We examine how shareholder dissent both affects and is affected by agency cost of debt, using credit ratings as a proxy. Specifically, we explore (1) whether agency costs of debt trigger dissent differently across corporate governance regimes characterized by greater stakeholder collaboration versus those with stronger shareholder dominance, and (2) whether credit rating agencies' subsequent responses to dissent vary across these regimes. We find evidence that dissent is lower when ratings are higher, but there is limited evidence that shareholders in more collaborative regimes dissent more. Dissent tends to improve subsequent credit ratings when shareholders are highly dominant, but this effect diminishes in more coordinated governance systems. This evidence suggests that dissent shifts power toward shareholders, which is more costly to debtholders in governance systems that are based on collaboration among stakeholders.
{"title":"Corporate governance characteristics, shareholder dissent and agency cost of debt","authors":"Wenjie Ding , Danial Hemmings , Lynn Hodgkinson , Patrycja Klusak , Gilad Livne","doi":"10.1016/j.irfa.2025.104850","DOIUrl":"10.1016/j.irfa.2025.104850","url":null,"abstract":"<div><div>We examine how shareholder dissent both affects and is affected by agency cost of debt, using credit ratings as a proxy. Specifically, we explore (1) whether agency costs of debt trigger dissent differently across corporate governance regimes characterized by greater stakeholder collaboration versus those with stronger shareholder dominance, and (2) whether credit rating agencies' subsequent responses to dissent vary across these regimes. We find evidence that dissent is lower when ratings are higher, but there is limited evidence that shareholders in more collaborative regimes dissent more. Dissent tends to improve subsequent credit ratings when shareholders are highly dominant, but this effect diminishes in more coordinated governance systems. This evidence suggests that dissent shifts power toward shareholders, which is more costly to debtholders in governance systems that are based on collaboration among stakeholders.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"111 ","pages":"Article 104850"},"PeriodicalIF":9.8,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-12DOI: 10.1016/j.irfa.2025.104988
He Ni , Jiahao He , Weijia Wang
This study examines how network centrality influences mutual fund performance among Chinese equity funds from 2007–2024. We construct networks using quarterly top-ten holdings where edges represent shared significant positions, and employ five complementary centrality measures: degree, closeness, betweenness, eigenvector, and structural holes to capture different dimensions of information access. Our findings reveal that funds occupying central network positions generate significantly higher risk-adjusted returns. We identify two key channels through which network effects operate. First, network advantages require active human management processes to transform soft information into returns, including dynamic portfolio rebalancing, discretionary strategy positioning, and strategic risk adjustment. Second, technological adoption disrupts this transformation pathway for funds with higher FinTech adoption and quantitative investment strategies, as automated systems substitute for the human judgment capabilities necessary to capitalize on network-derived information. Our results highlight the evolving trade-offs in modern asset management, where optimal investment strategies require balancing technological capabilities with the preservation of human management processes necessary to capitalize on discretionary information advantages.
{"title":"Can network centrality explain mutual fund alpha: Evidence from China","authors":"He Ni , Jiahao He , Weijia Wang","doi":"10.1016/j.irfa.2025.104988","DOIUrl":"10.1016/j.irfa.2025.104988","url":null,"abstract":"<div><div>This study examines how network centrality influences mutual fund performance among Chinese equity funds from 2007–2024. We construct networks using quarterly top-ten holdings where edges represent shared significant positions, and employ five complementary centrality measures: degree, closeness, betweenness, eigenvector, and structural holes to capture different dimensions of information access. Our findings reveal that funds occupying central network positions generate significantly higher risk-adjusted returns. We identify two key channels through which network effects operate. First, network advantages require active human management processes to transform soft information into returns, including dynamic portfolio rebalancing, discretionary strategy positioning, and strategic risk adjustment. Second, technological adoption disrupts this transformation pathway for funds with higher FinTech adoption and quantitative investment strategies, as automated systems substitute for the human judgment capabilities necessary to capitalize on network-derived information. Our results highlight the evolving trade-offs in modern asset management, where optimal investment strategies require balancing technological capabilities with the preservation of human management processes necessary to capitalize on discretionary information advantages.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"110 ","pages":"Article 104988"},"PeriodicalIF":9.8,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-11DOI: 10.1016/j.irfa.2025.105005
