IJBED 2051-848X 2051-8498 https://doi.org/10.24052/IJBED/ 33 Volume 14 Issue 01 2026-05-01

234 https://ijbed.org/details&cid=234 2026-04-03 Foreign direct investment (FDI) is a key indicator of regional economic dynamism, especially in countries characterized by structural disparities such as Mexico. This study examines the relationship between foreign direct investment (FDI) inflows received by Mexican states and variables including Gross Domestic Product (GDP), perceived insecurity, regional competitiveness, and geographic location. A multiple linear regression model was applied to data from 2019 to 2023, incorporating regional dummy variables to capture location-specific effects. The results reveal a clear and consistent advantage for northern regions—particularly the Northeast, Northwest, and North Center—in attracting investment, even after controlling for GDP levels, insecurity perception, and competitiveness. These regions concentrate on the highest FDI inflows and display positive and relevant coefficients in the model, suggesting a more favorable institutional, economic, and logistical environment. In contrast, regions such as the South Center, Southwest, and Southeast exhibit negative or statistically weak coefficients, pointing to a lower structural capacity to attract capital. This may be attributed to longstanding limitations in infrastructure, connectivity, political stability, and institutional development. This pattern reflects a well-documented trend in economic literature: the persistent territorial inequality between northern and southern Mexico. Such disparity stems from both historical legacies of centralized development models and the lack of continuity in public policies aimed at regional advancement. The study confirms that geographic location is not merely a spatial variable but an economic determinant perpetuating investment distribution asymmetries. Therefore, it is essential to promote regionally differentiated development strategies that not only enhance competitiveness indicators in the south but also foster institutional and security conditions conducive to sustained national and foreign investment. Aguila-Retureta, J. (2015). *Regional disparities and industrial clusters in Mexico.* Mexico City: UNAM. Botello; Juan (2025). *The role of state competitiveness and perceived insecurity in attracting foreign direct investment in Mexico*, IJBED , Volume 13 Issue 01 Christaller, W. (1933). *Central places in Southern Germany.* Jena: Gustav Fischer. Fujita, M. (1996). Economics of agglomeration. *Journal of the Japanese and International Economies, 10*(4), 339–378. Hamel, G. (1985). *The multinational corporation and global production strategies.* Cambridge: Harvard Business School Press. Henderson, J.V., Kuncoro, A., & Turner, M. (1992). Industrial development and the concentration of manufacturing. *The Review of Economic Studies, 59*(3), 479–496. Instituto Mexicano para la Competitividad (IMCO). (2023). *Competitiveness Index 2023.* Mexico City: IMCO. Instituto Nacional de Estadística y Geografía (INEGI). (2023). *Foreign Direct Investment Data 2019–2023.* Mexico City: INEGI. Jordaan, J.A. (2024). *Industrial agglomeration and regional inequality in Mexico: 1950–2019.* Mexico City: El Colegio de México. Krugman, P. (1991). *Geography and trade.* Cambridge: MIT Press. Krugman, P. (1999). The role of scale economies in economic geography. *International Economic Review, 40*(2), 223–247. Manet, C. (2014). *Urban economies and globalization.* Paris: OECD Publishing. Myrdal, G. (1957). *Economic theory and underdeveloped regions.* London: Duckworth. Office of the United States Trade Representative (USTR). (2020). *United States–Mexico–Canada Agreement (USMCA).* Washington, D.C.: USTR. Perroux, F. (1955). Note sur la notion de “pôle de croissance.” *Économie Appliquée, 8*(1), 307–320. Puga, D. (1999). The rise and fall of regional inequalities. *European Economic Review, 43*(2), 303–334. Rodríguez-Oreggia, E. (2005). Regional disparities and economic growth in Mexico. *World Development, 33*(3), 513–530. Thünen, J.H. von. (1966). *Isolated state: An analysis of agriculture and economics.* Oxford: Pergamon Press.  Weber, A. (1909). *Theory of the location of industries.* Chicago: University of Chicago Press. Wolman, H. (2010). Clusters and regional inequality. *Economic Development Quarterly, 24*(1), 23–36. https://ijbed.org/cdn/article_file/2026-04-03-11-37-51-AM.pdf Juan Carlos Botello Mariana Echeagaray Santibanez Foreign direct investment regional competitiveness insecurity state GDP territorial inequality Mexican regions. 331 10 0

