The international, peer-reviewed, and indexed scientific journal Globalization and Business (G&B) was established in 2016 as an interdisciplinary publication of European University. The journal’s mission is to advance the study and discourse on contemporary issues across a range of disciplines, including economics, business, education, tourism, technology, governance, and political science. By publishing rigorous, research-based analyses, the journal seeks to foster critical discussions and enrich existing debates in these fields. Through collaborations with both local and international scholars, we are dedicated to supporting the internationalization of research and contributing to the global academic community. The journal gives preference to studies that examine issues in a comparative context, ensuring that the papers are relevant and engaging for both national and international academic audiences. The journal’s primary objectives include: Fostering Scientific Innovation: Encouraging the development of novel ideas, methodologies, and advancements in the study of globalization and business. We continuously monitor all innovations in modern technologies and integrate them into the journal's activities. Providing Access to Cutting-Edge Research: We offer readers free, instant, and uninterrupted access to articles, making modern scientific works available to everyone. Supporting Interdisciplinary Research: Bridging multiple academic domains, including economics, business, technology, management, and political science, to address complex global challenges. Ensuring the Dissemination of Research: We take responsibility for bringing the research of scientists to a broader stage, making them as visible and accessible as possible to global scientific communities. The journal covers a wide range of topics, including but not limited to the following areas: Globalization and the Economic Policy of States Education, Innovation, and the Knowledge Economy Digital Development and Technological Transformation Business Management and Marketing Global Labor Markets and Human Resource Management Tourism in the Context of Globalization Political Science and International Relations Migration, Demographic Changes, Family Structures, and Social Transformations Gender Equality, Social Justice and Intercultural Dynamics in the Context of Globalization Environmental and Sustainable Development
SCIENTIFIC RESEARCH INSTITUTE OF ECONOMIC AND SOCIAL ISSUES OF GLOBALIZATION
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>.
Copyright (c) 2025 https://creativecommons.org/licenses/by-sa/4.0/
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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[81] US Energy Information Administration. (2019, January 7). [82] CRS. (2021). p. 22 [83] CRS, (2022). [84] US Energy Information Administration, (2020). [85] CRS, (2022). [86] International Business Times News. (2022, March 31). Exclusive-Venezuela’s PDVSA Seeks Oil Tankers in Anticipation of US Sanctions Easing. [87] Jaffe, A. M. (2018, January 23). How Much Worse Can It Get for Venezuela’s State Oil Firm PDVSA? Council on Foreign Relations. Available at: <https://www.cfr.org/blog/how-much-worse-can-it-get-venezuelas-state-oil-firm-pdvsa>. [88] CRS, (2021), p. 11. [89] CRS, (2021), p. 13. [90] Vizcaino, M. E., Yapur, N. (2022, March 8). Defaulted Venezuela Bonds Are Luring Buyers Betting on US Deal. Bloomberg. [91] Krauss, C. (2018, October 1). Venezuela’s Crisis Imperils Citgo, Its American ‘Cash Cow’. New York Times. [92] Garip, P. (2021, August 12). Venezuela Negotiating Agenda in Crosscurrent. Argus Media. [93] De La Cruz, A. (2020, April 10). [94] Sigalos, M. (2019, February 7). China and Russia loaned billions to Venezuela — and then the presidency went up for grabs. CNBC. [95] Garcia, I. (2021, December 22). The Future of the Sino-Venezuelan Relationship: Make or Break? Harvard International Review. [96] Parraga, M., Spetalnick, M. (2022, June 6). U.S. to let Eni, Repsol ship Venezuela oil to Europe for debt. Reuters. [97] Palacios, L., Monaldi F. (2022, March 23). Venezuela Oil Sanctions: Not an Easy Fix Available at: <https://www.energypolicy.columbia.edu/research/commentary/venezuela-oil-sanctions-not-easy-fix#_edn6>. [98] US Energy Information Administration, (2020). [99] Pons, C. (2018, September 10). Exclusive: Venezuela signs oil deals similar to ones rolled back under Chavez – document. Reuters. [100] Berg, R. (2021, October 12). The Role of the Oil Sector in Venezuela’s Environmental Degradation and Economic Rebuilding. 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Unveiling new insights about the influence of oil prices on GDP in OAPEC nations: MMQR investigation
Employing the methodology of moments quantile regression with fixed effects (MM-QR), this research examines the influence of variations in oil prices on economic development within Arab oil-exporting nations that are affiliated with the Organisation of Arab Petroleum Exporting Countries (OAPEC). Comprehensive data from 1990 to 2021 for eleven OAPEC member countries are analyzed. The empirical findings derived from the analysis reveal a significant and positively correlated association between the fluctuations in oil prices and economic growth, particularly when examined within the context of nations exhibiting higher Gross Domestic Product (GDP) quantiles, which suggests that countries possessing elevated GDP levels tend to derive greater economic advantages from increases in oil prices. Nevertheless, it is noteworthy that the impact of this correlation diminishes considerably for countries situated within the lower GDP quantiles. Additionally, population growth positively affects GDP but exhibits diminishing returns over time, while exchange rate fluctuations show negligible impact on overall economic stability and growth. Keywords: Oil price fluctuations, GDP, method of moments quantile regression, population, OAPEC. Introduction Strong turbulences marked by abrupt variations in oil prices have rocked the global oil market during the past few decades. The times of highest oil price volatility were 1973, 1979, 2008, and 2020, which followed the 2019–2020 coronavirus epidemic. Because the US has run out of storage space, the West Texas Intermediate futures crude oil price saw negative trading for the first time in April 2020. The global oil market’s past indicates that macroeconomic success and fluctuations in oil prices have historically been closely correlated. Both nations that import oil and nations that export oil may experience economic instability as a result of oil shocks. Furthermore, in some oil-dependent economies, sudden and severe swings in oil prices may be the cause of financial and economic crises. Since it can have an impact on producers, governments, and consumers, the volatility of global oil prices and how it affects macroeconomic performance have become more of an issue for economies.[1] For centuries, oil has pulsated through the veins of the Arab world, fueling not only its cars and industries but also its societies and political landscapes. The OAPEC members have witnessed an intricate and influential interaction between their oil wealth and economic fortunes. This relationship dances to the rhythm of the up-and-down nature of oil prices, a volatile melody that can uplift economies to soaring heights or plunge them into the abyss of stagnation. Hence, this investigation endeavors to enhance the existing literature in twofold. Initially, this paper measures the influence of fluctuations in oil prices on the trajectory of economic expansion in Arab nations that export oil. This involves analyzing historical data to identify patterns and correlations between oil prices and economic indicators such as Gross Domestic Product growth. The choice of these nations is according to its importance in the oil market since they contain leader countries such as Saudi Arabia, Iraq, Libya and Algeria. Second, for the first time, this analysis uses the modern MMQR procedure to allow us to track the effect of oil prices on several quantiles of GDP. This procedure will help us to determine and estimate what role oil prices play in low, medium and high GDP levels among the nations of the study. Literature Review The oscillations observed in oil prices exert significant ramifications on economic development within Arab nations, especially those that exhibit a pronounced dependence on oil exports. The link between oil price variations and GDP growth is complicated and varied, impacted by different economic, political, and social factors. To begin with, real GDP in the GCC countries, which include Saudi Arabia, Bahrain, Qatar, Kuwait, United Arab Emirates, and Oman, reacts asymmetrically to oil price changes, specifically, positive oil price shocks exert a more pronounced positive influence on GDP than negative shocks. This asymmetry suggests that while rising oil prices can stimulate economic activity, falling prices may not have an equally detrimental effect, particularly in nations like Kuwait and Qatar, where the negative impacts of price declines are more pronounced.[2] Moreover, the interconnectedness of oil prices, electricity consumption, and GDP in the GCC region further complicates this relationship. The petroleum sector constitutes the essential foundation of the economies in these countries, accounting for a substantial proportion of the Gross Domestic Product (GDP). Consequently, fluctuations in oil prices possess the capacity to trigger significant modifications in governmental revenue streams, which in turn affect public spending and investment endeavors. This cyclical interdependence engenders a situation wherein elevated oil prices may result in augmented government spending on infrastructure and social initiatives, thus facilitating economic development.[3] However, the fluctuations inherent in oil prices may concurrently generate a degree of unpredictability within the economic landscape, potentially impeding both investment activities and the formulation of economic strategies. Oil price shocks explain a significant portion of the variation in governmental income and gross domestic product within the Sultanate of Oman, indicating that fluctuations can lead to budgetary constraints during periods of low prices. This volatility can create a challenging environment for policymakers, as they must navigate the impacts of fluctuating revenues on fiscal policy and economic stability.[4] In addition to direct impacts on GDP, oil price volatility can also influence inflation rates and the overall economic climate. Oil shocks can lead to inflationary pressures, which can further complicate economic growth. In nations that derive substantial revenue from oil exports, escalating oil prices may result in heightened production costs, which may be passed on to consumers, thereby affecting consumption and investment decisions. This inflationary effect can dampen the positive impacts of rising oil prices on GDP growth.[5] Furthermore, the historical context of oil price shocks provides insight into their long-term effects on economic growth. The twin oil crises of the 1970s, resulted in significant economic transformations in Gulf oil exporters, as they utilized their increased revenues to invest in foreign aid and domestic development. This historical perspective underscores the potential for both beneficial and adverse outcomes stemming from oil price fluctuations, depending on how governments choose to manage their oil revenues.[6] The situation in Iraq exemplifies an additional aspect of the repercussions of oil price fluctuations on economic development. Rodhan’s research indicates that although elevated oil prices typically exert a beneficial influence on gross domestic product, the ramifications of decreasing prices are significantly more acute in nations such as Kuwait and Qatar, suggesting that the economic resilience of these nations is closely tied to their oil revenue stability.[7] An other study analysed the level of dependency between petroleum prices and the expansion of economic activity in four member states of OPEC during the timeframe spanning from September 3, 2000, to December 3, 2010. The study results indicate that fluctuations in oil prices during times of global economic fluctuations and financial instability impact the correlation between oil and economic development in OPEC nations.[8] Research has examined the significant influence of fluctuations in crude oil prices and their volatility on the economic expansion of countries in the MENA region. Additionally, the researcher examined the bidirectional and fluctuating correlation between economic development and oil prices. In addition, a distinct study was carried out for each MENA country that exports oil and each country that imports oil. The study employed a panel quantile regression methodology using alternative linear models. The research findings revealed that fluctuations and volatility of oil prices have differing impacts on countries that export and import oil. Across various quantiles, the effects of oil price variations and the level of uncertainty associated with them differed.[9] In conclusion, the influence of fluctuations in oil prices on the economic advancement of Arab countries is characterized by a complex interplay of positive and negative effects. While increasing oil prices may invigorate economic expansion and government revenues, volatility introduces uncertainty that can hinder investment and fiscal planning. The historical context and the specific economic structures of these nations further influence how they respond to fluctuations in oil prices. As such, there is a critical need for these countries to pursue economic diversification strategies to reduce their dependence on oil revenues and enhance their resilience to price shocks. 2.2. Data Table 1 provides an overview of the various variables, while Table 2 describes statistics for the sample. Table 1: Variable Description Table 2: Descriptive statistics Source: EViews 12 program output According to the data presented in Table 2, the skewness values for three variables (GDP, POP, and EXR) are negative and significantly different from zero, indicating a pronounced left skewness. The Skewness value for the variable OILP is close to zero, but its Kurtosis value is far from three. The Jarque-Bera statistical test unequivocally rejects the null hypothesis of normality, providing further confirmation that using OLS estimation will be unreliable, while adopting quantile regression is more appropriate and resilient for this investigation. Empirical Results 3.1. Correlation matrix / Variance inflation factor: Table 3: Correlation matrix - Variance inflation factor Source: STATA 17 program output Table 3 displays the correlation coefficients between the different variables, along with the findings of the variance inflation factor. The absolute values of all correlation coefficients between independent variables are below 0.7. The VIF test findings demonstrate that there is no multicollinearity among the independent variables, as the average value of 1.39 is below 5. The VIF findings support our perspective of including OILP, POP, and EXR in the same model. 3.2. Slope homogeneity test: Table 4: Slope homogeneity test results: Source: STATA 17 program output Before continuing, it is essential to perform a crucial test to verify the accuracy of the Slope homogeneity hypothesis for the provided data. Therefore, we will utilise two tests for analysis: (Pesaran & Yamagata, 2008)[15] and (Blomquist & Westerlund, 2013).[16] The findings delineated in Table 4 demonstrate the rejection of the null hypothesis of uniformity in the slope across different nations. Thus, it is crucial to take into account the limitations imposed by variability on the slope to guarantee reliable outcomes in estimating techniques. 3.3. Cross-section dependence tests Table 5: Cross-section dependence test results: *** Indicates the null hypothesis being rejected with a significance level of 1% Source: EViews 12 program output We utilize four distinct examinations: the Breusch-Pagan LM (BP) test suggested by (Breusch & Pagan, 1980),[17] the Pesaran Scaled LM (PS) test presented by (Pesaran M. , 2004),[18] the Bias corrected scaled LM (BCS) test proposed by (Baltagi et al., 2012)[19] and the Pesaran CD (PE) test (Pesaran, 2007)[20] The findings showed that the null hypothesis of “no CSD” is not accepted, they unequivocally affirm that any shock impacting a variable in one country would propagate its impact to the same variable in other nations. 3.4. MM-QR results and discussion: Table 6: The findings of the MMQR approach Notes: The symbols ***, **, and * represent statistical significance at the 1%, 5%, and 10% levels, respectively. Source: STATA 17 program output The findings of MM-QR across different quantiles have flourished in Table 6; the coefficient related to OILP is positive, significant and gradually increased from 0.2 to 0.9 quantiles and remains insignificant for the first quantile. Notably, this outcome is in line with findings for GCC members. [21] This heterogeneous impact across income levels is likely driven by several factors. MM-QR allows us to isolate these dynamics by revealing how oil price changes differentially affect various quantiles of the GDP distribution. The results indicate that as GDP increases from the 0.2 to the 0.9 quantiles, the impact of oil price fluctuations becomes stronger and more positive. This means that countries with higher GDP tend to benefit more from increases in oil prices in terms of economic growth. The insignificance of the coefficient for the lowest GDP quantile indicates that changes in oil prices have a minimal impact on the poorest sectors of the economy. This might be because they’re not as connected to global markets or rely more on industries other than oil for their economy. This outcome can be attributed to the fact that high-income countries (those with elevated GDP levels) benefit from a more robust economy through strategic investment projects yielding substantial economic returns. Nations such as Saudi Arabia, Qatar, and the UAE, when experiencing a rise in oil prices, acquire additional revenue that is subsequently channeled into local investments. This process directly and significantly impacts economic growth. Conversely, countries with lower GDP levels are characterized by limited and weak investment opportunities. In these nations, oil revenues are primarily allocated towards bolstering infrastructure and funding social expenditures, which do not contribute as substantially to economic growth. Population has a positive and significant impact on GDP and decreases gradually from the low to high quantiles confirming prior findings.[22] Accordingly, this outcome can be explained by the fact that when the population grows further, resources like land, infrastructure, and skilled labor might become relatively scarce, leading to diminishing marginal returns from additional population growth. This could explain the decreasing effect in higher quantiles. The effect of exchange rate for local currency on GDP is negative but insignificant across all quantiles, which aligns with previous research.[23] The insignificant effects could be explained by the fact that a substantial portion of oil exports from these nations are denominated in US dollars, meaning they receive a fixed income regardless of their local currency’s exchange rate. This reduces the direct impact of fluctuations on overall GDP. Conclusion In summary, our paper gives us a clearer picture of how oil prices affect the economies of Arab countries that export oil. The study’s duration was from 1990 to 2021 using a special analysis method called Moment of Quantile Regression (MM-QR). Our results support what we suspected: there’s a strong and positive connection between oil prices and economic growth in these countries. But what’s interesting is that this connection isn’t the same for everyone. We found that as a country’s wealth (measured by GDP) goes up, the impact of oil prices on its economic growth gets stronger. However, for the poorest parts of these countries, the impact is much smaller. This suggests that poorer areas might not be as affected by changes in oil prices, perhaps because they’re not as connected to the global economy or they rely more on industries other than oil. We also looked at how population growth and changes in exchange rates affect economic output. It turns out that while a growing population initially boosts economic growth, the effect decreases as a country becomes wealthier. This tells us that the correlation between population and economic growth is significantly more complicated than it seems. Similarly, changes in exchange rates don’t seem to have a big impact on overall economic output, likely because these countries mostly trade oil in foreign currencies. Recommendations: According to our research, we may provide some suggestions: Leaders should prioritise diversifying their sources of revenue, particularly in economically disadvantaged regions, to reduce their reliance on oil revenues and enhance their ability to rebound from challenging circumstances; Make strong plans to handle changes in money value, like saving money and being careful with spending, to protect against sudden changes in how much money is worth. Spend time and money learning about how money and economies work better, so we can make smart plans for when oil prices go up and down and keep our economies strong in the long term. Bibliography: Al Jabri, S., Raghavan, M., Vespignani, J. (2022). Oil prices and fiscal policy in an oil-exporter country: Empirical evidence from Oman. Energy Economics, 111(106103). Doi: <https://doi.org/10.1016/j.eneco.2022.106103>; Ayad, H., Ben-Salha, O., Ouafi, M. (2023). Do oil prices predict the exchange rate in Algeria? Time, frequency, and time‐varying Granger causality analysis. Economic Change and Restructuring, 56(5). Doi: <https://doi.org/10.1007/s10644-023-09545-1>; Baltagi, B., Feng, Q., Kao, C. (2012). A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model. Journal of Econometrics, 170(1). Doi: <https://doi.org/10.1016/j.jeconom.2012.04.004>; Benlaria, H., Almawishir, N. (2024). 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Doi: <https://doi.org/10.32479/ijeep.15681>; Werker, E., Ahmed, F., Cohen, C. (2009). How Is Foreign Aid Spent? Evidence from a Natural Experiment. American Economic Journal: Macroeconomics, 1(2). Doi: <10.1257/mac.1.2.225>; Zmami, M., Ben Salha, O. (2020). Oil price and the economic activity in GCC countries: Evidence from quantile regression. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(4). Doi: <https://doi.org/10.24136/eq.2020.028>. Footnotes [1] Marimoutou, V., Raggad, B., Trabelsi, A. (2009). Extreme Value Theory and Value at Risk: Application to oil market. Energy Economics, 31(4), pp. 519-530. Doi: <https://doi.org/10.1016/j.eneco.2009.02.005>. [2] Zmami, M., Ben Salha, O. (2020). Oil price and the economic activity in GCC countries: Evidence from quantile regression. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(4), pp. 651-673. Doi: <https://doi.org/10.24136/eq.2020.028>. [3] Benlaria, H., Almawishir, N. (2024). The Relationship between Electricity Consumption, Price of Oils, and Gross Domestic Product in the Gulf Cooperation Council Countries. International Journal of Energy Economics and Policy, 14(1), pp. 66-75. Doi: <https://doi.org/10.32479/ijeep.15108>. [4] Al Jabri, S., Raghavan, M., Vespignani, J. (2022). Oil prices and fiscal policy in an oil-exporter country: Empirical evidence from Oman. Energy Economics, 111(106103). Doi: <https://doi.org/10.1016/j.eneco.2022.106103>. [5] Gómez-Loscos, A., Gadea, M., Montañés, A. (2012). Economic growth, inflation and oil shocks: are the 1970s coming back? Applied Economics, 44(35), pp. 4575-4589. Doi: <https://doi.org/10.1080/00036846.2011.591741>. [6] Werker, E., Ahmed, F., Cohen, C. (2009). How Is Foreign Aid Spent? Evidence from a Natural Experiment. American Economic Journal: Macroeconomics, 1(2): 225-44. Doi: <10.1257/mac.1.2.225>. [7] Rodhan, M. (2024). Macroeconomic impacts of oil price shocks: evidence from Iraq by using vector autoregressive model. International Journal of Energy Economics and Policy, 14(3), pp. 162-170. Doi: <https://doi.org/10.32479/ijeep.15681>. [8] Ftiti, Z., Guesmi, K., Teulon, F., Chouachi, S. (2016). Relationship between crude oil prices and economic growth in selected OPEC countries. The Journal of Applied Business Research, 32(1), pp. 11-22. Doi: <http://dx.doi.org/10.19030/jabr.v32i1.9483>. [9] Mamdouh, A. (2023). Oil price fluctuations and economic growth: the case of MENA countries. Review of Economics and Political Science, 8(5), pp. 353-379. Doi: <http://dx.doi.org/10.1108/REPS-12-2019-0162>. [10] Machado, J., Silva, J. (2019). Quantiles via moments. Journal of Econometrics, 213(1), pp. 145-173. Doi: <https://doi.org/10.1016/j.jeconom.2019.04.009>. [11] Koenker, R., & Bassett, Jr., G. (1978). Regression Quantiles. Econometrica, 46(1), pp. 33-50. Doi: <10.2307/1913643>. [12] Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), pp. 74-89. Doi: <https://doi.org/10.1016/j.jmva.2004.05.006>. [13] Canay, I. (2011). A simple approach to quantile regression for panel data. The Econometrics Journal, 14(3), pp. 368-386. Doi: <https://doi.org/10.1111/j.1368-423X.2011.00349.x>. [14] Machado, J., & Silva, J. (2019). Quantiles via moments. Journal of Econometrics, 213(1), pp. 145-173. Doi: <https://doi.org/10.1016/j.jeconom.2019.04.009>. [15] Pesaran, M., Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), pp. 50-93. Doi: <http://dx.doi.org/10.2139/ssrn.671050>. [16] Blomquist, J., Westerlund, J. (2013). Testing slope homogeneity in large panels with serial correlation. Economics Letters, 121(3), pp. 374-378. Doi: <https://doi.org/10.1016/j.econlet.2013.09.012>. [17] Breusch, T., Pagan, A. (1980). The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics. The Review of Economic Studies, 47(1), pp. 239-253. Doi: <https://doi.org/10.2307/2297111>. [18] Pesaran, M. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. Cambridge Working Papers in Economics No. 0435, Faculty of Economics, University of Cambridge. [19] Baltagi, B., Feng, Q., Kao, C. (2012). A Lagrange Multiplier test for cross-sectional dependence in a fixed effects panel data model. Journal of Econometrics, 170(1), pp. 164-177. Doi: <https://doi.org/10.1016/j.jeconom.2012.04.004>. [20] Pesaran, M. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of applied econometrics, 22(2), pp. 265-312. Doi: <http://dx.doi.org/10.1002/jae.951>. [21] Zmami, M., Ben Salha, O. (2020). Oil price and the economic activity in GCC countries: Evidence from quantile regression. Equilibrium. Quarterly Journal of Economics and Economic Policy, 15(4), pp. 651-673. Doi: <https://doi.org/10.24136/eq.2020.028>. [22] Maestas, N., Mullen, K., Powell, D. (2023). The Effect of Population Aging on Economic Growth, the Labor Force, and Productivity. American Economic Journal: Macroeconomics, 15(2): 306-32. Doi: <10.1257/mac.20190196>. [23] Ayad, H., Ben-Salha, O., Ouafi, M. (2023). Do oil prices predict the exchange rate in Algeria? Time, frequency, and time‐varying Granger causality analysis. Economic Change and Restructuring, 56(5), pp. 3545-3566. Doi: <https://doi.org/10.1007/s10644-023-09545-1>.
Balancing Innovation and Risk: Regulatory Frameworks for Sustainable Fintech Growth
This paper investigates the transformative impact of Financial Technology (FinTech) and Artificial Intelligence (AI) on the global financial sector, moving beyond a descriptive overview to critically examine the challenges and opportunities they present. The study synthesizes a comprehensive review of empirical data, policy documents, and industry reports, including the EY Global FinTech Adoption Index (2023) and World Bank reports (2023), to analyze FinTech adoption across diverse regions and financial service categories. The research identifies key challenges related to electronic financial transactions, including cross-border complexities, decentralized systems, and cybersecurity risks. Furthermore, it addresses the crucial need for adaptable regulatory frameworks that balance innovation with financial stability and consumer protection. Findings reveal significant disparities in FinTech adoption globally, driven by factors such as technological infrastructure, regulatory environments, and socio-economic conditions. The study highlights the potential systemic risks associated with FinTech investments and underscores the importance of international cooperation in addressing cross-border challenges. By providing a holistic perspective that integrates technological, economic, ethical, and regulatory dimensions, this paper contributes to a more nuanced understanding of the dynamic interplay between technology and finance. It offers actionable recommendations for policymakers, industry practitioners, and academics seeking to foster responsible innovation and ensure the long-term resilience of the global financial system. Future research directions are proposed, including evaluating the effectiveness of different regulatory approaches, exploring the ethical dimensions of AI in finance, and conducting longitudinal studies to assess the long-term impacts of FinTech on financial stability and consumer welfare. Keywords: FinTech, artificial intelligence (AI), financial regulation, financial stability, digital finance. JEL Codes: G20 – G23 – O30 – O33. Introduction The global financial landscape is undergoing a radical transformation, spurred by the accelerating convergence of financial technology (FinTech) and artificial intelligence (AI). This technological revolution transcends simple digitization, fundamentally reshaping established business models and redefining the core functionalities of banking, investment management, and financial transactions. While the proliferation of digital banking services, enhanced by innovations such as real-time payment systems, AI-driven identity verification mechanisms, and round-the-clock chatbot support,[1] has undeniably enhanced customer experiences and improved operational efficiency, it simultaneously raises critical and complex questions. These include concerns regarding equitable financial inclusion, the potential for increased systemic risk, and the imperative of developing adaptive regulatory frameworks to govern these rapidly evolving technologies. Existing research, although valuable, often examines these issues in isolation, failing to capture the intricate interdependencies that characterize the modern FinTech ecosystem. This paper offers a comprehensive examination of the multi-layered impact of FinTech and AI on the financial sector. Moving beyond a descriptive overview, it provides a rigorous analysis of the primary challenges and opportunities these technologies present. The study leverages a comprehensive review of the most recent empirical data, relevant policy documents, and insightful industry reports, including crucial data from the EY Global FinTech Adoption Index (2023) and pertinent World Bank reports (2023). This data-driven approach allows for a detailed assessment of the factors driving FinTech adoption across diverse geographical regions and within specific financial service categories. Special attention is given to understanding the disparities in adoption rates across developed and developing economies, acknowledging the unique contextual factors that shape the FinTech landscape in each region. Further, the study explores the ethical dimensions of AI in finance, including biases in algorithms and the potential for discriminatory outcomes. A significant aspect of this research addresses the pressing need for adaptable and effective regulatory frameworks. In this regard, the study undertakes a detailed analysis of the characteristics, associated challenges, and necessary regulatory adaptations related to electronic financial transactions. It delves into the complexities arising from the cross-border nature of these transactions, the decentralization facilitated by blockchain technologies, and the ever-present threat of cybersecurity risks. Moreover, it explores the role of international organizations in establishing global standards and promoting cooperation among regulatory bodies, underscoring the necessity for a coordinated approach to FinTech regulation. The paper emphasizes the crucial balance that must be struck between fostering innovation and safeguarding financial stability, ensuring consumer protection, and promoting ethical behavior in the digital finance space. It challenges the notion that regulation inherently stifles innovation, arguing instead that well-designed regulatory frameworks can create a stable and trustworthy environment that encourages sustainable growth and development in the FinTech sector. In contrast to existing literature, which often compartmentalizes the analysis of FinTech, this study offers a uniquely holistic perspective that integrates technological, economic, ethical, and regulatory dimensions. By synthesizing diverse strands of research and drawing on a rich dataset, this research provides a more nuanced and comprehensive understanding of the complex dynamics shaping the future of finance. Addressing a gap in the current body of research, this research not only examines the growth in global FinTech investments from 2018 to 2023 but also rigorously analyzes how sector investments influence sector stability and systemic risks. The study’s findings are geared towards informing evidence-based policy and promoting responsible innovation in the FinTech arena. The paper seeks to answer the following overarching research questions: (1) How does the geographic distribution of FinTech adoption vary globally, and what are the key technological, economic, social, and political drivers behind these disparities? (2) What are the principal challenges posed by electronic financial transactions, particularly in relation to cross-border activities, decentralization, and cybersecurity, and how can these challenges be effectively mitigated through regulatory and technological innovations? (3) How can regulatory frameworks best balance the promotion of FinTech innovation with the imperative of ensuring financial stability, consumer protection, and ethical behavior, and what are the key principles that should guide the development of such frameworks? By providing robust empirical analysis and nuanced policy recommendations, this study aims to contribute to a more comprehensive and insightful understanding of the transformative potential and inherent challenges of FinTech and AI in shaping the financial sector’s future. The insights gleaned from this research will be highly valuable to academics conducting cutting-edge research, policymakers grappling with complex regulatory challenges, industry practitioners seeking to navigate the evolving FinTech landscape, and anyone with a keen interest in the intricate interplay between technology and finance in the 21st century. Ultimately, the research aspires to contribute to the development of a more inclusive, efficient, and resilient financial system that benefits all stakeholders. Literature Review The Impact of Fintech and Artificial Intelligence on the Financial Sector The financial sector has undergone significant transformations in recent years due to innovations in financial technology (Fintech) and artificial intelligence (AI), which have profoundly influenced how banking services, investment management, and financial transactions are conducted. Digital banking services provide a clear example of this transformation, allowing customers to manage most of their banking needs remotely without visiting physical branches. Advanced technologies, such as real-time money transfers, online account opening, identity verification technologies like facial recognition or fingerprint scanning, and 24/7 chatbot services, have enabled banks to significantly enhance customer experience and operational efficiency.[2] This shift, reflecting the increasing global adoption of Fintech, can be understood through a global heat map illustrating the levels of Fintech penetration in various countries. Regions depicted in warm colors, such as China and India, indicate high rates of Fintech adoption, particularly in areas like electronic payments and online lending. In contrast, other regions appear in cooler tones, signifying lower levels of Fintech adoption. The impacts of technological innovation, demographics, and government policies play a critical role in determining the rates of Fintech penetration. Countries with robust technological infrastructure, such as the United States and the United Kingdom, report high adoption rates, whereas some developing countries, such as Brazil and India, also exhibit high adoption rates due to the need to address the demands of the unbanked population.[3] Figure N°1: Global Heat Map of Fintech Penetration Source: EY Global FinTech Adoption Index 2023. Available at: <https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/banking-and-capital-markets/ey-global-fintech-adoption-index.pdf> Asia leads prominently in the adoption of financial technology, driven by the rapid growth of startups in China and India. In Europe, countries such as the United Kingdom and Sweden exhibit high adoption rates, benefiting from innovations in financial sectors. In contrast, Latin America and Africa, despite noticeable growth in some countries like Brazil and South Africa, still face relatively low adoption rates due to challenges related to infrastructure.[4] The leading sectors in Fintech include electronic payments and online lending, where startups are striving to provide innovative and unconventional solutions. With improvements in infrastructure and the adoption of supportive regulatory policies, regions such as Africa have the potential to experience significant growth in Fintech adoption in the future.[5] This transformation has also reshaped how individuals and businesses handle finances, with electronic payments enhancing the speed and convenience of financial transactions. These payments include the use of cryptocurrencies, such as Bitcoin and Ethereum, which offer decentralized payment methods, as well as mobile payments through services like Apple Pay and Google Pay. Furthermore, international money transfers have become more cost-effective thanks to companies like TransferWise (now Wise).[6] Robo-advisors have emerged as one of the most significant innovations in investment management, leveraging advanced algorithms to provide automated and low-cost investment services. These include dynamic asset allocation, which automatically adjusts investment portfolios in response to market changes, and complex investment strategies, such as factor investing, which were previously limited to institutional investors. Additionally, robo-advisors utilize behavioral analytics to understand investor behavior and offer personalized advice, alongside automated portfolio rebalancing to maintain target asset allocation.[7] Similarly, digital insurance has revolutionized the insurance industry by simplifying the process of purchasing and managing insurance policies and improving operational efficiency. Innovations in this field include usage-based insurance, such as car insurance based on driving habits, and automated claims processing using AI to expedite procedures. Instant insurance has also become available, allowing for the purchase of short-term policies like single-day travel insurance, along with the use of big data to enhance risk assessment accuracy.[8] Figure N°2: Comparison of Fintech Categories by Adoption Rate from 2015 to 2019 Source: EY Global FinTech Adoption Index 2019. Available at: <https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/banking-and-capital-markets/ey-global-fintech-adoption-index.pdf> The data presented highlights a significant transformation in the financial landscape between 2015 and 2019, shedding light on dynamic changes in consumer behavior and the evolution of financial services. The remarkable increase in the use of money transfers and payments, rising from 18% to 75%, reflects the widespread adoption of digital solutions, likely driven by the proliferation of smartphones and electronic payment applications. Parallel to this, the savings and investments sector experienced substantial growth from 17% to 40%, signaling heightened financial awareness and improved accessibility to digital investment tools. The notable rise in the utilization of budgeting and financial planning services (from 8% to 34%) and insurance (from 8% to 29%) indicates growing interest in personal financial health and risk management. Even the borrowing sector, although the least developed, showed a significant increase from 6% to 27%, potentially reflecting improved access to credit through digital platforms. Collectively, these trends underscore the rapid digitalization of the financial sector, emphasizing the increasing influence of financial technology (FinTech) in shaping consumer behavior and expectations. These developments also suggest a potential improvement in financial inclusion, as financial services have become more accessible to a broader segment of the population. This progress paves the way for further innovation and growth in the financial sector in the near future. These combined innovations have led to notable improvements in the financial sector by enhancing the efficiency of financial transactions through process automation and reducing the need for human intervention. This progress has contributed to cost reduction and increased market competition. Furthermore, financial services have become more accessible, particularly for financially marginalized groups in remote areas.[9] Nevertheless, these advancements come with new challenges, including cybersecurity concerns, privacy issues, and the need for modern regulatory frameworks to keep pace with these rapid changes. Therefore, technological innovation must be accompanied by robust policies and regulations to ensure the sustainability and stability of the financial sector. The Spread of FinTech and the Necessity for Regulatory Frameworks: Modern financial services are undergoing a revolutionary transformation thanks to the rapid advancement of financial technology (FinTech). This has led to the development of advanced regulatory frameworks to ensure a delicate balance between encouraging innovation, protecting consumers, and ensuring the stability of financial markets. The Payment Services Directive (PSD2) in the European Union serves as a prime example of these advancements. Introduced in 2018, this directive aims to enhance transparency and security in online financial transactions. It provides open access to banking data for licensed third parties, promotes two-factor authentication, and reduces consumer liability in cases of fraud[10]. In the United Kingdom, the Regulatory Sandbox framework provides an innovative environment where FinTech entrepreneurs can test their products and services under regulatory oversight. This approach reduces the time and cost associated with bringing innovations to market and fosters dialogue between innovators and regulators.[11] Furthermore, advancements in cryptocurrencies and digital assets necessitate updates to anti-money laundering and counter-terrorist financing (AML/CFT) laws. The “Know Your Customer” (KYC) principle is now being applied to cryptocurrency trading platforms, with requirements for reporting suspicious transactions by businesses operating in the digital asset space. These measures aim to combat cross-border financial crimes.[12] In the United States, the Financial Innovation Act promotes innovation while maintaining consumer protection. Meanwhile, Singapore’s FinTech regulatory framework features initiatives like “Sandbox Express” to expedite the testing of innovations.[13] Additionally, crowdfunding regulations in the European Union aim to organize crowdfunding platforms and protect investors, highlighting the importance of balancing innovation with small investor protection.[14] These regulatory advancements underscore the urgent need for flexible and effective frameworks that align with the rapid evolution of FinTech. In this context, Arner, Barberis, and Buckley emphasize that technology itself (RegTech) can play a pivotal role in improving regulatory compliance and risk management in the FinTech era.[15] Characteristics and Challenges of Electronic Financial Transactions: Amid significant transformations in the digital world, electronic financial transactions (E-transactions) have become one of the critical pillars of the global economy. However, these transactions pose various challenges rooted in their fundamental characteristics. Cross-Border Nature: E-transactions are characterized by their ability to transcend traditional geographical boundaries, creating a complex legal and regulatory environment. A single transaction may be subject to a variety of laws, potentially leading to conflicts among them, which complicates effective enforcement. For instance, determining tax jurisdiction for cross-border transactions can be challenging, as can addressing variations in consumer protection standards between countries, exposing consumers to differing levels of legal safeguards.