Pub Date : 2026-01-01DOI: 10.1016/j.bir.2025.100772
Ilker Yilmaz
This study investigates the impact of environmental, social, and governance (ESG) practices on working capital management (WCM) with a global sample of nonfinancial firms from 2004 to 2023. We hypothesize that ESG performance has a positive impact on WCM. Using a sample of 8350 firms in 73 countries, we perform panel data regressions and employ the generalized method of moments (GMM) as robustness check and to address endogeneity issues. Our results reveal that ESG performance, proxied by the combined ESG score, has a significantly negative impact on the cash conversion cycle (CCC). The majority of other ESG scores demonstrate a similar pattern, although some results are insignificant. The study contributes to the empirical literature on the impact of ESG performance by including multiple ESG dimensions and a large global sample. The findings have practical implications for managers and policy makers.
{"title":"Unraveling the influence of ESG performance on working capital management: An empirical analysis of a global panel dataset","authors":"Ilker Yilmaz","doi":"10.1016/j.bir.2025.100772","DOIUrl":"10.1016/j.bir.2025.100772","url":null,"abstract":"<div><div>This study investigates the impact of environmental, social, and governance (ESG) practices on working capital management (WCM) with a global sample of nonfinancial firms from 2004 to 2023. We hypothesize that ESG performance has a positive impact on WCM. Using a sample of 8350 firms in 73 countries, we perform panel data regressions and employ the generalized method of moments (GMM) as robustness check and to address endogeneity issues. Our results reveal that ESG performance, proxied by the combined ESG score, has a significantly negative impact on the cash conversion cycle (CCC). The majority of other ESG scores demonstrate a similar pattern, although some results are insignificant. The study contributes to the empirical literature on the impact of ESG performance by including multiple ESG dimensions and a large global sample. The findings have practical implications for managers and policy makers.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"26 1","pages":"Article 100772"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.bir.2025.10.027
Atta ul Mustafa , Ahmet Faruk Aysan , Nasim Shah Shirazi
This paper investigates how structured persuasive strategies, grounded in Cialdini's principles of influence, are embedded in the narrative disclosures of banks and influence financial outcomes. Using a novel persuasion index derived from supervised natural language processing (NLP) analysis of 544 annual reports from publicly listed firms in the Middle East and North Africa Region (MENA) region (2016–2023), we measure rhetorical intensity across five persuasion dimensions: reciprocity, consistency, authority, social proof, and liking. Using system generalized method of moments (GMM) to address endogeneity concerns, we find that higher persuasive framing significantly improves the return on assets, return on equity, and solvency (Z-score). Our sub-index analysis reveals that reciprocity and social proof cues enhance financial performance, whereas excessive authority claims negatively impact profitability. These findings have important implications for policy makers, suggesting that disclosure standards should account for the behavioral effects of narrative construction.
{"title":"Words that yield: The invisible hand of financial storytelling","authors":"Atta ul Mustafa , Ahmet Faruk Aysan , Nasim Shah Shirazi","doi":"10.1016/j.bir.2025.10.027","DOIUrl":"10.1016/j.bir.2025.10.027","url":null,"abstract":"<div><div>This paper investigates how structured persuasive strategies, grounded in Cialdini's principles of influence, are embedded in the narrative disclosures of banks and influence financial outcomes. Using a novel persuasion index derived from supervised natural language processing (NLP) analysis of 544 annual reports from publicly listed firms in the Middle East and North Africa Region (MENA) region (2016–2023), we measure rhetorical intensity across five persuasion dimensions: reciprocity, consistency, authority, social proof, and liking. Using system generalized method of moments (GMM) to address endogeneity concerns, we find that higher persuasive framing significantly improves the return on assets, return on equity, and solvency (Z-score). Our sub-index analysis reveals that reciprocity and social proof cues enhance financial performance, whereas excessive authority claims negatively impact profitability. These findings have important implications for policy makers, suggesting that disclosure standards should account for the behavioral effects of narrative construction.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"26 1","pages":"Article 100754"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.bir.2025.10.030
Hasan Meral , Behlul Ersoy , Mesut Dogan
Sustainability has become a critical concern in finance, in particular for the insurance industry, which faces rising environmental and social risks. This paper examines the influence of environmental, social, and governance (ESG) factors on the performance of global insurance companies. Using a comprehensive dataset of 22 life and 59 non–life insurance firms from 2013 to 2022, we employ panel data analysis to explore the relationship between ESG scores and key performance metrics. Our findings reveal that higher ESG scores are significantly associated with a higher return on assets, more efficient management of expense and loss ratios, and increases in investment returns. These results show the importance of incorporating ESG factors into insurance decision-making to enhance sectoral resilience and corporate performance. The study concludes by emphasizing the need for insurers to leverage their technical expertise and strategic risk management capabilities in order to address sustainability challenges effectively.