Pengcheng Song, Pang Paul Wang, Jinyu Xie, Qin Zhao
{"title":"Optimal pairs trading in theory and practice: A continuous-time approach with evidence from cross-market equities","authors":"Pengcheng Song, Pang Paul Wang, Jinyu Xie, Qin Zhao","doi":"10.1016/j.irfa.2025.105005","DOIUrl":"https://doi.org/10.1016/j.irfa.2025.105005","url":null,"abstract":"","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"52 1","pages":"105005"},"PeriodicalIF":8.2,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145732655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-10DOI: 10.1016/j.irfa.2025.104987
Haonan Wen , Yingjie Tian , Kun Guo
Corporate greenhouse gas (GHG) emissions disclosure remains incomplete, particularly in markets with weak regulatory enforcement. Given the strong correlation between energy consumption and GHG emissions, energy consumption data can serve as a crucial predictor for estimating corporate GHG emissions. However, similar to GHG emissions, corporate disclosure on energy consumption is often unavailable on a scale, limiting their utility in existing estimation methods. To address this challenge, we introduce frameworks of Learning Using Privileged Information (LUPI) and Generalized Distillation (GD) into the problem of corporate GHG emissions estimation, treating energy consumption data as privileged information, which is available during model training but not available during inference. We propose a teacher–student framework that incorporates a reliability-weighted distillation loss, enabling the student model to selectively learn from more reliable teacher outputs. Empirical results based on Chinese A-share and Hong Kong-listed companies demonstrate that our method improves the accuracy of the estimation while preserving the universality of the model across companies with varying disclosure levels, offering a scalable solution to address corporate GHG emissions disclosure gaps.
{"title":"Estimating undisclosed corporate greenhouse gas emissions using energy consumption data as privileged information","authors":"Haonan Wen , Yingjie Tian , Kun Guo","doi":"10.1016/j.irfa.2025.104987","DOIUrl":"10.1016/j.irfa.2025.104987","url":null,"abstract":"<div><div>Corporate greenhouse gas (GHG) emissions disclosure remains incomplete, particularly in markets with weak regulatory enforcement. Given the strong correlation between energy consumption and GHG emissions, energy consumption data can serve as a crucial predictor for estimating corporate GHG emissions. However, similar to GHG emissions, corporate disclosure on energy consumption is often unavailable on a scale, limiting their utility in existing estimation methods. To address this challenge, we introduce frameworks of Learning Using Privileged Information (LUPI) and Generalized Distillation (GD) into the problem of corporate GHG emissions estimation, treating energy consumption data as privileged information, which is available during model training but not available during inference. We propose a teacher–student framework that incorporates a reliability-weighted distillation loss, enabling the student model to selectively learn from more reliable teacher outputs. Empirical results based on Chinese A-share and Hong Kong-listed companies demonstrate that our method improves the accuracy of the estimation while preserving the universality of the model across companies with varying disclosure levels, offering a scalable solution to address corporate GHG emissions disclosure gaps.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"110 ","pages":"Article 104987"},"PeriodicalIF":9.8,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-07DOI: 10.1016/j.irfa.2025.104948
Mengmeng Zheng , Lu Zhang , David Tripe , Yuming Zhang
Green credit is intended to support firms with truly environmental potential, but the widespread greenwashing by firms undermines its effectiveness and hinders progress toward sustainable development goals. This study investigates whether the adoption of artificial intelligence (AI) by banks can address this issue. Using a dataset of 1209 loan contracts issued in China between 2019 and 2023, which is one of the largest polluters and green finance implementors, we find that banks adopting AI impose significantly higher interest spreads on firms exhibiting signs of greenwashing. The effect is more prominent for loan contracts granted by green-experienced banks and those to non-polluting firms. Our analysis identifies two underlying mechanisms: AI enhances banks' capabilities for both risk identification and legitimacy. These findings offer novel insights into the role of technological advancement in green credit practices and contribute to the growing literature at the intersection of finance, sustainability, and digital transformation.