[16] Decentralization: Blockchain technologies introduce a decentralized model for financial transactions, challenging traditional regulatory models. In this context, traditional oversight becomes difficult due to the absence of a central control point. Additionally, applying KYC principles in such systems becomes more complex, and new challenges emerge in freezing assets or reversing transactions in cases of fraud.[17] Cybersecurity Risks: With increasing reliance on technology, e-transactions are vulnerable to a wide range of cybersecurity risks. These include ransomware attacks targeting financial institutions and demanding payment to restore data, as well as advanced fraud techniques leveraging artificial intelligence (AI), which heighten the complexity of required cyber defenses.[18] Efforts by International Organizations: International organizations, such as the Financial Action Task Force (FATF), are actively working to establish global standards to address regulatory challenges in the digital age. These efforts include issuing updated recommendations to regulate virtual assets and virtual asset service providers (VASPs), along with enhancing international cooperation among regulatory bodies to ensure consistency across borders.[19] Data Privacy: As reliance on collecting and analyzing financial data grows, significant challenges arise regarding consumer privacy protection. Arner, Barberis, and Buckley highlight that FinTech introduces new dimensions to data protection, necessitating the development of regulatory frameworks that consider consumers’ rights in this context.[20] Financial Inclusion: FinTech contributes to advancing financial inclusion by expanding financial services to marginalized groups. However, these technologies can also create a new digital divide between those with access to technology and those without.[21] Regulatory Adaptation: The rapid evolution of FinTech demands the development of flexible regulatory frameworks that adapt to ongoing changes. Zetzsche, Buckley, Arner, and Barberis point out that the main challenge lies in transitioning from traditional regulatory systems to ones capable of managing data-driven finance.[22] Addressing these challenges requires a comprehensive approach that strikes a delicate balance between fostering innovation, ensuring financial stability, and protecting consumers. International cooperation among regulators and the private sector is crucial to tackling global challenges posed by e-transactions. Over time, the need for adaptable regulatory frameworks will persist to keep pace with the rapid advancements in FinTech.[23] The Impact of FinTech on Financial Sector Stability: A Comprehensive Analysis of Challenges and Opportunities The financial sector has undergone a radical transformation with the adoption of financial technology (FinTech), which has become a key tool for restructuring the global financial system. The following data illustrates global growth rates in FinTech investments from 2018 to 2023. Table: Growth in FinTech Investments from 2018 to 2023 Source: EY Global FinTech Adoption Index 2023 The table shows that investments in FinTech have experienced significant fluctuations in recent years. A major decline occurred in 2020, with a negative growth rate of -34.5%, attributed to the global economic and financial impact of the COVID-19 pandemic. However, there was a strong recovery in 2021, with a growth rate of 132.6%, driven by the rapid digital transformation necessitated by the pandemic. This momentum continued with high growth rates in subsequent years, reflecting increased confidence in FinTech’s ability to reshape the financial sector and achieve long-term gains. Research by Feyen et al. (2021) highlighted the distribution of FinTech investments across various sectors, as illustrated in the following chart: Figure N°3: Distribution of FinTech Investments by Sector Source: Feyen, E., Frost, J., Gambacorta, L., Natarajan, H. (2021). FinTech and the digital transformation of financial services: Implications for market structure and public policy. The chart reveals that digital banking services and electronic payments dominate the FinTech landscape, accounting for 65% of total investments. This dominance reflects the ongoing transformation of the financial system toward innovation and the adoption of modern technologies. Simultaneously, emerging sectors like InsurTech signify a growing diversification within FinTech, enhancing its ability to offer innovative and comprehensive solutions tailored to diverse market needs. Despite its benefits, FinTech faces significant challenges that affect financial stability. Figure N°4: Key Challenges Facing the Financial Sector Source: World Bank. (2023). “Key Challenges Facing the Global Financial Sector Amid Digital Transformation”. World Bank Report. The figure identifies key challenges, with regulatory risks being the most critical. Governments and institutions must develop flexible regulatory policies that balance fostering innovation with ensuring compliance. Cybersecurity remains a persistent concern in an increasingly complex digital environment, necessitating global collaboration to address cyberattacks and protect sensitive data. Moreover, technological adaptation poses a fundamental challenge for traditional institutions, requiring significant investments in infrastructure and cultural shifts to remain competitive. Three Main Challenges Systemic Risks: FinTech introduces new systemic risks, such as technical failures and cyberattacks. For instance, Knight Capital suffered a $440 million loss within 45 minutes due to a technical glitch in 2012.[24] Similarly, the Bangladesh Central Bank cyberattack in 2016 resulted in an $81 million theft.[25] These incidents demonstrate how technology can increase financial system fragility and expose it to significant risks. Changing Market Dynamics: The entry of BigTech companies like Google, Apple, and Amazon into the financial sector has significantly altered market dynamics. While these companies enhance competition, improving services and reducing costs for consumers,[26] their vast resources could lead to market concentration, reducing competition in the long term and increasing monopoly risks. Rapid Crisis Propagation: FinTech has accelerated the transmission of financial crises through global interconnectedness. High-frequency trading systems and advanced algorithms can quickly transmit market volatility. Additionally, social media and online trading platforms amplify the spread of news and rumors, heightening market volatility.[27] Regulatory Measures for FinTech National FinTech Regulations: By 2020, over 50 countries had developed or were developing national FinTech strategies,[28] reflecting global awareness of the need to regulate FinTech to ensure financial system stability and consumer protection. Principles for Effective Regulation Balancing Innovation and Stability: Regulatory sandboxes, such as those used by the UK’s Financial Conduct Authority,[29] allow companies to test innovative products under controlled environments. Consumer Protection: Ensuring transparency in transactions, safeguarding personal data, and increasing consumer awareness are critical to reducing risks associated with digital financial services.[30] International Cooperation: Organizations like the Financial Stability Board (FSB) play a pivotal role in coordinating global financial policies to enhance system stability.[31] Regulatory Flexibility: Adopting a principles-based regulatory approach allows flexibility and fosters innovation while maintaining oversight.[32] RegTech: The “Electronic Financial Regulation” (RegTech) represents a significant innovation in the field of financial technology, leveraging technology to enhance compliance and regulatory processes within the financial sector. RegTech aims to simplify and automate regulatory operations, thereby promoting efficiency and transparency. According to a report by Deloitte,[33] the global RegTech market is expected to grow at a compound annual growth rate (CAGR) of 21.27% between 2020 and 2025. This growth reflects the increasing demand for technological solutions that support regulatory compliance within the financial sector. Consequently, establishing regulations and principles for electronic financial systems is imperative to maximize the benefits of financial technology while mitigating associated risks. This requires a balanced approach that fosters innovation and stability, safeguards consumer rights, enhances international collaboration, and ensures the flexibility of regulatory frameworks to adapt to the rapid changes in this sector. Discussion The findings of this study provide several important insights into the impact of FinTech and AI on the financial sector. The analysis of FinTech adoption rates across different regions highlights the significant role of technological infrastructure, regulatory environments, and socio-economic factors in driving the uptake of digital financial services. The observed disparities underscore the need for tailored policy interventions that address the specific needs and challenges of each region. For instance, in developing countries, efforts to improve digital literacy and expand access to internet connectivity are crucial to promote financial inclusion and enable widespread FinTech adoption. Our examination of electronic financial transactions reveals the persistent challenges associated with cross-border activities, decentralized systems, and cybersecurity threats. The complex legal and regulatory landscape surrounding cross-border transactions requires greater international cooperation and harmonization of regulatory standards. The decentralized nature of blockchain-based systems poses unique challenges for regulatory oversight and consumer protection, necessitating innovative approaches such as the development of regulatory sandboxes and the implementation of smart contracts with embedded compliance mechanisms. The increasing sophistication of cyberattacks highlights the importance of investing in robust cybersecurity measures and fostering collaboration between financial institutions, technology providers, and law enforcement agencies to combat cybercrime. The study’s analysis of FinTech investments and their impact on financial stability sheds light on the potential systemic risks associated with the rapid growth of the FinTech sector. The increasing interconnectedness of financial institutions and FinTech companies creates new channels for the transmission of shocks and vulnerabilities. The entry of BigTech companies into the financial sector also raises concerns about market concentration and the potential for anti-competitive behavior. Effective regulatory oversight is essential to mitigate these risks and ensure that the benefits of FinTech are not outweighed by the potential for financial instability. Limitations While this study provides a comprehensive analysis of the impact of FinTech and AI on the financial sector, it is important to acknowledge its limitations. First, the study relies primarily on secondary data sources, such as industry reports, policy documents, and academic publications. While these sources provide valuable insights, they may be subject to biases or limitations in data availability. Future research should consider collecting primary data through surveys, interviews, and case studies to provide a more nuanced understanding of the impact of FinTech on different stakeholders. Second, the study focuses primarily on the impact of FinTech on the financial sector in developed countries. While the findings are relevant to developing countries as well, further research is needed to examine the specific challenges and opportunities facing these countries in the context of FinTech. Factors such as limited access to technology, weak regulatory frameworks, and high levels of financial exclusion may significantly influence the impact of FinTech in developing countries. Third, the study does not fully account for the dynamic and rapidly evolving nature of the FinTech landscape. The pace of technological innovation is accelerating, and new business models and regulatory challenges are constantly emerging. Future research should adopt a more agile and forward-looking approach to capture the dynamic nature of the FinTech sector and anticipate future trends and challenges. Finally, the study does not provide a comprehensive analysis of the ethical implications of FinTech and AI. The use of algorithms and data-driven decision-making in finance raises important ethical concerns about fairness, transparency, and accountability. Future research should explore these ethical dimensions in greater detail and develop frameworks for responsible innovation in the FinTech sector. This includes considering the potential for algorithmic bias, the need for data privacy and security, and the importance of ensuring that FinTech solutions are accessible and beneficial to all members of society. Acknowledging these limitations provides a balanced perspective and reinforces the value of the study while paving the way for future research. It demonstrates intellectual honesty and strengthens the credibility of the work. Conclusion This study has provided a comprehensive analysis of the multifaceted impact of FinTech and AI on the global financial sector, moving beyond a descriptive overview to identify key challenges, opportunities, and the critical role of regulatory frameworks in shaping the future of finance. Our analysis reveals that the rapid adoption of FinTech, while driving efficiency and expanding access to financial services, also introduces novel systemic risks and necessitates adaptable regulatory approaches. The geographic disparities in FinTech adoption highlight the importance of considering local contexts, technological infrastructure, and socio-economic conditions when formulating policy interventions. Specifically, our examination of electronic financial transactions underscores the persistent challenges posed by cross-border activities, decentralized systems, and cybersecurity threats. The increasing reliance on complex algorithms and data-driven decision-making in FinTech necessitates a renewed focus on transparency, accountability, and ethical considerations. The study findings suggest that effective regulatory frameworks must strike a delicate balance between fostering innovation and safeguarding financial stability, protecting consumers from potential harms, and promoting fair competition in the market. These frameworks should embrace a principles-based approach that allows for flexibility and adaptability, enabling them to keep pace with the rapidly evolving technological landscape. Furthermore, international cooperation is essential to address the cross-border challenges inherent in FinTech and to prevent regulatory arbitrage. The research highlights the crucial role of RegTech in enhancing regulatory compliance and risk management within the FinTech ecosystem. Investing in technological solutions that automate regulatory processes and improve data collection and analysis can significantly improve the efficiency and effectiveness of regulatory oversight. Additionally, fostering a culture of collaboration between regulators, industry stakeholders, and technology providers is essential to developing innovative RegTech solutions that meet the evolving needs of the financial sector. Ultimately, this study contributes to a more nuanced understanding of the transformative potential and inherent challenges of FinTech and AI in shaping the future of finance. The insights gleaned from this research have significant implications for policymakers, industry practitioners, and academics alike. By providing a robust empirical analysis and actionable recommendations, this work aims to inform the development of evidence-based policies that promote responsible innovation, enhance financial inclusion, and ensure the long-term stability and resilience of the global financial system. Future research should focus on evaluating the effectiveness of different regulatory approaches in promoting FinTech innovation while mitigating risks and exploring the ethical dimensions of AI in finance. Further, there is a need for longitudinal studies that track the long-term impacts of FinTech on financial stability, consumer welfare, and market competition. Only through a continued commitment to rigorous research and informed policymaking can we harness the full potential of FinTech to create a more inclusive, efficient, and resilient financial system for all. Bibliography: Arner, D. W., Barberis, J., Buckley, R. P. (2016). FinTech, RegTech, and the reconceptualization of financial regulation. 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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). 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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. Organizational Behavior and Human Decision Processes, 86(2), pp. 278–321. [93] 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. [94] Salam, A. (2020). Organizational justice as a predictor of organizational citizenship behaviour. International Business Education Journal, 13, pp. 29–42. [95] Boateng, F. D., Hsieh, M. L. (2019). Explaining Job Satisfaction and Commitment Among Prison Officers: The Role of Organizational Justice. Prison Journal, 99(2), pp. 172–193. [96] Estreder, Y., Tomás, I., Chambel, M. J., Ramos, J. (2019). Psychological contract and attitudinal outcomes: multilevel mediation model. Personnel Review, 48(7), pp. 1685–1700. [97] 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. [98] 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. [99] 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. [100] Karem, M. A., Mahmood, Y. N., Jameel, A. S., Ahmad, A. R. (2019). The Effect of Job Satisfaction and Organizational Commitment on Nurses’ Performance. Humanities and Social Sciences Reviews, 7(6), pp. 332–339. [101] 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. [102] Kumar Piaralal, N., Mat, N., Kumar Piaralal, S., Awais Bhatti, M. (2014). Human resource management factors and service recovery performance in Malaysian life insurance industry. European Journal of Training and Development, 38(6), pp. 524–552. [103] Arasanmi, C. N., Krishna, A. (2019). Employer branding: perceived organisational support and employee retention – the mediating role of organisational commitment. Industrial and Commercial Training, 51(3), pp. 174–183. [104] 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. [105] Swalhi, A., Zgoulli, S., Hofaidhllaoui, M. (2017). The influence of organizational justice on job performance. Journal of Management Development, 36(4), pp. 542–559. [106] Murdayanti, Y., Indriani, S., Umaimah, W. (2020). Determinants of participative budgeting and its implication on managerial performance. Accounting, pp. 1305–1312 [107] 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. [108] 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). [109] Arasanmi, C. N., Krishna, A. (2019). Employer branding: perceived organisational support and employee retention – the mediating role of organisational commitment. Industrial and Commercial Training, 51(3), pp. 174–183. [110] Swalhi, A., Zgoulli, S., Hofaidhllaoui, M. (2017). The influence of organizational justice on job performance. Journal of Management Development, 36(4), pp. 542–559. [111] Garg, N. (2017). Workplace Spirituality and Organizational Performance in Indian Context: Mediating Effect of Organizational Commitment, Work Motivation and Employee Engagement. South Asian Journal of Human Resources Management, 4(2), pp. 191–211. [112] 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. [113] Ringle, C. M., Wende, S., Becker, J.-M. (2015). SmartPLS 3. Boenningstedt: SmartPLS GmbH. [114] Hair, J. F., Risher, J. J., Sarstedt, M., Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), pp. 2–24. [115] Herath, T., Rao, H. R. (2009). Encouraging information security behaviors in organizations: Role of penalties, pressures and perceived effectiveness. Decision Support Systems, 47(2), pp. 154–165. [116] Hair, J. F., Risher, J. J., Sarstedt, M., Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), pp. 2–24. [117] Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), pp. 2–24. [118] Fornell, C., Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), p. 39. [119] Henseler, J., Ringle, C. M., Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), pp. 115–135. [120] Hair, J. F., Risher, J. J., Sarstedt, M., Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), pp. 2–24. [121] Ibid. [122] Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Academic press. [123] Hair, J. F., Risher, J. J., Sarstedt, M., Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), pp. 2–24. [124] Arab, H. R., Atan, T. (2018). Organizational justice and work outcomes in the Kurdistan Region of Iraq. Management Decision. [125] 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. [126] 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. [127] Boateng, F. D., Hsieh, M. L. (2019). Explaining Job Satisfaction and Commitment Among Prison Officers: The Role of Organizational Justice. Prison Journal, 99(2), pp. 172–193. [128] Estreder, Y., Tomás, I., Chambel, M. J., Ramos, J. (2019). Psychological contract and attitudinal outcomes: multilevel mediation model. Personnel Review, 48(7), pp. 1685–1700. [129] Khaola, P., Coldwell, D. (2019). Explaining how leadership and justice influence employee innovative behaviours. European Journal of Innovation Management, 22(1), pp. 193–212. [130] 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. [131] 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. [132] Arasanmi, C. N., Krishna, A. (2019). Employer branding: perceived organisational support and employee retention – the mediating role of organisational commitment. Industrial and Commercial Training, 51(3), pp. 174–183. [133] 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. [134] Swalhi, A., Zgoulli, S., Hofaidhllaoui, M. (2017). The influence of organizational justice on job performance. Journal of Management Development, 36(4), pp. 542–559. [135] 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. [136] 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.
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). 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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. 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Available at: <https://doi.org/10.61877/ijmrp.v2i3.126>. 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>; gov.dz. (2023). Connaître l’Algérie. Available at: <https://www.mta.gov.dz/connaitrelalgerie/?lang=fr>; 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. Available at: <https://doi.org/10.1007/978-3-030-596750_3>; 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. Available at: <https://doi.org/10.1080/09669582.2023.2230389>; 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>; 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>; (2023, December 15). Our commitment to net zero. Available at: <https://www.skyscanner.net/media/sustainability/our-commitment-to-net-zero>; (2024, July 12). Booking.com: Total website visits worldwide 2024. Available at: <https://www.statista.com/statistics/1294912/total-visits-to-booking-website/>; (2024, May 14). 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. Additionally, although the MQOQ and TVNQC approaches are powerful in uncovering nonlinear and asymmetric effects, they are limited in terms of dynamic impact analysis. Researchers can employ alternative methods, such as wavelet analysis or other dynamic quantile approaches. Lastly, the study does not account for other macroeconomic factors (e.g., technological innovations, global energy prices, international policy spillovers), which can be done by future studies to add more clarification to the impact of monetary and fiscal policy uncertainty on the U.S energy transition. Bibliography: Abbas, S., Saha, T., Sinha, A. (2024). Price response of top-five renewable energy firms to Russia-Ukraine conflict: An advanced quantile analysis to achieve net-zero in United States of America. Journal of Cleaner Production; Adebayo, T. S. (2024). Do uncertainties moderate the influence of renewable energy consumption on electric power CO2 emissions? A new policy insight. 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Energy research & social science, 22, 7-12. [6] Mohsin, M., Taghizadeh-Hesary, F., Iqbal, N., Saydaliev, H. B. (2022). The role of technological progress and renewable energy deployment in green economic growth. Renewable Energy, 190, 777-787. [7] Lahiani, A., Mefteh-Wali, S., Shahbaz, M., Vo, X. V. (2021). Does financial development influence renewable energy consumption to achieve carbon neutrality in the USA? Energy Policy, 158, 112524. [8] Xue, C., Shahbaz, M., Ahmed, Z., Ahmad, M., Sinha, A. (2022). Clean energy consumption, economic growth, and environmental sustainability: what is the role of economic policy uncertainty? Renewable Energy, 184, 899-907. [9] Adedoyin, F. F., Zakari, A. (2020). Energy consumption, economic expansion, and CO2 emission in the UK: the role of economic policy uncertainty. Science of the Total Environment, 738, 140014. [10] Shafiullah, M., Miah, M. D., Alam, M. S., Atif, M. (2021). Does economic policy uncertainty affect 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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Determinants of sustainability reporting and its impact on firm value: Evidence from the emerging market of Turkey. Journal of Cleaner Production, 143(February); 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); 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>; 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; Masoud, N., Vij, A. (2021). The effect of mandatory CSR disclosure on firms: empirical evidence from UAE. International Journal of Sustainable Engineering, 14(3); Matuszak, Ł., Różańska, E. (2020). Online corporate social responsibility (CSR) disclosure in the banking industry: evidence from Poland. Social Responsibility Journal, 16(8); Orazalin, N., Mahmood, M. (2020). Determinants of GRI-based sustainability reporting: evidence from an emerging economy. Journal of Accounting in Emerging Economies, 10(1); Pirveli, E. (2014). Accounting quality in Georgia: Theoretical overview and development of predictions. International Journal of Business and Social Science (USA), 5(3); Pirveli, E. (2015). Financial statement quality: First evidence from the Georgian stock exchange Shaker Verlag, Aachim, Germany; Pirveli, E. (2020). Earnings persistence and predictability within the emerging economy of Georgia. Journal of Financial Reporting and Accounting, 18(3); Pirveli, E. (2024). Corporate disclosure timing under IFRS: the case of emerging Georgia. Journal of Financial Reporting and Accounting, 22(5); 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); 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; Pirveli, E., Zimmermann, J. (2015). Time-series properties of earnings: the case of georgian stock exchange. Journal of Business and Policy Research, 10(1); Qiu, Y., Shaukat, A., Tharyan, R. (2016). Environmental and social disclosures: Link with corporate financial performance. The British Accounting Review, 48(1); Ruhnke, K., Gabriel, A. (2013). Determinants of voluntary assurance on sustainability reports: an empirical analysis. Journal of Business Economics, 83(9); Russo, M. V., Fouts, P. A. (1997). 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). 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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. 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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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Georgia’s informal economy size. <https://www.worldeconomics.com/Informal-Economy/Georgia.aspx> [Last Access 10.10.2024]. 47. World Travel and Tourism Council. (2023). Global travel & tourism catapults into 2023 says WTTC, economic impact research. <https://wttc.org/news-article/global-travel-and-tourism-catapults-into-2023-says-wttc#:~:text=A%20look%20back%20on%20last%20year&text=This%20recovery%20represented%207.6%25%20of,GDP%20contribution%20of%20%247.7TN> [Last Access 10.10.2024]. 48. World Travel and Tourism Council. (2024). World economic impact report. <https://researchhub.wttc.org/product/world-economic-impact-report> [Last Access 10.10.2024]. Footnotes [1] Dinello, N. (2022). Centrality of winemaking in Georgia: From prehistoric age to present-day globalization. Journal of Wine Research. <https://doi.org/10.1080/09571264.2022.2110050>. [2] National Statistics Office of Georgia. (2024a). Exports by commodity groups (HS 2-digit level) in 2015-2024, export. <https://www.geostat.ge/en/modules/categories/637/export> [Last Access 10.10.2024]. [3] Ibid. [4] Ibid. [5] National Statistics Office of Georgia. (2024a). Exports by commodity groups (HS 2 digit level) in 2015-2024, export. <https://www.geostat.ge/en/modules/categories/637/export> [Last Access 10.10.2024]. [6] Agenda.ge. (2024). Georgian wine exports to the US, Europe have significantly increased, National Wine Agency says. <https://agenda.ge/en/news/2024/39895#gsc.tab=0> [Last Access 10.10.2024]. [7] Kvakhadze, I., Surmava M., Beroshvili T. (2022). Georgian Wine Industry Overview: August 2022 Sector Report, TBC Capital. <https://tbccapital.ge/static/file/202208124343-georgian-wine-industry-overview-12.08.2022-tbccapital.pdf> [Last Access 10.10.2024]. [8] TASS. (2024). Georgian wine exports to Russia rise by 74% in Q1 2024. <https://tass.com/economy/1777963> [Last Access 10.10.2024]. [9] Transparency International Georgia. (2024). Georgia’s Economic Dependence on Russia: Summary of 2023. <https://transparency.ge/en/blog/georgias-economic-dependence-russia-summary-2023> [Last Access 10.10.2024]. [10] TASS. (2024). Georgian wine exports to Russia rise by 74% in Q1 2024. <https://tass.com/economy/1777963> [Last Access 10.10.2024]. [11] Jmukhadze, N. (2022). The Role and Influence of Wine Export on the Economic Growth of Georgia. Forbes. <https://forbes.ge/en/ghvinis-eqsportis-roli-da-gavlena-saqarthvelos-ekonomikur-zrdaze/> [Last Access 10.10.2024]. [12] Jmukhadze, N. (2022). The Role and Influence of Wine Export on the Economic Growth of Georgia. Forbes. <https://forbes.ge/en/ghvinis-eqsportis-roli-da-gavlena-saqarthvelos-ekonomikur-zrdaze/> [Last Access 10.10.2024]. * Calculated by authors from the data of the National Statistics Office of Georgia. [13] Jmukhadze, N. (2022). The Role and Influence of Wine Export on the Economic Growth of Georgia. Forbes. <https://forbes.ge/en/ghvinis-eqsportis-roli-da-gavlena-saqarthvelos-ekonomikur-zrdaze/> [Last Access 10.10.2024]. [14] GIZ. (2013). Kakheti Regional Development Strategy 2014-2021 (pp. 12-13). Tbilisi. <https://faolex.fao.org/docs/pdf/geo200876.pdf> [Last Access 10.10.2024]. [15] National Statistics Office of Georgia. (2024b). Unemployment, percentage and Labor Force Indicators by Regions. Employment and Unemployment. <https://www.geostat.ge/en/modules/categories/683/Employment-Unemployment> [Last Access 10.10.2024]. [16] International Trade Administration. (2023). Agricultural Sector. Georgia – Country Commercial Guide. <https://www.trade.gov/country-commercial-guides/georgia-agricultural-sector> [Last Access 10.10.2024]. [17] Georgia Today. (2021). Wine Production Sector in Georgia. <https://georgiatoday.ge/wine-production-sector-in-georgia/#:~:text=The%20wine%20production%20sector%20in,CAGR%20of%2012.1%25%20was%20reported> [Last Access 10.10.2024]. [18] National Statistics Office of Georgia. (2024b). Unemployment, percentage and Labor Force Indicators by Regions. Employment and Unemployment. <https://www.geostat.ge/en/modules/categories/683/Employment-Unemployment> [Last Access 10.10.2024]. [19] World Economics. (2024). Georgia’s Informal Economy Size. <https://www.worldeconomics.com/Informal-Economy/Georgia.aspx> [Last Access 10.10.2024]. [20] International Monetary Fund. (2024). Georgia. World Economic Outlook Database. <https://www.imf.org/en/Publications/WEO/weo-database/2024/April/weo-report?c=915,&s=NGDP_RPCH,NGDPD,PPPGDP,NGDPDPC,PPPPC,PCPIPCH,&sy=2022&ey=2029&ssm=0&scsm=1&scc=0&ssd=1&ssc=0&sic=0&sort=country&ds=.&br=1> [Last Access 10.10.2024]. [21] National Wine Agency. (2024). Promotion of Georgian wine on international markets will become more active in 2024. News. <https://wine.gov.ge/En/News/37081> [Last Access 10.10.2024]. [22] Gelashvili, S., Deisadze S., Seturidze E. (2022). An Overview of the Georgian Wine Sector: Policy Brief, Free Network. <https://freepolicybriefs.org/2022/11/21/overview-georgia-wine-sector/> [Last Access 10.10.2024]. [23] Georgia.to. (2024). Government Policy in the Georgian Wine Sector. <https://georgia.to/government-policy-in-georgian-wine-sector/> [Last Access 10.10.2024]. [24] Gelashvili, S., Deisadze S., Seturidze E. (2022). An Overview of the Georgian Wine Sector: Policy Brief, Free Network. <https://freepolicybriefs.org/2022/11/21/overview-georgia-wine-sector/> [Last Access 10.10.2024]. [25] Jmukhadze, N. (2022). The Role and Influence of Wine Export on the Economic Growth of Georgia. Forbes. <https://forbes.ge/en/ghvinis-eqsportis-roli-da-gavlena-saqarthvelos-ekonomikur-zrdaze/> [Last Access 10.10.2024]. [26] Deisadze, S., Gelashvili S., Katsia I. (2020). To Subsidize or Not to Subsidize Georgia’s Wine Sector? ISET Economist Blog. To Subsidize or Not to Subsidize Georgia’s Wine Sector? (iset-pi.ge) [Last Access 10.10.2024]. [27] This Day in Wine History. (2022). History of Wine Tourism in the Ancient World. <https://thisdayinwinehistory.com/history-of-wine-tourism-in-the-ancient-world/> [Last Access 10.10.2024]. [28] UN Tourism. (2016). 1st UNWTO Global Conference on Wine Tourism. <https://www.unwto.org/archive/global/event/1st-unwto-global-conference-wine-tourism> [Last Access 10.10.2024]. [29] UN Tourism. (2023). 7th UNWTO Global Conference on Wine Tourism. <https://www.unwto.org/7-UNWTO-Global-Conference-Wine-Tourism> [Last Access 10.10.2024]. [30] Municipal Development Fund of Georgia. (2018). Marketing, branding, and promotional strategy for Georgia, Part II – Strategy (pp. 31-72). RFP No.: IBRD/IDA/RDPII/CS/QCBS/03-2017. [31] Charaia, V., Lashkhi, M. (2022). Foreign direct investments during the coronomic crisis and armed conflict in the neighbourhood, Case of Georgia. Globalization and Business, 7(13), pp. 51-56. <https://eugb.ge/index.php/111/article/view/17> [Last Access 10.10.2024]. [32] Papava, V., Charaia, V. (2020). The coronomic crisis and some challenges for the Georgian economy. GFSIS, Expert Opinion, (136). <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3572124> [Last Access 10.10.2024]. [33] Georgia National Tourism Administration. (2024). Record $4.1 billion in tourism revenue and 7.1 million international travelers - 2023 statistics. <https://gnta.ge/ge/2023-statistics-info/?fbclid=IwAR3xD0boFcMaTR_L3jKrhwz_WQOGN_Eb4zOBaB0gQ6wMdePxx648hU2GFa4> [Last Access 10.10.2024]. [34] National Statistics Office of Georgia. (2024c). Inbound Tourism Statistics in Georgia (pp. 4-9). <https://www.geostat.ge/media/59934/Inbound-Tourism-Statistics---%282023-year%29.pdf> [Last Access 10.10.2024]. [35] National Statistics Office of Georgia. (2024c). Inbound Tourism Statistics in Georgia (pp. 4-9). <https://www.geostat.ge/media/59934/Inbound-Tourism-Statistics---%282023-year%29.pdf> [Last Access 10.10.2024]. [36] Ibid. [37] Georgian National Tourism Administration. (2023). Georgian Tourism in Figures: Structure and Industry Data 2022 (pp. 8-23). <https://gnta.ge/wp-content/uploads/2023/09/2022-eng-1.pdf> [Last Access 10.10.2024]. [38] Georgian National Tourism Administration. (2023). Georgian Tourism in Figures: Structure and Industry Data 2022 (pp. 8-23). <https://gnta.ge/wp-content/uploads/2023/09/2022-eng-1.pdf> [Last Access 10.10.2024]. [39] National Statistics Office of Georgia. (2024c). Inbound Tourism Statistics in Georgia (pp. 4-9). <https://www.geostat.ge/media/59934/Inbound-Tourism-Statistics---%282023-year%29.pdf> [Last Access 10.10.2024]. [40] World Travel and Tourism Council. (2023). Global Travel & Tourism Catapults into 2023 Says WTTC, Economic Impact Research. <https://wttc.org/news-article/global-travel-and-tourism-catapults-into-2023-says-wttc#:~:text=A%20look%20back%20on%20last%20year&text=This%20recovery%20represented%207.6%25%20of,GDP%20contribution%20of%20%247.7TN> [Last Access 10.10.2024]. [41] Georgian National Tourism Administration. (2023). Georgian Tourism in Figures: Structure and Industry Data 2022 (pp. 8-23). <https://gnta.ge/wp-content/uploads/2023/09/2022-eng-1.pdf> [Last Access 10.10.2024]. [42] World Travel and Tourism Council. (2023). Global Travel & Tourism Catapults into 2023 Says WTTC, Economic Impact Research. <https://wttc.org/news-article/global-travel-and-tourism-catapults-into-2023-says-wttc#:~:text=A%20look%20back%20on%20last%20year&text=This%20recovery%20represented%207.6%25%20of,GDP%20contribution%20of%20%247.7TN> [Last Access 10.10.2024]. [43] National Statistics Office of Georgia. (2024c). Inbound Tourism Statistics in Georgia (pp. 4-9). <https://www.geostat.ge/media/59934/Inbound-Tourism-Statistics---%282023-year%29.pdf> [Last Access 10.10.2024]. [44] University of Georgia Extension. (2024). Georgia’s Alcoholic Beverage Industry 2024 Outlook. <https://extension.uga.edu/publications/detail.html?number=AP130-2-15&title=georgias-alcoholic-beverage-industry-2024-outlook> [Last Access 10.10.2024]. [45] Tsereteli, M. (2024). Georgian Wine and its Narrative Drive Development. The Central Asia – Uncorking Georgia’s Wine Boom: A Statistical Deep Dive and Exploring Key Regions. 8Wines. <https://www.cacianalyst.org/publications/analytical-articles/item/13548-georgian-wine-and-> [Last Access 10.10.2024]. [46] International Trade Administration. (2023). Agricultural Sector. Georgia – Country Commercial Guide. <https://www.trade.gov/country-commercial-guides/georgia-agricultural-sector> [Last Access 10.10.2024]. [47] FAO. (2024). Georgia at a Glance. FAO in Georgia, Food and Agriculture Organization of the United Nations. <https://www.fao.org/georgia/programmes-and-projects/georgia-at-a-glance/en/> [Last Access 10.10.2024]. [48] UN. (2020). Building the resilience of mountain communities in the face of crisis. United Nations: Georgia. <https://georgia.un.org/en/104787-building-resilience-mountain-communities-face-crisis> [Last Access 10.10.2024]. [49] National Statistics Office of Georgia. (2024a). Exports by commodity groups (HS 2 digit level) in 2015-2024, export. <https://www.geostat.ge/en/modules/categories/637/export> [Last Access 10.10.2024]. [50] National Statistics Office of Georgia. (2024d). GDP at current prices, billion GEL. Gross Domestic Product (GDP). <https://www.geostat.ge/en/modules/categories/23/gross-domestic-product-gdp> [Last Access 10.10.2024]. [51] Lashkhi, M., Charaia, V., Boyarchuk, A., Ebralidze, L. (2022). The Impact of Fintech on Financial Institutions: The Case of Georgia. TalTech Journal of European Studies, 12(2), pp. 20-42. <https://intapi.sciendo.com/pdf/10.2478/bjes-2022-0010> [Last Access 10.10.2024]. [52] Lashkhi, M., Ogbaidze, S., Lashkhi, M., Charaia, V. (2022). Startup access to finance in Georgia and international experience. <https://ekonomisti.tsu.ge/?cat=nomer&leng=eng&adgi=692> [Last Access 10.10.2024]. [53] National Statistics Office of Georgia. (2024a). Exports by commodity groups (HS 2 digit level) in 2015-2024, Export. <https://www.geostat.ge/en/modules/categories/637/export> [Last Access 10.10.2024]. ** Calculated by authors from the data of the National Statistics Office of Georgia. [54] Tsereteli, M. (2024). Georgian Wine and its Narrative Drive Development. The Central Asia – Uncorking Georgia’s Wine Boom: A Statistical Deep Dive and Exploring Key Regions. 8Wines. <https://www.cacianalyst.org/publications/analytical-articles/item/13548-georgian-wine-and-> [Last Access 10.10.2024]. [55] Jmukhadze, N. (2022). The Role and Influence of Wine Export on the Economic Growth of Georgia. Forbes. <https://forbes.ge/en/ghvinis-eqsportis-roli-da-gavlena-saqarthvelos-ekonomikur-zrdaze/> [Last Access 10.10.2024]. [56] Market Entry Georgia. (2024). Automotive - Market Research. Tbilisi. <https://www.marketentry.ge/automotive#:~:text=In%20Georgia%20cars%20are%20mostly,is%20not%20producing%20cars%20itself> [Last Access 10.10.2024]. [57] Gabritchidze, N. (2023). Georgian miners strike as company cites global market crisis. Eurasianet. <https://eurasianet.org/georgian-miners-strike-as-company-cites-global-market-crisis> [Last Access 10.10.2024]. [58] Hellibrand GORI. (2024). California - Vineyard of the Americas. About-California.com, Explore the World’s Top Wine Regions. <https://about-california.com/wines.htm#:~:text=California%20%2D%20Vineyard%20of%20the%20Americas,87%25%20of%20US%20wine%20production> [Last Access 10.10.2024]. [59] The National Association of American Wineries. (2023). California Economic Impact Study 2022. <https://wineamerica.org/economic-impact-study/california-wine-industry/#:~:text=2022,the%20American%20economy%20in%202022> [Last Access 10.10.2024]. [60] Ibid. [61] Ibid. [62] Georgian National Tourism Administration. (2023). Georgian Tourism in Figures: Structure and Industry Data 2022 (pp. 8-23). <https://gnta.ge/wp-content/uploads/2023/09/2022-eng-1.pdf> [Last Access 10.10.2024]. [63] Georgian National Tourism Administration. (2023). Georgian Tourism in Figures: Structure and Industry Data 2022 (pp. 8-23). <https://gnta.ge/wp-content/uploads/2023/09/2022-eng-1.pdf> [Last Access 10.10.2024]. [64] National Statistics Office of Georgia. (2024d). GDP at current prices, billion GEL. Gross Domestic Product (GDP). <https://www.geostat.ge/en/modules/categories/23/gross-domestic-product-gdp> [Last Access 10.10.2024]. [65] World Travel and Tourism Council. (2024). World Economic Impact Report. <https://researchhub.wttc.org/product/world-economic-impact-report> [Last Access 10.10.2024]. [66] Tourism Economics. (2021). Data and Digital Platforms: Driving the Tourism Recovery in Georgia, an Oxford Economics Company. <https://s3.amazonaws.com/tourism-economics/craft/Google_Georgia_Final.pdf> [Last Access 10.10.2024]. [67] Georgia National Tourism Administration. (2024). Record $4.1 billion in tourism revenue and 7.1 million international travelers - 2023 statistics. <https://gnta.ge/ge/2023-statistics-info/?fbclid=IwAR3xD0boFcMaTR_L3jKrhwz_WQOGN_Eb4zOBaB0gQ6wMdePxx648hU2GFa4> [Last Access 10.10.2024]. [68] Ibid. [69] Statista. (2024). Number of international tourist arrivals in France from 2010 to 2023. <https://www.statista.com/statistics/436543/number-of-inbound-overnight-visits-france/#:~:text=The%20number%20of%20international%20tourist,by%20the%20destination%20to%20date> [Last Access 10.10.2024]. [70] UN Tourism. (2024). World Tourism Barometer. <https://pre-webunwto.s3.eu-west-1.amazonaws.com/s3fs-public/2024-06/Barom_PPT_May_2024.pdf?VersionId=U7O62HatlG4eNAj.wcmuQG1PMCjK.Yss> [Last Access 10.10.2024]. ***Calculated by authors using the average exchange rate in 2023 of Euro to USD of 1.0824 USD. ExchangeRates.org.UK. Euro to US Dollar Spot Exchange Rates for 2023 [Last Access 26.07.2024]. [71] Georgian National Tourism Administration. (2023). Georgian Tourism in Figures: Structure and Industry Data 2022 (pp. 8-23). <https://gnta.ge/wp-content/uploads/2023/09/2022-eng-1.pdf> [Last Access 10.10.2024]. [72] Quinn, C. (2020). The Tourism Industry Is in Trouble. These Countries Will Suffer the Most. Foreign Policy. <https://foreignpolicy.com/2020/04/01/coronavirus-tourism-industry-worst-hit-countries-infographic/> [Last Access 10.10.2024]. [73] Charaia, V., Chochia, A., & Lashkhi, M. (2020). The impact of FDI on economic development: The Case of Georgia. TalTech Journal of European Studies, 10(2), pp. 96-116. <https://intapi.sciendo.com/pdf/10.1515/bjes-2020-0017> [Last Access 10.10.2024]. [74] Veseth, M. (2020). Anatomy of Georgia’s Wine Export Surge. The Wine Economist. <https://wineeconomist.com/2020/12/08/ghvino/> [Last Access 10.10.2024]. [75] Georgia Today. (2021). Wine Production Sector in Georgia. <https://georgiatoday.ge/wine-production-sector-in-georgia/#:~:text=The%20wine%20production%20sector%20in,CAGR%20of%2012.1%25%20was%20reported> [Last Access 10.10.2024]. [76] Mamardashvili, G. (2022). Georgia, the Cradle of Wine. Georgian Folklore Magazine, Journal No.1. <https://geofolk.ge/en/article/saqartvelo--ghvinis-akvani/57#:~:text=The%20ancient%20Georgian%20deity%20of,Guria%20and%20Lechkhumi)%20until%20recently> [Last Access 10.10.2024].
