tourism industry, including parks and transportation.[72] Investment in winemaking and food and wine tourism can thus stimulate most of the Georgian economy – both urban and rural. As labor-intensive sectors, these sectors generate jobs, revenue, and taxes directly, as well as through ancillary industries and services. Georgia’s strong economic performance in 2021 and 2022, which the International Monetary Fund attributed to tourism revenues and a surge in war-related immigration and financial inflows, suggests sound business and investment conditions, favorably comparing the country to its regional peers Georgia’s investment attractiveness,[73] the high rank of wine in exports, and the closeness of tourism-related indicators to global averages reinforce the centrality of winemaking and wine tourism in the country’s economy. Given Georgia’s 8,000-year history of winemaking, the existence of more than 500 varieties of indigenous grapes, and distinctive traditional methods of wine production, the potential of the country’s wine industry is above the global average. Similarly, the potential of Georgia’s wine tourism is way above average. Wine tasting can be effectively combined with learning about the unique Georgian culture of hospitality and enjoying a rich and diverse natural landscape, as the country is blessed with majestic mountains, exceptional valleys, and a remarkable seaside. Furthermore, there are indications that winemaking can be more profitable in Georgia relative to other sectors of the economy and international competitors. A TBC Capital survey of large- to medium-size Georgian wineries revealed high financial returns—about twice the average for Georgian businesses in general.[74] According to EBIT Group, a financial consulting company, both net profit margin and return on equity are significantly higher for Georgian wine-producing companies compared to US winemakers.[75] Highlighting the reality and the potential of winemaking in Georgia, these assessments suggest its business priority for the country and its role as the engine of economic growth. The ancient Georgian deity of wine, Aguna, is the god of vineyard fertility and crop prosperity.[76] Amplified by a quintessentially Georgian attitude that “every guest is a gift from God”, a blend of winemaking and wine tourism offers the country a promise of economic prosperity, even though much is still to be done to gain Georgia’s recognition as a producer of the world’s best wines and a top tourist destination. Conclusion Winemaking is central to Georgia’s cultural identity and social life, but its direct economic contribution appears moderate: wine exports account for a small percentage of GDP, and the formal wine industry employs a relatively small portion of the workforce. However, considering indirect impacts and future potential, wine is a significant driver of the national economy and regional development: Importance beyond statistics: wine production is crucial for rural communities, offering employment and income security; the informal wine economy is substantial. Growth potential: wine exports are increasing, and Georgia has a competitive advantage due to its unique grape varieties, climate, and winemaking traditions. Multiplier effect: winemaking is linked to other sectors like agriculture, tourism, and transportation, stimulating overall economic activity. Tourism synergy: wine tourism is a major driver for regional economies, attracting visitors and boosting revenue from food and beverage services. Georgia’s future economic development can significantly benefit from investing in and promoting both winemaking and wine tourism. By leveraging its unique heritage and fostering a thriving wine industry, Georgia can attract investment, create jobs, and enhance its reputation as a global tourist destination, similar to the case of US wine industry centers. Bibliography: 1. Agenda.ge. (2024). 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