{"title":"Can artificial intelligence mitigate greenwashed green credit? Evidence from loan contracts of Chinese listed firms","authors":"Mengmeng Zheng , Lu Zhang , David Tripe , Yuming Zhang","doi":"10.1016/j.irfa.2025.104948","DOIUrl":"10.1016/j.irfa.2025.104948","url":null,"abstract":"<div><div>Green credit is intended to support firms with truly environmental potential, but the widespread greenwashing by firms undermines its effectiveness and hinders progress toward sustainable development goals. This study investigates whether the adoption of artificial intelligence (AI) by banks can address this issue. Using a dataset of 1209 loan contracts issued in China between 2019 and 2023, which is one of the largest polluters and green finance implementors, we find that banks adopting AI impose significantly higher interest spreads on firms exhibiting signs of greenwashing. The effect is more prominent for loan contracts granted by green-experienced banks and those to non-polluting firms. Our analysis identifies two underlying mechanisms: AI enhances banks' capabilities for both risk identification and legitimacy. These findings offer novel insights into the role of technological advancement in green credit practices and contribute to the growing literature at the intersection of finance, sustainability, and digital transformation.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"110 ","pages":"Article 104948"},"PeriodicalIF":9.8,"publicationDate":"2025-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1016/j.irfa.2025.104873
Shuiqing Lan , Lufei Yang
Utilizing panel data of Chinese listed companies from 2009 to 2023, this paper systematically examines the relationships among directors and officers (D&O) liability insurance placement, financial innovation, and the dynamic capabilities of listed companies. The empirical results indicate that the purchase of D&O liability insurance placement can significantly enhance the dynamic capabilities of listed firms, and financial innovation likewise exerts a significant positive effect on these capabilities. Further analysis reveals a synergistic effect between D&O liability insurance placement and financial innovation, jointly promoting the enhancement of dynamic capabilities in listed companies. Mechanism testing shows that financial innovation plays a partial mediating role in the impact of D&O liability insurance placement on dynamic capabilities, and this mediating effect demonstrates pronounced heterogeneity between firms with high and low information transparency.
{"title":"Directors and officers liability insurance placement, financial innovation, and the dynamic capabilities of listed companies","authors":"Shuiqing Lan , Lufei Yang","doi":"10.1016/j.irfa.2025.104873","DOIUrl":"10.1016/j.irfa.2025.104873","url":null,"abstract":"<div><div>Utilizing panel data of Chinese listed companies from 2009 to 2023, this paper systematically examines the relationships among directors and officers (D&O) liability insurance placement, financial innovation, and the dynamic capabilities of listed companies. The empirical results indicate that the purchase of D&O liability insurance placement can significantly enhance the dynamic capabilities of listed firms, and financial innovation likewise exerts a significant positive effect on these capabilities. Further analysis reveals a synergistic effect between D&O liability insurance placement and financial innovation, jointly promoting the enhancement of dynamic capabilities in listed companies. Mechanism testing shows that financial innovation plays a partial mediating role in the impact of D&O liability insurance placement on dynamic capabilities, and this mediating effect demonstrates pronounced heterogeneity between firms with high and low information transparency.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"110 ","pages":"Article 104873"},"PeriodicalIF":9.8,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1016/j.irfa.2025.104894
Kelin Li, Wanshan Guo, Qingquan Yang
Using panel data of Chinese A-share listed firms from 2013 to 2023, this paper examines the impacts of data elements and market competition on corporate radical innovation (CRI). The findings are as follows: data elements significantly promote CRI; market competition effectively promotes CRI; market competition moderates the relationship between data elements and CRI; the impact of data elements on CRI exhibits heterogeneity between high-tech and non-high-tech firms; and the impact of market competition on CRI exhibits heterogeneity between firms with a higher average managerial age and those with a lower average managerial age.
{"title":"Data elements, market competition, and corporate radical innovation","authors":"Kelin Li, Wanshan Guo, Qingquan Yang","doi":"10.1016/j.irfa.2025.104894","DOIUrl":"10.1016/j.irfa.2025.104894","url":null,"abstract":"<div><div>Using panel data of Chinese A-share listed firms from 2013 to 2023, this paper examines the impacts of data elements and market competition on corporate radical innovation (CRI). The findings are as follows: data elements significantly promote CRI; market competition effectively promotes CRI; market competition moderates the relationship between data elements and CRI; the impact of data elements on CRI exhibits heterogeneity between high-tech and non-high-tech firms; and the impact of market competition on CRI exhibits heterogeneity between firms with a higher average managerial age and those with a lower average managerial age.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"110 ","pages":"Article 104894"},"PeriodicalIF":9.8,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1016/j.irfa.2025.104867
Peigen Wang , Yingying Hu , Na Wei , Xiaoxu Wu
This study conducts an empirical investigation using data from Chinese publicly listed tourism enterprises between 2009 and 2023. It focuses on analyzing the two key pathways of cultural tourism integration and digital-intelligent transformation, examining their specific roles in promoting high-quality development among Chinese tourism enterprises. The research findings indicate that both cultural tourism integration and digital-intelligent transformation display robust driving forces that can significantly facilitate the achievement of high-quality development in tourism enterprises. The moderation mechanism analysis reveals that cultural tourism integration plays a positive moderating role in the process of digital-intelligent transformation aiding the high-quality development of tourism enterprises. Additionally, heterogeneity tests reveal distinct characteristics in the impact of cultural tourism integration and digital-intelligent transformation on the high-quality development of tourism enterprises, demonstrating notable differences across samples with varying levels of managerial compensation and different proportions of female managers.