The Banking Regulation’s Shifts in Light of Globalization and its Effect on the Banking Industry’s Performance: U.S.A. as a Model
Banking regulation is essential for the efficient functioning of banking activities and the optimal allocation of financial resources. It also plays a critical role in ensuring financial stability and safeguarding depositors by preventing banks from taking excessive risks and ensuring they maintain adequate liquidity to meet their obligations. These measures contribute to the development of the banking sector and enable banks to finance economic growth. This study seeks to examine the transformations in banking regulation over recent decades and their impact on the performance of the banking sector, focusing on the United States as a case study. To achieve this objective, a descriptive method was employed. The study found that banking regulation in the United States has undergone significant transformations, shifting from liberalization to increased restrictions. The global financial crisis of 2008 prompted regulators to tighten their frameworks, which, while initially having a slight negative impact on profitability, ultimately had a significant positive effect on the resilience of banks. Keywords: Banking Regulation, Performance, Globalization, United States, Dodd-Frank Act. Introduction The global economy had a significant increase in liberalization throughout the last years of the previous century; the surge in banking sector activity and cross-border capital flows is predominantly attributed to the advent of financialization. However, this was paralleled by an increase in the levels of risks faced by the banking system in countries around the world, leading to a series of successive crises. If a bank fails, it can have far-reaching economic consequences, particularly if the bank is considered to be systemically significant. Depositors, including individuals and corporations, face the risk of losing their deposited funds, which might potentially lead to a complete cessation of economic activity. This situation necessitates placing the banking sector within a framework that includes a set of rules and regulations to ensure its proper functioning and foster a high level of trust between the banking sector and other sectors. However, these laws and standards frequently make it difficult for the banking industry to grow and restrict high-yield, high-risk banking operations, which has an impact on the industry’s overall performance. The American banking sector is considered one of the most dynamic internationally. For decades, this sector has experienced extensive regulatory activity that alternates between liberalization and restriction, occurring simultaneously with disruptions to the American economy. Banking regulation is now an essential tool for properly supervising this important sector in a manner that protects the interests of the American economy without endangering taxpayer dollars. Considering the worldwide financial crisis and its substantial impact on the banking sector and the broader economy, there was a clear and important change in banking regulation in the United States, primarily involving an increase in regulatory constraints. This shift led to a divided American society: some supported regulation as necessary for the safety of the banking sector, while others opposed it, arguing that it burdens banks and significantly affects their performance. Therefore, this study aims to present the regulatory reform experience in the United States, the world’s leading economy, and highlight its effects on the performance of the American banking sector, with a focus on the period following the 2008 subprime mortgage crisis. Fundamentals of Banking Regulation 2.1. Concept of Banking Regulation Financial regulation refers to the set of rules and regulations that control the operations of businesses in the financial industry. Examples of entities include asset managers, banks, credit unions, insurance companies, and financial intermediaries. The Central Bank of Ireland has issued this proclamation, which mandates compliance with certain regulations. However, financial regulation requires ongoing monitoring and enforcement of these rules in addition to the mere implementation of regulations.[1] Spong defines banking regulation as specifically the body of laws and rules that control how banks conduct business. Banking supervision and banking agencies are distinct from each other. While banking supervision focuses on the enforcement of banking rules and regulations and the monitoring of financial conditions in banks, banking agencies operate under their direction.[2] Banking regulation, as defined by (Agborya-Echi, 2010),[3] refers to the collection of governmental rules established to supervise and control financial institutions. Banking regulation may be described as: “a collection of laws and regulations that oversee banking activities with the goal of fostering discipline and transparency in banking operations”. 2.2. Types of Banking Regulation There are two broad categories of regulations that affect banks: regulations for the soundness and safety of banks and regulations for consumer protection:[4] 2.2.1. Safety and Soundness Regulation This kind of oversight makes sure that banks run soundly and safely, not putting taxpayers or deposit insurance money at undue risk. Usually, the activities of the bank and the regulatory systems that oversee and examine these activities are the main subjects of these rules. 2.2.2. Consumer Protection Regulation Protecting consumers’ interests when they interact with banks and other financial service providers is the aim of these regulations. This set of legislation covers a wide variety of issues, including prohibiting discrimination in credit transactions, protecting consumers from misleading information, and ensuring that they are properly informed about how credit expenses related to loans and leases are calculated. 2.3. Motivations for and Objectives of Banking Regulation Banking institutions are regulated for two main reasons:[5] 2.3.1. Consumer Protection This reason is similar to why public utilities and telecommunications are regulated, which is to provide a framework of rules that can help prevent market mechanisms alone from controlling market excesses and failures. 2.3.2. Achieving Financial Stability Preserving financial stability is often seen as a crucial public advantage that necessitates the creation of a more extensive system for overseeing and controlling. The primary goals of banking regulation are as follows:[6] Ensuring the security and soundness of banks and other financial institutions is crucial to protect depositors and taxpayers, maintain financial stability, and uphold trust at both the national and global levels. Furthermore, it ensures the optimal utilization of the state’s finite resources and the central bank’s dedication to serving as the ultimate provider of funds for banks during periods of necessity; Achieve Monetary Stability and Maintain Efficient Payment System Operations: This includes ensuring that the monetary system is stable and that the payment systems operate efficiently; Create an Efficient and Competitive Financial System: This is achieved by preventing the excessive concentration of banking resources, which would otherwise lead to non-competitive conditions; Protect Consumers and Customers: This involves safeguarding borrowers against the arbitrary practices of credit-granting institutions by ensuring that consumers have equal opportunities to obtain the required credit. Banking Regulation in The Context of Globalization 3.1. Drivers of Banking Regulatory Transformation There are two components to the historical process of financial globalization. First, there is a rise in the amount of cross-border financial transactions; second, a series of institutional and regulatory reforms have been put in place to liberalize local financial systems and global capital movements.[7] Throughout the second half of the 20th century, there were numerous changes to banking regulations that affected the global economy. These changes were brought about by a number of interrelated factors, such as the development of various forms of regulatory evasions, such as offshore financial centers and off-balance-sheet financing methods, the rapid advancement of technology, and the declining efficacy of traditional controls as a result of financial innovation. International financial center rivalry, nonbank competition for a range of services (including mortgages, small business loans, and consumer credit), and multilateral accords also played a role in the liberalization of cross-border banking activity.[8] 3.2. Evolution of International Banking Regulation Between Liberalization and Restriction: The degree of restriction in banking safety standards has changed throughout time. Safety and soundness rules were very strict after the Great Depression, with a focus on keeping commercial and investment banking services separate and forbidding bank-holding corporations from partnering with insurance companies. Significant limitations on market forces, such as controls over interest rates, caps on the volume of business financial institutions could undertake, barriers to market access, and, in certain situations, restrictions on financing allocation, were features of financial systems in the early 1970s. Governments used these regulatory restrictions to further their social and economic policy objectives. In several post-war nations, direct controls were employed to direct funding toward businesses of choice. Financial stability concerns contributed to limitations on market access and competition, and safeguarding small savers with little financial literacy was a key goal of bank supervision. Since the mid-1970s, there has been a significant regulatory reform effort in place in the financial systems of most countries. In this process, there was a shift towards more market-oriented regulatory structures, as the table below illustrates: Table (01): Partial or Full Liberalization Measures in the Financial Sector since the Mid-1970s Field Partial or complete liberalization Controls on interest rates Most nations had extensive lending and borrowing restrictions in place up until the early 1970s. Banks controlled credit for preferred borrowers, and both rates were kept below levels of the free market. Only a few nations still had these restrictions in place by 1990. Restrictions on the transfer of funds internationally and the exchange of currencies In many developing countries as well as in OECD countries, the liberalization of capital movement regulations is almost complete. Nonetheless, there are still certain restrictions on long-term capital movements, mainly with regard to foreign direct investment and foreign ownership of real estate. Distinction between investment banking and commercial banking operations While many nations still impose considerable limitations on commercial lines, in many instances these limitations have been significantly reduced or eliminated entirely. Quantitative limits on banking institutions’ investments Banks were subject to a variety of investment limitations, such as mandates to hold government securities and guidelines for credit allocation. The early 1990s saw the complete elimination of these restrictions. Source: Biggar & Heimler, 2005. The above regulatory restraints were gradually lifted, although this did not result in the total emancipation of banking operations. Rather, it led to the implementation of new prudential regulatory instruments that better fit the banking industry’s competitive landscape. The first and most notable step in this new regulatory approach is the Basel Agreements. Large multinational banks in a group of twelve countries were required by the Basel I Accord, which was signed in July 1988, to begin achieving an 8% minimum capital adequacy ratio in 1992. Basel III: The subprime mortgage crisis prompted the committee to release its most recent version of its recommendations. After that, the committee made improvements to these plans in response to global economic shocks. Effects of Regulation on the Banking Sector’s Performance 4.1. Mechanism for Implementing Banking Regulation People might make the error of believing that powerful regulatory organizations only act in the public interest and that regulated institutions would abide by laws if they concentrated on the best regulatory method to remedy a specific market failure. In actuality, banking regulation is an economic game in which each player formulates a plan of action based on their personal goals. It is unrealistic to expect regulators to accomplish their objectives in a society where legislative structures limit their authority. It is also important to keep in mind that banks will adapt to regulations by creating new plans, such as offering financial innovations.[9] The mechanism by which banks interact with banking regulation can be summarized in the following figure: Figure (01): Mechanism for Implementing Banking Regulation Source: Freixas & Santomero, 2002. 4.2. Theories on How Banking Regulation Affects Bank Performance There are two contradictory arguments in the theory of banking regulation and its importance, outlined as follows:[10] 4.2.1. Public Interest Theory According to this hypothesis, the regulation of banking enhances the overall performance of banks by preventing new competitors from entering the market and thereby decreasing competition. Because there is less competition, banks are compelled to provide more cautious loans, which lowers banking risks. If there is no rivalry in the banking business, banks would only lend to borrowers with excellent credit ratings, but if there is fierce competition, banks may lend to customers with lower credit ratings. Moreover, this theory argues that direct bank supervision and control by government supervisors and regulators might eliminate financial failures entirely. Supporters of this viewpoint include Psillaki and Mamatzakis (2017)[11] and Beck et al. (2006).[12] 4.2.2. Private Interest Theory This financial regulation theory contends that contrary to the public interest view, stringent regulation has a negative impact on bank performance since it raises fee responsibilities. Entry restrictions make it harder for banks to innovate and operate efficiently, which makes them more dependent on more expensive funding sources like equity. As a result, riskier portfolios are chosen to offset high expenses and risk-taking brought on by high capital requirements, which lowers bank performance. According to this theory, stringent banking regulations result in unethical capital allocation, unscrupulous lending practices, and, eventually, poor bank performance, which may lead to bank closures. Supporters of this view include Laeven and Levine (2008)[13] and Pasiouras et al. (2009).[14] 4.3. The Impact of Banking Regulation on Bank Performance Different conclusions may be drawn from an examination of the research on how regulation affects bank performance. While some studies have demonstrated a beneficial relationship between regulation and bank performance, others have found a somewhat negative relationship.[15] assert that big banks gain from more freedom to raise the risks in their asset portfolios and that they engage in riskier behaviors more frequently when there is less supervision over them.[16] discovered that financial laws, which limit financial activity, may aid banks in achieving financial stability and help avert systemic issues. On the other hand, (Jomini, 2011)[17] argues that strict and harsh regulations can lead to high costs and poor performance due to the additional expenses incurred by regulated banks to comply with and manage these regulations. Since extensive regulations reduce competition, they also reduce economies of scale and innovation. Similarly, (Klomp & Haan, 2015)[18] concluded that stricter banking regulation improves bank performance. They explained that restrictive regulations reduce banking risks in large foreign banks, while liquidity constraints affect smaller banks. Additionally, they contended that banking regulation greatly impacts high-risk institutions while having less effect on low-risk banks. Uniqueness and Evolution of U.S Banking Sector Regulation 5.1. Uniqueness of U.S. Banking Sector Regulation The stability of the United States is of paramount importance to the global economy. The banking system is considered one of the most important financial systems globally because of its intricate nature, interconnectivity, and breadth. Compared to other nations, bank regulation in the US is extremely dispersed. In contrast to most other nations, which only have one bank regulatory agency, the United States has state and federal bank regulations. A financial institution may be governed by several federal and state banking laws, depending on its size and organizational design. In addition, the US has federal and state regulating bodies for commodities, insurance, securities and exchange, and banking in addition to the banking industry. This is in contrast to nations like the United Kingdom and Japan, where different domains are unified under a single regulatory agency. The table below illustrates the regulatory authorities that oversee the banking industry in the United States: Table (02): Regulatory Bodies of the U.S. Banking Sector Regulatory power The provided function The Federal Reserve Board (FRB) The federal Reserve, in its role as the country’s central bank, supervises monetary policy with the aim of sustaining low long-term interest rates, ensuring price stability, and attaining optimal employment levels in the American economy. Furthermore, its primary goal is to improve financial stability and efficiently manage and supervise risks that might impact the entire system.[19] The FDIC is the Federal Deposit Insurance Corporation This independent agency was established by Congress to supervise and examine financial institutions to ensure their safety and soundness, provide deposit insurance, and reassure the public that complex, large-scale financial institutions can be resolved. The major objectives of this institution are to preserve the stability of the nation’s financial system and sustain public trust.[20] The entity referred to as the Office of the Comptroller of the Currency (OCC) Created by the United States Department of the Treasury, the organization is responsible for establishing and enforcing regulations, and overseeing all national banks and federal savings institutions—including foreign bank branches and agencies—is the responsibility of this independent authority. The organization ensures impartial treatment of clients, equal opportunity to obtain financial services, secure and stable bank operations under its oversight, and adherence to all applicable rules and regulations.[21] The Bureau of Consumer Financial Protection (CFPB) The objective is to enhance consumer financial markets for the advantage of conscientious providers, consumers, and the overall economy. It protects customers against unjust, exploitative, or deceptive commercial activities and initiates legal proceedings against those who violate the law. Moreover, it provides individuals with the information, tools, and activities necessary to make prudent financial choices.[22] The Council for Financial Stability Oversight (FSOC) The council is tasked with evaluating the susceptibilities that may impact the stability of the US financial system, strengthening market discipline, and reacting to new dangers to that stability. By imposing risk-based capital requirements and limitations on short-term loans, including procedures for off-balance sheet transactions, it keeps an eye on big financial institutions. The council sets yearly stress tests, restricts leverage between 15% and 1%, and mandates that these businesses submit plans for an orderly resolution in the case of financial difficulties.[23] Source: Prepared by researchers relying on the official websites of the regulatory authorities and offices. 5.2. Evolution of U.S. Banking Sector Regulation The 1929 stock market crisis caused economic instability and ultimately resulted in the banking system collapsing, which made stricter banking regulations necessary. The Glass-Steagall Act of 1933 was responsible for creating the Federal Deposit Insurance Corporation (FDIC) and requiring the separation of commercial and investment banking operations. The New Deal implemented regulations on deposit interest rates. The 1935 Banking Act enhanced and consolidated the power of the Federal Reserve. There was some relative banking stability and economic growth between the New Deal banking reforms and 1980. However, it soon became evident that stringent banking laws limited American banks’ ability to innovate and remain competitive. Stricter regulation-bound commercial banks were falling behind more innovative, loosely regulated financial businesses. Consequently, there was an increase in the process of removing regulations over the latter two decades of the 20th century. The Depository Institutions Deregulation and Monetary Control Act was passed by Congress in 1980; the Federal Reserve was given additional authority to determine monetary policy, and financial institutions that received deposits were liberalized. The Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994 eliminated the prohibitions on bank branch openings that were imposed on a state-by-state basis. The 1999 Gramm-Leach-Bliley Act eliminated the restrictions set by the Glass-Steagall Act, therefore permitting banks to conduct commercial banking activities, securities, and insurance services all under one organization. Both the number of banking institutions and the volume of financial transactions increased throughout the next few years.[24] Contemporary Banking Regulation In The U.S 6.1. U.S. Banking Sector’s Response to Basel III Accords U.S. regulatory authorities have implemented the Basel III accords within the local banking regulations, highlighted by the following: 6.1.1. Capital Adequacy Ratio The key rules imposed include:[25] A bank must maintain a minimum of 4.5% of its capital in Common Equity Tier 1 (CET1). In addition, banks must have a 2.5% buffer for capital conservation on common shares. These laws require banks to maintain a total of 7% CET1 capital by the end of 2019. As a result, banks will need to retain 10.5% capital by the end of 2019 in addition to the 2.5% countercyclical buffer; The overall capital requirement for banks using the advanced strategy can be as high as 13%. This comprises the countercyclical buffer and the capital conservation buffer, which started at 0% and has the potential to increase to 2.5% by the end of 2019; The start date for compliance with the minimum capital requirement was January 1, 2014, for financial organizations utilizing the sophisticated methodology (generally, people or corporations must have a minimum of $250 billion in total assets or at least $10 billion in on-balance sheet international exposure). The start of 2015 was the compliance start date for other banking institutions; In order to circumvent limitations on dividend payouts and discretionary bonuses, advanced approach banks must maintain a combined buffer (capital conservation and countercyclical) of more than 5%. Banks are obliged to maintain a countercyclical buffer. 6.1.2. Liquidity Ratios September 2014 saw the announcement of the final Liquidity Coverage Ratio (LCR) regulation by U.S. banking authorities, with a few minor deviations. The standards are closely akin to those of Basel III. The proposed liquidity coverage ratio (LCR) applies to both US banking institutions and major non-bank financial firms. Bank-holding organizations with assets over $250 billion must maintain an adequate amount of liquid assets to meet net cash withdrawals within 30 days. For a regional organization with assets ranging from $50 billion to $250 billion, it is necessary for its liquid assets to be enough to cover net cash withdrawals within a 21-day timeframe. Bank holding firms are exempt from the LCR if their assets do not exceed $50 billion.[26] The United States has adopted the Net Stable Funding Ratio (NSFR) in line with global standards, and enforcement began in January 2018. 6.1.3. Leverage ratio One of the largest benefits of the Basel III requirements is the leverage ratio. The Basel Committee revised the methods for determining exposures both on and off the balance sheet in January 2014, and in 2010, it established a leverage ratio of 3%. The 3% leverage ratio was put into effect by US regulatory bodies in 2013 as part of an examination of capital requirements. Large financial institutions with total consolidated assets of at least $250 billion or foreign exposure on their balance sheet of at least $10 billion are subject to this ratio. U.S. authorities finalized the new leverage ratio, which was set at 6% for insured depository institutions and globally systemically important banks (G-SIBs). Banking authorities finalized these regulations in April 2014.[27] 6.2. The Dodd-Frank Act: Wall Street Reform and Consumer Protection The Dodd-Frank Act As a reaction to the global economic recession, the Obama administration implemented the Wall Street Reform and Consumer Protection Act of 2010 as part of a broader legislative effort to overhaul the financial industry. This law’s objectives are to safeguard American taxpayers by ending bailouts, enhancing financial system accountability and transparency, dismantling the “too big to fail” theory for major corporations, and protecting customers from deceptive financial services activities. The following are the main rules and clauses included in the Dodd-Frank Act:[28] Greater Quantity and Quality of Capital: The Dodd-Frank Act mandates that banks maintain greater amounts of capital of higher caliber by conforming to the international Basel III standards, which establish minimum risk-weighted capital levels, liquidity requirements, and leverage requirements. Systemically important financial institutions are subject to more stringent requirements; Annual Stress Tests: In order to promote market trust and transparency, institutions are put through annual stress tests; Government agencies changed the Act to provide more efficient supervision of the financial system as a whole. The Thrift Supervision Office was closed, and the Federal Reserve and the Office of the Comptroller of the Currency (OCC) currently share the responsibilities with the Federal Deposit Insurance Corporation (FDIC). The Federal Reserve acted as the main regulatory body for major financial enterprises. Additionally, the Consumer Financial Protection Bureau (CFPB) of the Federal Reserve and the Financial Stability Oversight Council (FSOC) under the Treasury were formed by Congress; Bailouts are specifically terminated by the Dodd-Frank Act, which is paid by taxpayers. According to Section 214, the financial industry is responsible for any losses incurred in the liquidation of any financial institution; taxpayers will not be held liable for such losses; Large banks are required to file comprehensive resolution plans; The Financial Stability Oversight Council (FSOC) was created with the aim of detecting risks that might potentially affect the whole financial system. It has jurisdiction over both non-bank financial firms and banks; Financial institutions that benefit from government deposit guarantees are prohibited from participating in proprietary trading for personal profit or to invest in hedge funds and private equity funds, but they are permitted to contribute up to 3% of their capital to these funds.[29] Performance of the U.S Banking Sector in the Light of Contemporary Banking Regulation 7.1. Capital Adequacy Ratio in the U.S. Banking Sector By bringing its banking system into compliance with Basel III requirements, the American banking industry has responded to the many directives and guidelines issued by regulatory bodies. The improvement of the capital adequacy ratio, which offers a capital buffer to absorb losses from unforeseen operational, credit, or market events, has been one of the main results. Table (03): Evolution of Tier 1 Capital Ratio from 2006 to 2019 Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 Tier 1 Core Capital 8.33 7.13 6.31 8.67 10.2 10.9 11.6 12.8 13.1 Year 2015 2016 2017 2018 2019 2020 2021 2022 2023 Tier 1 Core Capital 13.1 13.2 13.5 13.8 13.7 14.5 14.8 14.5 14.9 Source: International Monetary Fund (IMF), 2020. The Tier 1 capital ratio, which represents the best quality capital, has significantly improved, as the table demonstrates. The Tier 1 capital ratio decreased to around 6% at the onset of the global financial crisis, down from over 8% in 2006. However, it subsequently increased to 13.1% in 2014. The percentage remained consistently high in the subsequent years, concluding at 13.8% in 2023. This development shows how effective regulations have been in strengthening the stability of American financial institutions. Within this particular framework, there was a significant decrease in the quantity of banking institutions with insufficient capitalization subsequent to the worldwide financial crisis, as depicted in the subsequent table: Table (04): Evolution of the Percentage of Undercapitalized Banking Institutions in The United States (2006-2019) (End of Period) Year 2006 2007 2008 2009 2010 2011 2012 Less Capitalized Institutions/Total Institutions 1.04 1.58 4.36 6.24 5.57 4.66 3.59 Year 2013 2014 2015 2016 2017 2018 2019 Less Capitalized Institutions/Total Institutions 2.67 1.8 1.43 1.05 0.83 0.52 0.42 Source: Board of Governors of the Federal Reserve, 2019. A notable decrease in the number of financial institutions with inadequate capital is indicated by Table 05. These decreases coincided with the introduction of new regulations meant to raise capital adequacy ratios. By the end of 2011, the percentage of these undercapitalized institutions had dropped from 6.24% at the height of the financial crisis to 4.66%. By the end of 2016, the percentage had dropped below 1.05% in accordance with the Basel implementation plan that was suggested. The percentage of these institutions has decreased to about 0.42% by the middle of the year. The decline in the proportion of undercapitalized banking institutions is indicative of the effectiveness of banking reforms in this domain and shows how resilient the American banking industry has become in comparison to the years before the financial crisis. 7.2. Evolution of Profitability Rates in the U.S. Banking Sector Profitability rates, namely the return on assets and return on equity, serve as indications of banking institutions’ capacity to create financial returns. The capital adequacy ratio’s development in the US banking industry is displayed in the following table. Table (05): Both Return on Equity and Return on Assets in the U.S. Banking Sector (2006-2019) (End of Period) Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 ROA 1.28 0.81 0.04 -0.07 0.65 0.88 1 1.07 1.01 ROE 12.31 7.75 0.36 -0.72 5.87 7.8 8.91 9.54 9.01 Year 2015 2016 2017 2018 2019 2020 2021 2022 2023 ROA 1.04 1.04 0.97 1.35 1.29 0.72 1.23 1.11 1.1 ROE 9.29 9.29 8.61 11.98 11.38 6.85 12.21 11.82 11.5 Source: Federal Deposit Insurance Corporation (FDIC), 2024. The table illustrates a significant decrease in both return on equity (ROE) and return on assets (ROA) during the 2008 global financial crisis. In 2006, the return on assets (ROA) was 1.28%; by 2008, it had dropped to 0.04%, while the return on equity (ROE) had risen from 12.31% to -0.72% in 2009. Even if the US economy is recovering, by the end of 2010, the ROA remained below its pre-crisis level, reaching 0.65% at the end of 2010. It began to rise again in 2012 but remained nearly stable at around 1%. The ROE, although it rebounded after the crisis, never returned to its end-of-2006 level. This decline in profitability is attributed to the stringent capital and liquidity requirements that limited banking activity levels during this period. 7.3. The Volume of Non-Performing Loans in the U.S. Banking Industry The incidence of non-performing loans in the American banking industry increased before the start of the global financial crisis and reached its peak during the crisis. The table below illustrates the progression of the non-performing loan to total loan ratio in the US banking industry from 2006 to 2019. Table (06): Trends in the Non-Performing Loan Ratio in the U.S. Banking Sector (2006-2019) Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 Non-performing loans percentage 0.8 1.4 3 5 4.4 3.8 3.3 2.5 1.9 Year 2015 2016 2017 2018 2019 2020 2021 2022 2023 Non-performing loans percentage 1.5 1.3 1.1 0.9 0.9 1.1 0.9 0.7 0.8 Source: International Monetary Fund (IMF), 2024. The table indicates a substantial reduction in the non-performing loan ratio. The implementation of strict lending criteria and precise evaluation of borrowers’ creditworthiness led to a reduction in non-performing loans. The non-performing loan ratio decreased from 5% in 2009 to 1.9% at the end of 2014. The ratio dropped to 0.8% by the end of 2023, a low point akin to the two years preceding the financial crisis. 7.4. Liquidity of the U.S. Banking Sector The implementation of the final Basel Accords resulted in a significant rise in the amount of highly liquid assets within the banking sector of the United States. The following table displays the evolution of high-liquidity assets, such as cash assets, government securities, and Treasury bonds, as a proportion of all assets held by US commercial banks. Table (07): High-Liquidity Assets as a Percentage of Total Assets in the U.S. Banking Sector (2006-2019) (End of Period) Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 High-quality liquid assets / Total assets % 26 12.9 17.3 22.3 22.7 26 27.2 32 38.8 Year 2015 2016 2017 2018 2019 2020 2021 2022 2023 High-quality liquid assets / Total assets % 30.5 34.5 29.8 27.1 26.5 34 38.3 33 32.7 Source: Board of Governors of The Federal Reserve, 2023. The suggested liquidity coverage ratio by monetary authorities considers the quantity of high liquidity assets held by American banks, and the table illustrates this rapid development. Between the end of 2014 and 2021, the proportion of liquid assets, including cash, agency securities, and Treasury bonds, rose from around 17.28% of the total assets during the global financial crisis to more than 38%. Although there was a small decrease in the proportion of easily convertible assets, it remains higher than the pre-2008 financial crisis levels. This trend highlights the American banks’ move towards implementing the liquidity coverage ratio and maintaining larger liquid asset reserves to withstand periods of stress. The increasing levels of liquid assets indicate a greater capacity for banks to handle potential stress scenarios. Conclusion Due to the global economic crises, there is significant interest in the need to decrease financial deregulation and reorganize the banking sector on a worldwide scale. This aims to regulate various transactions between the banking sector and related parties, ensuring financial consumer protection on the one hand and achieving financial stability on the other. Although there are varying perspectives among theorists and researchers on the influence of banking regulation on banking performance levels, some believe that banking regulation is essential for regulating competition, enhancing banking services, and reducing risk, while others see it as having a negative impact on banking performance. In this context, the U.S. experience with banking regulation demonstrated the need for stringent application of the legislation during the 2008 global financial crisis, with an emphasis on safeguarding financial customers and enhancing the resilience and safety of systemically significant banking institutions. This had an impact on the banking industry’s cost structures, which temporarily reduced bank profitability. However, the banking industry’s resilience increased dramatically, as seen by a notable rise in the capital adequacy ratio and liquidity levels. Bibliography: Agborya-Echi, A.-N. (2010). 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The Dodd-Frank Act: Goals and progress. Hamilton Place Strategies; Spong, K. (2000). Banking regulation: Its purposes, implementation, and effects. Federal Reserve Bank of Kansas City, U.S.A. Footnotes [1] Central Bank of Ireland. (2010). What is financial regulation and why does it matter? <https://www.centralbank.ie/consumer-hub/explainers/what-is-financial-regulation-and-why-does-it-matter> [Last Access 20.04.2024]. [2] Spong, K. (2000). Banking regulation: Its purposes, implementation and effects. Federal Reserve Bank of Kansas City, U.S.A. [3]Agborya-Echi, A. N. (2010). Financial regulations, risk management and value creation in financial institutions: Evidence from Europe and U.S.A. (Master’s thesis, University of Sussex, UK). [4] Schmidt, J., Willardson, N. (2004, June 1). Banking regulation: The focus returns to the consumer. <https://www.minneapolisfed.org/article/2004/banking-regulation-the-focus-returns-to-the-consumer> [Last Access 20.04.2024]. [5] Quintyn, M. G., Taylor, M. W. (2004). Should financial sector regulators be independent? Economic Issues, 32, 2. [6] Mashaie, M. (2013). Profitability, and lending: An analysis of systemically important banks pre-2007-09 financial crisis (Master’s thesis, University of Ottawa, Department of Economics). [7] Frenkel, R. (2003). Globalization and financial crises in Latin America. CEPAL Review, 80, 39–51. [8] Biggar, D., Heimler, A. (2005). An increasing role for competition in the regulation of banks. International Competition Network Working Papers, Germany, 3–4. [9] Freixas, X., Santomero, A. (2002). An overall perspective on banking regulation. Federal Reserve Bank of Philadelphia Working Papers, No. 01-1, U.S.A., 11. [10] Almaw, S. (2018). The effect of bank regulation on the bank’s performance. Paper submitted for the partial fulfillment of the course Financial Institutions and Capital Market. Ethiopia: College of Business and Economics, Bahir Dar University, 6. [11] Psikalli, M., Mamatzakis, E. (2017). What drives bank performance in transition economies? The impact of reforms and regulations. Research in International Business and Finance, 39, 587–594. <https://doi.org/10.1016/j.ribaf.2016.09.010>. [12] Beck, T. H. K., Demirguc-Kunt, A., Levine, R. (2006). Bank concentration, competition, and crises. Journal of Banking and Finance, 30(5), 1581–1603. [13] Laeven, L., Levine, R. (2008). Bank governance, regulation, and risk taking. NBER Working Papers, 14113, Cambridge. [14] Pasiouras, F., Tanna, S., Zapounidis, C. (2009). Banking regulations, cost, and profit efficiency: Cross-country evidence. International Review of Financial Analysis, 18(5), 294–302. <https://doi.org/10.1016/j.jbankfin.2005.05.010>. [15] Barth, J. M., Caprio, G., Levine, R. (2004). Bank regulation and supervision: What works best? Journal of Financial Intermediation, 13(2), 205–248. <https://doi.org/10.1016/j.jfi.2003.06.002>. [16] Fell, J., Schinasi, G. (2005). Assessing financial stability: Exploring the boundaries of analysis. National Economic Review, 192(1), 102–117. <https://doi.org/10.1177/002795010519200110>. [17] Jomini, P. A. (2011, March). Effects of inappropriate financial regulation. Policy Brief, Sciences Po, France. [18] Klomp, J., Haan, J. D. (2015). Bank regulation and financial fragility in developing countries: Does bank structure matter? Review of Development Finance, 5(2), 82–90. <https://doi.org/10.1016/j.rdf.2015.11.001>. [19] Board of Governors of The Federal Reserve System. (2020). About the Fed. <https://www.federalreserve.gov/aboutthefed.htm> [Last Access 23.04.2024]. [20] Corporation, Federal Deposit Insurance. (2020). About FDIC. <https://www.fdic.gov/about/> [Last Access 23.04.2024]. [21] Office of the Comptroller of the Currency. (2020). About the OCC. <https://www.occ.treas.gov/about/who-we-are/index-who-we-are.html> [Last Access 23.04.2024]. [22] Consumer Financial Protection Bureau. (2020). About the Bureau. <https://www.consumerfinance.gov/about-us/the-bureau/> [Last Access 23.04.2024]. [23] Financial Stability Oversight Council (FSOC). (2020). About FSOC. U.S. <https://home.treasury.gov/policy-issues/financial-markets-financial-institutions-and-fiscal-service/fsoc/about-fsoc> [Last Access 23.04.2024]. [24] Johnston, M. (2019, 06 25). A Brief History of U.S. Banking Regulation. <https://www.investopedia.com/articles/investing/011916/brief-history-us-banking-regulation.asp> [Last Access 01.05.2024]. [25] Dempsey, M. C. (2017). Basel III Regulation and the Move Toward Uncommitted Lines of Credit. <www.lexology.com/library/detail.aspx> [Last Access 01.05.2024]. [26] Mohanta, A. (2014). Impact of Basel III liquidity requirements on the payments industry: Liquidity management strategy for banks providing payment services. CAPGEMINI Consulting Technology Outsourcing, 6. [27] Getter, D. (2014). U.S. implementation of Basel capital regulatory framework. Congressional Research Service, U.S.A. [28] Sims, P. (2013). The Dodd-Frank Act: Goals and progress. Hamilton Place Strategies, 2-4. U.S.A. [29] Markovich, S. J. (2013, 12 10). The Dodd-Frank Act. <https://www.cfr.org/backgrounder/dodd-frank-act> [Last Access 02.05.2024].