235 https://ijbed.org/details&cid=235 2026-04-03 Artificial Intelligence (AI) is transforming labour markets globally, creating high-skill opportunities while shrinking routine middle-skill jobs, intensifying inequality and urgent reskilling needs. This paper examines AI-driven labour market polarisation and workforce reskilling in India, where rapid technological change is reshaping job structures and skill demands. Grounded in Skill Biased Technological Change (SBTC) and Human Capital Theory, the study demonstrates that AI adoption disproportionately benefits high-skilled workers, driving growth in high-wage occupations, while routine middle-skilled roles decline, intensifying wage disparities and increasing demand for new competencies.  Using secondary data and official reports from 2020–2024, the analysis identifies India’s distinctive polarisation pattern: a shrinking middle-skill workforce alongside a persistently large low skill labour segment. Limited reskilling coverage further constrains workers’ ability to adapt to AI driven changes, risking a “low-skill trap.” Comparative insights from the United Kingdom, a developed economy with more systematic AI adoption and structured training programs, highlight how proactive reskilling mitigates workforce displacement, offering lessons for emerging economies like India.  The findings underscore the urgent need for targeted workforce planning, investment in human capital, and collaboration between industry, government, and educational institutions. By linking theory with empirical evidence, this study provides actionable insights for policymakers, business leaders, and  academics seeking to navigate AI-driven labour market transformations. The paper highlights how emerging economies can leverage AI for productivity and growth while addressing inequality and skill gaps, contributing to sustainable and inclusive workforce development. Acemoglu, P. R., 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor.". Journal of Economic Perspectives. Goos, M. A. M. a. A. S., 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring.". American Economic Review. Autor, D., 2019. Toward Understanding the Impact of Artificial Intelligence on Labor. Boston University School of Law. Maarten Goos, A. M., 2007. Lousy and Lovely Jobs: The Rising Polarization of Work in Britain. The Review of Economics and Statistics. Autor, D. H., 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation.". Journal of Economic Perspectives. Acemoglu, D. a. P. R., 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment.". American Economic Review . Acemoglu, 2018. The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment. American Economic Review. Becker, G. S., 1993. Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, Third Edition. National bureau of economic research . Venkat Ram Reddy Ganuthula, K. K. B., 2025. Skill-Based Labor Market Polarization in the Age of AI: A Comparative Analysis of India and the United States. Bresnahan, T. & Trajtenberg, M., 1995. General Purpose Technologies ‘Engines of Growth'?. Research gate. Jadhav, D. S., 2021. Understanding Artificial Intelligence Adoption, Implementation, and Use in Small and Medium Enterprises in India. Walden university. Bhalerao, K. & Kumar, A., 2022. A Study of Barriers and Benefits of Artificial Intelligence Adoption In Small And Medium Enterprise. Grace, I. & Onum, F. O., 2022. The Impact of Artificial Intelligence on Labor Markets and Wage Inequality: A Computational Economic Perspective. Research gate. Ionașcu, C. M., 2025. Artificial Intelligence Adoption in the European Union: A Data-Driven Cluster Analysis (2021– 2024). Upreti, A. & Sridhar, V., 2024. Effect of automation of routine and non-routine tasks on labour demand &wages Autor, D., Levy, F. & Murnane, R. J., 2003. The Skill Content Of Recent Technological Change: An Empirical Exploration. Macias, E. F., 2016. Routine-biased technical change and job polarization in Europe. Autor, D. H. & Dorn, D., 2013. The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market. American Economic Review. Bessen, J., 2019. Automation and jobs: when technology boosts employment. Research gate. Daniele Siena, R. Z., 2024. Job Polarisation, Labour Market Fluidity and the Flattening of the Phillips Curve. The Economic Journal. N. Giri, P. B. K. G., 2025. Bridging the Skills Gap: Reskilling and Upskilling India's Workforce for the AI Revolution". Pablo Illanes, S. L. M. M. S. R. M. T., 2018. Retraining and Reskilling Workers in the Age of Automation, s.l.: McKinsey Global Institute (MGI), McKinsey & Company. Kothari, A. & Cruikshank, S. A., n.d. 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Armonk, New York. Anon., 2021. Annual Report 2021, s.l.: International Labour Organization . Anon., 2022. NSDC. [Online] Available at: https://nsdcindia.org/ Anon., 2020. World Economic Forum. [Online] Available at: https://www.weforum.org/publications/the-future-of-jobs-report- 2020/? utm_source=chatgpt.com Autor, D., Levy, F. & Murnane, R. J., 2003. The Skill Content of Recent Technological Change: An Empirical Exploration. Anon., 2024. NASSCOM. [Online] Available at: https://nasscom.in/knowledge-center/publications/ai-adoption-index-20-tracking-indias-sectoralprogress-ai-adoption https://ijbed.org/cdn/article_file/2026-04-03-12-00-00-PM.pdf Gunjan Maan Artificial Intelligence (AI) labour market polarisation workforce reskilling Emerging Economies 366 11 0

