The incorporation of artificial intelligence (AI) into education has heralded a transformative era in the way students learn and faculties teach. Among the burgeoning array of AI tools, ChatGPT stands out as a versatile and powerful resource. Developed by OpenAI, ChatGPT is an AI-driven conversational model that generates human-like responses. This research draws on the Constructivism Learning Theory to uncover the key drivers pushing higher education students to use ChatGPT for academic purposes, and the multifaceted consequences it brings to the academic environment, by integrating the perspectives of key stakeholders: students, faculty, and education experts/leaders. The key findings of in-depth, face-to-face, interviews with key stakeholders revealed 12 main drivers that motivate students and their faculty to use ChatGPT mainly for learning purposes. However, the findings identified the multifaceted (six positive and another six negative) consequences of using ChatGPT for academic purposes. Recommendations for mitigating the negative consequences of ChatGPT were discussed with key stakeholders, particularly education experts/leaders, who were more concerned about using ChatGPT for academic reasons. The research reveals that higher education institutions should establish clear guidelines as a part of higher education policy, supplemented with training sessions for students and their faculty, about the responsible use of ChatGPT for academic purposes to mitigate any ethical concerns.

The worldwide pandemic of COVID-19 has forced higher education institutions to shift from face-to-face to online education. However, many public institutions, especially in developing countries, often do not have access to formal online learning management systems (LMS) for facilitating communication with students and/or among faculty members. This research empirically examines the extent to which social media sites are adopted by faculty members and students for sustaining formal, i.e., sole and official tools, academic communication. For this purpose, online questionnaire surveys, supplemented with in-depth interviews, were undertaken with both faculty members and students. The results showed that students’ personal usage of social media has promoted its effective usage for sustaining formal teaching and learning. However, significant differences were found between faculty members and students regarding social media usage for student support and building an online community. Students used social media for building an online community and supporting each other, whereas faculty members were focused on teaching and learning exclusively. The results confirm that proper usage of social media could promote a new era of social learning, social presence and an alternative platform to foster online learning. Research implications for higher education policymakers, especially in developing countries, and scholars are discussed.

Small lodging enterprises encompass a major proportion of the lodging industry worldwide. Nonetheless, limited research has addressed the HRM-innovation-performance link on these enterprises. This research draws on ability, motivation, opportunity (AMO) theory and resource-based view (RBV) theory to examine the influences of green human resources management (GHRM) practices by owner-managers of small lodging enterprises on their enterprises’ green innovation and environmental performance. More specifically, the research examines the direct influence of GHRM on the environmental performance of small lodging enterprises and the indirect influence through green innovation. A self-administered questionnaire was given to owner-managers of small lodging enterprises in Greater Cairo, Egypt. The results of structural equation modeling (SEM) showed direct, positive and significant influences of owner-managers’ green ability, motivation and opportunity on both enterprise green innovation and environmental performance. The ability of owner-managers was the most influential GHRM practices on both green innovation and environmental performance. Moreover, the results showed that the influence of GHRM on environmental performance was doubled with green innovation, reflecting the value and vital role of green innovation in small lodging enterprises’ environmental performance. Several policy-level, theoretical and practical implications are identified and discussed.

This study examines students’ acceptance and use of ChatGPT in Saudi Arabian (SA) higher education, where there is growing interest in the use of this tool since its inauguration in 2022. Quantitative research data, through a self-reporting survey drawing on the “Unified Theory of Acceptance and Use of Technology” (UTAUT2), were collected from 520 students in one of the public universities in SA at the start of the first semester of the study year 2023–2024. The findings of structural equation modeling partially supported the UTAUT and previous research in relation to the significant direct effect of performance expectancy (PE), social influence (SI), and effort expectancy (EE) on behavioral intention (BI) on the use of ChatGPT and the significant direct effect of PE, SI, and BI on actual use of ChatGPT. Nonetheless, the results did not support earlier research in relation to the direct relationship between facilitating conditions (FCs) and both BI and actual use of ChatGPT, which was found to be negative in the first relationship and insignificant in the second one. These findings were because of the absence of resources, support, and aid from external sources in relation to the use of ChatGPT. The results showed partial mediation of BI in the link between PE, SI, and FC and actual use of ChatGPT in education and a full mediation in the link of BI between EE and actual use of ChatGPT in education. The findings provide numerous implications for scholars and higher education institutions in SA, which are also of interest to other institutions in similar contexts.

Over the last few decades, environmental impacts have been a major concern not only for policymakers but also for scholars and leaders of organisations. The leadership of organisations can drive the green behaviour of their employees, thus driving the overall green performance of enterprises. In this research, we examined the direct influence of green transformational leadership (GTFL) on the environmental performance of food organisations and the indirect influence via green behaviour of employees. More specifically, we have examined the mediating effect of employee green behaviour, whether task-related or pro-environmental behaviour, on the association between GTFL and environmental performance. For this purpose, we adopted a pre-tested research instrument for data collection from 1050 employees in different food enterprises across the Kingdom of Saudi Arabia (KSA). We have used Amos structural equation modeling (SEM) to examine the direct and indirect effects of GTFL. The results confirmed a positive significant influence of GTFL on both dimensions of green behaviour, i.e., task-related and pro-environmental behaviour, and on environmental performance. The results showed a partial mediating effect of task-related behaviour in the link between GTFL and environmental performance, whereas pro-environmental behaviour has a perfect mediation effect. The results highlight the dynamic role of pro-environmental behaviour in affecting the above link and send a crucial message to leaders in the food industry about prioritizing pro-environmental behaviour when selecting and recruiting new employees. Additionally, development programs should be conducted to enhance the pro-environmental behaviours among employees.

The intensive adoption of ChatGPT by university students for learning has encouraged many scholars to test the variables that impact on their use of such AI in their learning. This study adds to the growing body of studies, especially in relation to the moderating role of students’ gender and their study discipline in their acceptance and usage of ChatGPT in their learning process. This study expanded the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating gender as well as study disciplines as moderators. The study collected responses from students in Saudi universities with different study disciplines and of different genders. The results of a structural model using Smart PLS showed a significant moderating effect of gender on the relationship between performance expectancy and ChatGPT usage. The results confirmed that the impact of performance expectancy in fostering ChatGPT usage was stronger in male than in female students. Moreover, social influence was shown to significantly affect males more than females in relation to ChatGPT usage. In addition, the findings showed that study discipline significantly moderates the link between social influence and ChatGPT usage. In the same vein, social influence significantly influences ChatGPT use in social sciences more than in applied sciences. Hence, the various implications of the study were discussed.