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This study aims to examine the effect of the board of directors (BoD) structure on environmental, social and governance (ESG) performance in publicly traded non-financial firms from the perspective of agency theory, with investors as the principal, the management team as the agent, the BoD as an information system that reduces information asymmetries between them and ESG performance as a shareholder’s expectation.

Sample data is cross-sectional as of January 2023 and includes 1,695 non-financial firms listed in 59 stock markets across 54 countries. Data were sourced from the FactSet Research Systems database. The generalized least squares method was used to run quadratic and exponential models to assess the research hypotheses.

Results revealed that board size, independence, age, gender diversity and participation on other corporate boards have a nonlinear relationship with ESG performance. Board tenure is the only BoD attribute for which a nonlinear association is not found. This study found that firms with larger boards and more female board members tend to exhibit a stronger commitment to ESG performance. In contrast, companies with a board of directors consisting of independent members, advanced age, service on other corporate boards and CEO duality may struggle to prioritize positive ESG outcomes.

This study contributes to the academic discussion on BoD–ESG by examining nonlinear relationships among a large sample of publicly traded firms; providing results that could be applied internationally; using ESG data that is based on the Sustainability Accounting Standards Board's materiality framework, which identifies key ESG factors for investors; emphasizing the significance of diversity and inclusion within the decision-making bodies of public companies, thereby improving their ESG performance; and supporting the agency theory perspective and suggesting that the effect of board structure on ESG may reflect the board's focus on investors’ best interests.

This study aims to examine the trends and advancements in AI-supported language learning over the past decade. By analyzing 15 empirical research articles, the study seeks to fill the gap in understanding the effectiveness and challenges of AI-assisted language learning for both first- and second-language learners.

The research utilizes activity theory, which includes seven components: tool, subject, object, rules, community, division of labor and outcome. This theoretical framework helps to reveal the dynamic interactions and contradictions among these elements. The selection and screening process for relevant articles followed the PRISMA method, ensuring a systematic and comprehensive review.

The study found that AI-supported technology shows promise in enhancing language learning, particularly in areas such as writing quality, scoring accuracy and learner engagement. However, challenges remain in terms of dialogic competence and the necessity of teacher intervention in pedagogical design. While AI-supported systems can effectively aid in language acquisition, improvements are needed to foster language use for communication and collaborative design.

The review highlights the need for more empirical studies on the pedagogical impacts of AI-supported language learning and the engagement levels of both learners and teachers. It also underscores the importance of investigating the application of AI-assisted language learning in actual classroom environments.

The implications of this study offer significant insights for both educational practice and future research in AI-supported language learning. As AI technologies continue to evolve, their potential to enhance learning outcomes and support teachers’ efforts becomes increasingly apparent. However, effective implementation requires not only the availability of technological tools but also proper pedagogical integration and teacher intervention. Furthermore, AI presents unique opportunities to personalize learning and foster collaboration among learners, aligning with the growing trend of hybrid learning environments.

This paper addresses the need for a comprehensive review of AI’s role in language education, providing insights into emerging trends and identifying areas for future research. It emphasizes the importance of integrating AI tools with educational theories and the necessity of teacher configuration in enhancing AI-supported language learning.

The study examined the influence of internal marketing orientation on employees’ innovative behaviour through the mediating role of workforce agility and the moderating role of psychological empowerment.

We collected 731 valid responses from frontline employees in the hospitality industry in Ghana. The data were analysed using hierarchical regression analysis in SPSS.

The findings show that internal marketing orientation significantly influenced workforce agility and innovative behaviour. Also, workforce agility significantly influenced employee innovative behaviour. Again, the study found that workforce agility partially mediated the relationship between internal marketing orientation and employee innovative behaviour. Psychological empowerment significantly moderated the relationship between workforce agility and employees innovative behaviour.

In order to promote agile behaviour and enhance innovative thinking when assigning tasks for company products and services, organisations should develop and implement suitable internal marketing orientation programmes and policies regarding opportunities for career growth, promotion and advancement.

This study offers timely empirical insights into how organisations can promote employee innovation, particularly in the hospitality sector, where human capital is imperative for service excellence and competitiveness.