236 https://ijbed.org/details&cid=236 2026-04-03 This paper introduces the WEMPOWERMENT Scorecard, a contextualized assessment tool designed to measure women’s entrepreneurial empowerment in developing economies. The purpose of the research is to conceptualize, develop, and validate a multidimensional tool that can guide inclusive ecosystem reform in developing economies. Grounded in Entrepreneurship Theory, Social Justice Theory, and Empowerment Theory, the scorecard is based on a multidimensional model developed from 72 phenomenological qualitative interviews with women entrepreneurs in Egypt, capturing empowerment as a dynamic and transformative process. A three-phase pilot involving 90 women entrepreneurs was conducted to test the tool’s clarity, cultural resonance, and empirical robustness. Reliability and validity were established through construct alignment with the model’s core dimensions, expert evaluations from scholars in gender and entrepreneurship, participant feedback on usability and relevance, and internal consistency analysis using Cronbach’s Alpha.  Findings reveal that empowerment is best understood across four interrelated dimensions: within, to, with, and over, each achieved through perceptual, cognitive, relational, and material transformations. These processes unfold across individual, organizational, and community levels, highlighting the systemic nature of women’s entrepreneurial empowerment.  The research presents a comprehensive and operational framework for assessing women’s empowerment in entrepreneurship in developing economies. The WEMPOWERMENT Scorecard emerges as a theoretically grounded and practically applicable disagnostic and strategic tool. It enables stakeholders accross policy, finance, development, education, and support sectors to design evidence-based interventions that address structural barriers and advance gender-inclusive and equitable ecosystem reform. Its adaptable design and methodological rigor make it a significant contribution to gendered entrepreneurship research, with strong potential for application across other developing country contexts.   Alkire, S., Meinzen-Dick, R., Peterman, A., Quisumbing, A., Seymour, G., & Vaz, A. (2013) 'The Women’s Empowerment in Agriculture Index', World Development, 52, pp. 71-91. Barsoum, M. (2024) 'Empowering Women Entrepreneurs in Egypt' Dual PhD/DBA Dissertation. Switzerland: Monarch Business School. Bies, R. , & Moag, J. (1986) 'Interactional justice: Communication criteria of fairness'. In B. Sheppard, Research on negotiation in organizations, pp. 43–55. Greenwich, CT: JAI Press. Business Insider Africa. 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237 https://ijbed.org/details&cid=237 2026-04-03 This research paper examines how circular economy (CE) principles influence urban sustainability in the real estate sector of Dhaka, Bangladesh, especially in relation to Sustainable Development Goal 11 (SDG 11). Given the rapid urbanisation challenges in cities such as Dhaka, Bangladesh, understanding CE's potential to foster inclusive, safe, and resilient urban environments is crucial yet insufficiently explored. Following PRISMA 2020 guidelines, we systematically searched the databases for peer-reviewed articles and grey literature published from January 2018 to October 2025. From 230 initial records, 81 studies were selected through rigorous screening and quality appraisal using the CASP and MMAT frameworks. This paper examines the economic alignment between Circular Economy (CE) strategies and the objectives of SDG 11. It explores economic barriers, financial enablers, and investment challenges, while proposing a comprehensive multi-theoretical framework and a conceptual model to understand the economic dimensions of CE transitions. CE practices significantly contribute to achieving SDG 11 by reducing waste and improving resource efficiency. However, notable research gaps exist regarding the economic aspects of CE in real estate, business-led transitions, informal sector inclusion, and social inclusion in rapidly urbanising areas.  