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The purpose of this paper is to examine whether corporate governance has an impact on portfolio selection within the usual mean‐variance framework, the idea being that by reducing agency conflicts, corporate governance increases the value of the firm.

Using a sample of 460 American firms between 1995 and 2004, the authors first determine the optimal mean‐variance portfolio. The authors then test whether governance characteristics explain the optimal portfolio weights.

The results show that the optimal portfolio weights are sensitive to internal control mechanisms, ownership concentration, managerial entrenchment and incentive compensation.

The results are relevant to academicians and investors concerned with portfolio selection. In fact, they underline the importance of including governance characteristics in their portfolio selection.

This study aims to highlight the current trends in the literature on corporate governance by applying a bibliometric review of papers on corporate governance topics published in the journal of Corporate Governance: The International Journal of Business Society (Bingley).

Bibliometric analysis is a quantitative and qualitative approach applied to bibliographic materials that highlights the core theoretical and empirical contributions to a specific research field. This analysis was based on keyword cartography, bibliometric authors’ citation analysis, bibliometric papers’ co-citation analysis, bibliometric references’ co-citation analysis, journals’ co-citation cartography and qualitative content analysis. It reviews 353 articles on corporate governance published in the journal of Corporate Governance (Bingley). Bibliometric analysis was performed using VOSviewer, and content analysis was performed using WordStat.

The results identify three major clusters: corporate governance; board of directors; and firm performance. In addition, the results reveal that the journal Corporate Governance (Bingley) has experienced increasingly important growth in research papers on corporate governance topics and citations, reflecting its significant contribution to the corporate governance research field. This study also presents recommendations for future research in this field.

The findings of this study have implications for corporate governance research, such as the impact of ownership structure and the board of directors on environmental, social and governance disclosure. To the best of the authors’ knowledge, this study is the only one to review the key corporate governance research topics on which papers published in the journal of Corporate Governance (Bingley) are focused and can be largely used for corporate governance practices.

This study provides an overview of how the literature on corporate governance research has developed, as well as a summary of the most influential authors, along with countries, organizations and journal sources. This offers an opportunity for future research to focus on this topic.

This study examines the effects of corporate governance on market returns during the first four waves of the COVID-19 crisis.

Event study and linear regression methods were applied on a sample of 293 US firms.

The results show that differences in abnormal returns are more significant during the second wave of COVID-19 and the two following waves. Moreover, estimations show that good corporate governance alleviated the effect of COVID-19 during the second wave and the two following waves. However, corporate governance did not affect abnormal returns during the first wave. Furthermore, evidence highlights that the effect of corporate governance is more observed in the industries most affected by COVID-19 than in the least affected industries.

Many studies have attempted to investigate the effect of corporate governance on stock returns during the first wave of the pandemic. However, to the authors' knowledge, this is the first study that focuses on different waves that occurred during 2020 and 2021.

Gender-based discrimination (GBD) in the workplace is a worldwide phenomenon. Both developed and developing states face this issue at different levels and magnitudes, though in the latter, it is more prevalent. We explore the overlooked possible root causes of workplace GBD.

Employing qualitative methods, data were collected via semi-structured interviews from 40 women employed in the service sector in Pakistan and the UK. Data underwent thematic analysis by applying the Gioia method.

Using ambivalent sexism theory to underpin our approach, we conclude that educational institutes, especially single-gender ones, could be among the primary reasons for GBD in Pakistani workplaces, but not those in the UK, where it is less prominent. We identify common factors that challenge this theory and point out current social, industrial and economic situations that link with such single-gender education.

This study can help “institutionalize” (establish policy and practice as organizational culture) a discrimination-free workplace and assist relevant stakeholders by facilitating policymakers and government agencies to more deeply understand causality and take corrective and preventative action against GBD.

The findings contribute to the studies of gender discrimination and educational provision by elucidating previously overlooked possible roots of persistent GBD.

This paper aims to contribute to the discussion on integrating humans and technology in customer service within the framework of Society 5.0, which emphasizes the growing role of artificial intelligence (AI). It examines how effectively new generative AI-based chatbots can handle customer emotions and explores their impact on determining the point at which a customer–machine interaction should be transferred to a human agent to prevent customer disengagement, referred to as the Switch Point (SP).

To evaluate the capabilities of new generative AI-based chatbots in managing emotions, ChatGPT-3.5, Gemini and Copilot are tested using the Trait Emotional Intelligence Questionnaire Short-Form (TEIQue-SF). A reference framework is developed to illustrate the shift in the Switch Point (SP).

Using the four-intelligence framework (mechanical, analytical, intuitive and empathetic), this study demonstrates that, despite advancements in AI’s ability to address emotions in customer service, even the most advanced chatbots—such as ChatGPT, Gemini and Copilot—still fall short of replicating the empathetic capabilities of human intelligence (HI). The concept of artificial emotional awareness (AEA) is introduced to characterize the intuitive intelligence of new generative AI chatbots in understanding customer emotions and triggering the SP. A complementary rather than replacement perspective of HI and AI is proposed, highlighting the impact of generative AI on the SP.

This study is exploratory in nature and requires further theoretical development and empirical validation.

The study has only an exploratory character with respect to the possible real impact of the introduction of the new generative AI-based chatbots on collaborative approaches to the integration of humans and technology in Society 5.0.

Customer Relationship Management managers can use the proposed framework as a guide to adopt a dynamic approach to HI–AI collaboration in AI-driven customer service.