Digital Finance in Algeria: Analyzing the Impact of COVID-19 on E-Banking Adoption
This study aims to analyze the impact of the COVID-19 pandemic on the development of electronic banking in Algeria, focusing on how the health crisis has accelerated the digital transformation of the banking sector and identify the challenges and opportunities associated with this transition in a specific Algerian context. The study uses a descriptive and analytical approach. It is based on statistical data to illustrate the evolution of electronic banking in Algeria. The analysis focuses on public policies, bank initiatives, and consumer behavior. The study reveals that the COVID-19 pandemic has significantly impacted the development of e-banking in Algeria. There has been a sharp increase in digital transactions, including bank transfers, electronic payments, and ATM withdrawals. Electronic banking has played a crucial role in ensuring the continuity of financial services during the lockdown periods. However, challenges persist in terms of security, financial inclusion, and the development of digital infrastructure. Keywords: COVID-19, Electronic banking, Algeria, Digital transformation, Challenges and opportunities. Introduction The world is currently living in the era of the digital revolution, in which information technologies prevail. Advances in information and communication technologies (ICT) have revolutionized business management methods. Technology serves as an essential link between the information and business processes. ICT has had a significant influence in almost every sector,[1] and banks, like other business entities, have been leveraging ICT for many years. The health crisis with the emergence of the COVID-19 pandemic at the end of 2019 and its rapid spread worldwide threatened the collapse of the global economy, banking sector, and various vital sectors in countries. Algeria is one of the countries where this pandemic appeared, which required preventive measures to prevent the spread of COVID-19 among the population; this is the process of closing borders and all public institutions, schools, and universities and freezing various economic, financial, and banking activities to preserve the security of citizens. To ensure the continuity of the banking sector in Algeria, it was necessary to support continuous developments in the field of technology by relying on digitization through the promotion and use of information and communication technologies. Where the State has sought to redouble its efforts to meet the needs of customers and achieve digital transformation because of its various positive effects on the national economy and the banking sector, by supporting and stimulating the use of digital means and electronic processes in payment, where the general framework for the transition to a non-monetary payment system has been developed, in accordance with recognized international standards, taking into account local variables, as came after the precautionary measures imposed by the health crisis and urged by the Ministry of Health, and the National Corona Virus Monitoring and Tracking Committee, by providing the most appropriate climate for the exercise of these online operations through remote work due to the activation of social distancing, the process adopted by the banking sector, which is considered an intermediary between customers, where electronic banking or online banking services have enabled the customer to manage online transactions. Internet and technological advances have transformed the way financial services are offered and used.[2] E-banking has transformed the banking sector by providing clients with the ease of doing financial transactions at any time and from any location. Furthermore, e-banking has enhanced the effectiveness of banking procedures and reduced the cost of providing services.[3] Banks and various financial institutions offer innovative and alternative electronic channels to maintain competitive advantage and meet customer expectations, and banking institutions offer various types of electronic banking services. These include ATMs, e-wallets, debit cards with chips, electronic payment terminals (EDCs), mobile banking, and online banking.[4] Customers are increasingly using their mobile devices and desktops to make payments for products and services through online banking.[5] Global e-banking played a pivotal role during the COVID-19 pandemic by operating entirely electronically without exchanging tangible goods to protect people and maintain social distance so that people feel completely safe and easily accessible in online transactions (such as payments for essential items (food and medicine), billing, top-up, money transfer, receipt of payments, etc.) Online banking is now an essential e-commerce application adopted by financial institutions to satisfy the growing demands of their customers and remain at the forefront of technological advances.[6] This study helps us understand how the COVID-19 pandemic accelerated the digital transformation of the banking sector in Algeria. As digitalization becomes essential worldwide, it is crucial to see how a country like Algeria has responded and adapted its banking services to this new reality. It also highlights the Algerian banking sector’s challenges, including security, financial inclusion, and digital infrastructure. At the same time, it explores the opportunities created by this digital transition, such as the potential to improve access to financial services for a more significant portion of the population. This study aims to review the evolution of electronic banking services in Algeria, focusing on recent developments related to the COVID-19 pandemic. The subsequent sections of this document are organized as follows: Section two provides a literature review. Section three outlines the conceptual framework. Section four discusses the role of the pandemic in accelerating the digitalization of the banking sector in Algeria. Section five examines the contribution of digital financial services to economic recovery. Finally, section six summarizes the progress in implementing electronic banking services in Algeria and suggests avenues for future research. Literature Review The rapid advancement of information and communication technologies has revolutionized the banking sector, leading to the widespread adoption of electronic banking.[7] E-Banking is an innovative tool that is rapidly becoming a necessity and a strategic asset for banks to remain profitable in a competitive market.[8] The Covid-19 pandemic accelerated this transformation, with lockdowns and social distancing measures requiring the use of digital channels. Several key factors influencing customer satisfaction with electronic banking services in Libyan banks. These factors include perceived usefulness, ease of use, credibility, and customer attitudes[9]. This study reveals that customer attitude is the most important factor, followed by ease of use, credibility, and perceived usefulness. These findings suggest that banks need to focus on these aspects to improve customer satisfaction. The adoption of electronic banking by Algerian customers is analyzed through factors such as technological acceptance, ease of use, and transaction security[10]. This study highlights that key barriers to adoption include security concerns and a lack of awareness of the benefits of e-banking. Suggested strategies to improve adoption include strengthening security measures and increasing awareness of the benefits of e-banking. In addition, another study also explores the relationship between the quality of electronic banking services and customer satisfaction with financial services, identifying key factors such as reliability, efficiency, and security[11]. This study provides empirical evidence of the importance of these factors in improving customer satisfaction and proposes strategies for banks to improve their e-banking services. The use of digital financial services has increased significantly, especially in developing economies where access to traditional banking services is limited.[12] During the COVID-19 pandemic, e-banking has highlighted its role in operating entirely electronically without exchanging tangible goods to protect people and maintain social distancing. People feel completely safe and easily accessible in online transactions (e.g., payments for essential items (food and medicine), billing, top-up, investment, money transfer, and receiving payments).[13] Digital financial services have enabled governments to disburse money to those who need it quickly and efficiently and have enabled many households and businesses to quickly access payments and financing online. Risks to stability and integrity may exist, which could be exacerbated if the use of digital financial services is rapidly expanded in times of crisis without appropriate regulations and safeguards.[14] Electronic financial services, developed during the 2008 financial crisis, played a crucial role in addressing the challenges posed by the COVID-19 pandemic[15]. The use of modern financial technology positively affects the work and policies of banks and financial institutions.[16] The pandemic has accelerated the digitization of banking services by several years, forcing banks to modernize their infrastructure and improve their online user experience.[17] The use of electronic payment methods in the Corona era accelerated and facilitated financial transactions and provided security.[18] The impact of COVID-19 on digital banking, noting a significant acceleration of digital transformation in the banking sector. Customers prefer these channels to traditional methods because of their convenience and security.[19] The pandemic has pushed banks to modernize their legacy systems to meet growing customer expectations.[20] To examine the impact of the COVID-19 pandemic on the adoption of online banking services in Indonesia, comparing the effects on Islamic and conventional banks, the study shows that the pandemic has significantly boosted the use of these services. Factors such as perceived usefulness, ease of use, and trust have proven to be crucial in this process[21]. This demonstrates the importance of meeting customer needs and preferences to drive the adoption of digital services. Traditional banks face several challenges when adapting to the digital age. These challenges include the need to update legacy systems, ensure the security of digital transactions, and address customer concerns about privacy and trust[22]. To overcome these challenges, banks should prioritize improving the perceived usefulness, ease of use, and credibility of their e-banking services. In addition, targeted marketing campaigns and incentives can help improve customer attitudes towards digital banking. The COVID-19 pandemic has catalyzed the development and adoption of e-banking across the globe, with banks investing heavily in technology to facilitate remote transactions and ensure the continuity of services during lockdowns.[23] Digital banking has played an important role in improving financial inclusion.[24] Fintech solutions play a crucial role in the banking industry’s digital transformation.[25] Fintech companies have introduced innovative financial services that are profitable, efficient, and convenient, thereby improving their financial inclusion. For example, digital wallets and peer-to-peer lending have enabled individuals and SMEs to access financial services without going through the strict processes of traditional banks.[26] Concept of Electronic Banking Services Electronic banking is defined as the conduct of banking operations using modern information and communication technologies, whether for withdrawal, payment credit,[27] transfer, securities trading, or other banking activities. It is also defined as the provision of banking services using information and communication technologies through the Internet, automated vending machines, private networks, mobile phones, and fixed and personal accounts. Banking service is available after and within 24 hours, every day of the week, at high speed, at a lower cost, and without a meeting place between the customer and the bank.[28] There are several types of electronic banking services, which are services that depend on the use of the Internet and rely on highly skilled human frameworks[29] and community trust in financial institutions, and the development of e-commerce in this environment. The Role of the COVID-19 Pandemic in Accelerating the Digitization of the Banking Sector in Algeria The Coronavirus has contributed to the acceleration of digitization in the banking sector in Algeria, where account-to-account transfers have reached a recovery, registering more than 2.9 billion dinars in 2020, an increase of 137% compared to 2019. Electronic payment has also been upgraded, and the number of transactions related to electronic payment services via the golden card has increased significantly, with more than 6.6 million cards with 3.8 million renewed cards issued in 2020. The Golden Card also recorded nearly 4 million transactions in 2020 compared to 2019 (about 670,000), an increase of 487% in one year. The new self-payment service launched by Algeria Post via the Postal Mob application (which allows Gold cardholders to schedule the transfer of funds from a current postal account to other postal accounts) increased by 557% in transfers in one year (991,991 transactions in 2020 compared to 150,992 transactions in 2019). The same goes for payments via the electronic payment terminal (EPT), which increased by 773%, in addition to ATM withdrawals, which amounted to DZD 956 billion, an increase of 15% compared to 2019.[30] The spread of the Coronavirus has forced the government to look for ways to develop electronic programs used in virtual transactions using the Internet between the customer and the banking and banking institution through virtual marketing, improving the quality of remote banking services and their expansion in Algeria, facilitating the adoption of receiving funds and allowing the receipt of hard currency funds, even partially, on “Western Union” in addition to establishing clear mechanisms for the process of sending money abroad that are distributed to all banks, and the establishment of bureau de change to ease the control of parallel markets. The state was able to reach the neediest groups through social transfers and other financial aid through digital financial services. In the era of the Corona pandemic, it is crucial to prioritize the augmentation of transfer money allocated to beneficiaries and promote the use of digital operations. Amidst the current circumstances, digital financial services aid companies in resolving pressing liquidity issues. They facilitate seamless communication with financial service providers, expedite the withdrawal of funds from existing credit lines, and provide alternative financing options to offset the scarcity of liquidity in conventional financial operations. How Can Digital Financial Services Pave the Way for Economic Recovery in Algeria? Algeria and the MENA area have experienced economic shocks worsened by the coronavirus epidemic, leading to decreased oil prices. The most recent estimates from the Economic Observatory indicate that the Algerian economy had a substantial decline in real GDP for 2020. Algeria’s pursuit of digital transformation, a prominent development objective before the epidemic, has become crucial in the country’s recovery efforts. Access to cheap financial services is crucial for reducing poverty, promoting economic development, and building resilience. It also facilitates financial inclusion, particularly for women. In Algeria, a significant portion of the population currently needs access to basic transaction accounts, with 57% of adults and 71% of women unable to safely and effectively make and receive payments. Consequently, they needed to provide access to more extensive financial services such as savings, insurance, and credit. In conjunction with conventional financial service providers, financial technology can decrease expenses, enhance efficiency, ensure safety and transparency, and provide more secure financial services. Expanding the availability of digital payment options would serve as an entry point for Algerians who need to be more knowledgeable about the financial industry to utilize digital financial services. The expansion of mobile phones in many developing nations has been used by mobile financial services to initiate the “first wave” of digital financial services. Despite having better access to mobile broadband networks than the MENA average, the adoption of digital financial services in Algeria still needs to grow. Only 16% of Algerian adults and 11% of women utilize digital payments, whereas the regional average is 23% for adults and 18% for women. In comparison, emerging and developing countries have a significantly higher adoption rate, with 36% of adults and 32% of women using digital payments. While many countries have begun to address the underlying enablers of digital financial services and digital payments management, they need vital enablers, enabling legal and regulatory frameworks, financial and digital infrastructure, and ancillary government support systems. To address these three areas, policymakers need to consider a wide range of critical issues, ranging from basic digital connectivity and mobile penetration, access to national payment infrastructure and e-money, non-banking services or the deployment of digital and biometric identity systems, enabling access to government data platforms and ensuring competition for digital financial services.[31] The benefits of financial services for the poor are well documented; however, they carry risks for users and the broader financial system: issues related to data privacy, unequal access to technology and the “digital divide”, cyber security and operational risks, financial integrity, and challenges for competition authorities. This requires high regulation, control, and supervision by the competent authorities. The Development of Certain Electronic Banking Services in Algeria Digital financial services provide governments with expedient and secure means to assist those in need via social transfers and other financial help, particularly when mobility is risky or restricted. Prior to the onset of the coronavirus crisis, it was evident that two specific applications of digital financial services, excluding mobile money transfers, money transfers, and government-to-person payments, were especially advantageous for impoverished individuals. Based on the World Bank’s Global Remittance Prices Database data, the average overall cost of sending funds is 6.8%; however, digital transactions will reduce the cost to 3.3%. According to Findex statistics, many Algerians own a bank account, although they continue using services outside their bank accounts for domestic transactions. Hence, augmenting the financial resources allocated to remittance beneficiaries and promoting digital platforms is crucial. Implementing digital payment systems may enhance the transparency and oversight of governments that provide emergency cash to individuals and enterprises by facilitating the monitoring of financial disbursements and actions. Digital financial services provide solutions for companies facing liquidity issues, allowing them to engage with financial service providers, access credit quickly and seamlessly, and secure alternative financing options. These services are helpful not only for addressing liquidity gaps in traditional financial channels but also for supporting innovative business models that cater to underserved populations. Significant e-commerce platforms are becoming more critical as Jumia expands its operations into Algeria to join existing local platforms like OuedKnis, Batolis, and IdealForme. Telecommunications operators have used the capabilities of digital financial services to streamline payments and provide pay-as-you-go options for solar energy, insurance, and loan services. Although Algeria has made strides in supporting fintech technologies and advancing digital financial services, there is still room for improvement in increasing awareness of their advantages and fostering their expansion. Algeria aims to promote economic activity and improve the lives of its residents by increasing the availability of digital financial services. This will enable individuals to grow their wealth, make productive investments, and, most importantly. Electronic banking services in Algeria have made good progress in recent years. Most Algerian banks have set up mobile applications and online banking services through which customers can carry out banking transactions such as checking their balance, transferring funds, paying bills, etc. The advent of electronic debit cards (CIB, Visa, and MasterCard) has also facilitated access to online banking services. Fig.1. Check of balance by phone or Internet in Algeria (+15%) Source: Prepared by researcher based on World Bank data <https://www.worldbank.org/en/publication/globalfindex/Data> This chart effectively communicates the steady growth in digital banking adoption in Algeria, mainly using mobile and Internet technologies for essential banking functions such as checking account balances. The graph shows a gradual increase in the use of mobile phones or the Internet to check the balance of accounts from 2011 to 2021. In 2011, usage was minimal; there was a slight increase in 2014, with a notable increase in 2017. The most significant growth in 2021 indicates a significant adoption of numerical account balance verification. This increase could be influenced by increased Internet penetration, the development of online banking, and increased public awareness and confidence in digital banking in Algeria. This period also coincides with global trends in digital transformation and the impact of the COVID-19 pandemic, which has accelerated the adoption of digital services across the globe. This rise is fuelled by several factors, such as the proliferation of mobile devices, improved internet access, emerging online banking services, and increasing public awareness and confidence in Algeria’s electronic banking environment. It is also an era of global digital transformation, boosted by the COVID-19 pandemic, which has led to the rapid implementation of digital service proposals worldwide. Fig.2. Digital payment in Algeria (% aged 15 +) Source: Prepared by researcher based on World Bank data https://www.worldbank.org/en/publication/globalfindex/Data Both graphs show that there has been a general increase in digital payment activities in Algeria between 2014 and 2021. However, the growth rate differs between those who make payments and those who receive them. Approximately 10% of people aged 15 and older have made a digital payment. This percentage increased to around 12%, showing modest growth in digital payments adoption over three years. The percentage continues to increase to around 15%. This suggests an increasing trend in the use of digital means of payment among the Algerian population, probably due to the expansion of digital infrastructure and a better familiarity with digital transactions. This concerns the Digital Payments received (% aged 15 and over) in Algeria. In 2014, approximately 20% of people received digital payments. In 2017, the percentage decreased slightly to around 15%, showing a decline in the receipt of digital payments during this period. The percentage rebounded significantly in 2021 to around 25%, indicating strong growth in the receipt of digital payments. The sharp increase in digital payments received between 2017 and 2021 may reflect broader economic or social changes, such as increased trust in digital payment systems, increased e-commerce, government initiatives to promote digital financial inclusion, the effects of the COVID-19 pandemic, which may have accelerated the shift to digital transactions. Fig. 3. The adoption of online services (purchases and bill payments) in Algeria Source: Prepared by researcher based on World Bank data <https://www.worldbank.org/en/publication/globalfindex/Data> In 2017, less than 5% of people aged 15 and over made online purchases; in 2021, this percentage reached about 8%, indicating a growing trend towards online shopping. In 2017, around 2% of the population aged 15 and over used online services to pay their bills; in 2021, this doubled to around 4%, reflecting a growing adoption of digital payment methods. Both graphs show an upward trend in adopting online services (purchases and bill payments) between 2017 and 2021 among Algerians aged 15 and over. This can be attributed to increased internet penetration, better smartphone access, and a shift to digital platforms, potentially accelerated by the COVID-19 pandemic. The data suggests that Algerians are increasingly embracing digital platforms for shopping and paying bills, reflecting a broader trend toward digital transformation in the country. Increased digital engagement could provide businesses and decision-makers opportunities to develop e-commerce and digital payments infrastructure further. Conclusion This study has highlighted the significant acceleration of the digital transformation of the banking sector in Algeria, largely due to the COVID-19 pandemic. As the world turned to digital solutions to overcome the restrictions imposed by the health crisis, Algeria also embraced this trend, adopting digital technologies to maintain the continuity of financial services. The findings show that despite progress, the Algerian banking sector still needs to overcome several challenges to capitalize on this transformation fully. Issues of security, limited financial inclusion, and still underdeveloped digital infrastructures still need to be addressed. However, the post-pandemic period offers unique opportunities to overcome these challenges, with the rise of digital financial services and the possibility of further innovation to meet the growing needs of consumers. Ultimately, the ability of the Algerian banking sector to continue evolving and adapting to this new digital era will determine its resilience and future success. Concerted efforts by regulators, financial institutions, and the government must be made to ensure an inclusive, secure, and sustainable digital transition, thereby ensuring that all segments of society can benefit from this transformation. Authorship of the Work All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication. Conflicts of Interest The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding Information This research has not been funded. Bibliography: 1. Agency, A. P. (2022). Electronic payment “evolved” due to the COVID-19 pandemic in Algeria. Retrieved on April 2, 2024. (in Arabic); 2. Allada, V., Dubey, R., Agarwal, S. (2014). 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Electronic Banking as an Approach to Modernizing Algerian Banks. Proceedings of the National Symposium on the Algerian Banking System and Economic Transformations - Realities and Challenges - University of Chlef, Algeria, 98. (In Arabic). [28] Nourine, B., Kandouz, A. (2007). Electronic Banking in Banking Institutions as an Approach to Building the Digital Economy in Algeria. Afak Journal, 04, 21. (in Arabic). [29] Tala, L. (2020). Electronic Administration and Modernization of Public Service: A Strategic Technological Choice for Administrative Reform. Al-Asil Journal of Economic and Administrative Research, 42. (in Arabic). [30] Agency, A. P. (2022). Electronic payment “evolved” due to the COVID-19 pandemic in Algeria. Retrieved April O2, 2024. (in Arabic). [31] Report, W. B. (2015). Aspects of Payment by the Committee on Payments and Market Infrastructures.
Forecasting Customer Bank Behavior Using Weka and Classification Algorithms
Banks derive significant profits from loans, necessitating careful customer selection to mitigate default risks. This study analyzes customer behavior at Société Générale Algeria Bank using three classification algorithms and using Weka software. A dataset comprising 300 customers was evaluated with three algorithms: Bayesian Network, Naïve Bayes, and the J48 Decision Tree. The goal of this study was to identify the most effective algorithm for classifying prospective customers as acceptable or not for loan approval. The performance of these algorithms was compared, focusing on accuracy and reliability. The results of this study indicated that the J48 Decision Tree algorithm outperformed the other methods, demonstrating superior classification accuracy. This suggests its potential as a robust tool for optimizing decision-making processes in the bank’s loan system. By integrating the J48 Decision Tree into its operations, the bank could enhance its ability to identify suitable customers, minimize risks, and ensure sustainable profitability in its lending practices. Keywords: Data Mining, Weka, Bank, Loans, Classification Algorithms. Introduction Banks and businesses alike are in a volatile, pressured world. They need to be more responsive to customers, helping them manage finances and access services quickly and easily on their channel of choice while at the same time delivering operational efficiencies. To accomplish that, these modern banks are not only employing management information systems but are also starting to introduce robust data mining practices more and more into their core business processes. Data mining, the process of identifying hidden patterns from the data that are relevant to the business, is considerably practical in the business area and yields successful results.[1] The data mining methods are benefiting from ever-developing technology, and people are also intensifying their efforts. Over 60% of banks are currently using data mining methods to help them gain a better understanding of their customers’ behaviors. One of the best-known open-source tools for data mining practice is Weka. Weka contains tools for data pre-processing, classification, regression, clustering, association analysis, and visualization and allows for output model and inclusion function diagrams.[2] The dataset used in the study contains financial transactions associated with people. The study has considered the prediction of customer banking behavior, and for this, several algorithms of the Weka tool are applied. The necessity of being able to predict the future possible application of the customer is needed to prevent possible negative results. The aim is to determine whether or not the account of the customer will be open or closed in the future. The methods applied are Naive Bayes Classifier, Random Tree Classifier, J48 Classifier, SMO Classifier, and Simple Logistic Classifier. The best success result has been achieved with the J48 Classifier. With the data mining methods, marketing campaigns for the customer can be applied, and business strategies can be developed and tailored to the target customers’ behaviors. Literature Review A Classification-based model to assess customer behavior in the banking sector.[3] This study used three classifiers, K-NN, decision tree, and artificial neural networks, for predicting customer behavior in the banking sector, and this study concluded that Artificial neural networks (ANNs) outperform both decision trees (DTs) and k-nearest neighbors (k-NNs). A Case Study of Predicting Banking Customers’ Behaviour by Using Data Mining.[4] In this study, the proposed data mining framework manages the relations between banking organizations and their customers, the results indicate that the Neural Network model achieves better accuracy but takes a longer time to train the model. An Efficient CRM-Data Mining Framework for the Prediction of Customer Behaviour.[5] The goal of this study is to predict the behavior of customers to enhance the decision-making processes for retaining valued customers, using two classification models, Naïve Bayes, and Neural networks, in the end, the results show that the accuracy of Neural Network is comparatively better. A Prediction Model for Bank Loans Using Agglomerative Hierarchical Clustering with Classification Approach.[6] The goal of this study is to leverage machine learning techniques to enhance decision-making processes in the banking sector, it reached the following findings: the data with decision tree obtained an accuracy of 84%, with the random forest obtained an accuracy of 85% Methodology Data mining is a scientific and computational process used to extract knowledge represented by hidden relationships in large datasets. It relies on various computational and statistical tools and techniques to enable machines to learn and deduce new knowledge. Below, we introduce the algorithms used in our data mining study and the Weka software utilized for different stages of the study. 3.1. Bayesian Network Algorithm (Bayes Net Classifier) This probabilistic model addresses the problem of interdependent relationships among variables. It is used for the formal representation of variables and probabilistic relationships in a network structure called a Bayesian network, which consists of nodes (representing variables) and links (indicating relationships between variables). This network structure assumes that parent variables influence others, relying on mathematical and statistical principles such as conditional probability.[7] Conditional Probability: P(A/B) This represents the occurrence of event A, given that event B has occurred. It is expressed by the following phrase: (1) Chain Rule of Probability This rule allows us to express the joint probability of multiple variables using conditional probabilities. For example, given three variables A, B, and C, we can express it with the following formula: (2) Bayes’ Rule or Bayesian Theorem Bayes’ rule allows us to calculate the conditional probability of a hypothesis H given evidence E, using the likelihood of the evidence given the hypothesis and the prior probability of the hypothesis. It is expressed by the following formula: (3) Where: P(H/E) is the posterior probability of the hypothesis H given the evidence E. P(E/H) is the likelihood of the evidence E given the hypothesis H. P(H) is the prior probability of the hypothesis H. P(E) is the probability of the evidence E. The Structure of the Bayesian Network The Bayesian network is represented by a directed acyclic graph (DAG), where the nodes represent variables, and the directed edges represent probabilistic dependencies between the variables. The structure of the Bayesian network encodes the conditional probability distribution over all the variables.[8] 3.2. Naïve Bayes Classifier The Bayesian Theory, Named after Thomas Bayes, this theory is vital in probability studies. It relates the probability of event A given event B to the probability of event B given event A. (4) Naïve Bayes classification organizes information into categories by making predictions based on a simplistic assumption that all variables are independent, though this is often not realistic. Despite this assumption, Naïve Bayes works effectively in fields such as healthcare.[9] The basic idea of the Naive Bayes classifier is to determine the probability that a person with certain characteristics (X) belongs to a particular group (class). It assumes that these characteristics are independent of each other and calculates the probabilities accordingly. Then, it selects the group with the highest probability as the most likely group for that person. Let Ci​ be the individual’s class, and X the characteristics. This probability is expressed by the following statement:[10] (5) 3.3. Decision Tree Algorithm (J48) The J48 algorithm, an improved version of the C4.5 algorithm,[11] classifies data by building a tree model that relies on sequential decisions. Each branch in the tree represents a decision, and the leaves represent final classifications. In data mining, decision trees help to describe, classify, and generalize specific datasets.[12] Tree Structure The internal non-terminal nodes are tests and are called decision nodes. The branches are the outcomes of these tests. The terminal leaf nodes represent decisions and are referred to as default classes. Each leaf represents a decision for a specific class based on all the tests performed from the root to that leaf. Figure 01: The decision tree diagram Source: prepared by the researcher[13] 3.4. Model Evaluation Confusion Matrix Using the confusion matrix and performance indicators like accuracy, sensitivity, and error rate, we evaluated the model’s performance, assessing correct and incorrect classifications.[14] Performance Metrics These indicators are calculated based on the confusion matrix (Adnan, Sarno, & Sungkono, 2019, 124) [15]: We use the following symbols: VP: True Positive; FP: False Positive; VN: True Negative; FN: False Negative; P: Total number of positive observations; N: Total number of negative observations. Error Rate = (FP + FN) / (N + P), which represents the percentage of individuals or observations that the model classified incorrectly. Sensitivity = VP / (VP + FN), which measures the model’s ability to detect true positives. Specificity = VN / (VN + FP), which measures the model’s ability to correctly identify true negatives. Accuracy = (VP + VN) / (N + P), which represents the percentage of individuals that the model correctly predicted. Empirical Result and Discussion The data mining study using Weka followed these steps: data collection, training, application of classification algorithms, and selection of the optimal classification model to make predictions on new classifications. Figure 02: Study Stages Using the Data Mining Methodology Source: Prepared by the Researcher Study Variables The study aimed to create a model aiding bank consultants in decision-making regarding loans. Variables considered include previous credit history, loan purpose, salary, gender, housing status, loan duration, and age. The sample comprised 300 customers. Descriptive Study of Study Variables The following section presents various statistics for each variable. The Weka software displays detailed information for each variable. Figure 03: Statistics for All Variables Source: Outputs of the Weka Software For instance, regarding the customer’s previous loans variable, 133 customers had no prior loans, 74 had paid off all their loans, 31 had delayed payments, and 62 still had outstanding balances. The loan purpose variable showed that 125 customers took loans for household appliances, 61 for home layouts, and 114 for purchasing a motorcycle. The income variable ranged between 25,000 DZD and 125,000 DZD. For the gender variable, 158 were male and 142 were female. The loan value variable ranged from 180,000 DZD to 1,800,000 DZD. The age variable spanned from 20 to 71 years. In terms of housing status, 74 customers owned their homes, 131 rented, and 95 lived in free accommodations. The loan term ranged between 3 and 7 years. The customer classification variable resulted in 192 classified as ‘good’ and 108 as ‘bad’. Study Results The classification process involves grouping data based on shared variables in the form of categories. To achieve this, data mining offers numerous classification algorithms, including those used in this study: Naïve Bayes Algorithm; Bayesian Network Algorithm; J48 Decision Tree Algorithm. These algorithms were applied to create a model to predict the behavior of new loan-seeking customers. The results were as follows: Classification Results with J48 Decision Tree Algorithm After applying the J48 algorithm using Weka on the sample under study, the results were as shown in the following table: Figure04: Results of the J48 Decision Tree Algorithm Source: Outputs of the Weka Software After applying the J48 algorithm using Weka on the sample data, the results are shown in the following table. We observe that the Kappa statistic has a value of 0.58, indicating a moderate agreement between predicted classifications and actual data categories. The model’s classification accuracy was 81%, correctly classifying 243 customers, while 19% (57 customers) were misclassified. Classification Results with Bayesian Network Algorithm After applying the Bayesian Network algorithm using Weka on the sample under study, the results were as shown in the following table: Figure05: Results of the Bayesian Network Algorithm Source: Outputs of the Weka Software The Bayesian Network algorithm, when applied with Weka on the sample data, showed a Kappa statistic of 0.55, indicating a moderate level of agreement between predicted and actual classifications. The model’s accuracy was 80.33%, correctly classifying 241 customers, while 19.66% (59 customers) were misclassified. Classification Results with Naïve Bayes Algorithm After applying the Naive Bayes algorithm using the Weka program on the sample under study, the results are as shown in the following table: Figure06: Results of the Naive Bayes Algorithm Source: Outputs of the Weka Software The Naïve Bayes algorithm produced a Kappa statistic of 0.36, indicating a lower agreement level. The model achieved a classification accuracy of 68.66%, correctly classifying 206 customers, while 31.33% (94 customers) were misclassified. Selecting the Optimal Classification Algorithm The following table shows the performance metrics for the three algorithms, based on which we determined the optimal algorithm: Table 01: Evaluation Metrics for the Three Algorithms Indicator J48 Algorithm Bayesian Network Algorithm Naive Bayes Algorithm Sensitivity 0.810 0.803 0.687 False Positive Rate 0.241 0.265 0.294 Accuracy 0.808 0.801 0.719 F-Measure 0.808 0.799 0.693 MCC 0.581 0.563 0.378 ROC Area 0.842 0.863 0.819 PRC Area 0.825 0.875 0.832 Source: Prepared by the researcher based on Weka software. The J48 Decision Tree algorithm achieved the highest classification accuracy, making it the best choice for customer classification in this case. Decision Tree Diagram Below is the decision tree diagram obtained using the J48 algorithm: Figure 07: J48 Decision Tree Source: Weka Software Outputs Predicting New Cases of Prospective Loan Customers To verify the quality of the obtained model, we tested it on five customer cases with known outcomes, and the results were as follows: Figure 07 represents the decision tree obtained from the J48 classification algorithm, which will be used to predict the status of new loan applicants. The figure illustrates the decision tree followed by decision-makers in the institution under study to determine or predict customer behavior. The tree considers all cases, and when applied to the cases shown in the following table, the results are as follows: Table 02: prediction results Previous Loan Status Loan Purpose Monthly Income Gender Loan Amount Age Housing Status Loan Payment Term (Years) Actual Classification Predicted Classification Has outstanding payments Motorcycle purchase 25,000 Male 340,000 28 Homeowner 3 Poor Good Payment delays Home appliances 25,000 Female 280,000 30 Rented 4 Poor Poor Fully paid Home appliances 60,000 Female 640,000 39 Rented 4 Good Good No previous loans Home renovation 59,000 Male 890,000 60 Homeowner 5 Good Good Has outstanding payments Home renovation 82,000 Male 600,000 54 Free 6 Poor Poor Source: Prepared by the researcher using J48 Decision Tree From the table, we have five out-of-sample cases. We predicted each case’s behavior based on the J48 decision tree, and almost all results matched the actual classifications except for the first case. In that instance, the true classification categorized the customer as “Poor,” while the decision tree classified them as “Good”. Analysis of Study Results Three different classification algorithms were applied: the J48 decision tree algorithm, the Naive Bayes algorithm, and the Bayesian Network algorithm. These were implemented using Weka software, with a sample of 300 customers for whom all relevant variables were available and whose loan behavior was known. Classification was based on whether the customer was “Good” or “Bad” for the loan. The model was trained using cross-validation, and the results were as follows: Using the correct classification rate as the evaluation criterion, J48 Decision Tree had the highest accuracy at 81%. To evaluate this model’s performance, the indicators were as follows: Kappa Statistic: The kappa coefficient was 0.58, indicating moderate agreement between predicted and actual classifications, suggesting a reliable classification model, though some error is present. Correct Classification Rate: The model’s accuracy reached 81%, equating to 243 correctly classified customers, as indicated by the sensitivity metric, which reflects the model’s capability to detect correct classifications. Incorrect Classification Rate: The error rate was 19%, corresponding to 57 misclassified customers. False Positive Rate (FP Rate): The FP rate was 0.24, meaning that 24% of negative cases were incorrectly classified as positive. Precision: The model’s precision reached 0.808, as reflected in the F-measure, indicating that 80.8% of cases predicted as positive were indeed positive, while 19.2% were incorrectly classified as positive. ROC Area: The ROC area was 0.842, indicating a reasonable ability of the model to distinguish between positive and negative cases, with an 84.2% probability that a randomly selected positive case would be correctly classified over a negative one. PRC Area: With a PRC area of 0.825, the model demonstrated a good balance between precision and recall for distinguishing positive and negative cases. The final form of the decision tree comprised 36 nodes with 21 leaves. The root node was represented by the “Credit History” variable, indicating its primary influence on loan eligibility decisions. We used this model to predict the behavior of loan-seeking customers with a sample of 5 customers outside the previously used dataset. The results were satisfactory, as 4 out of the five customers were classified correctly. Conclusion This methodology contributes to the early prediction of the behavior of loan-seeking customers in the banking institution, providing decision-makers, such as customer advisors, with a preliminary understanding of the individual’s behavior. This, in turn, enhances and rationalizes decision-making. It allows decision-makers to reject cases where indications suggest that the customer might be unsuitable for the loan, thereby reducing the risk of dealing with clients who are unable to repay loans and improving the overall quality of the bank’s clientele. Bibliography: 1. Adedipe, T., Shafiee, M., Zio, E. (2020). Bayesian network modeling for the wind energy industry: An overview. Reliability Engineering & System Safety, 202, 107053. <https://doi.org/10.1016/j.ress.2020.107053>; 2. Adnan, M., Sarno, R., Sungkono, K. R. (2019, September). Sentiment analysis of restaurant reviews with a classification approach in the decision tree-J48 algorithm. 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In 2022, the 3rd International Conference on Intelligent Engineering and Management (ICIEM). IEEE. <https://doi.org/10.1109/ICIEM54221.2022.9853036>; 7. Kaur, G., Oberai, E. N. (2014). A review article on Naive Bayes classifier with various smoothing techniques. International Journal of Computer Science and Mobile Computing, 3(10); 8. Kulkarni, E. G., Kulkarni, R. B. (2016). Weka: Powerful tool in data mining. International Journal of Computer Applications, 975(8887). 9. Larranaga, P., Karshenas, H., Bielza, C., Santana, R. (2013). A review on evolutionary algorithms in Bayesian network learning and inference tasks. Information Sciences. <https://doi.org/10.1016/j.ins.2012.12.051>; 10. Lee, C. S., Cheang, P. Y. S., Moslehpour, M. (2022). Predictive analytics in business analytics: Decision tree. Advances in Decision Sciences, 26(1); 11. Rahman, A., Khan, M. N. A. (2018). A classification-based model to assess customer behavior in the banking sector. Engineering, Technology & Applied Science Research, 8(3); 12. Thuraisingham, B., Maning, D. (1999). Technologies, techniques, tools, and trends. CRC Press; 13. Wickramasinghe, I., Kalutarage, H. (2021). Naive Bayes: Applications, variations, and vulnerabilities: A review of the literature with code snippets for implementation. Soft Computing, 25(3). <https://doi.org/10.1007/s00500-020-05297-6>; 14. Zhou, X., Bargshady, G., Abdar, M., Tao, X., Gururajan, R., Chan, K. C. (2019, October). A case study of predicting banking customers’ behavior by using data mining. In 2019, the 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC). IEEE. <https://doi.org/10.1109/BESC48373.2019.8963436>. [1] Thuraisingham, B. (1999). Technologies, techniques, tools, and trends. CRC Press, 1. [2] Kulkarni, E. G., Kulkarni, R. B. (2016). Weka: A powerful tool in data mining. International Journal of Computer Applications, 975(8887), 10. [3] Rahman, A., Khan, M. N. A. (2018). A Classification Based Model to Assess Customer Behavior in Banking Sector. Engineering, Technology & Applied Science Research, 8(3). [4] Zhou, X., Bargshady, G., Abdar, M., Tao, X., Gururajan, R., Chan, K. C. (2019, October). A case study of predicting banking customers’ behavior by using data mining. In 2019 6th international conference on behavioral, economic and socio-cultural computing (BESC), (1-6). IEEE. [5] Bahari, T. F., Elayidom, M. S. (2015). An efficient CRM-data mining framework for the prediction of customer behaviour. Procedia computer science, 46, 725-731. [6] Arowolo, M. O., Adeniyi, O. F., Adebiyi, M. O., Ogundokun, R. O. (2022). A Prediction Model for Bank Loans Using Agglomerative Hierarchical Clustering with Classification Approach. Covenant Journal of Informatics and Communication Technology. [7] Larranaga, P., Karshenas, H., Bielza, C., Santana, R. (2013). A review on evolutionary algorithms in Bayesian network learning and inference tasks. 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Key Aspects of Implementation of Participatory Budgeting Model in Georgian Municipalities
The article, based on the latest literary sources and factual materials, consistently studies such an important issue of financial theory and economic practice as the key aspects of implementing participatory budgeting in Georgian municipalities. The factors affecting the effectiveness of the implementation of the participatory budgeting model are discussed: the urban structure of the municipality, the size of the budget of the municipality, and the development of civil society. It is determined that any model of participatory budgeting should adhere to the following principles: model design and implementation procedures should be based on good management principles; The selected procedures should take into account the specific context of a particular municipality, including urban structure, budget size, and population participation; At the planning stage, active actors of the model, interested parties should be identified and their rights and duties defined; The model should fully comply with the legislation of Georgia and the established forms of citizen participation. Based on the international experience and the reality of Georgia, the factors affecting the effectiveness of the implementation of the participatory budgeting model are discussed: the urban structure of the municipality, the size of the municipality’s budget, and the development of civil society. It stands to reason that any participatory budgeting model should have, as a minimum, the following working procedures: population group meetings, information campaigns, development and submission of project proposals, voting, and final decision, and Evaluation of participatory budgeting process and work procedures. Keywords: participatory budgeting, city-type municipality, subsidized municipal unit, Deming cycle, urban development, civil society, project proposal. I. Introduction Since the 1990s, the formulation of a “participatory budgeting model” or “participatory budgeting process” has increasingly appeared in scientific discourse, which was more closely associated with the activities of local government bodies. However, later, it was associated with other spheres, such as educational and/or social service organizations. As a result, we have the reality that various models of participatory budgeting are being actively implemented in an increasing number of cities, municipalities, and organizations around the world, more and more people are involved in the processes, and both the population and the state benefit more. The participatory budget process is one model of participatory democracy in which the population decides what to allocate municipal and state budget funds and then checks the effectiveness of the use of the allocated resources. This approach to the state budgeting process allows citizens to identify, discuss, and prioritize projects to be funded by public spending and empowers them effectively to make real decisions about how money is spent. The local specifics of a particular municipality, the combination of goals and objectives declared by its executive and representative authorities, provide the diversity that currently characterizes the models of participatory budgeting. As a result of their systematization, a typology of participatory budgeting was developed in 2012, through which all the existing models were described, and the following six models of participatory budgeting were identified: Participatory Democracy Model, Proximity Democracy Model, Participatory Modernization Model, Multi-Stakeholder Participation Model; Neo-Corporatism Model; Community Development Model. Out of 6 practical models of participatory budgeting, the most widespread in the world are the Participatory Democracy Model, Proximity Democracy Model, and Community Development Model, which is, due to a greater focus on social justice with a certain uniformity of legislation defining the powers of local government; extensive use of formal and informal instruments of direct democracy in the processes. The practice also shows that the success or failure of participatory budgeting is not necessarily dependent on the magnitude of municipal budgets. Its implementation may be successful in very poor cities/settlements where public resources are severely limited, as well as in very wealthy municipalities. The global trend of implementing participatory budgeting could not pass by Georgia unnoticed. Therefore, based on international practice and the experience of Georgia, it is necessary to discuss the main aspects of the implementation of the participatory budgeting model in order to better adapt to the characteristics of a particular municipality in our country. II. Results and Discussion II.1. Factors affecting the effectiveness of the implementation of the participatory budgeting model. According to the study, when implementing a particular model of participatory budgeting, it is necessary to take into account several main factors that have the greatest impact on the effectiveness of the model implementation based on the realities of Georgia. These factors include (1) the urban structure of the municipality, (2) the size of the municipality’s budget, and (3) the development of civil society.[*] The urban structure of a municipality. Based on the territorial arrangement system of Georgia, there are a total of 76 municipalities.[**] Of these, 71 are self-governing communities, and five are self-governing cities. Accordingly, three types of municipalities are distinguished: An urban municipality.[***] When implementing participatory budgeting in city-type municipalities (self-governing cities), the main challenges of the model[****] are the high concentration of the population in a small territory, less self-organization of the population, and a low level of communication in urban areas, neighborhoods, and within the neighborhood; a nihilistic attitude to the processes taking place in the municipality; a low level of awareness about the processes taking place in the municipality; a high level of politicization of society; A large number of citizens live in the township who are not registered voters in the municipality, which raises the question of allowing these citizens to participate in the municipal budget process; The need to implement large and costly infrastructure projects.[1] When implementing participatory budgeting in urban-type municipalities (self-governing cities), strengths include the following circumstances: a relatively strong desire of citizens for democratic governance; a sufficiently developed civil society, which is an important factor in solving problems at the local level; a large volume and less deficient budget of the municipality; municipality management is more inclined to introduce new initiatives and innovative methods in management; the ability to use developed. These advantages can be effectively used with the use of e-government tools and the involvement of active citizens and interest groups to implement a specific model of participatory budgeting. A Rural municipality.[*****] When implementing participatory budgeting in rural municipalities (self-governing communities), the main challenges of the model are the conservatism of citizens and increased resistance to innovation, simultaneously with a nihilistic attitude to the processes taking place and a high level of politicization; with a low level of the municipality’s budget revenue and strong dependence on targeted and equalizing transfers from the central budget; with a complex socio-economic background; The rural township is home to a large number of voters who have moved to other regions of Georgia, as well as temporarily or permanently moved to live abroad. The strengths of participatory budgeting in rural settlements are the following: a sufficiently high level of self-organization of citizens within districts and communities; a high level of communication based on family ties; a high level of involvement of residents in common cause based on archetypes of behavior historically developed in the community; the possibility of achieving visible results with small investments; less need for large and costly infrastructure projects. These advantages can be leveraged by using direct communication tools and engaging formalized and informal community groups to implement a particular model of participatory budgeting. Mixed municipality.[******] A mixed-type municipality has both the problems and advantages typical of both urban and rural municipalities. In such municipalities, as a rule, the center of the municipality (city or town) has the characteristics of an urban-type municipality, and the rest of the settlements correspond to the rural type. Accordingly, the implementation of participatory budgeting should take into account these circumstances and choose an appropriate model. The size of a municipality’s budget. Depending on the size of the budget revenues in Georgia, the following types of municipalities can be distinguished: Subsidized municipalities.[*******] A number of municipalities in Georgia suffer from a lack of budget revenues when exercising their powers and are subsidized municipalities. On the one hand, the municipality’s revenues are low due to the absence of large economic agents on the territory of the municipality and the tax policy determined by Georgian legislation. At the same time, most of their budget is formed at the expense of financial resources coming from the state budget at the expense of equalizing and targeted transfers. Because of all this, the availability of financial resources necessary for the participatory budgeting process is very low. On the other hand, it is precisely this circumstance that should push the leadership of the municipality to the result-oriented and effective planning of activities and finances. A participatory budgeting process can help a municipality’s leadership to better prioritize and focus its scarce resources on the most pressing issues. In the case of subsidized municipalities, it is possible to use the model of participatory budgeting, which is better adapted to address thematic (for example, social, youth, gender, and vulnerable groups) issues.