{"title":"Enhancing sustainability: The impact of ESG factors in global insurance performance","authors":"Hasan Meral , Behlul Ersoy , Mesut Dogan","doi":"10.1016/j.bir.2025.10.030","DOIUrl":"10.1016/j.bir.2025.10.030","url":null,"abstract":"<div><div>Sustainability has become a critical concern in finance, in particular for the insurance industry, which faces rising environmental and social risks. This paper examines the influence of environmental, social, and governance (ESG) factors on the performance of global insurance companies. Using a comprehensive dataset of 22 life and 59 non–life insurance firms from 2013 to 2022, we employ panel data analysis to explore the relationship between ESG scores and key performance metrics. Our findings reveal that higher ESG scores are significantly associated with a higher return on assets, more efficient management of expense and loss ratios, and increases in investment returns. These results show the importance of incorporating ESG factors into insurance decision-making to enhance sectoral resilience and corporate performance. The study concludes by emphasizing the need for insurers to leverage their technical expertise and strategic risk management capabilities in order to address sustainability challenges effectively.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"26 1","pages":"Article 100757"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.bir.2025.100765
Ali Yavuz Polat , Erhan Mugaloglu , Khaled Elmawazini
We investigate the dynamic interplay between climate policy uncertainty (CPU), geopolitical risk (GPR), oil prices, and stock market performance within the Middle East and North Africa (MENA) region, considering the dependence of the region's economies on oil. CPU is used to capture a nuanced understanding of how global environmental policy uncertainties shape financial market dynamics. Employing a Smooth Transition Vector Error Correction Model, we analyze both long-term co-integration and short-term fluctuations. The results reveal that oil and capital market shocks have a similar, initially positive impact on the Dow Jones MENA index (DJMENA), while the responses to CPU and GPR differ over time. Geopolitical shocks initially boost the DJMENA index owing to supply disruptions, but eventually exert a negative impact as alternative energy investments may increase in the long run. However, the DJMENA index responds positively to increasing uncertainty in the CPU. In the short run, oil and capital market shocks account for up to 98 % of the variation in the DJMENA index, whereas the CPU and GPR play a larger role in the long run. The historical decomposition highlights how the COVID-19 pandemic and the Russia–Ukraine conflict further intensified market volatility. Although the GPR exerts a more pronounced immediate effect, CPU's impact intensifies over time, highlighting the necessity for MENA markets to account for climate uncertainty in their financial strategies. These findings underscore the importance of adapting to shifting global pressures to maintain resilient performance in oil-dependent economies.
