Search results

Despite the extensive body of research on absolute corporate social responsibility (CSR) performance, limited attention has been given to the distinct concepts of optimal and aggressive CSR engagement, as well as their associations with CSR awarding. This study aims to differentiate between optimal and aggressive CSR engagement and examine their relationship with CSR awarding while considering the moderating influence of board characteristics from the perspectives of stakeholder and agency theories.

This empirical analysis draws on an international dataset comprising 43,803 observations from nine sectors across 41 countries. We employ a least squares dummy variable regression approach that accounts for country, industry and year effects to conduct the analysis.

The results reveal that engagement in aggressive CSR activities beyond the optimal level leads to the generation of a social reputation through CSR awarding. However, the influence of board characteristics on this relationship is significant. Specifically, the presence of a dedicated CSR committee encourages CSR awarding in the context of aggressive CSR engagement. Conversely, board independence constrains the relationship between aggressive CSR engagement and CSR awarding. Notably, board gender diversity does not have a discernible impact on this connection.

Our evidence provides valuable insights to help firms seeking to enhance their social reputation through CSR activities better allocate their resources and avoid unnecessary financial commitments.

This study advances the current understanding by exploring the relationship between aggressive CSR engagement and the recognition of CSR awards. Furthermore, it scrutinises the factors that dictate when such aggressive CSR engagement translates into enhanced social reputation, as evidenced by the attainment of CSR awards.

This study aims to examine the joint effect of accounting background and cross-membership of Islamic Supervisory Board (ISB) members on bank investment efficiency.

This study uses data collected from 36 Islamic banks across 15 countries globally, spanning the period from 2012 to 2021. This research uses an ordinary least squares regression and a comprehensive set of endogeneity and robustness tests.

The findings show a negative relationship between the accounting background of ISB members and investment efficiency. However, when ISB members with accounting backgrounds also have ISB cross-memberships, the banks exhibit high investment efficiency. These results suggest that ISB cross-membership plays a crucial role in facilitating Islamic banks’ access to timely information on investment opportunities. This enables ISB members with accounting expertise to thoroughly assess the benefits and risks associated with their investment prospects. These findings imply that ISB members with accounting backgrounds and cross-memberships have greater motivation and thoughtful considerations for making better investment decisions. Consequently, Islamic banks are better positioned to undertake high profitable investment projects, which enhance their investment efficiency.

The current study holds immense value for Islamic bank management in their selection of ISB members who possess an accounting background and cross-membership.

This study delves into a comprehensive investigation of the proficiency, underlying principles and unique characteristics exhibited by ISB members with an accounting background. Moreover, this study acknowledges the burgeoning global prominence of Islamic banks.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

Green technology innovation is the organic combination of green development and innovation driven. It is also a powerful guarantee for shaping sustainable competitive advantages of manufacturing enterprises. To explore what kind of executive incentive contracts can truly stimulate green technology innovation, this study aims to distinguish the equity incentive and reputation incentive, upon their contractual elements characteristics and green governance effects, and then put forward suggestions for green technology innovation accordingly.

This study establishes an evaluation model and uses empirical methods to test. Concretely, using data from A-share listed manufacturing companies for the period from 2007 to 2020, this study compares and analyzes the impact of equity and reputation incentive on green technology innovation and explores the relationship between internal green business behavior and external green in depth.

This study finds that reputation incentives focus on long-term and non-utilitarian orientation, which can promote green technology innovation in enterprises. While equity incentives, linked to performance indicators, have a inhibitory effect on green technology innovation. Internal and external institutional factors such as energy conservation measures, the “three wastes” management system, and environmental recognition play the regulatory role in the relationship between incentive contracts and green technology innovation.

Those findings validate and expand the efficient contracting hypothesis and the rent extraction hypothesis from the perspective of green technology innovation and provide useful implications for the design of green governance systems in manufacturing enterprises.