[2] Less subsidized and/or under-subsidized municipalities.[********] A number of municipalities in Georgia do not suffer from a shortage of budget revenues. As a rule, these are municipalities with large urban settlements of urban type. Revenues derived from taxes and local levies of economic entities in the municipality (including large ones) allow for the efficient provision of public services to the population, applying for funding for infrastructure, social, cultural, and other types of projects. As a result, in a participatory budgeting process, a municipality’s leadership can safely allocate significant financial resources and promote the involvement of the population in the redistribution process. On the other hand, access to resources may encourage municipal leaders to prioritize their allocation without involving the population and to direct resources to projects that the population not only does not support but even opposes. Civil Society Development. According to the level of development of civil society (non-governmental organizations, business associations, trade unions, organized groups of citizens, etc.), the following types of municipalities can be distinguished in Georgia: Municipalities with highly developed civil society.[*********] Civil society is very well developed in some municipalities of Georgia. Civil society organizations have an influence on the decision-making process at the municipal level, actively cooperate both with the population and local self-government bodies, and have networks and external relations at the local level. They enjoy the high authority and trust of the population. Also, civil society has the desire and often the resources to actively support the participatory budgeting process to help the municipality with information and educational campaigns. On the other hand, there is a danger that in the case of a strong civil society, a number of active organizations will try to gain influence over the participatory budgeting process. To reduce this risk, a form of participatory budgeting should be chosen that ensures, on the one hand, high involvement of civil society and, on the other hand, covers the associated risks. Municipalities with less developed civil society.[**********] In those municipalities of Georgia, where the level of development of civil society is low, the municipality leadership loses an active partner in the process of participatory budgeting. Therefore, it will be forced to shift the entire burden of logistics and information support within the process onto its shoulders. The management of the municipality is also deprived of an external controller who will point out problems that arise in the process and jointly try to fix them. Therefore, a form of participatory budgeting should be chosen, where a low or medium level of involvement of civil society is determined, on the other hand, in this situation, precisely within the framework of the selected model, the process of participatory budgeting can contribute to the formation of a strong civil society in the municipality, to make thematic groups (vulnerable groups, disabled people, the elderly and others) to form at the formal level and to gain knowledge, experience, and authority within the process.[3] II.2. Principles and requirements of participatory budgeting. Any model of participatory budgeting should adhere to the following operational principles: (1) The model’s design and implementation procedures should be based on good governance principles, including transparency and accountability; (2) All processes of the model should follow the PDCA cycle (Plan, Do, Check, Act) also known as the Deming cycle, which ensures effectiveness and compliance with relevant legislation; (3) Customized procedures should consider the specific context of a particular municipality and its geographical characteristics, including urban structure, budget size, and population participation; (4) During the planning stage, the active actors and stakeholders of the model should be identified and their rights and responsibilities defined. It is essential that each process within the model has its responsible executor/accountable entity. Additionally, an independent organization or agency responsible for process management, monitoring, and evaluation should be established; (5) The model should fully comply with the laws of Georgia and the established forms of citizen participation. If existing forms are considered insufficiently effective in engaging the population in processes, the legislation of Georgia allows for alternative forms that better meet the requirements of citizen participation. II.3. Models of participatory budgeting by types of participation. Based on the results of the assessment and typology of existing participatory budgets at the international and Georgian levels, we can identify three types of participatory budgeting models: Procedure of the community-type participatory budgeting model. The procedures of this model are oriented towards the active involvement of small groups within the municipality, for which the territory of the municipality is divided into smaller operational areas (zones). These areas may correspond to existing administrative divisions or historically defined thematic criteria. It is also important to consider the inclusion of diverse groups (socially vulnerable, youth, newcomers, women, elderly, PWDs, and others) in the model. The participation of a larger number of small groups in decision-making and the implementation process is crucial for a more effective and diversified allocation of funds on various projects. The participatory budgeting model of the territorial type is characterized by the following main features: (a) The model is more focused on local, specific residential areas and the resolution of their problems, with a greater emphasis on infrastructure development/renewal projects. (b) It involves the implementation, discussion, and coordination of interzonal and subzonal project initiatives. (c) The selection of such project initiatives, which will mainly address the existing problems of the entire municipality, is more challenging. Some of the weaknesses of the model are the high logistical and organizational effort and the availability of human resources, but these issues can be corrected by optimizing the size of the area and planned work, as well as additional support from various actors (donors, non-governmental and humanitarian organizations, local businesses in social responsibility) through the involvement of human, material and financial resources. The drawbacks of the model can be overcome by excluding certain types of infrastructure projects (e.g., road construction, outdoor lighting, sewage, water supply, etc.) from the line item of the participatory budgeting and transferring them to other budget items. Thus, the achievement is innovative, socio-cultural, and more focused on the needs of vulnerable groups. Thematic type participatory budgeting model procedures. Within the framework of the thematic model, all project proposals must comply with a pre-defined topic (social assistance and allowances, support of youth and elderly population, development of school readiness and non-formal education system, development of certain skills of adults, etc.). The thematic model of participatory budgeting is characterized by the following main features: (a) The model is primarily focused on addressing issues at the municipal level, through which services are provided to the entire population of the municipality. Projects can be implemented within a specific locality, but in such cases, the entire municipality should benefit, not just the residents of that particular area. (b) In some cases, this model, as implemented in different countries, excludes the implementation of infrastructure projects that provide benefits exclusively to a single territorial unit. One of the disadvantages of this model is that the population is less ready to actively participate in the process of solving problems at the municipal level. Hence the importance of the awareness campaign. Only a well-organized and active campaign ensures the high involvement of the population. Civil society is a very important actor in this model. Its role is all the more important, the larger the budget. The involvement of active representatives of civil society in the development of model procedures and control processes will only have a positive impact on the effectiveness of the model. Procedures of the model of participatory budgeting of the mixed type. The mixed participatory budgeting model is a compilation of the two previous models: the model allows for discussion and voting on both community proposals and thematic projects. Therefore, from the very beginning, it should be determined which part of the PB budget will be allocated to the needs of the community and which part to thematic project proposals. The mixed-type model of participatory budgeting is characterized by the following main features: (a) the model is focused both on solving local problems of one particular settlement or community, as well as on the development of projects to be implemented within the municipality as a whole; (b) the main actor of the model should be the active representatives of the civil society, from which the implementing, regulatory and controlling formal bodies will be formed; (c) The structural units of the municipality are involved in the process as supporting actors who will carry out the expertise and logistical support of the project proposal. As practice shows, the involvement of the population within the mixed model is high, as a socially active person can participate in the process of budgeting in the role most convenient for him (controlling, organizational, or group of development of project proposals). As a result, the readiness of the population to participate in the processes and trust in the actual results is high under the competent management of the processes. Nevertheless, in the above model, the influence of entities formed from the population on the final decision is small because, under current Georgian legislation, the mayor/governor of the municipality is responsible for developing the budget, and the developed budget is approved by the city council, so they have leverage over the final decision. II.4. The procedure for selecting a participatory budgeting model. As we have already mentioned above, when choosing a model of participatory budgeting, it is necessary to take into account the socio-cultural and geographical features of a particular municipality. As part of this process, several basic issues should be discussed, and based on the results, a model adapted to the municipality should be selected: The amount of funding for the participatory budgeting process by the municipality in the next budget year. The amount of available funds determines the amount of funds needed to implement project proposals in the next budget year, as well as the amount of work needed to develop information and education activities and the project proposal under development. As a result of the analysis, the approximate answers reflecting the amount of financing of the participatory budgeting process are “small” and “large”, after which the desired model is determined by additional questions. The given answers, in turn, determine the subsequent questions: if the answer is “low”, you go to question №2, and if “high”, - go to question №3. Ultimately, it is important that all three questions are answered. Georgian and international practice shows that in those models of participatory budgeting, where small financial resources are allocated, the intended goal - maximum involvement of the population - has not been achieved. At the same time, those models where large amounts of financial resources are available require more attention and external control. Therefore, it is important to determine from the beginning what financial resources will be available when choosing a model. For the participative budgeting process, the funds needed to finance the outreach campaign and other logistical costs should be allocated. At the same time, it is necessary to carry out at least three budgeting cycles in order to be able to evaluate both the model itself and the effectiveness of the works to be implemented. The type of urban development of the municipality. As we mentioned above, the type of urban development of the municipality reflects the logistical problems that arise in the implementation of the model, the difficulties of delivering information to the target groups, and the involvement of the masses in the decision-making process. As a result of the analysis, the probable answers reflecting the urban development of the municipality are “rural type”, “urban type”, and “mixed type”. As Georgian and international practice shows, the type of urban development has a great influence on the participatory budget model. What can be easily achieved in a city-type settlement is associated with very high logistical, human, and financial costs in rural municipalities with difficult terrain (and not only), which directly limits the effectiveness of the model: (a) In most cases, in rural and mixed-type municipalities, depending on their specificity, it will be more appropriate to introduce a model of participatory budgeting that ensures high involvement of the population of historically existing communities and small settlements. This is due to the close ties of relatives and acquaintances within the community and the experience accumulated within the framework of community mobilization projects historically formed in the community and implemented by the efforts of various municipal or donor organizations. It is also important that the standard forms of ensuring citizens’ participation defined by the Local Self-Government Code (general meeting of the settlement, meetings with the mayor/governor, and petition) are better adapted to the specifics of small settlements and communities and are actively used by the municipality’s leadership; (b) In city-type settlements there are less close social ties between the population, that is why it is important to involve the civil society as much as possible in the process. The level of development of civil society. As mentioned above, an analysis of the level of development of civil society is important for choosing a model suitable for high-budget funding and/or urban-type settlements. In these models, civil society is included both as a subject of monitoring of the process and as a subject of outreach campaigns. Moreover, active representatives of civil society have skills in developing project proposals and experience in implementing such types of work. As a result of the analysis, the probable answers reflecting the level of civil society development are “high” and “low”. As Georgian and international practice shows, in the model of participatory budgeting, where civil society is developed, the involvement of citizens is high, the implementation of projects is effective, and the spending of public funds is efficient. Such models represent a mixed type of participatory budgeting, where project proposals correspond to both thematic and community-type processes, which ensure low risks. At the same time, regardless of the size of the municipality’s budget and/or the municipality’s urban development, if the level of civil society development is low, in order to minimize logistical risks, it is preferable to select only participatory budgeting thematic models. Within such a model, the processes are easier to manage, and the methods of direct democracy can be used for decision-making (for example, municipal voting, including the use of electronic systems). At the same time, it should be taken into account that what can be easily achieved in an urban settlement is associated with very high logistical, human, and financial costs in the case of rural and mixed-type municipalities, which directly limits the effectiveness of the model. II.5. Work procedures of the participatory budgeting model. Any model of participatory budgeting consists of various working procedures, which must comply with a set of methods and approaches that characterize this particular model. At the same time, it is necessary to comply with the principles of good governance and to ensure their effectiveness and compliance with the law as much as possible. Regardless of which model is chosen, the sequence of work must be very clearly established and detailed in the work procedures, and the actors responsible for it must be identified. At a minimum, any model should have the following work procedures: (1) population group meetings; (2) outreach campaign; (3) development and submission of project proposals; (4) voting and final decision; (5) evaluation of the participatory budgeting process and work procedures. Group meetings of the population. One of the important working procedures of participatory budgeting is group meetings of the population. The purpose of these meetings is to identify problems and priorities at the local and municipal levels through the involvement of the population and to identify ways to solve them. Depending on the model, group meetings of the population can be held: (a) at the level of a community, village, township, or city with a small area or a historically formed district; (b) at the village, district, and/or city level; (c) at the municipality level; (d) in specific vulnerable population groups. All decisions at group meetings must be made by voting and/or other methods of direct democracy. The type of voting and how the results are determined must be determined in advance and outlined in the voting procedures for group meetings with the public. At a minimum, the ballot should identify (a) budget priorities for the next year, (b) problems at the local and municipal level, (c) possible solutions to the problems identified, and (d) representatives of the population who will be involved in the work of the entities created by election. Conducting and facilitating group meetings should be provided by the subject introducing participatory budgeting. Besides, the active participation of public mobilizers, representatives of the mayor’s office, and deputies of the city council in this activity is possible. Active participation of non-governmental organizations is also possible. However, it must not reduce the level of involvement and influence of citizens in decision-making. Maximum attention should be paid to the gathering of citizens in places for which: (a) citizens’ meetings should be held in places easily accessible to the public so that they do not have to travel long distances; (b) school buildings should be used as much as possible for meetings with young people; (c) transportation services will be provided to vulnerable groups to attend both thematic and general meetings, if necessary. Informational and educational campaign. As part of the participatory budgeting process, it is mandatory to conduct an outreach campaign as intensively and extensively as possible. The purpose of the campaign is to raise public awareness of the rules and principles of participatory budgeting, to provide information about the development of the state budget, and to provide multifaceted, reliable, and up-to-date information about the budgeting process. The outreach campaign should be conducted throughout the entire budget period. It is important from the very beginning to determine both the work plan and the organization responsible for implementation and allocate the appropriate amount of financial and human resources.[4] As part of the outreach campaign, the following should be planned: Providing information on participatory budgeting (including up-to-date information on objectives, principles, working procedures, and ongoing processes). It is also important that information about submitted project proposals be provided in as broad and detailed a manner as possible; Supply of reference and outreach materials. The materials should reflect the information and results of the implementation of various projects planned within the budget of the previous year, as well as financing from the municipal and central budgets; Providing information about public and municipal budgeting rules. Provide reference and informational materials that reflect the rules for developing public and municipal budgets and municipal projects; Providing reference and information materials. Materials should reflect the information and results of various projects planned under the previous year’s budget, as well as those financed from the municipal and republican budgets; What the working procedures of the outreach campaign will be depends entirely on the model chosen. For example: (a) If the model is based only on the extensive use of the Internet system and less attention is paid to the gathering of population groups, it is important that all available communication and media tools are provided to disseminate detailed information about the current participatory budgeting processes and the project proposals submitted; (b) If proposal development and final decision-making is the mandate of a participatory budgeting entity, it is important that their members are trained in the rules and requirements of municipal budgeting.[***********] Development and submission of project proposals. Working procedures for the development and submission of project proposals must reflect the approaches and characteristics initially incorporated into the chosen model of participatory budgeting: (a) who is the subject of submission of project proposals - only citizens or also represented by groups of citizens are acceptable; (b) submission of proposals for documentation is carried out through the Internet system or in the documentary form. The latter issues, on the one hand, are purely technical, but they need to be well understood when developing working procedures. It is important to use all possible ways to submit project proposals and to be as close to the voters as possible. For example: additionally, project proposals can be submitted in schools located in localities and in the service centers of the Ministry of Justice, for which, on the one hand, procedures must be developed from the beginning and, on the other hand, appropriate funds and human resources must be allocated.[5] Voting and making final decisions on project proposals. The main requirement of participatory budgeting is the determination of project proposals for funding by citizens through voting, which can be implemented using the following model: Directly by citizens using traditional voting procedures. This model requires large logistical, human, and financial costs, although its level of legitimacy is the highest. In addition, it is possible to achieve the maximum involvement of vulnerable groups by arranging a special polling station for them; Directly by citizens using electronic voting procedures. This model is similar to the previous one and relies on information and communication technologies for which websites and phone applications are used. The drawback of this model is the low level of skills in using information and communication technologies for certain groups of the population and technical problems with access to the Internet in some municipalities; Participatory budgeting by representative bodies composed of citizens and, in some cases, elected using voting procedures. Depending on who has the right and duty to make the final decision on project proposals within the selected model of participatory budgeting, an appropriate procedure should be developed. The content of the procedure also depends on the method of voting - electronic or traditional. The decision itself can be made by the following type of voting: (1) single-choice voting, when a citizen chooses only one project proposal that is most acceptable to him; (2) multiple-choice voting, when a citizen chooses several project proposals that are most acceptable to him; (3) multiple-choice voting, when a citizen chooses several project proposals in the ballot, prioritizing them in the ballot.[*************] How many projects will be included in the municipality’s budget for next year depends on the amount of funds allocated and other parameters and must be determined in advance. Evaluation of the participatory budgeting process and working procedures. Evaluation of the participatory budgeting process and working procedures should be carried out to improve the model of participatory budgeting, increase efficiency, and gain and strengthen public confidence. Evaluation procedures are carried out by the supervisory body of participatory budgeting policies and processes. The evaluation should look at how thoroughly the procedures were followed, whether there were any systemic problems and/or complaints from actors involved in the processes, how existing problems were resolved, and how effectively the allocated funds were spent. Particular attention should be paid to the effectiveness of the outreach campaign and the involvement of vulnerable groups in the processes. The content of each procedure depends entirely on the specifics of a particular municipality, but depending on the chosen model, if necessary, it is possible to add other procedures, which will further increase the effectiveness of the planned work. Conclusion When implementing a specific model of participatory budgeting, it is necessary to take into account several main factors, which most affect the effectiveness of the model’s implementation, based on the reality of Georgia. These factors include (a) the urban arrangement of the municipality, (b) the size of the municipality’s budget, and (c) the development of civil society. Any participatory budgeting model should be based on the following operating principles: (a) good governance principles should be respected in the model design and implementation procedures; (b) all model procedures should be based on the so-called PDCA cycle (Deming cycle). This cycle ensures the effectiveness of the procedural management system and compliance with applicable legislation; (c) the established procedures should take into account the context and geographical characteristics of the particular municipality; (d) the actors of the model should be identified and their authority clearly defined at the planning stage; (e) the forms of citizen involvement defined by Georgian legislation and additionally should be used to the maximum extent possible. Taking into account the international practice and experience in the field of participatory budgeting in Georgia, there are three types of participatory budgeting models: the model of participatory budgeting of the community type, the model of participatory budgeting of the thematic type, the model of participatory budgeting of the mixed type. When selecting a model of participatory budgeting, the socio-cultural and geographical features of a particular municipality should be taken into account. As part of this process, several basic issues should be discussed, and based on the results choose a model adapted to the municipality: the amount of funding of the participatory budgeting process by the municipality in the next budget year; the type of urban development of the municipality; the level of development of civil society. Any participatory budgeting model should have at least the following operating procedures: (a) group public meetings; (b) an outreach campaign; (c) development and submission of project proposals; (d) voting and final decision; (e) evaluation of the participatory budgeting process and operating procedures. Bibliography: 1. Kokashvili,, Sosanidze, M., Vanishvili, M. (2022). Gender budgeting in the field of Georgian health and social protection: Analysis and evaluation. European Science Review, (5-6); 2. Kokashvili, N., Vanishvili, M., Osadze, L. (2022). Methodical foundations and challenges of gender budgeting in Georgia. European Science Review, (7-8); 3. Vanishvili,, Chelidze, M. Gelitashvili, G. (2023). Challenges and Perspectives of Municipal Participatory Budgeting in Georgia. Conference proceedings of the International Scientific and Practical Conference «Modern Knowledge: Research and Discoveries».Vancouver, Canada; 4. Vanishvili, M., Katsadze, I., Vanishvili, N. (2021). Public finance reform and state transfer policy in Georgia. Theoretical and empirical scientific research: Concept and trends: Collection of scientific papers «ΛΌГOΣ» with proceedings of the II International Scientific and Practical Conference, (Vol. 1); 5. Vanishvili, M., Shanava, Z. (2022). Legislative and legal provision of local budgeting in Georgia (on the example of self-governing cities). Scientific Collection “InterConf”, (122). Footnotes * Each factor and its combination determine what problems we may encounter when implementing participatory budgeting and how effective the process itself will be. ** The presented number of municipalities does not include the Autonomous Republic of Abkhazia and the 4 occupied municipalities in the Shida Kartli area: Akhalgori, Tighvi, Eredvi, and Kurti municipalities. *** Municipalities of this type are self-governing cities: Tbilisi, Rustavi, Kutaisi, Poti, and Batumi. **** Each challenge and its combination creates logistical problems, making it difficult to reach target groups and involve the masses in the decision-making process. [1] Vanishvili, M., Shanava, Z. (2022). Legislative and legal provision of local budgeting in Georgia (on the example of self-governing cities). Scientific Collection “InterConf”, (122), 38-55. ***** Municipalities of this type are represented by small self-governing communities, such as Ambrolauri, Tianeti, Kazbegi, Ninotsminda, Chkhorotsku, and others. ****** Such municipalities are represented by self-governing communities such as Telavi, Zugdidi, Marneuli, Khashuri, Gori, Samtredia, and others. ******* Municipalities of this type are represented by self-governing communities such as Tsalenjikha, Chkhorotsku, Ninotsminda, and others. ******** Municipalities of this type are represented by: self-governing cities - Tbilisi, Poti, Batumi; Self-governing communities - Marneuli, Bolnisi, Kazbegi and others. [2] Kokashvili, N., Sosanidze, M., Vanishvili, M. (2022). Gender budgeting in the field of Georgian health and social protection: Analysis and evaluation. European Science Review, (5-6), 61. ********* Municipalities of this type are self-governing cities such as Tbilisi, Rustavi, Kutaisi, Poti, and Batumi. ********** Municipalities of this type are represented by self-governing communities such as Tsalenjikha, Chkhorotsku, Ninotsminda, and others. [3] Kokashvili, N., Vanishvili, M., Osadze, L. (2022). Methodical foundations and challenges of gender budgeting in Georgia. European Science Review, (7-8), 48-53. [4] Vanishvili, M., Katsadze, I., Vanishvili, N. (2021). Public finance reform and state transfer policy in Georgia. Theoretical and empirical scientific research: Concept and trends: Collection of scientific papers «ΛΌГOΣ» with proceedings of the II International Scientific and Practical Conference, (Vol. 1), 26-30. *********** At any stage of the campaign, it is possible and desirable to involve representatives of non-governmental organizations and donor organizations. [5] Vanishvili, M., Chelidze, M., Gelitashvili, G. (2023). Challenges and perspectives of municipal participatory budgeting in Georgia. Conference proceedings of the International Scientific and Practical Conference «Modern Knowledge: Research and Discoveries» (102-119). Vancouver, Canada. ************ In order to make the budgeting process even more effective, it is possible to use several voting rules, which will be adapted to each work procedure and the rights and duties of the subject.
Copyright (c) 2024 Merab Vanishvili, Nanuli Kokashvili , Ramaz Otinashvili (Author) https://creativecommons.org/licenses/by-sa/4.0/
The Impact of Financial Inclusion on Economic Growth in Algeria
This research explores the impact of financial inclusion on economic growth in Algeria during the period 2004–2021. To achieve this objective, the researcher utilized the Bootstrapped coefficient estimates method, recognized for its accuracy in analyzing relationships within economic data. The study establishes a significant and noticeable relationship between financial inclusion and economic growth, highlighting the critical role of inclusive financial services in fostering economic development. Specifically, the findings emphasize that borrowing from commercial banks and the availability of ATMs have a positive and meaningful effect on economic expansion. These elements facilitate access to credit and enhance financial accessibility, which are crucial drivers of growth. On the other hand, the study identifies a surprising negative influence of the total number of bank branches on economic growth. This could point to inefficiencies or structural challenges within the banking system that warrant further investigation. The findings underline the need for tailored financial policies. Keywords: Financial Inclusion, Economic Growth, Bootstrapped coefficient estimates, Algeria. Introduction Global financial inclusion history demonstrates that achieving universal access to basic financial services has been a protracted and constantly changing process. Many organizations started to transition from providing only microcredit services to providing basic availability of financial facilities like insurance and savings starting in the late 1990s and early 2000s.[1] Financial inclusion became one of the major issues that surfaced on the global scene following the 2008 global financial crisis, highlighting its significance. Low-income households were among those whose financial well-being was significantly impacted by the crisis. The 2009 G20 Pittsburgh Summit recommended pre-financial inclusion to widely open the doors for financial subsidy to unprivileged groups, with recommendations for the improvement of financial inclusion concluded at the 2010 G20 Toronto Summit.[2] The pandemic of COVID-19 has demonstrated the essentiality of financial inclusion, as governments paced to offer monetary funds to unprivileged groups, providing opportunities for expanding financial inclusion amid social distancing.[3] In light of the economic significance of financial inclusion, the paper targets exploring the influence of financial inclusion on economic growth by scrutinizing the following question: To what extent could financial inclusion affect the Algerian economic boom significantly? The research timespan co-occurred with a series of econometrics from 2004 to 2021. The study combines the following divisions: Section 2 comprises a review of previous studies in this discipline, section three manifests the relationship between financial inclusion and economic boom, section four highlights the research methodology, and section five contains a discussion and the salient conclusions. Literature Review According to (Shahid Manzoor & Amjad, (2023)), Financial inclusion is a frequently debated subject among scholars, governmental officials, and financial experts.[4] International financial institutions, such as the IMF, Alliance for Financial Inclusion (AFI), and World Bank (WB), along with central banks, are actively seeking to promote financial inclusion domestically. Financial inclusion, according to the Reserve Bank of India (RBI) definition, involves providing financially threatened and vulnerable groups with suitable access to satisfactory monetary commodities and services fairly by dominant institutional agents.[5] According to (G20, (2021)), financial inclusion implies guaranteeing individuals and businesses can access basic financial services like credit, transactions, savings, payments, and insurance that satisfy their essentials in a sustainable promoted way.[6] In words of (Ozili, (2018)), financial inclusion is viewed as the potential of people to reach governmental financial facilities primarily by having formal bank accounts.[7] Governmental officials responsible for policies and scholars have shown noticeable concern in financial inclusion for four distinct justifications. They have shown a significant interest in Financial inclusion for four key reasons. Financial inclusion is seen as a significant approach to reaching sustainable development objectives, as it enhances social inclusion, decreases poverty, and provides various socio-economic advantages.[8] According to (Hannig & Jansen, (2010)), financial inclusion can be assessed using various factors, such as:[9] Access: The capability to utilize financial facilities and products provided by official institutions. Comprehending degrees of access may necessitate understanding and evaluating possible hindrances to opening and utilizing a bank account for any justification, like expenses and proximity of bank service locations (such as branches and ATMs). A simple way to measure access is by tallying open accounts at different financial institutions and evaluating the percentage of the population. Quality: It refers to how well a financial service or product meets the client’s bases. Quality is reflected in the way clients perceive and feel about the products that are accessible to them. The quality measurement determines the level of the financial service provider’s relationship with the clients. Usage: The emphasis is on long-lasting effects and the utilization of the product. To gauge usage, it is necessary to have information on the consistency, frequency, and length of usage throughout a period of time. Impact: it evaluates how clients’ lives have changed due to using a financial product or service. The Correlation Between Financial Inclusion and Economic Development These perspectives are evident in the results of the current studies. For example, it was demonstrated (Bayar & Gavriletea, (2018)) that economic boost is boosted by financial inclusion due to improved availability to monetary agencies and markets.[10] This implies that financial inclusion will provide individuals with increased opportunities to access commodities, services, and privacies provided by official financial agencies and in monetary markets. Individuals have the opportunity to utilize these financial commodities to either establish financial work or participate in economic endeavors that support economic development.[11] (Hussain, Rehman, Ullah, Waheed, & Hassan, (2024)) investigated how financial inclusion is linked to economic growth using data from 21 Asian states between 2004 and 2019. Moreover, they addressed the minor samples by separating the total samples into first-world and third-world nations. Financial inclusion in Asia has a salient influence on economic growth in the future, according to their findings. Additionally, the research found that the impact of financial inclusion on economic growth is stronger in first-world nations as opposed to third-world nations. In addition, these results offer valuable policy ideas for policymakers to create significant and inclusive financial policies to consolidate sustainable economic boom fairly.[12] In the same vein, (Chuka, et al., (2022)) analyzed how financial inclusion determines the economic growth of Sub-Saharan African states from 2012 to 2018 through Panel data. This study employed the Generalized Method of Moments (GMM). By utilizing a combination index of financial inclusion along with specific financial inclusion measures, it was found that the accessibility aspect, reach aspect, and overall access to financial services have a noteworthy effect on economic prosperity, whereas the utilization aspect of access to financial services enhances economic boom but not noticeably. Furthermore, the presence of bank branches and ATMs has a notable effect on economic advancement. Deposit accounts and loans contribute to economic growth, but their impact is not as substantial. On the other hand, high levels of eminent deposits harm economic development. Furthermore, research on moveable money indexes between 2012 and 2018 demonstrated that the presence of mobile money agents inhibits economic growth, whereas the existence of moveable money accounts and transactions adds to economic growth, albeit not noticeably. That is, it is salient to implement financial education policies in Africa to assist Africans have a better grasp of the advantages of using banking services.[13] (christopher & Eunice , (2024)) aims to explore how financial inclusion influences the enlarging of the economy in sub-Saharan Africa. The research was conducted in 47 African countries between 2010 and 2020. The research revealed a significant connection between financial inclusion and economic prosperity.[14] (Biswas, (2023)) investigated to what extent financial inclusion contributes to an economic boom in (4) South Asian states by focusing on its positive impact on human capital. Utilizing panel data and various indicators of financial inclusion to uncover the link between increased access to financial services leading to growth in the economy. The research shows that financial inclusion has a beneficial effect on the economic boom in these nations, indicating that it aids in the development of a state’s monetary infrastructure, ultimately boosting economic concerns and generating job opportunities.[15] (Siddiki & Bala-Keffi, (2024)) Retackles the connection between economic boom and financial inclusion by analyzing information obtained from 153 states. Their examination shows that the connection displays positive but fluctuating impacts at different levels of financial development. Therefore, there is a consistent connection between economic growth and financial inclusion, although the strength and effects of this link differ across countries with varying levels of financial improvement, underscoring the need to customize financial inclusion strategies in light of the particular stage of the monetary industry’s development.[16] (Van Dinh & Linh , (2019)) Assesses the consequences of indicators of financial inclusion on economic boost. The finding manifests that relationships are found between the many bank branches, ATMs, domestic credit in the private sector, and the aggregated rate of prosperity at the economic level. Citizens will attain a luxurious lifestyle resulting from this improvement.[17] Data & Methodology This part presents the data, approach, and methodology employed to evaluate the link between financial access to services and economic boost in Algeria. Data, Source, and Description The paper exploits per annum information for Algeria Country from 2004 to 2021. The choice of the state and sample time range depended upon the access to data on financial inclusion. The study variables are financial inclusion- the independent variable- which can be evaluated by a group of indexes, the sum of (ATMs) amounts to 100,000 for every grown-up adult employed to assess account ownership among individuals or businesses in formal financial institutions, sum of branches of bank which equals 100,000 for adults (NBB) has been used as an alternative indicator to signify to spread of financial institutions, borrowers from commercial banks per 1,000 adults (BOR) have been used as an alternative indicator for credit. The dependent variable is (GDP) assimilating the economic boom. All data were gathered by the World Bank. Depending on recent literature on financial inclusion (Morgan & Pontines, (2014)),[18] (Park & Mercado, Jr, (2015)),[19] (Sarma, (2008)).[20] Model A Bootstrap model was utilized to elucidate the connection between economic boom and access to financial services in Algeria. 〖LNGDP〗_t= α_0+α_1 〖LNATM〗_(t-1)+α_2 〖LNNBB〗_(t-1)+α_3 〖LNBOR〗_(t-1)+ε_t LNGDP is the dependent variable representing the logarithm of gross domestic product. LNATM, LNNBB, and LNBOR denote the logarithmic forms of the quantities of automated teller machines, bank branches, and loaners from capital banks. serves as the intercept while are parameters for estimation, representing the error term. In conclusion, stands for temporal relations. Data Analysis It is significant to elucidate thoroughly the fixedness of the variables before estimating the model to validate correct application. For the end of this goal, unit root measures such as the Augmented Dickey-Fuller (1981) and Phillips-Perron (PP) test (1988) were utilized. Table 1. The result of the unit root measure At the level At first difference Variables ADF PP ADF PP LNGDP -2.283243 (0.4198) -2.254232 (0.4336) -4.408726 (0.0157) -6.961824 (0.0002) LNATM -5.044651 (0.0010) -12.50823 (0.0000) -2.483070 (0.1384) -1.668647 (0.4271) LNNBB -4.736690 (0.0028) -6.844436 (0.0000) -3.168009 (0.0428) -3.390251 (0.0274) LNBOR -1.086911 (0.6955) -1.086911 (0.6955) -4.485694 (0.0034) -4.459014 (0.0036) Source: Eviews 13 program outputs. The findings of the ADF test and PP test (Table 1) indicate that all the variables fixedness at the first difference I (1). Except for two variables (LNATM, LNNBB), their stationarity was confirmed at the level I (0). Model Estimation Table 2. Model Estimation Results Dependent variable: LNGDP strategy: Least Squares Sample: 2004/2021 Included reviews: 18 Bootstrapped coefficient values and standard errors (10000 repetitions) Variable Coefficient Std. Error t-Statistic Prob LNNBB -1.728851 3.676974 -0.470183 0.6455 LNBOR 0.615002 0.270753 2.271453 0.0394 LNATM 0.457639 0.200055 2.287565 0.0382 C 30.08081 5.680555 5.295400 0.0001 R-squared 0.929392 Mean dependent var 30.25266 Adjusted R-squared 0.914261 S.D. dependent var 0.383215 S.E of regression 0.112210 Akaike info criterion -1.343762 Sum squared resid 0.176275 Schwarz criterion -1.145901 Log-likelihood 16.09386 Hannan-Quinn criteria -1.316480 F-statistic 61.42566 Durbin-Watson stat 1.658549 Prob (F-statistic) 0.00000 Source: Eviews 13 program outputs. The totality of branches of the bank is 100,000 per adult, which has a negative impact of -1.728851 on GDP, but this impact is not noticeably significant at a 5% level. This implies an inverse link between the total sum of branches of the bank and GDP, where an accretion in bank divisions brings a decrease in GDP. This outcome does not align with the earlier study (Wibowo, Mardani, & Iqbal, (2023)) that identified a direct correlation between the number of bank branches and economic advancement.[21] A significant (0.615002) effect of the people who borrow from commercial banks was proven to be 1,000 per adult (BRO) on GDP, and this effect is significant at a 5% level, which means there is a direct relationship between the people who borrow from business banks and GDP. In other words, the more increase in the percentage of the borrowers from commercial banks, the greater the degree of GDP. This finding is consistent with previous work (Arab & Allai, (2023)).[22] There is a positive effect (457639) of ATMs per 100,000 adults on GDP, and this effect is significant at 5%, that is, there is an immediate link between ATMs and GDP, which is consistent with economic theory.That is, as long as the total sum of ATMs increases, the GDP will increase in turn. This finding is consistent with previous work (Van Dinh & Linh , (2019)).[23] In conclusion, the R-squared coefficient measures 0.929392. This percentage indicates how well the model explains the changes in (GDP) by examining the impact of independent variables and their contribution to understanding these changes. In simpler terms, the model’s variables account for 92.93% of the changes observed, with the remaining 7% attributed to variables not part of the model. The Jarque-Bera test is utilized to assess if the residuals adhere to a normal distribution. The outcomes of this test are displayed in the following diagram: Figure 1. Result of Jarque-Bera test Source: Eviews 13 program outputs. From Fig.1, it is noted that the rest of the parts of the graph take a normal standard of differentiation since the Jarque-Bera value is 3.88, which is smaller than the tabulated Chi-square value of 5.99. Additionally, the p-value is 0.143. It is larger than 5%. Serial Correlation Test: The Breusch-Godfrey Serial Correlation LM Test is utilized to examine the values of autocorrelation. The test value (Obs*R-squared) is 0.297623 and has a p-value of 0.8617, exceeding 5% (P-value = 0.8617 > 0.05). This shows agreement with the null hypothesis, which posits that there is no autocorrelation in the residuals of the estimated model. The Following Table 3. Table 3. Breusch-Godfrey LM test for autocorrelation Breusch-Godfrey Correlation LM Test Null hypothesis: No serial correlation at up to 2 lags F-statistic 0.100876 Prob. F (2,12) 0.9048 Obs*R- Squared 0.297623 Prob. Chi-Square (2) 0.8617 Source: Eviews 13 program outputs. Test of Heteroscedasticity: There are several tests to determine heteroskedasticity in time series econometric, namely the Breusch-Pagan Godfrey. The result of Table 4 showed that the test value was (Obs*R-squared = 0.919528) with a probability greater than 5% (P-value = 0.8207> 0.05). Such findings consolidated the truth of the null hypothesis and highlighted that the variation of the error evaluations is similar. Table 4. Test of Heteroskedasticity Heteroskedasticity Test Breusch-Pagan-Godfrey Null hypothesis: Homoskedasticity F-statistic 0.251230 Probability. F (3,14) 0.8591 Obs*R-squared 0.919528 Probability. Chi-square (3) 0.8207 Scaled explained SS 0.815198 Prob. Chi-square (3) 0.8458 Source: Eviews 13 program outputs. Conclusion This work highlighted the ties between increased access to financial services leading to growth in the economy in Algeria. Hence, the paper concluded the following: There is an inverse link between the total sum of branches of banks and economic boom, indicating a negative deviation. According to Cameron, this means that the level of bank proliferation is insufficient, in addition to the low-scaled access of banking facilities to all social sectors. A noticeable relationship between ATMs and the economic boom in Algeria was concluded. This means that ATMs increase in number results in easy reach of the citizens to governmental financial sources. Thus, recognition of financial facilities will be aggregated, making people more knowledgeable about the different financial products offered. There is a significant link between borrowers from commercial banks and economic growth. This result can be interpreted as a large segment of individuals using formal borrowing channels. Recommendations: Banking institutions must adopt savings products for marginalized and poor segments of society. The state must open opportunities for the youth, they represent a large percentage of the Algerian society because they suffer from obstacles such as not benefiting from financial facilities. The government should work on decreasing the differences between the higher and lower classes- from a financial point of view- by expanding social protection programs, supporting marginalized groups, and meeting their needs for goods and necessities for daily life. Bibliography: 1. Arab, F., & Allai, F. (2023). Measuring the impact of financial inclusion and digital financial services on the level of economic activity in Algeria in light of the Corona pandemic. Journal of Economic Growth and Entrepreneurship (JEGE), 6(4); 2. Bayar, Y., Gavriletea, M. (2018, June). Financial inclusion and economic growth: Evidence from transition economies of the European Union. Journal of International Finance and Economics, 18(2). <https://doi.org/10.18374/JIFE-18-2.9>; 3. Biswas, G. (2023, July). Financial inclusion and its impact on economic growth: Empirical evidence from South Asian countries. European Journal of Business and Management Research, 8(4). <https://doi.org/10.24018/ejbmr.2023.8.4.20>; 4. Christopher, B., Eunice, A.-D. (2024). The effect of financial inclusion on economic growth: The role of human capital development. Cogent Social Sciences, 10(1). <https://doi.org/10.1080/23311886.2024.2346118>; 5. Chuka, I., Kenechukwu, O., Eze, F., Samuel, M., Anthony, E., Godwin, I., & Onwumere, J. (2022, April 16). Financial inclusion and its impact on economic growth: Empirical evidence from sub-Saharan Africa. Cogent Economics & Finance, 1-28. <https://doi.org/10.1080/23322039.2022.2060551>; 6. (2021). The impact of COVID-19 on digital financial inclusion; 7. Hannig, A., Jansen, S. (2010, December). Financial inclusion and financial stability: Current policy issues. ADBI Working Paper Series (No. 259); 8. Hussain, S., Rehman, A., Ullah, S., Waheed, A., Hassan, S. (2024). Financial inclusion and economic growth: Comparative panel evidence from developed and developing Asian countries. SAGE Open, 14(1). <https://doi.org/10.1177/21582440241232585>; 9. Morgan, P., Pontines, V. (2014, July). Financial stability and financial inclusion. ADBI Working Paper Series (No. 488); 10. National Financial Educators Council. (2024, March 26). <https://www.financialeducatorscouncil.org/history-of-financial-inclusion/> [Last Access 25.07.2024]; 11. Ozili, P. (2018, March 17). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4), 329-340. <https://doi.org/10.1016/j.bir.2017.12.003>; 12. Ozili, P. K. (2020, July). Financial inclusion research around the world: A review. Forum for Social Economics, 1-23. <https://doi.org/10.1080/07360932.2020.1715238>; 13. Pant Josh, D. (2011, June 28). Financial inclusion & financial literacy. BI OECD seminar roundtable on the updates on financial education and inclusion programmes in India. <https://www.oecd.org/finance/financial-education/48303408.pdf> [Last Access 26.07.2024]; 14. Park, C.-Y., Mercado, R., Jr. (2015, January). Financial inclusion, poverty, and income inequality in developing Asia. ADB Economics Working Paper (No. 426); 15. Sahay, R., Allmen, U., Lahreche, A., Purva, K., Ogawa, S., Bazarbash, M., Beaton, K. (2020). The promise of fintech: Financial inclusion in the post-COVID-19 era. International Monetary Fund (No. 20/09); 16. Sarma, M. (2008, June). Index of financial inclusion. Working Paper (No. 215); 17. Shahid Manzoor, S., Amjad, A. (2023, January). Macro dimensions of financial inclusion index and its status in developing countries. MPRA Paper, No. 118036. <Retrieved from https://mpra.ub.uni-muenchen.de/118036/> [Last Access 28.07.2024]; 18. Siddiki, J., Bala-Keffi, L. (2024, March). Revisiting the relation between financial inclusion and economic growth: A global analysis using panel threshold regression. Economic Modelling. <https://doi.org/10.1016/j.econmod.2024.106707>; 19. Van Dinh, T., Linh, N. (2019). The impacts of financial inclusion on economic development: Cases in Asian-Pacific countries. Comparative Economic Research, 22(1); 20. Wibowo, D., Mardani, Y., Iqbal, M. (2023). Impact of financial inclusion on economic growth and unemployment: Evidence from Southeast Asian countries. International Journal of Finance & Banking Studies, 12(2); Footnotes [1] National Financial Educators Council. (2024). <https://www.financialeducatorscouncil.org/history-of-financial-inclusion/> [Last Access 25.07.2024]. [2] Wibowo, D., Mardani, Y., Iqbal, M. (2023). Impact of financial inclusion on economic growth and unemployment: Evidence from Southeast Asian countries. International Journal of Finance & Banking Studies, 12(2), pp. 55-66. [3] Sahay, R., Allmen, U., Lahreche, A., Purva, K., Ogawa, S., Bazarbash, M., Beaton, K. (2020). The promise of fintech: Financial inclusion in the post-COVID-19 era. International Monetary Fund (No. 20/09). [4] Shahid Manzoor, S., Amjad, A. (2023). Macro dimensions of financial inclusion index and its status in Developing Countries. MPRA Paper. No. 118036. pp. 1-20. <https://mpra.ub.uni-muenchen.de/118036/> [Last Access 25.07.2024]. [5] Pant, J. D. (2011). Financial inclusion & financial literacy. BI OECD Seminar-Roundtable on the Updates on Financial Education and Inclusion Programmes in India. <https://www.oecd.org/finance/financial-education/48303408.pdf> [Last Access 26.07.2024]. [6] G20. (2021). The impact of COVID-19 on digital financial inclusion. [7] Ozili, P. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4), pp. 329-340. <https://doi.org/10.1016/j.bir.2017.12.003>. [8]Ozili, P. K. (2020). Financial inclusion research around the world: A review. Forum for Social Economics. pp. 1-23. <https://doi.org/10.1080/07360932.2020.1715238>. [9] Hannig, A., Jansen, S. (2010). Financial inclusion and financial stability: current policy issues. ADBI Working paper series (No. 259). [10] Bayar, Y., Gavriletea, M. (2018). Financial inclusion and economic growth: evidence from transition economies of European Union. Journal of International Finance and Economics. 18(2). <https://doi.org/10.18374/JIFE-18-2.9>. [11] Ozili, P., Ademiju, A., Rachid, S. (2023). Impact of financial inclusion on economic growth: review of existing literature and directions for future research. Munich Personal RePEc Archive (MPRA) (No. 118788). <https://mpra.ub.uni-muenchen.de/118788/> [Last Access 28.07.2024]. [12] Hussain, S., Rehman, A., Ullah, S., Waheed, A., Hassan, S. (2024). Financial Inclusion and Economic Growth: Comparative Panel Evidence from Developed and Developing Asian Countries. SAGE Open. 14 (1), pp. 1-15. <https://doi.org/10.1177/21582440241232585>. [13] Chuka, I., Kenechukwu, O., Eze, F., Samuel, M., Anthony , E., Godwin, I., Onwumere, J. (2022). Financial inclusion and its impact on economic growth: Empirical evidence from sub-Saharan Africa. Cogent Economics & Finance. pp. 1-28. <https://doi.org/10.1080/23322039.2022.2060551>. [14] Christopher, B., Eunice, A.-D. (2024). The effect of financial inclusion on economic growth: the role of human capital development. Cogent Social Sciences. 10 (1). <https://doi.org/10.1080/23311886.2024.2346118>. [15] Biswas, G. (2023). Financial Inclusion and Its Impact on Economic Growth: An Empirical Evidence from South Asian Countries. European Journal of Business and Management Research. 8 (4). <http://dx.doi.org/10.24018/ejbmr.2023.8.4.20>. [16] Siddiki, J., Bala-Keffi, L. (2024). Revisiting the relation between financial inclusion and economic growth: a global analysis using panel threshold regression. Economic Modelling. <https://doi.org/10.1016/j.econmod.2024.106707>. [17] Van Dinh, T., Linh, N. (2019). The impacts of financial inclusion on economic development cases in Asian-Pacific Countries. Comparative Economic Research. 22 (1), pp. 7-16. [18] Morgen, P., Pontines, V. (2014). Financial stability and financial inclusion. ADBI Working Paper Series (No. 488). [19] Park, C.-Y., Mercado, Jr, R. (2015). Financial inclusion, poverty, and income inequality in Developing Asia. ADB Economics Working Paper (No. 426). [20] Sarma, M. (2008). Index of financial inclusion. Working Paper (No. 215). [21] Wibowo, D., Mardani, Y., & Iqbal, M. (2023). Impact of financial inclusion on economic growth and unemployment: Evidence from Southeast Asian countries. International Journal of Finance & Banking Studies, 12(2), 55-66. [22] Arab, F., & Allai, F. (2023). Measuring The Impact of Financial Inclusion And Digital Financial Srvices on The Level of Economic Activity in Algeria In Light of the Corona Pandemic. Journal of Economic Growth and Entrepreneurship JEGE. 6 (4). [23] Van Dinh , T., & Linh , N. (2019). The impacts of financial inclusion on economic development cases in Asian-Pacific Countries. Comparative Economic Research. 22 (1), 7-16.