{"title":"Risk or resilience? Assessing the impact of climate policy uncertainty on MENA stock markets: A ST-VECM analysis","authors":"Ali Yavuz Polat , Erhan Mugaloglu , Khaled Elmawazini","doi":"10.1016/j.bir.2025.100765","DOIUrl":"10.1016/j.bir.2025.100765","url":null,"abstract":"<div><div>We investigate the dynamic interplay between climate policy uncertainty (CPU), geopolitical risk (GPR), oil prices, and stock market performance within the Middle East and North Africa (MENA) region, considering the dependence of the region's economies on oil. CPU is used to capture a nuanced understanding of how global environmental policy uncertainties shape financial market dynamics. Employing a Smooth Transition Vector Error Correction Model, we analyze both long-term co-integration and short-term fluctuations. The results reveal that oil and capital market shocks have a similar, initially positive impact on the Dow Jones MENA index (DJMENA), while the responses to CPU and GPR differ over time. Geopolitical shocks initially boost the DJMENA index owing to supply disruptions, but eventually exert a negative impact as alternative energy investments may increase in the long run. However, the DJMENA index responds positively to increasing uncertainty in the CPU. In the short run, oil and capital market shocks account for up to 98 % of the variation in the DJMENA index, whereas the CPU and GPR play a larger role in the long run. The historical decomposition highlights how the COVID-19 pandemic and the Russia–Ukraine conflict further intensified market volatility. Although the GPR exerts a more pronounced immediate effect, CPU's impact intensifies over time, highlighting the necessity for MENA markets to account for climate uncertainty in their financial strategies. These findings underscore the importance of adapting to shifting global pressures to maintain resilient performance in oil-dependent economies.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"26 1","pages":"Article 100765"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.bir.2025.10.028
Mehmet Benturk
This paper examines the relationship between institutional ownership and stock price crash risk for non-financial firms listed on Borsa Istanbul from 2005 to 2023. The findings show that greater institutional investor participation increases the risk of future crashes, supporting the short-termism theory rather than monitoring theory. This result aligns with research on emerging markets, such as China and Vietnam, but it contrasts with evidence from developed markets such as the US. The relationship is statistically and economically significant in the traditional framework that covers only investment funds and investment trusts, including local and foreign institutional investors. A fixed-effect model, using the first-difference of overall and local professional institutional ownership, provides robust evidence for short-termism theory: institutional investors heighten crash risk by reducing holdings (i.e., “voting with their feet”). However, this approach does not yield statistically significant results for foreign institutional investors.
{"title":"Stock price crash risk and institutional ownership: Evidence from Borsa Istanbul","authors":"Mehmet Benturk","doi":"10.1016/j.bir.2025.10.028","DOIUrl":"10.1016/j.bir.2025.10.028","url":null,"abstract":"<div><div>This paper examines the relationship between institutional ownership and stock price crash risk for non-financial firms listed on Borsa Istanbul from 2005 to 2023. The findings show that greater institutional investor participation increases the risk of future crashes, supporting the short-termism theory rather than monitoring theory. This result aligns with research on emerging markets, such as China and Vietnam, but it contrasts with evidence from developed markets such as the US. The relationship is statistically and economically significant in the traditional framework that covers only investment funds and investment trusts, including local and foreign institutional investors. A fixed-effect model, using the first-difference of overall and local professional institutional ownership, provides robust evidence for short-termism theory: institutional investors heighten crash risk by reducing holdings (i.e., “voting with their feet”). However, this approach does not yield statistically significant results for foreign institutional investors.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"26 1","pages":"Article 100755"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.bir.2025.100771
Yüksel Okşak , Yasin Büyükkör , Tufan Sarıtaş
In this study, we develop a hybrid forecasting framework that integrates discrete wavelet transform with multiple machine and deep learning architectures to address nonlinearity and regime-dependent dynamics in financial markets. Log-return series using daily data from the BIST 100, S&P 500, and Shanghai Composite indexes spanning 2015–2025 are subject to three-level Daubechies-4 wavelet decomposition, which yields approximation and detail coefficients that capture multiresolution temporal patterns. Four feature configurations are systematically evaluated: base (lagged returns only), pure wavelet approximation (A1–A3), hybrid wavelet approximation (lags combined with A1–A3), and wavelet approximation-detail (A1–A3 with D1–D3). Random forest, Support Vector Regression, Long Short-Term Memory, and Gated Recurrent Unit models are trained on each configuration, enabling direct assessment of the effectiveness of wavelet feature engineering. A three-state Gaussian hidden Markov model identifies bull, bear, and sideways regimes based on risk-adjusted returns, stratifying out-of-sample results to examine model robustness across varying market conditions without influencing training procedures. Our results demonstrate that wavelet-enhanced configurations, in particular the full approximation-detail specification, reduce forecast errors by 20–40 percent across all indexes and algorithms. Diebold–Mariano tests confirm statistical significance both globally and within each market regime. Our findings confirm that discrete wavelet transform is essential preprocessing for volatile financial markets, offering actionable insights for algorithmic trading, risk management, and policy frameworks in emerging economies.