This paper presents a multi-theoretical framework integrating Circular Economy Theory, Social Transition Theory, Institutional Theory, and Community Governance Theory to examine the adoption of CE practices in the real estate sectors of developing countries such as Bangladesh. It enhances theoretical understanding by uniting various perspectives on CE transitions relevant to the Global South. Additionally, it outlines practical strategies for policymakers, developers, and urban planners to effectively implement CE practices aligned with SDG 11 in Dhaka, Bangladesh. The review also identifies critical gaps in institutional frameworks and policy coherence that impede CE progress in rapidly urbanising cities, laying the groundwork for future empirical research on business-led CE initiatives. Abubakar, F. 2018. An investigation into the drivers, barriers and policy implications of circular economy usinsg a mixed-mode research approach. University of Sheffield. Abunyewah, M., Erdiaw-Kwasie, M. O., Okyere, S. A. & Boateng, F. G. 2023. Advancing a slum–circular economy model for sustainability transition in cities of the Global South. Nature Sustainability, 6, 1304-1311. Ahmad, S., Daddi, T. & Iraldo, F. 2024. Integration of open innovation, circularity and sustainability: A systematic mapping of connections, analysis of indicators and future prospects. 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238 https://ijbed.org/details&cid=238 2026-04-03 This study examined the influence of green business practices on the sustainability of small and medium-scale enterprises. A quantitative research approach and a survey design were deployed. A structured questionnaire was administered to 150 SME owners and managers across various sectors, including retail, services, and manufacturing. The data was analyzed using SPSS version 29. The findings show that green business practices had a positive impact on SME sustainability, with enhanced operational efficiency and market competitiveness observed. Key benefits of green business practices included enhanced brand image, compliance with regulations, increased customer loyalty, and cost savings. The findings underscore the relevance of the Natural Resource-Based Theory (NRBT), which emphasises pollution prevention, product stewardship, and sustainable development as strategic capabilities for long-term success. Furthermore, the findings showed a relatively high rate of adoption of green business practices; however, this adoption is primarily limited to basic and easily implementable practices such as waste reduction and the use of eco-friendly products. While overall awareness of green business concepts remains moderate, some SMEs may engage in these practices out of perceived benefits like cost savings, compliance with regulations rather than a deep understanding of sustainability principles. It also emerged that ethical considerations and the desire to enhance corporate reputation are among the most influential drivers of green business practice adoption. Financial constraints, lack of institutional support, and technical knowledge are the most significant barriers. Organising regular capacity-building programmes and awareness campaigns targeting SME owners and managers would contribute to improving their understanding of sustainable business practices. 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239 https://ijbed.org/details&cid=239 2026-05-15 This research analyses the short-run and long-run relationship between exports, imports, labour, capital and gross domestic product of Mexico from 2002 to 2024 by means of a neoclassical framework under an autoregressive distributed-lagged error correction model. We reveal that these series are cointegrated. The empirical examination applies several diagnostic tests to analyse the error terms and the appropriateness of the model specification. It was found a long-run convergence among the observed variables providing evidence in the long-run that imports and capital positively influence output net of exports and that exports and labour have negative effects on such variable. In the short-run, estimates showed that exports have a positive impact on GDP net of exports whereas imports and capital display negative coefficients. The findings must also be interpreted in light of Mexico’s trade liberalization strategy and its network of free trade agreements. It is important to consider that the 2008 financial crisis and the COVID-19 pandemic, exposed vulnerabilities in Mexico’s dependence on external demand. These results raise questions about the sustainability of an export-oriented growth model. JEL Classification: F1, F4, O4, C220, C32, C18. Akaike, H. (1970). Statistical predictor identification. Annals of the Institute of Statistical Mathematics, 22, 203-217. https://doi.org/10.1007/BF02506337 Akaike, H. (1974). A New Look at the Statistical Model Identification. IEEE Transactions on Automatic Control, AC-19, 716–723. https://doi.org/10.1109/TAC.1974.1100705 Al-Yousif, Y. (1997). Exports and economic growth: some empirical evidence from the Arab Gulf countries. Applied Economics, 29, 693-697. https://www.tandfonline.com/doi/abs/10.1080/000368497326624 Abual-Foul, B. (2004). 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