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Economies of Scale, Efficiency and Optimal Size of the Hospital
Hospitals are being expanded all over the world. Hospitals are becoming larger (i.e., increasing patient admissions each year) and more complex (i.e., offering a wider range of services to patients with more diverse medical care needs). In the hospital sector and other branches of the economy, economies of scale are important, according to which the volume of medical services can be increased by reducing average costs and increasing quality. However, measuring this relationship between the volume of medical services and costs is difficult because hospitals differ substantially in terms of specialization, patient composition, and other parameters that affect the volume of costs. The paper discusses the features of economies of scale in the healthcare sector and the dependence of the volume of medical services on costs and quality. Studies confirm that the influence of various factors on the costs and quality of medical services depends on the environment and the system of incentives in which hospitals operate. Relationships between patients and healthcare providers based solely on price negotiations do not ensure adequate healthcare quality. Due to informational asymmetry with respect to the real cost of hospital services and quality of treatment, medical service buyers cannot influence cost reductions and increase the quality of treatment, which increases hospital power. Thus, when evaluating the impact of hospital competition on costs and quality of care, we must remember that market mechanisms in health care do not always increase public welfare. Keywords: Economies of Scale, Quality of Medical Services, Cost of Medical Services, Hospital, Healthcare Market Introduction Regardless of economic development, modern hospitals are affected by demographic changes, the complications of the structure of diseases, and the development of new medical technologies. The hospital’s operation results depend on various links of the healthcare system: providers of medical services, customers, competitors, and other entities of the healthcare system. The theory of economies of scale is used to explain efficiency in production systems. Economies of scale argue that unit cost decreases as the volume of output increases. Several mechanisms, including the effect of volume on fixed costs, resource specialization, and market positions vis-à-vis suppliers, can explain this relationship between cost and volume. On the other hand, economies of scale are usually related to the phenomenon in which a service’s unit cost decreases when the production volume increases (Bernet & Singh, 2015) [1]. Economies of scale refer to when producing various services in one large unit is profitable rather than in several specialized production units. In the hospital sector and other branches of the economy, economies of scale are important, according to which the volume of medical services can be increased by reducing average costs and increasing quality. The results of many studies conducted in the health sector support the existence of the phenomenon of economies of scale (Giancotti et al., 2017) [2]. Still, applying the concepts of economies of scale in the health sector is becoming more difficult. The fact is that measuring the relationship between the volume of medical services and costs is difficult because hospitals differ substantially in terms of the level of specialization, composition of patients and other parameters that affect the volume of costs. The article discusses the peculiarities of economies of scale in the healthcare sector and the complexity of the dependence of the volume of medical services on the incurred costs and quality. Hospital Efficiency Quantitative and qualitative parameters determine the evaluation of the effectiveness of hospital results. Three aspects of quality are distinguished: 1. Quality of resources - investment and human resources, including the level of competencies of medical personnel. 2. Quality of the process of providing services - medical technologies, compliance with medical standards, intensity of treatment, level of service to patients. 3. The level of clinical result - the outcome of the patient’s treatment. Two main aspects of efficiency are considered when studying the functioning of hospitals in the medical market. Technical (local) efficiency - the ratio between resources and the produced product, for example, the ratio of personnel to the volume of services rendered (the number and structure of treatment cases in the hospital). The volume of the hospital influences technical efficiency, the medical technologies used, and the motivation of the organization and each worker. Allocative efficiency - the ratio between different directions of resource allocation, which determines the rationality of the cost structure, taking into account alternative costs. Different trends in technical and allocative efficiency are possible. For example, an increase in the technical efficiency of hospital activity that does not require hospitalization may be accompanied by a decrease in allocative efficiency - a significant concentration of resources in hospital services. The organization of medical services differs significantly from country to country. However, it is possible to distinguish the main trends in the formation of hospitals: Transformation of a large part of hospitals into large complexes where complex and expensive medical technologies are used; Transfer of some types of inpatient services to the ambulatory level; Increasing the intensity of treatment and, as a result, reducing the delay of patients in the hospital; Reducing the demand for beds and increasing the concentration of resources on the treatment of complex diseases in hospitals; Rapid increase in resource saturation per hospitalization case. Despite the general tendency to reduce the number of beds, the share of hospital sector costs in the total health care costs in developed countries has been quite stable for the last 20 years and amounts to 20-35%. For comparison, in Georgia, it exceeds 60%, resulting from high levels of hospitalization and long-term treatment. Another general trend is the reduction in the duration of hospital treatment. Hospitalization rates per 10,000 population vary by country. In some countries, it is decreasing (in 1990-2005 in Canada it decreased by 32%, in Sweden - by 10%), while in other countries it is increasing (in the same period in Great Britain it increased by 41%, in Spain - by 14%, in Norway - by 20%). (OECD, 2007) [3]. The number of medical personnel per bed increased in European countries in 1990-2005 (the minimum was in Germany - 6%, the maximum in Great Britain - 2.6% (OECD, 2007) [4]. These trends are due to the special nature of technical progress in the hospital sector: new medical technologies rarely lead to an economy of labour resources. Often, they require the recruitment of a new category of medical workers, which increases the saturation of resources for each case of hospitalization. One day of hospitalization in Great Britain is about $ 500; in some hospitals in the USA, it exceeds $2000. Economic Status of the Hospital According to economic status, hospitals are divided into three groups: public, private non-profit and private commercial. In the countries with a budgetary health care system (Great Britain, Scandinavian countries, Ireland, Italy, Spain, and Portugal), the share of public hospitals is 70-95%. In countries with a compulsory medical insurance system, this share is relatively small, although it still has a larger share; for example, in France, 65% of beds are located in state hospitals; in Germany - 55%; in Belgium - 60%. In countries where private health insurance is more developed, for example, in the USA, the share of private hospitals (commercial and non-commercial) is relatively large - up to 70-80% (Cutler, 2002) [5]. In the late 1990s, the World Bank proposed another typology, according to which medical organizations are divided into budgetary, autonomous and corporate types (Preker & Harding, 2003) [6].In an autonomous organization, managers have full decision-making authority. The global budget provides financing. Medical organizations have the full right to dispose of property. An autonomous organization is mainly formed by transforming a traditional budgetary organization into another organizational-legal form - trusts (Great Britain, Italy), non-profit organizations (Spain), and public state organizations (Lithuania). Corporate organizations appear as independent entities - corporation operating according to the general rules of entrepreneurship. The state owns the corporation’s property and manages its activities as its representative in the governing body. The organization assumes full economic responsibility for its obligations. In essence, it is a model of a state enterprise. Compared to an autonomous organization, there are more rights to use the income and more responsibility for obligations. The state acts as the corporation’s owner and tries to maintain strategic control over the activities of the medical organization while leaving the medical organization free to make current business decisions. The most famous examples of corporations are the state corporations of Sweden, Denmark, New Zealand, and Israel in the hospital sector. Many countries in the 1990s tried to give public hospitals more autonomy by converting them into other public organizations. The most famous form is the transformation of state organizations into trusts. For example, in Great Britain in the early 1990s, all public hospitals were converted into NHS trusts. Trusts have established contractual relationships with purchasers of medical services, in particular with public authorities and large general medical practices. Another form of autonomization is the transformation of budgetary medical organizations into public healthcare organizations, such a transformation was carried out in Lithuania. Lithuania first adopted the Law on Public Organizations (1996), which established the main features of such organizations: income is generated based on contracts with customers. Profit is not the goal of the activity; it does not bring to the founder but is directed to the development of medical activity. In 1997, the Law on Public Reorganization of Budgetary Organizations was adopted. In many countries, there is a diversity of ownership and organizational-economic forms of hospitals. Given the medical market’s peculiarities, many countries face a difficult choice of the optimal ratio of private and public hospitals. On the one hand, private commercial hospitals can respond promptly to market changes because their goal is to make a profit. When the necessary incentives are created to influence private commercial hospital decisions regarding the volume and quality of services, then the service delivery function can be transferred to the private commercial sector. On the other hand, the existence of information asymmetry allows commercial hospitals to increase the volume or price of the service, as well as to reduce the quality. Low-income countries prefer private, non-profit hospitals, even if they are technically less efficient. It is important to consider that the development of one or another form of hospital organization is conditioned by the historically formed representations of the role of a commercial hospital in different countries. For example, in the US, market relations in health care were dominated by commercial hospitals from the beginning. Historically, the main role in Europe belonged to state organizations. Since the 1980s and 1990s, many European countries have turned to autonomous organizational forms. Hospital Expences In the short term, hospital costs - the number of beds (hospital capacity), supplies, and equipment - are mostly fixed. A decrease in the number of patients leads to a decrease in average costs. In the long run, all costs are variable. Hospital administration may hire more doctors and invest in additional beds or expensive equipment. By predicting patient flow, a hospital can minimize average costs. When a daily intake of 150 patients is expected, a medium-sized hospital and a large hospital for 300 patients are required. Thus, at each expected level of demand, the administration can determine the capacity (capacity) of the hospital, as well as the number of medical personnel, minimizing average costs. A U-shaped curve theoretically represents the dependence of hospital volume on costs. As the volume of the hospital increases, average costs decrease to a certain minimum, after which they increase again. With the increase in the volume of medical services, it is possible to increase the number of doctors who specialize in warfare and increase access to high-tech equipment. Hospitals can also purchase large volumes of equipment at a reduced cost. However, as the size of the hospital increases, so do the costs of organizational coordination and management control. Thus, it may be economically prudent to expand the size and scope of the hospital to better utilize existing expertise, infrastructure, and equipment. However, at some point, the hospital moves away from the optimal efficiency level and begins to exhibit diseconomies of scale. Also, small hospitals can be inefficient because fixed infrastructure and administrative costs are spread over a very small number of cases, increasing the average hospital visit cost. In this regard, studies show that negative effects of scale diseconomies are expected below 200 beds and above 600 beds (Roh et al. 2010) [7]. The existence of economies of scale is one of the factors determining the intensity of competition. When economies exist, the limits of competition are limited. Therefore, it is important to identify the limits of this economy for the health sector. At this point, we need to understand whether the market structure of medical service providers is a natural monopoly, where only large hospitals can achieve an efficient volume of services, or whether the market structure is more diverse, where many smaller hospitals can exist. However, it is important to understand that this ratio of volume and costs is ambiguous, as is the conclusion about the existence of economies of scale. Studies confirm that there is an economy of scale in health care, but it is significantly lower (11-14%) than in other sectors of the economy (60-95%) (Eastaugh, 2004) [8]. Hospitals are not uniform in terms of the composition of treated patients, the complexity of the services provided, and the amount of scientific research spent on the training of doctors (some hospitals perform the functions of both teaching and research centres simultaneously). Let’s compare two hospitals: hospital B has more beds than hospital A, but patients in hospital B have a more complex disease structure. It can be assumed that the average costs in this hospital will be higher, making it less efficient. But in this case, such a conclusion does not correspond to the truth. Many parameters are used to evaluate the impact of hospital volume on costs: hospital volume, the structure of diseases, quality of treatment process, severity of disease, differences between doctors’ salaries, and costs of doctors’ training. Empirical studies in this direction are associated with certain limitations from the data, adequate indicators, and the technical side. It can be said that many studies in the USA confirm the existence of economies of scale, although not very significant, for hospitals with a capacity of 200-300 beds. An insignificant average percentage of savings justifies the presence of competition in the supplier market. At first glance, hospital A, which provides a few medical services, has lower average costs than hospital B and is, therefore, more efficient. But if we take into account the many factors that affect the long-run costs of a hospital, that is, if we compare short-run and long-run costs, we can see that hospital B is more efficient because it provides services with the lowest long-run average costs. Thus, lower average costs are not an indicator of higher hospital efficiency. Other factors also affect the efficiency of the hospital. Therefore, it is necessary to empirically assess the existence of economies of scale in each hospital operating in the local market, taking into account the peculiarities of the case structure. This refers to economies of scale not only for costs but also for the quality of services. It is important to consider that the quality of medical services is often determined by increasing the level of specialization of hospitals. The greater the volume of types of medical services, the greater the results of treatment. It is also necessary to consider the possibility of economies of scale in relatively small medical organizations and individual sub-departments. For example, a large hospital with a large set of specialities may not provide economies of scale, while an individual sub-department may be able to provide such economies through the power of replication of well-utilized medical technologies. It is also necessary to consider the different effects of scale (increase in the volume of services) on the quality of treatment for different specializations and types of services. For example, an increase in the volume of services significantly increases the quality of open heart operations but practically does not change the quality of cholecystectomy. Behavior of commercial and non-commercial hospitals in the medical market The status of the hospital is determined by the objective function, which in turn is related to the status of the hospital. A commercial hospital maximizes profits, while a non-profit hospital may include other factors in its function, such as serving socially vulnerable citizens, providing services that have public benefits, and conducting research in commercially unprofitable areas. The number of beds determines the capacity of the hospital. The number of hospitalizations is determined in proportion to the number of beds. The optimal number of beds for a commercial hospital-monopolist is lower than for a commercial hospital in a monopolistically competitive market, which in turn is lower than the optimal capacity of a non-profit hospital. The price set by a non-profit hospital is lower than that of a commercial hospital. Theoretical models of hospital competition The relationship between providers of medical services takes place within the framework of the existing and changing market structure. The market structure is determined by the degree of differentiation of economies of scale services, the presence of hospital service providers, and market entry and exit barriers. The wider the market boundaries, the more hospitals can compete. And conversely, in the absence of hospitals within the geographical reach, the hospital gains market power. Studies confirm the importance of the geographic accessibility factor of the hospital in the market structure. According to one study, a 10% reduction in the distance to a hospital increases the demand for its services by 13-14% (Henderson, 2005) [9]. However, the market for certain specialized services may extend beyond local boundaries as patients are willing to travel significant distances to receive a specific type of treatment. According to neoclassical economic theory, competition leads to efficient economic results. The services of healthcare providers are very different from other services. Due to informational asymmetry and uncertainty in the origin of demand, competition opportunities and outcomes in health care may differ from those in other areas of the economy. Hospitals can compete on two levels: Competition for individual users of services; Competition on the collective buyer of services - insurance companies. Competition between hospitals can be carried out according to prices and the quality of medical supplies. The main condition for ensuring the positive effects of hospital competition is the availability of information for all interested parties of the system according to two parameters: Effective use of resources; Quality of provided services. When the object of hospital competition is the collective buyer of services, competition helps hospitals allocate and use resources more efficiently. In this case, the buyer of services, due to its size (for example, a large insurance company), has a relatively high (compared to individual buyers) power and, as a result, has a stronger influence on costs and non-price parameters of services. The effectiveness of competition depends on the organization of the insurance system - the market structure of hospitals and insurance services free contracting with selected hospitals. Increasing the volume of hospitals (by merging them), which leads to economies of scale and provides relatively high indicators of the quality of treatment, can strengthen the market position. At the same time, the ability of the hospital to impose its conditions on the insurance company regarding the prices of hospital services is expanded. When many hospitals operate in a local market, their ability to impose their terms on a powerful insurance company is substantially reduced. Methods of reimbursement for hospital services also influence the effectiveness of competition. Hospital reimbursement can be based on two approaches. Retrospective compensation is based on the actual volume of services rendered, where the role of the financier is minimal. However, the buyer can control hospital cases. The second approach involves reimbursing medical services using the prospective method based on the pre-agreed volume of services provided. Factors of effectiveness of competition in the medical market Based on the theoretical aspects of competition, it is possible to systematize the factors that influence the results of hospital competition. Institutional environment factors. The availability of information on the quality of treatment (mortality, re-hospitalization rates) and effective use of resources are the most important factors in making a rational decision by the buyer and user of medical services. The scarcity of information is reflected in the imperfection of contracts and leads to high transaction costs, which reduces competition. State regulation in such areas as licensing, establishment of quality standards, and provision of information on hospital activities contributes to the increase of quality in the conditions of competition. Peculiarities of local markets. The existence of empirically justified economies of scale limits the possibilities of competition. When the large size of the hospital, i.e. market concentration, allows for lower costs of services, increasing the number of hospitals is inefficient. In addition, the larger the hospital, the greater the volume of services provided, and the quality of many types of treatment depends on the experience of doctors and the number of procedures performed. In this case, expanding the number of hospitals is not justified from the point of view of quality improvement. When there is a need to expand hospitals to meet growing demand - a situation where demand exceeds supply - the opportunity to compete on quality and price increases. Attitudes of hospitals to purchasers of medical services. An interested, well-informed buyer of medical services is a key factor influencing decisions made by a hospital on the volume and quality of services. The higher the buyer power, the stronger the buyer’s influence on service quality and costs. Another way to influence the buyer’s hospital is through reimbursement. Pre-negotiated, prospective funding creates additional incentives to contain costs, hospitals compete on price, while retrospective reimbursement methods do not create incentives to increase efficiency. In addition to the collective buyer, the hospital’s activity is influenced by the individual user of medical services, who makes a rational choice of the hospital based on price and quality. In the case of compulsory insurance, the price elasticity of demand is zero. At this time, the hospital may increase the cost of its services. When the consumer pays for some of the services themselves, the price elasticity of demand increases, and the hospital’s price competition becomes more effective because it attracts many patients. The hospital’s response to changes in external conditions. Hospital behaviour is driven by internal motivations that depend on economic status. When a hospital has large decision-making powers, competition encourages the search for ways to increase operational efficiency. A for-profit hospital will focus more on cost containment, while a not-for-profit hospital will focus more on increasing quality. Empirical Assessment of Hospital Performance Volume of medical services and quality of treatment It is known that special importance is attached to the experience and skills of doctors in clinical practice in medicine. For example, open-heart surgeries are allowed only in hospitals that can perform a set minimum of such surgeries. Large hospitals can easily meet this minimum. Better clinical outcomes can be achieved in more concentrated hospitals, where large hospitals dominate (in less competitive markets) and volume drives quality. Studies confirm that the cumulative number of cardiac operations (its increase in a given period) significantly impacts outcome indicators (lethality and complications). Also, the impact of volume on quality is confirmed by studies, according to which, in hospitals where the number of operations is large, mortality is significantly lower (Welke et al., 2008; [10] Lee et al., 2015 [11]). Hospital competition and production costs Some studies confirm that when hospitals are financed by a retrospective method (actual costs), competition leads to an increase in the volume of services, costs and prices (Krabbe-Alkemade, et al., 2017; [12] Fournier & Mitchell, 1992 [13]). However, there are studies according to which competition reduces costs and prices (Connor et al., 1998; [14] Dranove et al., 1993; [15] Proppe & Söderlund, 1998; [16] Dranove & Satterthwaite 2016 [17]). In addition, competition increases the widespread adoption and use of expensive technologies (Deng & Pan, 2019) [18]. The most common indicators of competition among medical service providers are: The Herfindahl-Hirschman Index is calculated based on hospital volume (number of beds, level of capital expenditures) within a country or region. In the US, the Federal Trade Commission has defined the following criteria for the degree of market concentration: HHI < 1000 - unconcentrated market, 1000 < HHI < 1800 - medium concentration, and HHI > 1800 - high concentration. The highest index of 10,000 corresponds to a monopoly; number of doctors per hospital in the country/region; Share of hospitalizations by hospital in the country/region. Hospital competition is determined by the market structure, which is determined by the boundaries and characteristics of that market’s population. Therefore, the measurement of competition makes sense only during the correct analysis and assessment of local market boundaries. As a result of the introduction of statutory methods of financing hospitals and the definition of agreed volumes of hospital services, competition in the early 1990s in the USA was associated with relatively low costs and prices. (Fulton, 2017) [19]. Hospital competition, treatment costs and quality Studies confirm that in the conditions of competition of hospitals in terms of quality, there is an intensification of expensive services, which leads to an increase in costs and prices (Strumann et al., 2022) [20]. In the US, this kind of competition in the medical market, which causes cost inflation, is called a “medical arms race”. However, excessive duplication and intensification of services can reduce the effectiveness of patient care because hospitals cannot afford to invest in research into more effective treatment methods. Studies evaluating the impact of hospital competition on costs and quality of care have produced mixed results. High competition in the US until the 1990s was ineffective because it increased hospital costs while not significantly affecting treatment outcomes (for example, the fatality rate of myocardial infarction did not decrease). In the 1990s, the competitive landscape in the US changed substantially due to the emergence of managed health insurance schemes. During this period, prospective reimbursement methods of financing hospitals were introduced, which means financing medical services not according to actual costs but according to predetermined prices. At the same time, stricter requirements were established for using expensive resources. After the 1990s, high competition led to cost reduction and quality improvement. Consequently, competition has become a useful mechanism for influencing hospital performance. In Great Britain, the reform of the National Health Service, which began in 1991, was aimed at stimulating competition among hospitals. Studies confirm that the price of hospital services was lower in regions with high competition among hospitals; However, the higher the volume of the medical organization, the lower the price (Joynt et al., 2011) [21]. According to other studies, competition between hospitals reduced the quality of patient treatment (Lyon, 1999) [22]. Thus, American researchers note the impact of competition on quality, and according to British researchers, competition strengthens the price signal. In Britain, healthcare purchasers (local governing bodies) focused more on price reduction than quality when negotiating with healthcare providers. When analyzing the impact of competition on quality, researchers took more into account the size and status of the hospital. Conclusion Empirical studies confirm that the influence of various factors on the quality of treatment depends on the environment and system of incentives in which hospitals operate. Relationships between buyers and providers of medical services, which are based only on price negotiations, do not lead to the provision of adequate quality medical services. Due to informational asymmetry with respect to the real cost of hospital services and quality of treatment, medical service buyers cannot influence cost reductions and increase the quality of treatment, which increases hospital power. Thus, when evaluating the impact of hospital competition on costs and quality of care, we must keep in mind that market mechanisms in health care do not always increase public welfare. References: Bernet, PM., Singh, S. (2015). Economies of scale in the production of public health services: an analysis of local health districts in Florida. Am J Public Health. Giancotti, M., Guglielmo, A., Mauro, M. (2017). Efficiency and optimal size of hospitals: Results of a systematic search. PLoS One. OECD Health Data. Version: 2007. OECD Health Data. Version: 2007. Cutler D. (2002). Healthcare and the Public Sector. Handbook of Public Economies. Vol.4. Elsevier. Preker, A., Harding, A. (2003). Innovations in Health Service Delivery: The Corporatization of Public Hospitals. World Bank Publications. Washington, D.C. Roh, CY., Moon, MJ., Jung, C. (2010). Measuring Performance of US Nonprofit Hospitals Do Size and Location Matter? Public Performance & Management Review. 34(1):22–37. Eastaugh, S.R. (2004). Health Care Finance and Economics. Boston: Jones and Barlett Publishers. Henderson, J. (2005). Health Economics and Policy. Thomson – South Western. Welke, KF., Diggs, BS., Karamlou, T., Ungerleider, RM. (2008). The Relationship Between Hospital Surgical Case Volumes and Mortality Rates in Pediatric Cardiac Surgery: A National Sample, 1988–2005. The Annals of Thoracic Surgery; 86 (3): P889-896. 1 Lee, KC., Sethuraman, K., Yong, J. (2015). On the Hospital Volume and Outcome Relationship: Does Specialization Matter More Than Volume?. Health Serv Res. 50(6):2019–2036. doi:10.1111/1475-6773.12302 12. Krabbe-Alkemade, Y.J.F.M., Groot, T.L.C.M. & Lindeboom, M. (2017). Competition in the Dutch hospital sector: an analysis of health care volume and cost. Eur J Health Econ 18, 139–153. 13. Fournier, G.M., Mitchell, J.M. (1992). Hospital costs and competition for services: a multiproduct analysis. Rev. Econ. Stat 74(4), 627–634. 1 Connor, R.A., Feldman, R., Dowd, B.E. (1998). The effects of market concentration and horizontal mergers on hospital costs and prices. Int. J. Econ. Bus 5(2), 159–180. 1 Dranove, D., Shanley, M., White, W.D. (1993). Price and concentration in hospital markets: the switch from patient-driven to payer-driven competition. J. Law Econ 36, 179–204. Propper, C., Söderlund, N. (1998). Competition in the NHS internal market: an overview of its effects on hospital prices and costs. Health Econ. 7, 187–197. 1 Dranove, D., Satterthwaite, MA. (2016). Chapter 20 the industrial organization of health care markets. Handb Health Econ. 1:1093–139. 1 Deng, C., Pan, J. (2019). Hospital competition and the expenses for treatments of acute and non-acute common diseases: evidence from China. BMC Health Serv Res. 19, 739. 1 Fulton, BD. (2017). Health care market concentration trends in the United States: evidence and policy responses. Health Aff. 36(9):1530–8. Strumann, C., Geissler, A., Busse, R., Pross, C. (2022). Can competition improve hospital quality of care? A difference-in-differences approach to evaluate the effect of increasing quality transparency on hospital quality. Eur J Health Econ. 23(7):1229-1242. Joynt, KE., Orav, EJ., Jha, AK. (2011). The association between hospital volume and processes, outcomes, and costs of care for congestive heart failure. Ann Intern Med. 18;154(2):94-102. Lyon, T.P. (1999). Quality competition, insurance, and consumer choice in health care markets. J. Econ. Manag. Str. 8(4), 546–580.
Economic Effects of Introduction of Modern Technologies in Beekeeping
The article discusses the economic impact of integrating modern technologies in beekeeping, such as Artificial Intelligence (AI), Machine Learning (ML) and the Internet of Things (IoT). The balance between initial investment and Return on Investment (ROI), operational scalability, market competitiveness, and government policy influences is studied. The importance of Comprehensive Economic Analysis in optimizing benefits and overcoming the challenges beekeeping faces is emphasized. Introducing new technologies in the field leads to the scaling effect, which allows beekeepers to manage more processes and operations faster and with fewer costs and to enter wider markets, leading to increased revenue and high profitability. In addition, challenges related to the scale of activity and market conditions are noted, mainly faced by small apiaries in conditions of insufficient financial support (subsidies) from the state. In addition, the need to develop special training programs for the effective use of technologies is emphasized, which will make it easier for beekeepers to gain a competitive advantage, in particular, improving the quality of products, developing an appropriate marketing strategy and making effective decisions based on databases. The final part of the article presents the macroeconomic benefits that integrating modern technologies in beekeeping can bring - creating new jobs, increasing the incomes of the rural population, expanding the market, and increasing exports. The need for a comprehensive economic analysis of the field to achieve sustainable and useful technological progress in beekeeping is noted. KEY WORDS: Beekeeping, innovative technologies, investments, agriculture, economic efficiency Introduction Introducing modern technologies in beekeeping is an important phase for this ancient, multi-century agricultural practice, which can significantly increase the sector’s efficiency. The use of the latest technologies, such as Artificial Intelligence (AI), Machine Learning (ML) and the Internet of Things (IoT), is linked with the increased initial investments, retraining and training of the beekeepers and the additional operational costs on the one hand and with the management of the high efficiency of the bee farm on the other hand. In particular, this is due to increased productivity, a rise in quality, and savings in labour costs. In order to introduce modern technologies in beekeeping efficiently, especially for small-scale beekeepers, it is important to have respective state interventions, in particular, the development of adequate regulating and legislative normative framework and financial stimulation of the sector to support innovations. Innovative technologies in beekeeping lead to not only perfection of the production process but also increased market competitiveness. Market analytics in real-time use of the respective relative data creates the opportunity for the movement of the entire sector to a new level. Main Text The economic effect of beekeeping is directly linked with technological advancement. Innovations and digital transformation increase productivity, operational efficiency and market competitiveness, though they are still accompanied by certain economic challenges and barriers, which are important to be considered for the efficient integration and optimization of the technologies (Huet..., 2022 [1]; Singh..., 2023 [2]). Investments in modern technologies have fundamental economic importance. Integration of technologies, like Artificial Intelligence (AI), Machine Learning (ML) and Internet of Things (IoT) into beekeeping requires significant financial resources. Initial capital and ongoing operational expenses, linked to introducing and applying the technologies, are necessary economic aspects to be considered (Bunde…, 2016 [3]; Rumman..., 2021[4]; Nikulina…, 2022 [5]). The return on investment (“getting back”) (ROI) highlights the economic viability of the technological integration. Improved management of bee colonies, increased productivity, and quality improvement result in positive ROI, meaning that economic profit is higher than linked costs (Zhilin, 2009) [6]. Automatization of the intensive processes of labour causes savings in labour costs and raises operational efficiency (Usenko …, 2020) [7]. Large-scale beekeeping operations support technological integration and show other economic aspects. The technology enables beekeepers to enhance their operations, better manage more bee hives, and intervene in more significant market segments, resulting in increased income and profitability. (Senchuk..., 2022 [8]; Vural…, 2009 [9]). Chart - Economic aspects and results of implementation of modern technologies in beekeeping Source: Chart developed by author Economic outcomes are not linear and depend on variabilities such as the scale of the operation, integrated specific technologies and market dynamics (Vapa-Tankosic..., 2020) [10]. Small-scale beekeepers can also face problems linked to the accessibility of modern technologies. They need financial support and subsidies to overcome economic difficulties (Giorgashvili, 2020) [11]. Training and development of beekeepers related to introducing the technologies also have economic outcomes (Adgaba..., 2014) [12]. Special training requires expenses related to curriculum development and implementation to optimize the application of modern technologies. (Chepik, 2007) [13]. The technologies strengthen competition in the market. It enables beekeepers to produce quality products that meet international standards, improve branding, and implement efficient marketing strategies, leading to market expansion and increased income (Vaziritabar..., 2016) [14]. Based on data analysis and artificial intelligence, the possibility of identifying market tendencies in real time allows beekeepers to optimize their pricing strategy and improve profitability (Subaeva, 2012) [15]. State policy and regulating frames also affect beekeeping’s technology and economic outcomes. Supporting policy for integration technologies ensures financial stimulation and supports a favourable environment for innovations; it improves the economic efficiency of using modern technologies (Albore et al., 2019 [16]; Nabieva, 2022 [17]). In the larger economic context, integrating technologies in beekeeping supports the country’s economic development. Job creation, increased prices on bee products, and the emergence of new market segments are the macroeconomic benefits caused by the technological development of beekeeping. (Delena…, 2021) [18]. Conclusion Thus, the potential economic outcomes of introducing modern technologies in beekeeping are multifaced and dynamic. They depend on factors like the scale of the bee farm, market dynamics, political environment and purpose of an applied technology. As the beekeeping sector continues the technological transformation, comprehensive economic analysis, which includes cost-benefit evaluation, Return on Investment (ROI) and large-scale macro-economic results, is crucial for making informed decisions. Accordingly, such solutions optimize economic profit and mitigate accompanying problems. References Huet, J.-C., Bougueroua, L., Kriouile, Y., Wegrzyn-Wolska, K., & Ancourt, C. (2022). Digital Transformation of Beekeeping through the Use of a Decision Making Architecture. Applied Sciences, 12(21), 11179. https://doi.org/10.3390/app122111179 Singh, A. S., Kibirige, D., & Malaza, P. S. (2023). Analytical Study of Small Scale Beekeeping Farming in Eswatini: A Case Study in Manzini Region, Eswatini. Asian Journal of Advances in Agricultural Research, 23(1), 1–9. https://doi.org/10.9734/ajaar/2023/v23i1449 Bunde, A., & Kibet, K. (2016). Socio-Economic Factors Influencing Adoption of Modern Bee Keeping Technologies in Baringo County, Kenya. International Journal of Science and Research (IJSR), 5(6), 960–969. https://doi.org/10.21275/v5i6.NOV164195 Rumman, S., Reybroeck, W., & Islam, T. (2021). Precision Apiculture in Bangladesh: Opportunities and Challenges. Ecology Journal, 3(2), 193–202. https://pureportal.ilvo.be/en/publications/precision-apiculture-in-bangladesh-opportunities-and-challenges [Last Access: 05.10.2023]. Nikulina, O. V., & Ledovskoy, M. A. (2022). Analysis of the development of the beekeeping industry in Russia: identifying problems and searching for reserves to increase competitiveness in the international arena. Regional Economics and Management,1–10. https://cyberleninka.ru/article/n/analiz-razvitiya-otrasli-pchelovodstva-v-rossii-vyyavlenie-problem-i-poisk-rezervov-dlya-povysheniya-konkurentosposobnosti-na [Last Access: 05.10.2023]. Zhilin, V. V. (2009). Increasing the Efficiency of Production Process in Beekeeping (theory, methodology, practice) [Bashkir Institute of Social Technologies (branch) of the Academy of Labor and Social Relations].https://www.dissercat.com/content/povyshenie-effektivnosti-proizvodstvennykh-protsessov-v-pchelovodstve-teoriya-metodologiya-p [Last Access: 05.10.2023]. Usenko, L. N., & Chepik, A. G. (2020). Economic and Organizational and Managerial Problems of Beekeeping Development in Russia. Economic Development Issues, 74–83. https://cyberleninka.ru/article/n/ekonomicheskie-i-organizatsionno-upravlencheskie-problemy-razvitiya-pchelovodstva-v-rossii [Last Access: 05.10.2023]. Senchuk, T., Peliukhnia, I., & Didenko, V. (2022). Sustainable Development of the Ukrainian Beekeeping Industry. Baltic Journal of Economic Studies, 8(5), 170–175. https://doi.org/10.30525/2256-0742/2022-8-5-170-175 Vural, H., & Karaman, S. (2009). Socio-economic analysis of beekeeping and the effects of beehive types on honey production. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 37(2), 223–227. https://notulaebotanicae.ro/index.php/nbha/article/view/3298 [Last Access: 05.10.2023]. Vapa-Tankosić, J., Miler-Jerković, V., Jeremić, D., Stanojević, S., & Radović, G. (2020). Investment in Research and Development and New Technological Adoption for the Sustainable Beekeeping Sector. Sustainability, 12(14), 5825. https://doi.org/10.3390/su12145825 Giorgashvili G. (2020). Modern state system of export support. Tbilisi. [International University of the Caucasus]. p. 5-11. https://openscience.ge/handle/1/1996 [Last Access: 05.10.2023]. Adgaba, N., Al-Ghamdi, A., Shenkute, A. G., Ismaiel, S., Al-Kahtani, S., Tadess, Y., Ansari, M. J., Abebe, W., & Abdulaziz, A. (2014). Socio-Economic Analysis of Beekeeping and Determinants of Box Hive Technology Adoption in the Kingdom of Saudi Arabia. JAPS: Journal of Animal & Plant Sciences, 24(6). p. 1876-1883. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=889fef1aa338a9ab02e187921cbd648564bc4ca3 [Last Access: 05.10.2023]. Chepik, A. G. (2007). Increasing the efficiency of beekeeping development in the Russian Federation: theory, methodology and practice. p. 6-14. https://www.dissercat.com/content/povyshenie-effektivnosti-razvitiya-pchelovodstva-v-rossiiskoi-federatsii-teoriya-metodologiy [Last Access: 05.10.2023]. Vaziritabar, S., Mehdi Esmaeilzade, S., & Shakib Vaziritabar, C. (2016). Profitability and socio-economic analysis of beekeeping and honey production in Karaj state, Iran. Journal of Entomology and Zoology Studies, 4(4), 1341–1350. https://www.entomoljournal.com/archives/2016/vol4issue4/PartO/4-4-34-701.pdf [Last Access: 05.10.2023]. Subaeva, A. (2012). Increasing the economic efficiency of beekeeping production. – Ulyanovsk State Agricultural Academy named after P.A. Stolypin. p. 4-15. https://e.lanbook.com/book/133748 [Last Access: 05.10.2023]. Albore, A., Anshiso, D., & Abraham, G. (2019). Adoption and intensity of adoption of beekeeping technology by farmers: The case of Sheko Woreda of Bench-Maji Zone, South West Ethiopia. Ukrainian Journal of Ecology 9, 9(3), 103–111. https://cyberleninka.ru/article/n/adoption-and-intensity-of-adoption-of-beekeeping-technology-by-farmers-the-case-of-sheko-woreda-of-bench-maji-zone-south-west [Last Access: 05.10.2023]. Nabieva, A. R. (2022). Development of the Market for Beekeeping Products in the Regions of Russia. Scientific-Theoretical Journal, 1, 3–11.https://www.ruc.su/upload/medialibrary/8aa/p9thoixzv3ozy39eigzhjkoo0jsed053.pdf [Last Access: 05.10.2023]. Delena, M. F., & Kayamo, S. E. (2021). Beekeeping opportunities, challenges and technology adoption in Gedeo Zone, Southern Ethiopia. Journal of Apicultural Research, 1–6. https://doi.org/10.1080/00218839.2021.1961429
Exporting Beekeeping Products: Importance of Detailed Market Analysis and Brand Positioning
To strengthen the export potential of Georgian bees and intervene in international markets, it is necessary to make a comprehensive and profound analysis. The article discusses the influences of market segmentation, consumers’ preferences, international trading agreements, legal regulations, product certification, technological innovations and competition on the development of marketing and branding strategies, supporting the efficient positioning of the high-quality Georgian bee products on the international markets and increase in export. Competition evaluation is critical for determining market possibilities and positioning Georgian beekeeping on global markets. The physiological and qualitative functions of the Georgian mountain grey bee must be emphasized: its gentleness, excessive productivity, and resistance to ailments. The article additionally mentions the importance of a strategic method to boost export capability in integrating technological improvements and contemporary advertising strategies, which include digital technology and database analytics, which will have an instantaneous effect on increasing the charm of beekeeping products. Determining purchaser preferences, cooperation with international organizations and obtaining first-rate certificates are crucial for the global reputation of Georgian beekeeping manufacturers and gaining agreement with customers. Market analysis, contemporary branding, and dynamic marketing are considered the basis for the hit export of Georgian beekeeping products and their established order in international markets. KEY WORDS: Beekeeping, Market analysis, Export, Branding, Legal framework Introduction International markets, with their many opportunities and challenges, require detailed analysis of their complicated mechanisms, especially for a field with unused potential like Georgian beekeepers. International markets, with their multiple opportunities and challenges, require analyzing their complex mechanisms in detail; this is especially true for the Georgian beekeeping sector, which has such untapped potential. A detailed analysis of the international markets is crucial for the potential expansion of Georgian beekeeping exports. Comprehensive analysis is necessary to intervene in those markets and create a niche for quality and unique Georgian bee products. By exporting of bee products on the international market, market segmentation, study of consumers’ preferences and competitive environment are required, along with the international trading agreements, determining of legislative regulations and product certification criteria and requirements. A detailed market analysis creates the ground for branding and marketing strategy development, which is directly linked to the increasing export potential of Georgian beekeeping. Main Text The importance of the market segments and a detailed understanding of their specific features are highlighted in Begdarashvili’s Master Thesis about Georgia’s export potential. The study of scale and segmentation is the foundation for a detailed market analysis. Each exporting direction has its own unique combination of market dynamics, resulting in individual approaches to product specification, marketing and distribution (Begdarashvili, 2019: 60) [1]. To meet different market demands, understanding consumers’ behaviour, needs, and preferences plays a great role in the selection of bee products. Therefore, the study of consumer preferences is a necessary component of the market analysis. The nature of the consumers’ preferences is dynamic, which is caused by the necessity of meeting the quality of the production, packaging and branding to the market expectations (Giorgashvili, 2020: 35) [2]. Conformity of products to consumer expectations increases market attractiveness and ensures competitive advantage of Georgian beekeeping products. The legal and regulatory framework is also an important factor for entering the international market and meeting compliance requirements. Each market has its own unique regulatory environment, with specific standards, certificates and legal requirements regulating access to the market and operation. Analysis of the regulatory framework ensures bee products meet the applied requirements. (Nabieva, 2022) [3]. In the global world of beekeeping, competitors use different strategies to occupy market niches and dominate their brands. A detailed study of competitors’ strategies, strengths and weaknesses provides an opportunity to identify market challenges and prospects. It defines the strategic positioning of Georgian beekeeping products, emphasizes their competitive advantages and formulates strategies to strengthen market dominance. (Zhizhiashvili, 2019:22-63) [4]. International trade dynamics are also a defining factor in export potential. A study of the European honey market will clarify the import/export tendencies, rates and the role of trade agreements in developing market potential. Information about trade flows and market access conditions provides the basis for developing trading strategies considering market opportunities and challenges. It identifies potential export destinations, trade partnerships and market diversification opportunities (Achelashvili, 2019: 49) [5]. The role of technological innovations is clear in increasing the international competitiveness of bee products. Technological achievements in production, processing and packaging increase the quality and attractiveness of the product. By promoting innovations, beekeeping products are differentiated in highly competitive international markets. Integrating technologies in product development and marketing increases awareness and attractiveness of products in the market and export potential (Santana De Figueiredo..., 2015) [6]. The relationship between detailed market analysis, marketing and branding strategies and positioning of Georgian beekeeping products on the international market can be schematically expressed as follows: Chart - The relationship between market analysis and marketing and branding strategies Source: Chart developed by authors Proper branding and marketing strategies also play a crucial role in increasing the export potential of Georgian beekeeping products. A comprehensive approach based on empirical evidence and innovative practices is necessary to overcome the complexities of the international market. Creating a strong brand - product awareness - is crucial. The organic origin of beekeeping products is primely important in shaping consumer choice. When branding Georgian bee products, it is necessary to emphasize their quality and natural origin. Branding should be based on the authenticity of the products, the unique nature of the country, untouched landscapes, the uniqueness of the Georgian Mountain Grey Honeybee and traditional beekeeping methods. (Ceylan..., 2019 [7]; Gencer..., 1999 [8]; Kara..., 2012 [9]; Bokuchava, 2019 [10]). It is impossible to imagine modern marketing without digital online platforms. They are important for disseminating detailed information. A strategic approach to applying digital marketing tools on a global level, including SEO, social media and “content” marketing, is essential to increase brand awareness. (Hussen, 2023 [11]; Philfan, 2020: 47 [12]). Understanding consumers’ preferences is also an important marketing task. Taste, brand perception and packaging play an important role in consumer choice. Thus, according to consumer preferences based on market research, adaptation of marketing strategies will contribute to the entry and establishment of Georgian bee products in the international markets. Cooperation with international organizations and institutions is important for strengthening brand image (Giorgashvili, 2020: 48). International certificates and accreditation verify the product’s quality and safety. In addition, compliance with legal and regulatory frameworks is strategically important to build consumer confidence and facilitate market entry (Bero, 2017) [13]. Integration of innovations in marketing, data analytics, and artificial intelligence are important elements for improving marketing efficiency. It allows the creation of personalized, targeted offers and advertising for the user. Therefore, incorporating technology into marketing strategies is necessary to optimize return on investment (ROI) and expand international access to Georgian beekeeping products. (Novelli..., 2021) [14]. Conclusion Challenges and opportunities characterise the export potential of Georgian Bee Products. To introduce these products to the international market, it is necessary to analyse the market in accordance with global customer requirements, market segmentation, and competitive environment research. This creates the basis for developing branding and innovative marketing strategies, which determines the attractiveness of Georgian beekeeping products at the international level - forms a unique market niche. Compliance with international standards and integration of modern technologies in producing and marketing beekeeping products are also strategic necessities. The growing global demand for natural beekeeping products creates a great potential for exporting Georgian beekeeping products in the competitive international market. Thus, the future success of Georgian beekeeping use of the industry’s export potential depends on implementing marketing strategies developed based on analysing the factors affecting international markets. References Begdarashvili T. (2019). Georgia’s export opportunities and prospects in international trade. Tbilisi. [TSU]. p. 1-82. https://openscience.ge/handle/1/859 [Last Access: 05.10.2023]. Giorgashvili G. (2020). Modern state system of export support. Tbilisi. [International University of the Caucasus]. p. 35-48. https://openscience.ge/handle/1/1996 [Last Access: 05.10.2023]. Nabieva, A. R. (2022). Development of the Market for Beekiping Products in the Regions of Russia. Scientific-Theoretical Journal,1, 3–11. https://www.ruc.su/upload/medialibrary/8aa/p9thoixzv3ozy39eigzhjkoo0jsed053.pdf [Last Access: 05.10.2023]. Zhizhiashvili Z. (2019). Prospects for the export of agricultural products of Georgia to the European Union market. Tbilisi. [TSU]. p.22-63. https://openscience.ge/handle/1/864 [Last Access: 05.10.2023]. Achelashvili N. (2019). The impact of export diversification on the growth of the country’s economy (on the example of Georgia). Tbilisi. [TSU]. p. 46-61. https://openscience.ge/handle/1/616 [Last Access: 05.10.2023]. Santana De Figueirêdo, H., & Santana De Figueirêdo Junior, J. H. (2015). Assessment of strategies for value chains using an extended Structure-Conduct-Performance (SCP) framework: an application to the honey business in Brazil. p. 143-145. https://library.wur.nl/WebQuery/wurpubs/492595 [Last Access: 05.10.2023]. Ceylan, A., Sevin, S., & Ozgenç, O. (2019). Histomorphological and histochemical structure of the midgut and hindgut of the Caucasian honey bee (Apis mellifera caucasia). Turkish Journal of Veterinary and Animal Sciences, 43(6), 747–753. https://doi.org/10.3906/vet-1906-55 [Last Access: 05.10.2023]. Gencer, H. V., & Firatli, Ç. (1999). Morphological Characteristics of the Central Anatolian (A. m. anatoliaca) and Caucasian (A. m. caucasica) Honey Bees. Turkish Journal of Veterinary & Animal Sciences, 23(7), 107–114. https://journals.tubitak.gov.tr/veterinary/vol23/iss7/17 [Last Access: 05.10.2023]. Kara, A., Kara, M., & Sezgin, E. (2012). Importance of Caucasian Honeybee and Its Characteristics as a Gene Resource. Journal of Agricultural Science and Technology, 2(10A), 1197–1202. https://www.researchgate.net/publication/290338723 [Last Access: 05.10.2023]. Bokuchava b. (2019). Statistical analysis of the export of goods from Georgia to EU countries. Tbilisi. [TSU]. p. 14-27. https://openscience.ge/handle/1/782 [Last Access: 05.10.2023]. Hussen, A. W. (2023). Beekeeping Practices, Challenge and Honey Marketing in West Guji Zone, Oromia Regional State, Ethiopia. Journal of Indigenous Knowledge Development Studies, 5(1), p. 26–48. http://ejol.aau.edu.et/index.php/JIKDS/article/view/8583 [Last Access: 05.10.2023]. Filfan b. (2020). Georgia’s export potential and the role of marketing in export development. Tbilisi. [International University of the Caucasus]. p. 44-52. https://openscience.ge/handle/1/2044 [Last Access: 05.10.2023]. Bero, U. (2017). Approaching the Pollinator Problem Through Human-Bee Relations: Perspectives & Strategies in Beekeeping. p. 106-109 http://dx.doi.org/10.20381/ruor-20791[Last Access: 05.10.2023]. Novelli, S., Vercelli, M., & Ferracini, C. (2021). An Easy Mixed-Method Analysis Tool to Support Rural Development Strategy Decision-Making for Beekeeping. Land, 10(7), 675. https://doi.org/10.3390/land10070675 [Last Access: 05.10.2023].