{"title":"Wavelet-enhanced multimodel framework for stock market forecasting: A comprehensive analysis across market regimes","authors":"Yüksel Okşak , Yasin Büyükkör , Tufan Sarıtaş","doi":"10.1016/j.bir.2025.100771","DOIUrl":"10.1016/j.bir.2025.100771","url":null,"abstract":"<div><div>In this study, we develop a hybrid forecasting framework that integrates discrete wavelet transform with multiple machine and deep learning architectures to address nonlinearity and regime-dependent dynamics in financial markets. Log-return series using daily data from the BIST 100, S&P 500, and Shanghai Composite indexes spanning 2015–2025 are subject to three-level Daubechies-4 wavelet decomposition, which yields approximation and detail coefficients that capture multiresolution temporal patterns. Four feature configurations are systematically evaluated: base (lagged returns only), pure wavelet approximation (A1–A3), hybrid wavelet approximation (lags combined with A1–A3), and wavelet approximation-detail (A1–A3 with D1–D3). Random forest, Support Vector Regression, Long Short-Term Memory, and Gated Recurrent Unit models are trained on each configuration, enabling direct assessment of the effectiveness of wavelet feature engineering. A three-state Gaussian hidden Markov model identifies bull, bear, and sideways regimes based on risk-adjusted returns, stratifying out-of-sample results to examine model robustness across varying market conditions without influencing training procedures. Our results demonstrate that wavelet-enhanced configurations, in particular the full approximation-detail specification, reduce forecast errors by 20–40 percent across all indexes and algorithms. Diebold–Mariano tests confirm statistical significance both globally and within each market regime. Our findings confirm that discrete wavelet transform is essential preprocessing for volatile financial markets, offering actionable insights for algorithmic trading, risk management, and policy frameworks in emerging economies.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"26 1","pages":"Article 100771"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.bir.2025.10.019
Meiyi Li , Yufei Gan
Strategic environmental, social, and governance (ESG) disclosure practices that create favorable impressions while concealing unfavorable environmental performance have become increasingly common among corporations. This study investigates how such practices influence green technology innovation bubbles, where firms prioritize innovation quantity over quality. Drawing on institutional theory and impression management perspectives, we examine this relationship using Chinese A-share listed companies (2015–2024). Through propensity score matching, difference-in-differences, placebo tests, and IV approaches, we establish that strategic ESG disclosure positively influences green-innovation bubbles. CEO green experience weakens this relationship, whereas managerial myopia strengthens it. Information asymmetry and greenwashing mediate this relationship. The effects are stronger for non-SOEs, during periods of high economic uncertainty and under weaker environmental regulations. Our study contributes to the sustainability literature by documenting how strategic ESG behavior distorts innovation patterns and provides policy implications for designing effective disclosure regulations.