{"title":"Dual pathways for high-quality development: The role of cultural tourism integration and digital-intelligent transformation in Chinese tourism enterprises","authors":"Peigen Wang , Yingying Hu , Na Wei , Xiaoxu Wu","doi":"10.1016/j.irfa.2025.104867","DOIUrl":"10.1016/j.irfa.2025.104867","url":null,"abstract":"<div><div>This study conducts an empirical investigation using data from Chinese publicly listed tourism enterprises between 2009 and 2023. It focuses on analyzing the two key pathways of cultural tourism integration and digital-intelligent transformation, examining their specific roles in promoting high-quality development among Chinese tourism enterprises. The research findings indicate that both cultural tourism integration and digital-intelligent transformation display robust driving forces that can significantly facilitate the achievement of high-quality development in tourism enterprises. The moderation mechanism analysis reveals that cultural tourism integration plays a positive moderating role in the process of digital-intelligent transformation aiding the high-quality development of tourism enterprises. Additionally, heterogeneity tests reveal distinct characteristics in the impact of cultural tourism integration and digital-intelligent transformation on the high-quality development of tourism enterprises, demonstrating notable differences across samples with varying levels of managerial compensation and different proportions of female managers.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"110 ","pages":"Article 104867"},"PeriodicalIF":9.8,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1016/j.irfa.2025.104859
Rui Zhao , Dandan Wang , Ping Cao , Hui Cui , Na Wang , Ming Zhao , Yingjie Zhang
Using Chinese A-share listed firms from 2012 to 2023 as the sample, this paper systematically examines the relationships among internal control quality, supply chain risk perception, and corporate risk-taking (RiskTaking). The findings are as follows: First, internal control quality significantly reduces RiskTaking, while there exists a significant positive association between supply chain risk perception and RiskTaking. Second, the impacts of supply chain risk perception and internal control quality on RiskTaking differ significantly between firms with high versus low managerial ownership. Finally, supply chain risk perception plays a mediating role in the effect of internal control quality on RiskTaking, and this mediating effect exhibits heterogeneity between regions with high and low levels of digital economy development. This study not only deepens the understanding of how internal control influences firms' risk decisions, but also provides empirical evidence and theoretical insights for firms to optimize internal governance, manage risk expectations, and make prudent decisions in complex environments.
{"title":"Internal control quality, supply chain risk perception, and corporate risk-taking","authors":"Rui Zhao , Dandan Wang , Ping Cao , Hui Cui , Na Wang , Ming Zhao , Yingjie Zhang","doi":"10.1016/j.irfa.2025.104859","DOIUrl":"10.1016/j.irfa.2025.104859","url":null,"abstract":"<div><div>Using Chinese A-share listed firms from 2012 to 2023 as the sample, this paper systematically examines the relationships among internal control quality, supply chain risk perception, and corporate risk-taking (RiskTaking). The findings are as follows: First, internal control quality significantly reduces RiskTaking, while there exists a significant positive association between supply chain risk perception and RiskTaking. Second, the impacts of supply chain risk perception and internal control quality on RiskTaking differ significantly between firms with high versus low managerial ownership. Finally, supply chain risk perception plays a mediating role in the effect of internal control quality on RiskTaking, and this mediating effect exhibits heterogeneity between regions with high and low levels of digital economy development. This study not only deepens the understanding of how internal control influences firms' risk decisions, but also provides empirical evidence and theoretical insights for firms to optimize internal governance, manage risk expectations, and make prudent decisions in complex environments.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"110 ","pages":"Article 104859"},"PeriodicalIF":9.8,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145689483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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