Information War - International Security Dilemma in the Modern World
In the modern world, in the field of international security, one of the important challenges is the information war. On the other hand, information is a universal and cheap weapon with a limitless scope and high efficiency. Therefore, it can be more dangerous than any conventional means of warfare. During its implementation, the attacking side achieves the desired outcome through the psychological manipulation of common beliefs. During the last ten years, the rate of disinformation has increased sharply. Also, propaganda, espionage, uncontrolled dissemination of state secrets and personal information, massive cyber-attacks and so on. Both states and terrorist organizations use such mechanisms. Today, the most functional means of information in this field are used by terrorist organizations, which often use social media to recruit so-called “Islamic Fighters” and lay out fundamentalism. Cooperation at the international and regional levels is important in fighting cybercrime and protecting critical information infrastructure. For this purpose, within the framework of the Council of Europe, the European Union, the United Nations, NATO, and other international organizations, it carries out active activities on cyber security topics. In addition, protecting against cyber intrusion, even on a small scale, is in the country’s national security interests, and it is crucial to involve each state in the proceeding discussion about information warfare. Keywords: Information War, International Security, “Islamic State” Introduction In the modern world, in the field of international security, one of the important challenges is the information war. In its broadest sense, information war is a fight through information to gain a specific advantage. Over the past few decades, the rapid growth of information and communication technologies and their increasing distribution have significantly increased the importance and consequences of information warfare. In the 21st century, in the conditions of broken boundaries between war and peace, the escalation of conflict, according to the causes and features of detection, is significantly related to information. Information conflicts, in terms of a general theoretical approach, are recognized by specialists in the field as one of the five main types of conflict, the origin of which is related to the scarcity-abundance of information, disinformation, and propaganda, and it can be equally dangerous in a closed totalitarian as well as in a democratic society. This is unequivocally confirmed by the current political processes in the world (Jorbenadze, 2001, 31) [1]. Main Part Information warfare is a modern concept that uses information technology to gain an advantage over an adversary. Current events in the world have made it clear how vulnerable this or that society can be in the case of information manipulation and how public opinion changes under the conditions of information management. Because information is a universal and cheap weapon, with an unlimited area of action and high efficiency, it can be a greater threat than any traditional means of war. At first glance, it does not bring devastating results from a physical point of view, such as is inevitable in the case of an armed conflict. Still, the success of information warfare is mainly expressed in the fact that, during its implementation, the attacking party can crack the opponent’s institutional structure and universally recognized fundamental values, confuse them and limit the truth. And lie between reality and illusion to achieve the desired result by psychologically manipulating public opinion. However, there are more active methods in the information warfare framework; the initiating party has various means to fulfil the set goal. These are: 1) Cyber-war (cyber-attack) - “the action of a state-nation aimed at penetrating the computer network of another state, to cause damage to the latter or to completely disable it”. In other words, it is a complex of offensive measures carried out in cyberspace or by several states and directed against another state or international non-state entity; 2) Cyber-terrorism, which is used by terrorist organizations in cyberspace and is directed against the national security of the country; 3) Anti-cyber-terrorism, used against terrorist organizations and carried out in cyberspace; 4) Cybercrime is used by various criminals or transnational groups, during which cyberspace is used for theft, information theft, fraud, etc. Sh. Their objects can be both individuals and large companies. Its purpose is to obtain economic profit; 5) Anti-cyber crime includes protective measures by state law enforcement or private individuals and companies against cyber criminals (Svanadze, 2015: 20-21) [2]. The information war consists of two main stages: a) the information-psychological period, which takes place in the conditions of information competition, continuously and affects the armed forces of the opponent, the population, and political and intellectual elites; b) the information-technological period, which is activated directly during hostilities. In this case, information is collected, processed and transmitted to achieve specific tasks, including illegal methods. Of course, one-time actions cannot achieve the result, and the system must operate continuously for years with sensitive topics identified by the special services, which are precisely selected for the target groups (Khidasheli, 2017: 7) [3]. The following groups can be singled out as initiators of the information war: National subversive groups; National and transnational criminal groups (Mafia, Yakuza, Triad, Camorra); Terrorist organizations; Multinational companies with their financial means; Companies with foreign capital; Extra-parliamentary opposition groups (right-wing extremists, xenophobic groups); Religious sects; Hacker groups; Other state and national military-political, as well as financial associations; Associations, foundations, non-profit organizations; Non-governmental and international organizations; Political organizations and trade unions; State institutions (Svanadze, 2015: 21-22). The unprecedented scale of the scientific and technical field development led to opportunities for introducing new technologies, which do not always serve to create public good. Moreover, if they are used for an irrational, destructive purpose, the world’s superpowers and international organizations become vulnerable. Understanding this threat forced the leading actors of modern international relations to name cyber and hybrid threats as the main challenge for the organization’s member states at the 2016 NATO Warsaw Summit (Warsaw Summit Communiqué, 2016) [4]. Although modern technologies are the greatest achievement of the civilized world, we cannot ignore the problems related to technological progress. Over the last decade, the rate of disinformation spread through the Internet has increased significantly. Also, propaganda, espionage, uncontrolled dissemination of state secrets and personal information, massive cyber-attacks and so on. Such methods are used by both states and terrorist organizations, and in this way, Russia launched active attacks against Georgia during the 2008 war (Gotsiridze, 2019) [5]. However, when it comes to talking about Russia in the named context, special attention is drawn to the events that developed around the US presidential elections. The reports developed as a result of the investigation, together with the statements made by Donald Trump, completely overshadowed the list of cases that the Russian side conducted even against Ukraine or Georgia. In the presidential elections of the United States of America, he tried to help a specific presidential candidate win by means of internet manipulations, information propaganda and cyber attacks, which is confirmed in the reports of the US Central Intelligence Service (Entous, 2016) [6]. Today, the most active means of information used by terrorist organizations, which are the so-called Social media such as Facebook and YouTube, are often used to recruit “Islamic fighters” and spread fundamentalism. Terrorist organizations also create special pages blogs, where they spread extremist materials and ideas, engage in propaganda, and publish photo and video material depicting terrorist activities carried out by them, thus successfully sowing panic among the population and directly in those specific individuals, financial institutions or political organizations. against which the mentioned list of actions is directed. In 2015, a series of terrorist attacks in Paris was preceded by a series of no less large-scale cyber attacks, the targets of which were both state and private organizations. In addition, the companies whose activities were connected to France and French companies in various ways became the objects of active hacking attacks. Groups suspected of cyber terrorism: “the Middle Eastern Cyber Army” (the Middle Eastern Cyber Army - MECA), Fallaga Hackers Team and Cyber ​Caliphate. According to The National Interest, the Cyber Caliphate is linked to the so-called “Islamic State” (ISIS) (King, 2015) [7]. In the last decade, especially in Syria, since the intensification of hostilities and the emergence of the so-called “Islamic State” ISIS, the number of cyber attacks has practically doubled. For example, from the reality of our country, we can name the activation of the terrorist organization ISIS in the Georgian Internet space in 2015 and the creation of a page by it, which served to implement all the goals named above. The website was saturated with various types of information, such as a propaganda photo gallery, official appeals to Georgian Muslim youth to join the fighting activities carried out by the Islamic State, letters from various members of the terrorist organization, and video materials depicting scenes of execution of opponents. It should be noted that the site only existed for a few months and later, Georgian special. It was blocked as a result of the services. Cooperation at the international and regional level is of great importance in fighting cybercrime and protecting critical information infrastructure. Similar cooperation in cyberspace protection includes international and regional conventions, forums, organizations and alliances, meetings and discussions, joint resolutions, decisions and recommendations, and directives. Within the framework of the Council of Europe, the European Union, the United Nations, NATO, and other international organizations, it carries out active activities on the topic of cyber security. In addition, protecting against cyber intrusion, even on a small scale, is in the country’s national security interests, and it is important to involve each state in the ongoing discussion about information warfare.[1] Conclusion In the end, we can conclude that the threats caused by the information war equally threaten the Internet space, both locally and internationally, which creates a great challenge in terms of international security. Cyberspace is less secure, and therefore, the number of cybercrimes is increasing irreversibly. In such a situation, great importance is attached to cooperation at the regional and international levels, the direct purpose of which is developing a common defence mechanism. In addition, efforts by the state to raise public awareness in this area are equally important, as they will reduce risks at the local and global levels. References: Jorbenadze R. (2001). Management of Political Conflicts, Tbilisi, “Science”. Svanadze V. (2015). Cyberspace and Cyber Security Challenges (Collection), Tbilisi. Khidasheli T. (2017). From World War II to Cyber War, How to Win the Information War? Tbilisi, Georgian Strategy and International Relations Research Foundation. Warsaw Summit Communiqué, Issued by the Heads of State and Government participating in the meeting of the North Atlantic Council in Warsaw 8-9 July 2016 - https://www.nato.int/cps/en/natohq/official_texts_133169.htm [Last Access: 30.05.2024] Gotsiridze A. (2019). The Cyber Dimension of the 2008 Russia-Georgia War, 2019 - https://gfsis.org.ge/ge/blog/view/970 [Last Access: 30.05.2024]. Secret CIA assessment says Russia was trying to help Trump win White House, By Adam Entous, Ellen Nakashima and Greg Miller, December 9, 2016 - https://www.washingtonpost.com/world/national-security/obama-orders-review-of-russian-hacking-during-presidential-campaign/2016/12/09/31d6b300-be2a-11e6-94ac-3d324840106c_story.html [Last Access: 30.05.2024]. The National Interest, Why to Fear ISIS’s Cyber Caliphate, 2015 - https://nationalinterest.org/blog/the-buzz/why-fear-isiss-cyber-caliphate-12023 [Last Access: 30.05.2024]. Author’s note: The site is currently blocked in response to threats from the Georgian government and the named materials are no longer searchable - https://xalifati.files.wordpress.com
Analysis of the Relationship between Privatization, Foreign Direct Investment, and Economic Growth in Azerbaijan
The solution of the main problems of the innovative development of the national economy directly depends on the attractiveness of foreign investments. In this study, the relationship between privatization, foreign direct investment, and economic growth is examined. In the analysis part, fully modified Least squares (fmols) and canonical cointegrating regress (CCR) tests, which show the cointegration rate, causal relationship, and correlation, were applied for statistical data reflecting the annual time series between 1996-2021. According to the results of the study, according to the FMOLS test results, it was concluded that a 1 percent increase in GDP led to 1.924,866 percent in privatization, and a 1 percent change in privatization led to a 0.906129 percent change in GDP. It also found that a 1 percent increase in privatization led to a 0.080900 percent (0.1811919 percent per CCR) increase in foreign direct investment. According to the CCR test, a 1 percent change in foreign direct investment also led to a 0.893101 percent change in privatization. Keywords: Privatization, Foreign Direct Investment, Economic Growth, FMOLS Test, CCR Test Introduction The addressed topic is mostly relevant in post-Soviet and other countries where the state owns a large share of the economy. Studying the results of this process, conducted at a high rate in the former Soviet countries about 30 years ago, may create opportunities for generating new ideas and hypotheses for both economic science and appropriate political decision-making. The key goal of privatization, i.e., transforming state property into private one, is to save financial resources and create a ground for more fruitful activity. Privatization as a way to implement economic reforms is a condition for strengthening the market mechanisms in the economic system. It increases the efficiency of the economy and the state budget revenues, creates conditions for healthy competition, and reduces the state’s share and intervention in economic processes and the state’s burden in business modernization. Privatization creates opportunities for expanding the operation of market mechanisms in economic regulation by strengthening the role of private property in the economic system. However, to ensure the desired outcome of this process, the country’s institutional environment should meet many conditions. How does privatization affect the inflow of foreign direct investment in technologically backward countries rich in natural resources? Can it support economic growth in the country? The choice of Azerbaijan’s economy as a research object to answer these questions is not accidental. One of the former Soviet republics, Azerbaijan, faced serious difficulties after gaining independence in 1991. The country commenced building a socially oriented market economy and started privatization. At that time, the country’s foreign economic relations, determined by the communist ideology, were destroyed, and various areas of the economy experienced a sharp crisis. Processing and agrarian sectors suffered the most from such a situation. Considering that state bodies had neither formed market institutions nor regulatory experience at that time, we can say that in Azerbaijan, privatization proceeded under unique conditions. The almost non-existent government bodies could not provide businesses with the required support. The economic consequences of privatization under such conditions are of particular interest. In this context, the research objective analyzed the relationship between privatization, foreign direct investment, and economic growth in Azerbaijan. Literature Overview The analysis of privatization and economic growth shows contrasting and sharply diverging results. These differences may be caused by the techniques implemented and the databases used. However, considering the fundamental differences in the institutional and economic structures of countries in the models may also significantly affect the relationship between privatization and growth. The analysis of the relationship between FDI and economic growth using data from 2003 to 2009 for 129 countries has shown that it is in all countries. However, FDI contributes more to low-income countries than high- and middle-income ones (Jawaid and Raza, 2012) [1]. Another study analyzed the impact of foreign direct investment, portfolio investment, and the 2008 global financial crisis on economic growth in developing countries and its sustainability and found that foreign direct investment increased economic growth in developing countries. This result approves the policy of developing countries to increase and stimulate foreign direct investment. Portfolio investment with short-term capital inflow in developing countries was not found to be associated with economic growth. The exchange rate and unemployment are other factors affecting economic growth in developing countries. The exchange rate negatively affects economic growth. The appreciation of the exchange rate and the depreciation of the national currency led to worsening expectations and uncertainty in the economy (Kuzucu, 2018) [2]. Indicators for 1996-2020 and the Granger causality test were used to study potential long-term relationships between foreign direct investment (FDI), economic growth, and employment in Azerbaijan. The empirical results showed a lack of causality between foreign direct investments and economic growth in the analyzed period. The causal relationship between foreign direct investment and employment has also not been established. This lack of causality can be attributed to the focus of direct investment in Azerbaijan, mainly on sectors such as finance, communications, and transport, which have limited opportunities for creating jobs. A lack of a significant relationship is, therefore, not surprising. (Guliyeva, 2023) [3]. A panel econometric assessment of the impact of foreign direct investment (FDI) on economic growth in 19 Latin American countries provides strong empirical evidence that it is not statistically significant in the aggregate. However, this result varies depending on the country’s development level. In highly developed countries, FDI positively and significantly impacts growth, while in upper-middle-income countries, it is uneven and insignificant. Finally, the impact is negative and statistically significant in lower-middle-income countries. Such results suggest that in Latin American countries, except for high-income ones, FDI is not an adequate mechanism to accelerate economic growth (Alvarado, Iñiguez, Ponce, 2017) [4]. The impact of foreign direct investment (FDI) on African economic growth was studied by processing panel data for 1980-2009 for 50 African countries. It has shown that FDI inflows significantly affected economic growth in Africa. However, this impact has changed throughout the period. It was also found that although the low level of human resources did not limit the impact of FDI on economic growth, it was negative between 1980 and 1994 and positive between 1995 and 2009 (Gui-Diby, 2014) [5]. The impact of FDI on economic growth was analyzed using a threshold regression model in the example of sub-Saharan African countries. The FDI inflow limit per capita was found to be approximately $44.67 per year. To have a significant FDI impact on economic growth, countries should have the minimum opportunity to assimilate the FDI benefits. E.g., the technology gap between foreign and domestic enterprises should be at least 0.6904. Thus, reaching the FDI threshold is required but insufficient for economic growth. Some countries use tax incentives to increase FDI inflows. It is argued that such incentives can be inefficient when low FDI inflows. Estimates of FDI coefficients below the minimum threshold are negative, meaning that the high costs of such incentives outweigh the potential benefits of FDI’s direct contribution to economic product and distribution (Asafo-Agyei and Kodongo, 2022) [6]. Empirical data on the relationship between foreign direct investment (FDI) and economic growth suggests a bidirectional causality. Processing data on FDI and economic growth for 1971-2010 for 124 countries shows positive and negative relationships between FDI and economic growth. The labour force, open trade, and economic freedom are the major determinants of the impact of FDI on economic growth (Iamsiraroj, 2016) [7]. Data for 1970-2019 and 2 estimation techniques (OLS and WLS) were used as part of the Cobb-Douglas production model to assess foreign direct investment’s impact on Albania’s economic development. The study results show that, except for employment, FDI does not affect Albania’s economic development, but when evaluated by the WLS technique, it has a direct positive effect on economic development. In striving for high economic development, Albania should increase its investments and create favourable conditions for attracting foreign direct investment to ensure long-term economic progress (Brahimi, 2022) [8]. Brief Description of Privatization and Foreign Direct Investment in Azerbaijan In the early days after 1991, when the Republic of Azerbaijan declared its independence, the agricultural structures and processing industry facilities forming the starting point of the national economy were virtually state-owned. Under these conditions, transferring those enterprises to the private sector to stabilize, liberalize, and improve the economy has become important from the development standpoint. In 1992, the institutional framework of privatization was created with the approval of the Charter of the State Property Committee. The development of the State Program for Privatizing State Property in the Republic of Azerbaijan in 1995-1998 accelerated these processes. Adopting the Presidential Decree On Approving Some Regulatory Documents for Privatizing State Property in 1996 documented the regulatory legal framework of privatizing state property. In Azerbaijan, privatization started much later than in other post-Soviet countries. Privatization preparations in Azerbaijan can be divided into two important stages, namely, the arrangement and use of the conceptual-legal system. The period up to 1996 can be specified as a preparatory stage and considered the start of privatization. At this stage, along with creating the concept of privatization, the latter was performed in the transport, passenger carriage, trade, and catering sectors. In the second privatization stage, by 2002, many large and medium businesses were privatized. In both stages, the key reason for privatization was to ensure the integration of the administrative framework into private ownership to accelerate the transition to a model economy. An army of entrepreneurs emerged during this period, irrespective of the property owner. From the start of privatization to 01.01.2003, 36,869 small enterprises, facilities, and other equipment were privatized for a total value of AZN 110.0 mln (SSCAR, 2023) [9]. The inflow of additional funds in the state budget can be evaluated as a positive impact of privatization on the economy. Attracting foreign investors to privatize medium and large businesses was also important to ensure their sustainable, productive and developed activity. Table 1 provides appropriate indicators of the distribution of privatized small state enterprises and facilities by years and sectors required for the analysis. Table 1. Distribution of privatized small state enterprises and facilities by years and sectors Source: State Service for Property Issues under the Ministry of Economy of the Republic of Azerbaijan [10]. https://emlak.gov.az/page/view/19 Foreign investment is also associated with using the country’s potential resources. When considering the available resources, we can see the need for long-term support from the regions that require speculation to improve production. In this regard, for local markets with great development prospects, the lack of technical innovations and the effective use of this potential are among the critical issues for promoting foreign investment in the country. On the other hand, attracting foreign investments is fruitful in terms of the impact on the country’s economy. Thus, the investment inflow mainly directed to the manufacture of products imported into the country will simultaneously improve the competitiveness, material well-being, employment, and the development of regional infrastructure in the country. Herewith, the attraction of direct foreign investment in the country’s economy to manufacture import-substituting products may reduce prices. Building a strong economy and decentralizing it will encourage the creation of relations with large regions in various fields. When attracting FDI to import-substituting products, the production components, innovative methods, efficiency, and generational similarity of the manufactured product should be considered. The Azerbaijan Export and Investment Promotion Foundation (AZPROMO), established in 2003, deals with attracting FDI. The key areas of AZPROMO’s activity are (https://azerbaijan.az/en/information/408): [11]. Development of the country’s new image; Provision of diverse services to local and foreign investors; The attraction of investors and negotiating with them; Creation of a database on investment and export opportunities; Exploring the export potential of the Azerbaijani market in the area of regional trade; Provision of consultancy and marketing research services to export-oriented companies; Spreading the “Made in Azerbaijan” trademark internationally. Statistical indicators of FDI in Azerbaijan for 1995-2021 are given in Table 2 (mln USD) Source: State Statistics Committee of the Republic of Azerbaijan, https://www.stat.gov.az [9] Several studies are devoted to the impact of other regulatory measures required to achieve the desired privatization results in Azerbaijan. Seyfullayev (2020 and 2022) [12], [13] obtained empirical data proving that the internal market protection and open trade policy are not satisfactory for the development of the country’s non-oil sector. The country’s current financial sector development level cannot give positive impulses for the processing industry development (Seyfullayev and Seyfullali, 2023) [14]. Despite positive relations found between some components of the state’s fiscal policy and the development of the non-oil sector, the benefits above were mainly manifested in non-commercial areas (Mammadov and Ahmadov, 2021 [15], Mukhtarov, S., Humbatova, S. and Seyfullayev, I. (2019) [16], Aliyev & Mikayilov, 2016 [17]). DATA AND METHODS Statistical data on privatization, FDI, and economic growth in Azerbaijan for 1996-2021 were used herein. The privatization, FDI, and economic growth (annual GDP growth) data used herein were obtained from, respectively, the State Property Committee of the Republic of Azerbaijan (SPCRA, 2023), the State Statistics Committee of the Republic of Azerbaijan (SSCAR, 2023), and the World Bank database (WB, 2023) [18]. The estimation model used herein is shown in the forms (1), (2), (3), (4), (5), and (6): A regression model of the relationship between GDP, FDI, and privatization (Khasanah, Ulfatun, Abdul Karim and Indah Manfaati Nur. “Pemodelan produk domestik regional bruto (pdrb) provinsı jawa tengah dengah pendekatan spasial autoregressive model panel data”. Prosiding seminar nasional and internasional.,2017) [19]. Yit = α + β1 Xit + εit, Yit - dependent variableα - intersectionβ1 - independent variable slopeXit - independent (explanatory) variableεit - over (error) Analyzing the Relationship between Privatization, FDI, and Economic Growth analytical regression model. GDPit = α + β1 PRIVit + εit (1), PRIVit = α + β1 GDPit + εit (2), PRIVit = α + β1 FDIit + εit (3), FDIit = α + β1 PRIVit + εit (4), GDPit = α + β1 FDIt + εit (5). FDIit = α + β1 GDPit + εit (6) Evaluation of econometric methods and results Herein, the time series stationarity analysis was performed using the Augmented Dickey-Fuller (ADF) unit root test developed by Dickey and Fuller (Dickey & Fuller, 1981) [20]. The following formula was used in this analysis. (3) In this formula, ΔY is the 1st differential of the variable tested for stability, t is the common trend variable, and is the lagged difference terms. The reason for adding the lagged difference terms is to ensure sequential independence of the error terms. To obtain normal results from the ADF test, the estimated model should not have a sequential independence problem. The lag expressed as k in the formula is determined using the Akaike or Schwarz criteria. To perform the cointegration test, the sequences used should be stable, therefore, the unit root test was implemented. Thereby, the variable stability has been analyzed. Table 3 shows the unit root test results for the analyzed variables. Table 3a. Unit Root Test Results (ADF) At Level PRIV FDI GDP With Constant t-Statistic -2.4822 -1.7745 -1.5360 Prob. 0.1330 0.3833 0.4980 no no no With Constant & Trend t-Statistic -2.4612 -2.6772 -1.5697 Prob. 0.3417 0.2543 0.7734 no no no Without Constant & Trend t-Statistic -1.1606 -0.2952 -0.4939 Prob. 0.2170 0.5688 0.4910 no no no Graph 1. Unit Root Test Results Chart Table 3b. Unit Root Test Results (ADF) At First Difference DPRIV DFDI DDGP With Constant t-Statistic -5.8535 -6.1006 -4.7745 Prob. 0.0001 0.0000 0.0011 *** *** *** With Constant & Trend t-Statistic -5.7723 -5.9375 -4.6340 Prob. 0.0006 0.0004 0.0067 *** *** *** Without Constant & Trend t-Statistic -6.9196 -6.2501 -4.9196 Prob. 0.0000 0.0000 0.0000 *** *** *** Note: (*) Significant 10 percent; (**) Substantial 5 percent; (***) Means 1 percent significant and (none) Means not significant. Graph 2. Unit Root Test Results Chart Table 1a and Graph 1 show that the analyzed variables are unstable at a certain level. The sequences had to be stabilized by obtaining the first differential and solving the unit root problem. Table 1b and Graph 2 show that the obtained data are stable at the first differential and 1% significance level. For privatization, FDI, and economic growth sequences, the Dickey-Fuller test shows their stability at the first level since the probability equals 0, and the critical values are smaller than the respective ADF test results. After checking the stability of the analyzed sequences, a cointegration test should be performed to determine the availability of a long-term relationship. The cointegration test examines whether multiple variables are interrelated. If this test shows a cointegration (i.e., variables change together over a long term), the cause-and-effect relationship is confirmed. The cointegration test checks the relationship between two nonstable time series. Two or more time series can be considered cointegrated if their linear combinations are stable, even though they are nonstable themselves. Johansen Cointegration Test was developed to check the existence of a long-term relationship between variables. Table 4 provides the Cointegration Test results for the privatization and FDI series. Table 4. Results of the Johansen Cointegration test on privatization and FDI. Trace test Eigen Value statistics Trace statistics A critical value of 5 percent Probability None * 0.779330 41.99815 15.49471 0.0000 At most 1 * 0.386655 10.26537 3.841466 0.0014 Maximum Eigen Value Test Eigen Value statistics Max-Eigen statistics A critical value of 5 percent Probability None * 0.779330 31.73278 14.26460 0.0000 At most 1 * 0.386655 10.26537 3.841466 0.0014 Table 4 shows that there is a cointegration equality between the privatization and FDI variables at 1% significance levels for both Trace and Maximum Eigenvalues. This allows for drawing the conclusion that there is a long-term relationship between privatization and FDI. Table 5 shows the Johansen Cointegration Test results for the privatization and economic growth series. Cədvəl 5: Results of the Johansen Cointegration test on Privatization and GDP Trace test Eigen Value statistics Trace statistics A critical value of 5 percent Probability None * 0.481629 16.78238 15.49471 0.0318 At most 1 * 0.132463 2.984043 3.841466 0.0841 Maximum Eigen Value Test Eigen Value statistics Max-Eigen statistics A critical value of 5 percent Probability None * 0.481629 13.79833 14.26460 0.0591 At most 1 * 0.132463 2.984043 3.841466 0.0841 Table 5 shows that there is a cointegration between privatization and economic growth variables at 5% and 10% levels for Trace values and at 10% level for Maximum Eigenvalue. These results allow for drawing the conclusion that there is a long-term relationship between privatization and economic growth. Table 6 shows the Johansen Cointegration Test results for FDI and economic growth series. Table 6: Results of the Johansen Cointegration test for FDI and GDP Trace test Eigen Value statistics Trace statistics A critical value of 5 percent Probability None * 0.468041 17.17237 15.49471 0.0277 At most 1 * 0.138752 3.286195 3.841466 0.0699 Maximum Eigen Value Test Eigen Value statistics Max-Eigen statistics A critical value of 5 percent Probability None * 0.468041 13.88617 14.26460 0.0573 At most 1 * 0.138752 3.286195 3.841466 0.0699 Table 6 shows the cointegration relationship between FDI and economic growth at 1 percent and 10 percent significance levels for the tracking value and 10 percent for the Maximum Eigenvalue. According to this result, there seems to be a long-run relationship between FDI and economic growth. Estimates of long-run coefficients due to the cointegration relationship for the 6 models considered in the analysis are presented in Table 7 in the form of FMOLS and CCR test results. Table 7. FMOLS and CCR test results GDPit = α + β1 PRIVit + εit PRIVit = α + β1 GDPit + εit PRIVit = α + β1 FDIit + εit FDIit = α + β1 PRIVit + εit GDPit = α + β1 FDIit + εit FDIit = α + β1 GDPit + εit Variables Coefficient Standard error t-statistic Probability value FMOLS GDP → PRIV 1.924866 0.732670 2.627195 0.0157 FMOLS PRIV → GDP 0.906129 0.386596 2.343866 0.0285 FMOLS PRIV → FDI 0.080900 0.032300 2.504651 0.0206 FMOLS FDI → PRIV 0.007561 0.096930 0.078005 0.9385 FMOLS GDP → FDI 0.130425 0.077549 1.681840 0.1074 FMOLS FDI → GDP -0.049169 0.446229 -0.110188 0.9133 CCR GDP → PRIV 1.839495 1.078867 1.705026 0.1029 CCR PRIV → GDP 0.098310 0.057010 1.724442 0.0993 CCR PRIV → FDI 0.181919 0.134410 1.353466 0.1903 CCR FDI → PRIV 0.893101 0.438463 2.036893 0.0539 CCR GDP → FDI 0.043941 0.655920 0.066991 0.9472 CCR FDI → GDP 0.014582 0.103967 0.140254 0.8897 According to the FMOLS and CCR test results given in Figure 7, the positive privatization, foreign direct investment, and economic growth coefficients indicate a positive relationship between these variables. According to the FMOLS test, a 1% change in GDP causes a change in privatization by 1.924866% (an estimate according to CCR does not confirm the effect). Likewise, a 1% change in privatization leads to a 0.9061295% change in GDP (an estimate according to CCR does not confirm the effect). According to the FMOLS test, a 1% change in privatization causes a 0.080900% change in FDI (an estimate according to CCR does not confirm the effect). However, for FDI, estimates according to FMOLS and CCR confirm the effect. The aforementioned FMOLS and CCR tests do not confirm the relationship between GDP and FDI. Conclusion This analysis examines the relationship between privatization, FDI, and economic growth. FMOLS and CCR tests providing cointegration, causality, and correlation coefficients were performed for the data’s annual time series for 1996-2021. According to the FMOLS test, a 1% change in GDP increases privatization by 1.92%, and a 1% change in privatization increases GDP by 0.9%. According to the FMOLS test, a 1% increase in privatization leads to a 0.08% growth in FDI. The study shows that GDP growth has a greater impact on privatization, which, in turn, leads to greater market efficiency, and the demand for privatization rises with expanding economic growth. Although privatization has led to positive changes such as improved management, reduced bureaucracy, and increased market efficiency, it has a relatively slight impact on FDI inflows. Studying the impact of political stability, infrastructure development, market volume, and other regulatory instruments on attracting foreign investment in the country’s non-oil sector may create opportunities for obtaining more coherent arguments. REFERENCES: Jawaid, Syed Tehseen and Raza, Syed Ali. (2012). Foreign Direct Investment, Growth and Convergence Hypothesis: A Cross Country Analysis. https://mpra.ub.uni-muenchen.de/39000/MPRA Paper No. 39000. [Last Access: 26.02.2024]. Kuzucu, S. (2018). Do foreign direct investment and portfolio investment stimulate economic growth? Evidence from developing countries. Journal of Economics, Finance and Accounting (JEFA), V.5(4). p. 331-338. Shafa Guliyeva. (2023). The Relationship Between Foreign Direct Investments, Economic Growth And Employment, Vol 33, Mar 20. RafaelAlvarado, María Iñiguez, Pablo Ponce. (2017). Foreign direct investment and economic growth in Latin America, Economic Analysis and Policy Volume 56. pp. 176-187. Steve LorisGui-Diby. (2014).Impact of foreign direct investments on economic growth in Africa: Evidence from three decades of panel data analyses, Research in Economics Volume 68, Issue 3. pp. 248-256. George Asafo-Agyei, Odongo Kodongo. (2022). Foreign direct investment and economic growth in Sub-Saharan Africa: A nonlinear analysis, Economic Systems, Volume 46, Issue 4, 101003. SasiIamsiraroj. (2016).The foreign direct investment–economic growth nexus International Review of Economics & Finance Volume 42. pp. 116-133. FilloretaBrahimi. (2022).The role of Foreign Direct Investments in the Economic Development of Albania, IFAC-Papers OnLine Volume 55, Issue 39. pp. 399-403. SSCAR – State Statistic Comitee of Azerbaijan Republic, 2023. https://www.stat.gov.az [Last Access:02.2024]. State Service for Property Issues under the Ministry of Economy of the Republic of Azerbaijan. https://emlak.gov.az/page/view/19 [Last Access:02.2024]. Azerbaijan, General Informatıon. https://azerbaijan.az/en/information/408 [Last Access:02.2024]. Seyfullayev, I. (2020). Protectionism and non-resource economic growth: Evidence from Azerbaijan. Problems and Perspectives in Management, 18(4). pp. 121- 129. http://dx.doi.org/10.21511/ppm.18(4).2020.11. Seyfullayev, I. (2022). Trade openness and economic growth: Evidence from Azerbaijan. Problems and Perspectives in Management, 20(1). pp.564-572. http://dx.doi.org/10.21511/ppm.20(1).2022.45. Seyfullayev, I., & Seyfullali, R. (2023). The impact of financial development on the manufacturing industry in resource-rich countries: Empirical evidence from Azerbaijan. Journal of Eastern European and Central Asian Research (JEECAR), 10(3). pp. 478–486. https://doi.org/10.15549/jeecar.v10i3.1289. Mammadov, I., Ahmadov F. (2021) Financial Development and Economic Growth: Evidence From Azerbaijan. WSEAS Transactions on Business and Economics, Volume 18, 2021. pp. 237-252 https://DOI:37394/23207.2021.18.25. Mukhtarov, S., Humbatova, S. and Seyfullayev, I. (2019). The impact of bank credits on non-oil GDP: evidence from Azerbaijan. Banks and Bank Systems, 14(2). pp. 120-127. doi:21511/bbs.14(2).2019.10. Aliyev, K., & Mikayilov, C. (2016). Does the Budget Expenditure Composition Matter for LongRun Economic Growth in a Resource Rich Country? 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Copyright (c) 2024 Sevil Abdullayeva, Leyla Yusifova (Author) https://creativecommons.org/licenses/by-sa/4.0/
Factors affecting the use of e-banking services among customers of Algerian banks: A qualitative study