{"title":"From disclosure to distortion: How strategic ESG disclosure shapes green innovation bubbles","authors":"Meiyi Li , Yufei Gan","doi":"10.1016/j.bir.2025.10.019","DOIUrl":"10.1016/j.bir.2025.10.019","url":null,"abstract":"<div><div>Strategic environmental, social, and governance (ESG) disclosure practices that create favorable impressions while concealing unfavorable environmental performance have become increasingly common among corporations. This study investigates how such practices influence green technology innovation bubbles, where firms prioritize innovation quantity over quality. Drawing on institutional theory and impression management perspectives, we examine this relationship using Chinese A-share listed companies (2015–2024). Through propensity score matching, difference-in-differences, placebo tests, and IV approaches, we establish that strategic ESG disclosure positively influences green-innovation bubbles. CEO green experience weakens this relationship, whereas managerial myopia strengthens it. Information asymmetry and greenwashing mediate this relationship. The effects are stronger for non-SOEs, during periods of high economic uncertainty and under weaker environmental regulations. Our study contributes to the sustainability literature by documenting how strategic ESG behavior distorts innovation patterns and provides policy implications for designing effective disclosure regulations.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"26 1","pages":"Article 100746"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.bir.2025.10.018
Fatima Khaleel, Hajra Ihsan, Abdul Rashid
Diversification in asset management companies is the key feature delivered by mutual funds. Fund managers are responsible for allocating assets in the fund's portfolio to improve risk-adjusted performance and decrease risk. This study analyzes the diversification and governance mechanisms of mutual funds in Pakistan. Moreover, it examines the impact of corporate governance on the asset allocation of Islamic and conventional mutual funds. The main findings revealed that the diversification level of mutual funds is quite satisfactory, which means that funds in Pakistan are diversified on average. Surprisingly, Islamic mutual funds are more diversified than their conventional counterparts. The comparative analysis of Islamic and conventional mutual funds shows that Shariah governance supports the equity type, sukuks, and income funds investment, while it negatively affects the bonds, T-bills, and cash investments. It is also observed that conventional mutual funds prefer to invest in equity and cash-type investments. Similarly, domestic, managerial, and foreign ownership increases diversification in conventional mutual funds, while government, trustees, and institutional ownership escalate diversification in Islamic mutual funds. These findings have important implications for the governance set-up, ownership structure, and diversification of the mutual fund industry to improve the efficiency of asset allocation decisions. The findings also guide managers in a strategic direction to identify the fund's governance features and their impact on the fund's diversification.
{"title":"Do ownership structure and governance matter in asset allocation decisions of Islamic and conventional mutual funds? Empirical evidence from Pakistan","authors":"Fatima Khaleel, Hajra Ihsan, Abdul Rashid","doi":"10.1016/j.bir.2025.10.018","DOIUrl":"10.1016/j.bir.2025.10.018","url":null,"abstract":"<div><div>Diversification in asset management companies is the key feature delivered by mutual funds. Fund managers are responsible for allocating assets in the fund's portfolio to improve risk-adjusted performance and decrease risk. This study analyzes the diversification and governance mechanisms of mutual funds in Pakistan. Moreover, it examines the impact of corporate governance on the asset allocation of Islamic and conventional mutual funds. The main findings revealed that the diversification level of mutual funds is quite satisfactory, which means that funds in Pakistan are diversified on average. Surprisingly, Islamic mutual funds are more diversified than their conventional counterparts. The comparative analysis of Islamic and conventional mutual funds shows that <em>Shariah</em> governance supports the equity type, <em>sukuks,</em> and income funds investment, while it negatively affects the bonds, T-bills, and cash investments. It is also observed that conventional mutual funds prefer to invest in equity and cash-type investments. Similarly, domestic, managerial, and foreign ownership increases diversification in conventional mutual funds, while government, trustees, and institutional ownership escalate diversification in Islamic mutual funds. These findings have important implications for the governance set-up, ownership structure, and diversification of the mutual fund industry to improve the efficiency of asset allocation decisions. The findings also guide managers in a strategic direction to identify the fund's governance features and their impact on the fund's diversification.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"26 1","pages":"Article 100745"},"PeriodicalIF":7.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.bir.2025.10.011
Walaa J.K. Almoghayer , Haitham A. Mahmoud
This study analyzes cross-border payment systems in Belt and Road Initiative (BRI) countries, exploring how technological, regulatory, and socioeconomic factors shape their adoption. By combining quantitative data from 43 BRI countries (2018–2024) with insights from interviews with 127 stakeholders, we identify four distinct adoption archetypes: digital pioneers (high technological and cultural acceptance), regulatory harmonizers (policy driven), institutional trust builders (focused on governance), and hybrid adopters (selective integration). Our findings reveal that successful adoption hinges on the interplay of infrastructure, regulation, and cultural attitudes, not just technology. We introduce a Cross-Border Payment Adoption Index (CPAI) to measure payment system maturity across technological, regulatory, institutional, and cultural dimensions and predict paths for integration. Our research extends the technology acceptance model to multinational contexts and offers actionable insights for policy makers and financial institutions, particularly as digital currencies reshape the BRI payment environment.
