Cloud computing has been adopted by many healthcare firms throughout the world especially in developed countries to enhance their service levels. The main objective of this study was to find the constructs from the prior literature review which influence the adoption of cloud computing from the prospering nation’s perspective. The main pillars of the theoretical framework are technology, organizational, environmental and ethical factors. The responses were collected from the employees or staff who were working in this sector with the help of a structured questionnaire. The analysis was performed utilizing SPSS 20.0 and AMOS 22.0. The hypothesis developed was tested utilizing a structural equation modelling approach. The findings indicated that the assumed variables each under technology, organization, environment and ethics have an impact on the dependent variable that is cloud computing adoption in the healthcare segment, thereby increasing the efficiency. The study is unique when compared to past studies as it considered ethical factors, thereby extending the cloud computing literature. It also provides a base for future studies and cloud technology development for a prospering nation perspective.

Lately, organizations are giving attention to enhancing employee resilience due to turbulent economic times caused by lockdowns in the last couple of years. This explanatory research proposes and tests the mediating role of employee resilience to link task challenge and employee performance during the COVID-19 pandemic in government schools of Oman using the broaden-and-build theory. An explanatory research design was used for this empirical study. An Arabic-translated questionnaire version was designed to collect primary data online during the lockdown using simple random sampling. We used the Preacher and Hayes macro to analyze moderated mediation using cross-sectional data and analyzed 441 responses. The findings confirm the mediation roles of employee resilience and moderating roles of digitalization during unusual circumstances. The study has implications for the school administrators, Omani policymakers and schooling staff of the Middle Eastern educational industry.

This research investigates the effects of green logistics practices on the sustainability performance of manufacturing enterprises in Oman, with a particular focus on the mediating role of circular economy practices. Analyzing data from 220 manufacturing companies through the PLS-SEM method, the findings reveal that green logistics management significantly enhances an organization’s sustainability and adherence to circular economy principles. Notably, while supply chain trackability greatly impacts circular economy practices, it does not moderate the relationship between sustainable performance and green logistics. This study enhances the understanding of how green logistics can support sustainable development and the implementation of circular economy practices in the manufacturing sector

Purpose: This study aims to examine how environmental strategy typologies (reactive, preventive and proactive) are associated with the depth of green human resource development (GHRD) practices and the internal bundle consistency across green training, appraisal and rewards/career pathways and how these GHRD configurations relate to environmental performance in an Indian manufacturing firm. The analysis is anchored in strategic human resource management, the ability–motivation–opportunity (AMO) framework and the natural resource-based view (NRBV) of the firm. Design/methodology/approach: Using a structured survey administered via computer-assisted telephone interview methodology, data were collected from 489 Indian manufacturing firms. The study classified firms by self-identified environmental strategies and measured GHRD using nine indicators. Statistical methods, including one-way ANOVA, Kruskal–Wallis test and Spearman's correlation analysis, were employed to analyze the relationship between strategy types and human resource development (HRD) practices. Internal consistency was assessed using standard deviation as a proxy for horizontal fit. Findings: The results reveal that firms adopting proactive environmental strategies demonstrate significantly higher adoption of GHRD practices than preventive or reactive firms. Among GHRD components, green training and appraisal were more consistently implemented than green career development pathways. However, inconsistencies in horizontal alignment were observed across firms, with only a minority demonstrating strong internal coherence in GHRD practices. Practical implications: The findings underscore the need for Indian manufacturers to develop integrated human resource (HR) strategies that support long-term sustainability goals. Structured green training programs, sustainability-linked performance appraisals, and internal green career pathways can enhance organizational readiness for environmental transformation. This study examines the linkage between environmental strategy typologies and both the depth and internal consistency of GHRD practices. The consistency index is calculated for the GHRD practice bundle to capture the degree of internal alignment among green training, appraisal, and rewards/career pathways. Originality/value: This study contributes to the literature by empirically examining the underexplored relationship between environmental strategy typologies and GHRD in a major emerging economy. It introduces a structured framework for evaluating vertical and horizontal consistency in HR practices, offering theoretical and practical insights into how human resource management can support environmental sustainability in the manufacturing sector.

The rapid rise of generative artificial intelligence (AI) tools such as ChatGPT and Gemini has introduced new complexities to academic assessment, particularly in technical education where skill-based evaluations are central. This study investigates how generative AI is impacting assessment practices in technical education institutions across the Gulf Cooperation Council (GCC) region. Employing a convergent mixed-methods approach, the research draws on survey responses from 120 students and faculty members, as well as in-depth interviews with academic staff from three GCC countries. Quantitative findings reveal a significant disparity in AI tool usage between students and faculty, with students more frequently relying on AI for academic tasks. A chi-square test confirmed that this difference is statistically significant (χ² (3, N = 120) = 11.73, p = .008). Qualitative analysis identified four key themes: rising concerns over AI-enabled academic dishonesty, perceived threats to fairness and learning outcomes, institutional policy gaps, and emerging assessment adaptations such as oral exams and reflective evaluations. This study underscores an urgent need for institutional reforms, including AI-specific academic integrity policies, faculty training, and assessment redesign. By aligning pedagogy and policy with the realities of AI-integrated learning environments, technical education institutions in the GCC can uphold academic standards while fostering ethical, future-ready learning ecosystems.