This study aims to identify the factors influencing the use of e-banking services among clients of Algerian banks. To this end, a theoretical model was proposed based on the technology acceptance model (TAM) and the concept of electronic word of mouth (eWOM). To validate the variables of the proposed model in the Algerian context, we conducted a qualitative study using semi-structured interviews, which were carried out with 17 clients from various cities across Algeria, including those in the east, west, north, and south of the country. The data collected were subjected to thematic content analysis using a constructivist research approach. The results revealed significant effects of perceived usefulness, perceived ease of use, perceived trust, and electronic word-of-mouth (eWOM) on the use of e-banking services among clients of Algerian banks. The results also uncovered other variables that are expected to have a significant effect on e-banking use in Algeria, namely perceived costs and perceived service quality. Keywords: e-Babking use, Algeria, TAM, eWOM 1. Introduction: The use of technology in modern banking services, known as e-banking systems, enhances banking performance, impacts productivity, and reinforces the intention to use these technologies in the digital age (Fatonah et al., 2018, p. 13) [1]. Designated by other terms, such as internet banking, electronic banking, tele-banking, mobile banking, etc. (Hasan et al., 2010, p. 3) [2]. The evolution of e-banking has put an end to endless queues in front of different bank counters, as the internet now allows for multiple banking transactions from anywhere and at any time (Ataya & Ali, 2019, p. 6) [3]. Moreover, in developed countries, many financial transactions are conducted through electronic money (Anouze & Alamro, 2020, p. 11) [4]. Like other developing countries, the Algerian banking sector has made colossal efforts over the past two decades (Bellahcen & Latrech, 2020, p. 6) [5]. These efforts have yielded results since 2023 with the circulation of 10.712.133 interbank cards, of which 70% were active, and the establishment of 3.030 ATMs and 38.144 POS machines for merchants (GIE-Monétique, 2023) [6]. Despite the progress made by the banking sector to keep up with the rapid pace of innovation and ICT worldwide, the use of e-banking in Algeria is still in its early stages compared to the density of the national economic fabric (Bellahcene & Mehdi KHEDIM, 2016, p. 4) [7]. This has been proven by the numbers provided by the Economic Interest Group, where only 2.204.836.081,42 DZD of transactions per bank card were carried out in 2023. This is a very small number considering a population of 44.6 million inhabitants and a GDP per capita of around 2,568 dollars in 2023, according to the IMF (2023). In contrast to this situation, it would be crucial to investigate with clients of Algerian banks the factors likely to influence their use of electronic banking services, namely, Algeria has made a remarkable leap in the development of electronic banking systems during the past two decades. A wide range of research studies worldwide have been interested in this subject, aiming to demonstrate the effect of different determinants influencing clients’ use of e-banking. Previous research concerning the adoption of e-banking has utilized prominent innovation adoption theories, such as the technology acceptance model (TAM) (Salloum & Al-Emran, 2018) [8], with its two pivotal variables. We note that perceived ease of use was identified as a key factor in the study by Sarkam et al., (2021), p. 6 [9], and perceived usefulness in the study by Kurnia et al., (2010). p. 11 [10]. Likewise, in Algeria, the studies by (Bellahcen & Latrech, 2020, p. 9) [11] confirmed the effect of perceived ease of use and perceived usefulness on the adoption of e-banking, as well as the Theory of Planned Behavior (TPB) (Hanafizadeh et al., 2014, p. 2) [12] in which behavioural intention is a significant determinant of the use of information systems. While their findings identify various factors responsible for the limited adoption of e-banking, a consensus has yet to be reached on the specific variables that influence e-banking adoption, and results vary depending on the location, context, and timeframe (Bellahcene & Latreche, 2023, p. 6) [13]. Moreover, the issue has not been extensively explored in the broader context of developing countries and, more specifically, in the case of Algeria. Henceforth, the aim of this research is to examine the principal factors that influence the use and adoption of electronic banking services among Algerian bank customers. More precisely, this study puts forth, tests and validates an all-encompassing theoretical framework for customer adoption of e-banking by incorporating both, the Technology Acceptance Model (TAM) and the theory of planned behaviour (TPB). The subsequent sections of this paper are organized as follows: Section two provides a literature review. Section three puts forward the conceptual framework. Section four elucidates the research methodology employed in this study. Section five presents the findings. Lastly, section six concludes the work and suggests avenues for future research. 2. Literature review: Electronic banking services have been defined by (Daniel, 1999, p. 4) [14], as providing banking services to customers via the Internet. The same researcher has defined them as an information service where banks provide certain banking services via the Internet (Sheikh & Rahman, 2020, p. 9) [15], describes e-banking as all banking activities that can reduce customers’ different expenses when they can access their accounts without visiting bank branches. At this stage, the researchers have directed their attention to technology adoption, drawing upon several theories, among which the most well-known is the theory of reasoned action (TRA) (Fishbein & Ajzen, 1975, p. 19) [16]. The technology acceptance model (TAM) (Davis et al., 1989, p. 7) [17]. The theory of planned behaviour (TPB) (Ajzen, 1991, p. 3) [18], and the unified theory of acceptance and use of technology (UTAUT) (Viswanath Venkatesh et al., 2003, p. 6) [19]. In recent times, there has been significant academic interest in adopting electronic banking, with many researchers, such as Roy et al., (2017), p. 9 [20], integrating the technology acceptance model. The analysis indicates that the level of acceptance of internet banking among customers is influenced by two critical factors - perceived ease of use and external risk. On their part, Gharaibeh et al., (2018), p. 11 [21] employed a mixed-method approach to the Unified Theory of Acceptance and Use of Technology (UTAUT 2) to demonstrate that the acceptance of mobile banking services is significantly and positively influenced by factors such as mass media, trust, effort expectancy, performance expectancy, facilitating conditions, and social influence. However, it was observed that there was no significant relationship between hedonic motivation and the adoption of mobile banking services in the Malaysian context. Similarly, Martins et al., (2014) [22] used the UTAUT model to understand the main determinants of internet banking adoption in the Portuguese context. The findings provide support for certain relationships posited by the UTAUT model, including performance expectancy, effort expectancy, and social influence, as well as the significance of risk as a stronger predictor of intention. Furthermore, Ahmad et al., (2020), p. 9 [23] examined the current usage of e-banking through the Technology Acceptance Model (TAM). The study’s findings demonstrate that e-service quality has a positive impact on perceived usefulness, perceived ease of use, and intention to use e-banking, while perceived usefulness has a positive effect on attitude towards using e-banking and behavioural intentions to use e-banking. Alalwan et al., (2015) [24] employed an extended TAM model by including two external variables, namely perceived risk and self-efficacy, to investigate customers of the Jordanian bank. The findings indicate that perceived usefulness, perceived ease of use, and perceived risk significantly influence behavioural intention. On the other hand, Anouze & Alamro, (2020), p. 10 [25] introduced confusion between the TAM and TPB models in testing the intention to use electronic banking services. The data analysis shows that several key factors, such as perceived ease of use, perceived usefulness, security, and reasonable pricing, emerge as barriers to the intention to use e-banking services in Jordan. To explore the intention to use m-banking, Thanh D. Nguyen et al., (2019), p. 5 [26] integrated electronic Word of Mouth (e-WOM) into the TAM model. Based on the research findings, it can be inferred that e-WOM holds a predominant position within the structural model of the intention to adopt mobile banking. On the other hand, in the United Arab Emirates, Salloum & Al-Emran, (2018), p. 8 [27], expanded the Technology Acceptance Model (TAM) by incorporating the trust factor to study the use of electronic payment services among students. The findings from the empirical study indicate that trust plays a significant role in predicting perceived usefulness, perceived ease of use, and adoption of e-payment. Moreover, perceived ease of use is a crucial factor influencing perceived usefulness and adoption of e-payment. Employing the modified Technology Acceptance Model (TAM) in an under-researched Zambian context, Mwiya et al., (2017), p. 3 [28] explored how the perceived usefulness, perceived ease of use, and trust (in terms of safety and credibility) of e-banking technology impact its adoption. The results indicate that the perceived usefulness, ease of use, and trust each have a significant positive influence on the attitude towards electronic banking. In Algeria, Mansour et al., (2022), p. 6 [29] incorporated socio-demographic factors into the TAM model to predict the factors influencing the adoption of e-banking among clients of Algerian banks. The results revealed that gender moderates the influence of perceived usefulness and perceived trust on e-banking adoption and that profession moderates the relationship between perceived ease of use and e-banking adoption. There is a low level of internet user penetration in developing countries, as a result, many individuals prefer traditional methods (such as personal contact) for obtaining financial services when conducting business, which could account for the low adoption rate of online banking (Anouze & Alamro, 2020, p. 9) [30]. In Algeria, the use of e-banking still remains in the embryonic stage (Bellahcene & Mehdi KHEDIM, 2016, p. 4) [31]. 3. Proposed model To identify the factors likely to influence the use of e-banking services among Algerian bank customers, an integrated model combining the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) was constructed. Based on previous studies, TAM, originally proposed by Davis (1986), p. 6 [32], aims to provide verification and explanation of the determinants of acceptance and use of information technologies. Over the past two decades, the Technology Acceptance Model (TAM) has been the most commonly employed framework among researchers in the field of information systems and has amassed substantial empirical evidence (Bellahcene & Latreche, 2023, p. 11) [33]. Therefore, the conceptual model proposed in this study includes all factors adopted by TAM. Then, and in addition to the TAM, our model was based on TPB. The theory of planned behaviour (TPB) (Ajzen, 1991, p. 13) [34] represents an expansion of the Theory of Reasoned Action (TRA) developed by Lai, (2017), p. 8) [35], which was deemed necessary due to the TRA’s limitations in accounting for behaviours that are not completely under individuals’ voluntary control. In the theory of planned behaviour, similar to the original theory of reasoned action, the individual’s intention to perform a particular behaviour is a central factor (Ajzen, 1991, p. 6) [36]. Building upon this, we have augmented our proposed model by including the behavioural intention factor to predict the adoption of electronic banking services. In addition, our proposed model incorporates e-WOM and perceived trust, in addition to the TAM and TPB. Accordingly, the research model contains five main factors affecting e-banking use, figure (1). Electronic Word-of-Mouth (e-WOM): as defined by Thanh D. Nguyen et al., (2019), p. 9 [37] represents the dynamic and continuous process of exchanging information among potential, actual, or past consumers regarding a product, service, brand, or company, which is available to a multitude of people and institutions via the internet. e-WOM is also an extraordinary tool for free communication about services or products and has become an interesting research topic for managers on social media (Nguyen et al., 2019, p. 11) [38]. This variable has been discussed in several studies, such as the study by (Augusto & Torres, 2018, p. 7) [39], which focuses on e-WOM in the banking industry context, as well as the study by(Petrović et al., 2021, p. 8) [40], which examines the influence of electronic word-of-mouth on the use of m-banking. From there, we propose the following hypotheses: H1a: eWOM will affect the perceived usefulness of behavioural intention to use e-banking among clients of Algerian banks. H1b: eWOM will affect the perceived ease of use of the behavioural intention to use e-banking among Algerian banks’ clients. H1c: eWOM will affect the perceived trust in the behavioural intention to use e-banking among Algerian banks’ clients. As previously stated, the original TAM is based on two main variables: Perceived usefulness: Defined by (Davis, 1989, p. 4) [41] as a measure in which a person believes that the use of a technology should increase work performance. This arises from the definition of the term “useful”: “capable of being used advantageously”. (Farrell & Petersen, 1982, p. 8) [42]. The IS community has also conducted extensive research providing evidence of the significant impact of perceived usefulness on usage intention (Mansour et al., 2022, p. 4) [43]. Thus, we have tested the following hypothesis: H2: Perceived usefulness will have a positive effect on the behavioural intention to use e-banking among clients of Algerian banks. Perceived ease of use: Defined as the measure in which a person believes technology can be used without significant effort (Viswanath Venkatesh et al., 2003, p. 9) [44]. Previous research on the adoption of e-banking has established that consumers’ attitudes towards e-banking adoption are significantly influenced by their perception of ease of use (Sarkam et al., 2021, p. 8) [45]. Consequently, we propose the following hypothesis: H3: Perceived ease of use will have a positive effect on the behavioural intention to use e-banking among clients of Algerian banks. According to the TAM, these two variables determine the intention to use, which determines the behaviour of using technology. Over the past two decades, numerous studies have tested the TAM, demonstrating the positive influence of perceived usefulness and perceived ease of use on the adoption of information technologies in general and e-banking in particular (Bellahcene & Latreche, 2023, p. 11) [46]. The research model introduced a third independent variable: perceived trust. Gefen et al., (2003), p. 2 [47] defined trust as the affection reflecting a sense of security towards another party. Doney & Cannon, (1997), p. 6 [48] suggested that perceived trust is a complex concept in marketing and social psychology. Moreover, several studies using the TAM have emphasized the importance of the trust concept in using ICT. Therefore, the fourth hypothesis of this model was formulated as follows: H4: Perceived trust will have a positive effect on the behavioral intention to use mobile banking among clients of Algerian banks. Behavioural intention: The Theory of Planned Behavior (TPB), posit that adoption behaviour is driven by behavioural intentions which are a function of an individual’s attitude and the influence of external factors (Hanafizadeh et al., 2014, p. 8) [49]. Behavioural intention measures the strength of one’s willingness to exert effort while performing certain behaviours (Lee, 2009) [50]. TAM suggests that two specific beliefs perceived ease of use and perceived usefulness, determine one’s behavioural intention to use a technology, which has been linked to subsequent behaviour (Viswanath Venkatesh, 2000, p. 6) [51]. H5: Behavioral intention positively influences the use of e-banking among clients of Algerian banks. Figure (1): The proposed model Source: (Viswanath Venkatesh & Davis, 1996, p. 7) 4. Research Methodology: According to relativists, people who belong to different social classes and ethnic groups experience the same reality differently. This is why we chose a constructivist research approach that acknowledges a subjective epistemology and relativist ontology. To validate the proposed variables in the Algerian context and identify any potential new variables, an exploratory qualitative survey was conducted with bank customers, randomly selected from several cities across Algeria, namely the provinces of Tlemcen, Ain-Temouchent, Sidi-Bel-Abbès, Oran, Algiers, El-Bayad, M’sila, and Khenchla. The construction of the Interview Guide, also known as a grid or framework, the interview guide represents “the inventory of themes to be addressed during the interview and data that, at some point in the exchange, will be the subject of intervention by the investigator if the interviewee does not address them spontaneously (Marie et al., 2016, p. 13) [52]. An interview guide was developed based on previous research on “The use of electronic banking services”. During this process, measurement tools - including the reliability of coding used in previous studies - were used to evaluate the proposed conceptual model. To avoid biased information that may result from a misunderstanding of the questions by respondents, the interview guide was tested on a small sample of two (2) respondents who were interviewed face-to-face. This allowed us to modify our question framework appropriately, avoid poorly worded questions, and address them accordingly. It should also be noted that the appellations of some constructs adopted in our model were modified in our interview guide, using synonyms to facilitate perception by the interviewees. 5. Data Analysis Technique: To address the research question, the collected data was subjected to the following techniques: - Descriptive analysis using Nvivo 10 to highlight the characteristics of the sample; - Thematic content analysis, also on Nvivo 10, involves frequency coding of words to identify repetitive and similar words referencing the variables in our proposed conceptual model. Additionally, a description of coding words was used to link expressions with keywords to obtain reliable support for confirming our proposed model. - Sample Characteristics and Description: Initial contact with the respondents was made through various methods, such as phone, email, or Facebook, to explain the purpose of the interview the project goal, obtaining prior agreement to record the interviews, scheduling appointments, and agreeing on the location of the interview. The constructed interview guide covered seventeen (17) interviewees from all over Algeria, including the East, West, North, and South regions. The only requirement was that interviewees be users of e-banking services, regardless of the degree of their usage. As shown in Table 02, the age of the respondents ranged from 24 to 48 years old. The majority of the respondents (6 persons) were managers in the public sector, while the rest consisted of two (4 persons) PhD students, two (2 persons) branch managers, three (3 persons) managers in insurance, one (1 person) retired and one (1 person) unemployed. With regards to their domiciliary banks, we observed that the interviewees had no preference between public banks such as BEA, CPA, BDL, BNA, BEA, CNEP, or Algérie poste, and multinational banks such as AGB, TRUST BANK, and SGA. The seventeen interviewees used at least one bank. Regarding the number of e-banking services used, we noticed that there is only one interviewee who uses a single electronic banking service, while the others use between two and five services. Regarding their city of residence, we found that four (4) respondents lived in Tlemcen, while the remaining respondents were dispersed, with only one respondent residing in each of the following cities: Ain-Temouchent, Sidi-Belabess, Oran, Alger, M’sila, El-bayadh, or Khenchla. Table 1 : Sample Characteristics Interviews Sex Age Professional situation Domiciliary banks e-banking services used Town of residence Interviewee 1 Male 44 Manager in insurance BEA, TRUST BANK 1 Tlemcen Interviewee 2 Male 27 PhD Student AGB, Algérie Poste 4 Tlemcen Interviewee 3 Male 37 Branch Manager CPA 2 El bayadh Interviewee 4 Male 38 Branch Manager CPA, BNA, BEA 4 Tlemcen Interviewee 5 Male 36 Manager in the public sector. CPA, Algérie poste 5 Tlemcen Interviewee 6 Male 33 Manager in insurance BEA, AGB, CNEP 3 Oran interviewee 7 Male 48 Retired SGA, Algérie Poste 2 Sidi Belabes Interviewee 8 Male 36 Manager in insurance CPA, Algérie poste 4 Tlemcen Interviewee 9 Male 26 Manager in the public sector. CPA 3 M’sila Interviewee 10 Male 43 PhD Student BDL, Algérie Poste 3 Khenchla Interviewee 11 Male 28 Manager in the public sector. BNA, Algérie Poste 3 Alger Interviewee 12 Male 29 Manager in the public sector. TRUST BANK, Algéria Poste office 5 Ain Temouchent Interviewee 13 Female 26 PhD Student Paysera bank 5 Tlemcen Interviewee 14 Female 32 Manager in the public sector Trust bank 3 Oran Interviewee 15 Female 28 Manager in the public sector Algéria Poste office 3 Alger Interviewee 16 Female 24 Unemployed Algéria Poste office 2 Alger Interviewee 17 Female 25 PhD Student BEA 4 Tlemcen Source: By researchers based on Nvivo10 outputs However, we observed an average interview duration of thirty-eight (38) minutes, conducted in various locations and recorded by several means and in different modes, either face-to-face or online, as shown in Table 2 below. Table 2: Characteristics of the interviews Interviews Recording equipment Duration of the interview Location of the interview Mode of the interview Interviewee 1 - Smartphone OPPO F11 - Audacity 26,44 mins Tlemcen Face to face Interviewee 2 - Smartphone OPPO F11 - Audacity 41,57 mins Tlemcen Face to face Interviewee 3 - Smartphone OPPO F11 - Audacity 42,06 mins Tlemcen Online Interviewee 4 - Smartphone OPPO F11 - Audacity 40 mins Tlemcen Face to face Interviewee 5 - Smartphone OPPO F11 - Audacity 44,06 mins Tlemcen Face to face Interviewee 6 - Smartphone OPPO F11 - Audacity 39,58 mins Oran Face to face Interviewee 7 - Smartphone OPPO F11 - Audacity 31,34 mins Sidi Belabes Face to face Interviewee 8 - Smartphone OPPO F11 - Audacity 33,03 mins Tlemcen Face to face Interviewee 9 - Smartphone OPPO F11 - Audacity 35,11 mins Tlemcen Online Interviewee 10 - Smartphone OPPO F11 - Audacity 34,10 mins Tlemcen Face to face Interviewee 11 - Smartphone OPPO F11 - Audacity 46,28 mins Tlemcen Online Interviewee 12 - Smartphone OPPO F11 - Audacity 44,18 mins Ain Temouchent Face to face Interviewee 13 - Smartphone OPPO F11 - Audacity 41,22 mins Tlemcen Online Interviewee 14 - Smartphone OPPO F11 - Audacity 39,58 mins Tlemcen Online Interviewee 15 - Smartphone OPPO F11 - Audacity 34,20 mins Tlemcen Online Interviewee 16 - Smartphone OPPO F11 - Audacity 31,06 mins Tlemcen Online Interviewee 17 - Smartphone OPPO F11 - Audacity 40,04 mins Tlemcen Face to face Source: By researchers based on Nvivo10 outputs 6. Results: 6.1 Trustworthiness of qualitative findings: The trustworthiness or rigour of a study is determined by the level of confidence in the data, interpretation, and methods used to ensure its quality. For a study to be considered credible by readers, researchers must establish the necessary protocols and procedures for each study (Connelly, 2022, p. 11) [53]. To do so, we conducted a coding reliability test as follows”. Coding Reliability Test: We performed a data coding operation during this stage by categorizing them into significant words or phrases related to the research question. In a qualitative study, coding reliability refers to the stability of the coding, and it helps to verify if the coding rules are unambiguous (Allard-Poesi, 2003, p. 16) [54]. This coding reliability test was implemented through the steps proposed by (Allard-Poesi, 2003, p. 17) [55]. Coding stability or intra-evaluator reliability: when the same coder codes the data repeatedly. To do this, we performed several coding operations several times, with consistent results, which confirmed the accuracy and reliability of the coding. Coding reproducibility (or inter-coder reliability ICR): The extent to which the coding produces the same results when different people code the same data. A high level of ICR demonstrates that the coding is both reliable and replicable, which therefore strengthens evidence that the results of a qualitative study are scientifically valid (MacPhail et al., 2016, p. 8) [56]. To pass this test, we handed our data to another researcher, “PhD student”, who performed an independent coding. A similarity test was then conducted using the Nvivo 10 software, which allowed us to assess the reliability of our data coding, with a similarity exceeding 85%. 6.2 Thematic analysis approach: This study employed a qualitative approach to thematic analysis. Thematic content analysis is centred around identifying recurring patterns or themes across the entire dataset and is a widely utilized technique for qualitative data analysis (Braun & Clarke, 2006, p. 3) [57]. The first step of analysis involved open coding, an important process of breaking down the data into units (Jin & Hurd, 2018, p. 7) [58]. Therefore, we opted for two coding approaches to clarify our content analysis. 6.2.1 Coding by word frequency: Each coding process begins with the preparation of the corpus. This preparation involves working on the corpus and its indexing (Gavard-Perret et al., 2008, p. 11) [59]. Following Quivy and Van Campenhoudt (1995), p. 12 [60], we first coded the relevant data for the research during the data collection phase. The first form of coding involved selecting all sources from the corpus, including all interviews and attributes, and searching for repetitive keywords with unlimited word count and a maximum word length of four (04) letters. The goal of this step is to avoid overwhelming the researcher with the richness of information presented in the analysis corpus. Table 3 : Codes Interviews e-banking Trust Ease Use e-WOM or Social Medias Advantage or Usefulness Costs, fees Quality Interviewee 1 5 2 0 1 2 0 1 2 Interviewee 2 6 7 1 2 2 4 1 1 Interviewee 3 8 4 1 7 2 1 1 1 Interviewee 4 14 3 0 0 1 0 1 1 Interviewee 5 11 2 0 4 3 2 1 3 Interviewee 6 5 4 0 3 3 0 1 2 Interviewee 7 1 1 1 2 4 0 2 1 Interviewee 8 5 2 0 2 3 1 1 0 Interviewee 9 10 2 1 4 4 0 1 1 Interviewee 10 1 2 0 4 3 0 1 2 Interviewee 11 2 2 1 2 3 1 1 2 Interviewee 12 6 3 1 1 2 3 1 1 Interviewee 13 9 2 1 2 1 2 1 1 Interviewee 14 5 1 0 4 5 2 1 2 Interviewee 15 3 2 2 2 3 1 1 1 Interviewee 16 6 3 2 1 1 2 3 1 Interviewee 17 8 2 3 1 0 1 2 1 Total 104 44 14 42 42 20 21 23 Source: Resulting from Nvivo10’s word frequency coding Emerging from the first coding, we unveiled a significant list of keywords (Table 3), which can serve as the basis of our content analysis and confirm our research model. These words were shared either multiple times within a single interview or across all interviews, confirming the shared similar ideas among the interviewees regarding the different factors discussed, which can influence the use of online banking services. It is essential to note that some constructs, as cited in the literature and theories, were replaced in our interview guide based on their understanding by the interviewees. As observed by (Frédiric, 1996, p. 8) [61], “even with rigorous coding procedures, the researcher intervenes in the actor’s own language by transforming the discourse’s form”. Hence, it was necessary for us to integrate similar names for our variables to facilitate maximum understanding among the interviewees. 6.2.2 Coding by text frequency (Categorization): BARDIN (1977) [62] defined the unit of analysis, which can be a word, the meaning of a word or group of words, a whole sentence, sentence fragments such as “subject/verb/object,” one or several paragraphs, or an entire text. To better illustrate the frequency coding of words, we deemed it necessary to move to a phrase-based coding method in relation to all the codes demonstrated in Table 3 above. This method aims to highlight and identify expressions related to codes to have broader and more indicative confirmation support to validate our proposed research model. Table 4 below shows a description of the codes Table 4: The description of the codes Codes The sentences encoded in relation to the keyword E-banking · There are interesting and functional e-banking services available in Algeria. · Let’s be logical, e-banking services play a huge role in everyday life. · For me, e-banking is very necessary, I can withdraw money through ATMs whenever I need to. Trust · E-banking services are not always trustworthy. · Trust is relative, I cannot fully trust online banking services. · It is a great advantage that we can trust a machine (ATM). Ease · Yes, they play an important role in my life as they make daily tasks easier. · E-banking is important for making life easier. · The first advantage is the facilitation of daily financial transactions. Use · Personally, I am very limited in the use of these services in my daily life. · Undoubtedly, we will reach a more advanced stage in the use of electronic banking systems. · There is no reason to stop using electronic banking services. Social Medias (eWOM) · Certainly, social media can be a means of negative or positive influence on the use of electronic banking services. · Social media have a very high degree of influence on internet users. · I think that social media have a noticeable impact and can influence e-banking users in both positive and negative ways. Advantage or Usefulness · I can check my account at any time, either through ATMs or my smartphone or computer, which is a real advantage. · A major advantage is that it saves on travel, time, effort, and even expenses. · In my opinion, these applications are of great usefulness, representing a significant advantage for me. Costs or fees · Transaction fees are never verified, and they can be inflated without us being able to realize it. · Other banks offer better services in terms of costs compared to my bank. · I would have liked them to stop generating fees for current accounts like mine. Services’ quality · It is good to avoid human contact through the use of e-banking, but the quality of the services still needs improvement. · The quality of e-banking services in Algeria still needs to be improved. · I compare the electronic services offered by my bank, with those of others banks, and I see that they offer better services in terms of quality compared to my bank Source : By researchers, based on Nvivo10 outputs. Referring to Table 4 above, sentence encoding has provided a significant analytical framework for each of the keywords listed above. To extract salient points, randomly selected sentences from the corpus were used. Main theme 1: e-banking use Regarding the concept of e-banking, all interviewees repeatedly mentioned that electronic banking services are of immense importance and necessary for daily life. For example, one respondent stated, “I think it is now obligatory to use e-banking services given all the advantages they can provide”. It was also discovered that the concept of usage is significant for all interviewees, which was mentioned 42 times. Almost all of the sentences referred to usage, particularly regular usage, sometimes even intense usage, and only a few times limited usage by electronic bank customers. Moreover, one of the interviewees noted that is good to avoid human contact through the use of e-banking, but the quality of the services still needs improvement”. Main theme 2: Technology acceptance Regarding the concept of usefulness or advantage as evoked by the interviewees, all respondents admit that electronic banking services are indispensable for the user’s daily life, which is why they listed many advantages regarding electronic banking services, each according to their degree of usage and integrity in information systems. Example: I can check my account and credit at any time, either from ATMs or from my smartphone or computer, and it is a real advantage. Ease of use of electronic banking services was mentioned by half of the interviewees, noting that this factor can contribute to users’ intention to adopt e-banking, especially since respondents have varying degrees of IT proficiency. Therefore, it is justifiable that not everyone finds ease of use important when using e-banking services. For example, one respondent said, “I find banking applications on my mobile very useful for daily life. It makes payment for products and services easier”. The concept of Trust was found to be very influential, as it was present in all randomly selected sentences and was mentioned by all interviewees. Some customers trust electronic banking services completely, while others prefer to be more cautious and have relative trust instead of complete trust. For example, one respondent stated, “Trust for me is relative, I cannot completely trust electronic banking services”. Main theme 3: Electronic word of mouth (e-WOM) Called upon by “social media” in the interview guide to facilitate its perception, electronic word-of-mouth (e-WOM) was very significant for this study. Sometimes negative, sometimes positive, but most of the time, playing a mixed role, having both a positive and negative influence on electronic banking clients, and it varies depending on the personality or social orientation of the internet user. Example: They have a very significant effect, whether positive or negative, I think that social media can influence e-banking users through all the stories we hear about on the internet regarding this kind of technology. However, besides the variables proposed in the theoretical model, we have identified other variables influencing customers to use electronic banking services in Algeria. Costs and fees were very significant in our study. This variable was defined by (Nguyen et al., 2019, p. 11) [63] as the level to which an individual believes that using e-banking will incur costs. Constantinides (2002), p. 8 [64] as the possible expenses associated with using ICT, namely equipment costs, access costs, and transaction fees. All interviewees mentioned bank charges (commissions, costs, fees, etc.) at least once. All respondents complained about the fees, sometimes called exorbitant, especially when the bank does not clearly communicate these fees and are automatically deducted during banking operations (transfer, withdrawal, etc.). In fact, one interviewee told us that he cancelled his bank account because of unclear commissions deducted from his account. Example: I submitted a request to cancel my account because it generated many fees without being able to have a clear picture of these deductions. These results are consistent with several studies in e-banking, such as Thanh D. Nguyen et al., (2019), p. 7 [65] study, in which perceived costs significantly affected the use of m-Banking. Also, in the study by Anouze & Alamro, (2020), p. 9 [66], reasonable prices, stand out as the barrier to intention to use e-banking services in Jordan. On the other hand, the qualitative analysis has highlighted the determinant of “Quality”, which is a significant factor in the use of online banking services in Algeria. Example: The quality of e-banking services in Algeria still needs to be improved. It was defined by Venkatesh; Viaswanath & Davis; Fred D., (2000), p. 10 [67] as the degree to which an individual believes the system performs its tasks effectively. In Yaseen & El Qirem’s (2018), p. 6 [68] study, perceived quality has a vital impact on the behaviour intention in an electronic context, which is adequate with our results. Similarly, Naik et al., (2010), p. 8 [69] found that dominant dimensions of service quality directly influence behaviour intention and consumer satisfaction. Figure 2: Structural model Source: By researchers, based on content analysis. 7. Discussion and implications: 7.1 Discussion: This qualitative study attempted to confirm the factors listed in the Technology Acceptance Model of Davis, (1989), and possibly discover other factors influencing the adoption of electronic banking services among Algerian bank customers. Like other researchers, such as Thanh D. Nguyen et al., (2019), p. 9 [70] we confirm in our proposed model the influence of electronic word-of-mouth, perceived usefulness, perceived trust, and perceived costs on the use of electronic banking services by Algerian bank customers. However, perceived ease of use was found to be less influential among Algerian bank customers, unlike Salimon et al., (2017), p. 4 [71] study, which classified ease of use as crucial for use and considered banking services to be easy to use if the user expends little physical and mental effort compared to other proposed factors. Furthermore, our results were aligned with the findings of Salloum & Al-Emran, (2018), p. 11 [72], who were able to confirm the significant influence of perceived usefulness and perceived trust among electronic payment users. The results also support Kurnia et al., (2010), p. 7 [73] study conducted in China, which confirmed that customers’ lack of trust seriously impedes the growth of e-banking. Similarly, our results were in agreement with those of Petrović et al., (2021), p. 4 [74], who confirmed the influence of electronic word-of-mouth (eWOM) on the intention to use mobile banking. The results of Luarn & Lin, (2005), p. 8 [75] like ours, also confirmed the influence of perceived costs on the intention to use e-banking. Based on an inductive qualitative survey conducted throughout Algeria, the results showed that using e-banking is determined by several factors. Such as the perceived ease of use adopted in the model, perceived usefulness adopted in the original TAM model by Davis et al., (1989), as well as perceived trust taken into account in several studies, such as Garín-Muñoz et al., (2019) p. 9 [76] study. 7.2 Academic implications: This study provides significant academic contributions to the literature on technology adoption and acceptance. Firstly, our study proposes an extended theoretical model that integrates a fusion of the Technology Acceptance Model and Theory of Planned Behaviour with the extension of two variables that we deemed potential: namely, e-WOM and perceived trust. All of these variables were tested on a sample of customers in the Algerian context as a developing country. Secondly, this study aimed not only to validate the proposed variables but also to open the field of appearance to other variables that may be significant for Algerian bank customers, such as perceived trust and perceived costs. Thirdly and finally, our qualitative study adopted a thematic content analysis, which is a crucial tool for addressing many scientific questions in the field of ICT that may have been taboo for statistical analysis on the one hand and, on the other hand, to form a platform for a possible quantitative study in the same context. 7.3 Managerial Implications: On the managerial side, the findings will provide researchers with a broader view of factors that may influence the use of electronic services provided by Algerian banks. Important insights from this qualitative study have emerged, forming an ideal platform for future, more precise quantitative studies. Firstly, the perceived ease of use and perceived usefulness factors extracted from Davis’ (1989) original TAM model were confirmed in this study for clients operating in a developing banking sector. These factors have a crucial impact on Algerian e-banking users. Perceived trust and perceived costs modified in the technology acceptance model have also proven their impact on the use of electronic banking services by Algerian clients. On the other hand, the electronic word-of-mouth (eWOM) factor was also deemed significant for e-banking users in Algeria. For IT managers, the results suggest studying the ergonomics of all available e-banking channels in the country and ensuring they are easy to use and useful for users. This can be achieved by launching demonstration campaigns through videos on banks’ official websites, on social media, as well as in bank waiting rooms, and by investing in advertising in this sense. Secondly, Algerian clients will adopt e-banking services only if they believe they are equipped with all security measures. The lack of a reliable and robust system for managing financial transactions can affect clients’ trust in this system. On the other hand, the Algerian banking sector must pay attention to the costs demanded from clients to benefit from the system, as this is a young society that is very careful about understanding and using IT. Finally, Algerian banks must take their interaction with clients on social media and all electronic platforms seriously, as the influence of electronic word-of-mouth can be fatal for potential or prospective clients. Therefore, it would be clear to involve bank managers to salvage the image of the banks (GBADEBO, 2016, p. 3) [77]. 8. Limitations and Conclusion: Despite the interesting contributions this study provides, it is not without limitations. On the one hand, using qualitative survey data on a restricted number of respondents does not provide definitive evidence. Therefore, quantitative and longitudinal studies, which establish causality through the temporal precedence of constructs, are needed to justify the validity of the proposed model and the relationships among the constructs. On the other hand, the sample size of the qualitative study is relatively small; thus, a quantitative study is strongly recommended to boost the statistical power of the results (Champely & Verdot, 2007, p. 14) [78]. Finally, the data were collected in Algeria, and the generalizability of the results to other developing countries may be limited. This study examined the factors that influence customers’ use of electronic banking services in Algeria, namely ease of use, perceived usefulness, perceived trust, perceived costs, behavioural intention, and electronic word-of-mouth (eWOM). This paper proposes a modified model of the Technology Acceptance Model (TAM). 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