{"title":"The adoption of cross-border payment: A comparative study of belt and road countries","authors":"Walaa J.K. Almoghayer , Haitham A. Mahmoud","doi":"10.1016/j.bir.2025.10.011","DOIUrl":"10.1016/j.bir.2025.10.011","url":null,"abstract":"<div><div>This study analyzes cross-border payment systems in Belt and Road Initiative (BRI) countries, exploring how technological, regulatory, and socioeconomic factors shape their adoption. By combining quantitative data from 43 BRI countries (2018–2024) with insights from interviews with 127 stakeholders, we identify four distinct adoption archetypes: digital pioneers (high technological and cultural acceptance), regulatory harmonizers (policy driven), institutional trust builders (focused on governance), and hybrid adopters (selective integration). Our findings reveal that successful adoption hinges on the interplay of infrastructure, regulation, and cultural attitudes, not just technology. We introduce a Cross-Border Payment Adoption Index (CPAI) to measure payment system maturity across technological, regulatory, institutional, and cultural dimensions and predict paths for integration. Our research extends the technology acceptance model to multinational contexts and offers actionable insights for policy makers and financial institutions, particularly as digital currencies reshape the BRI payment environment.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"25 6","pages":"Pages 1626-1644"},"PeriodicalIF":7.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.bir.2025.07.017
Yunus Emre Akdogan
This study employs machine learning and explainable artificial intelligence to examine the impact of working capital strategies—aggressive, moderate, and conservative—on Tobin's Q and EBITDA (earnings before interest, taxes, depreciation, and amortization), identifying key financial indicators for each approach. When the LightGBM algorithm is run, the R2 values for Tobin's Q are 57 percent (aggressive), 40 percent (moderate), and 55 percent (conservative) and, for EBITDA, the R2 values were 43 percent, 60 percent, and 60 percent, respectively. SHAP-based analyses reveal that Tobin's Q is predominantly affected by macroeconomic variables, especially in aggressive and moderate strategies, while EBITDA is mainly determined by operational efficiency and liquidity indicators across all strategies. The findings indicate that advanced algorithms—such as random forest, LightGBM, and XGBoost, when paired with SHAP explainability—capture the complex dynamics of working capital management more effectively than traditional approaches. Practically, these insights can help firms optimize liquidity, profitability, and debt policies to enhance sustainable competitive advantage.
{"title":"AI-driven insights into working capital strategies: An application on Borsa Istanbul","authors":"Yunus Emre Akdogan","doi":"10.1016/j.bir.2025.07.017","DOIUrl":"10.1016/j.bir.2025.07.017","url":null,"abstract":"<div><div>This study employs machine learning and explainable artificial intelligence to examine the impact of working capital strategies—aggressive, moderate, and conservative—on Tobin's Q and EBITDA (earnings before interest, taxes, depreciation, and amortization), identifying key financial indicators for each approach. When the LightGBM algorithm is run, the <em>R</em><sup>2</sup> values for Tobin's Q are 57 percent (aggressive), 40 percent (moderate), and 55 percent (conservative) and, for EBITDA, the <em>R</em><sup>2</sup> values were 43 percent, 60 percent, and 60 percent, respectively. SHAP-based analyses reveal that Tobin's Q is predominantly affected by macroeconomic variables, especially in aggressive and moderate strategies, while EBITDA is mainly determined by operational efficiency and liquidity indicators across all strategies. The findings indicate that advanced algorithms—such as random forest, LightGBM, and XGBoost, when paired with SHAP explainability—capture the complex dynamics of working capital management more effectively than traditional approaches. Practically, these insights can help firms optimize liquidity, profitability, and debt policies to enhance sustainable competitive advantage.</div></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":"25 6","pages":"Pages 1359-1377"},"PeriodicalIF":7.1,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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