This study examines the impact of artificial intelligence (AI)-driven insights on sustainable Human Resource Management (HRM) performance in higher education institutions. It explores the mediating roles of HRM practices optimization and decision-making enhancement, as well as the moderating effects of organizational culture, AI adoption readiness, and ethical considerations. By incorporating innovative insights into artificial intelligence technologies, this research contributes to career and HRM literature by revealing how AI transforms workforce dynamics in academic institutions. Data was collected via a quantitative survey from 215 participants, including administrators, AI and data science experts, data analysts, human resource management professionals, institutional leaders, IT staff, and policymakers from higher education institutions in the UAE. Using non-probability quota sampling. Data analysis was conducted through descriptive statistics, t-tests, correlation analysis, and structural equation modeling (SEM) using Partial Least Squares SEM (PLS-SEM) in SmartPLS software. Findings confirm that AI-driven insights significantly enhance sustainable HRM performance. Both HRM practices optimization and decision-making enhancement mediate this relationship. While ethical considerations, organizational culture, and AI adoption readiness directly influence HRM sustainability, they do not significantly moderate AI’s impact, suggesting that individual engagement with AI technologies plays a more pivotal role than broader organizational factors. This research uniquely integrates the Resource-Based View (RBV) and Technology Acceptance Model (TAM) to examine AI adoption in HRM within higher education—an area previously underexplored. It underscores the importance of HRM optimization and decision-making in maximizing AI’s benefits. The findings offer strategic insights for higher education institutions seeking to enhance HRM sustainability through effective AI integration.

This study examines the impact of Environmental, Social, and Governance Performance (ESGP) on profitability and firm value, focusing on 75 listed companies on the Stock Exchange of Thailand (SET) over the period 2014 to 2023. ESGP has emerged as a critical measure of corporate sustainability, yet its financial implications in emerging markets like Thailand remain underexplored. Employing the Generalized Method of Moments (GMM) approach the findings reveal that ESGP positively impacts ROA, ROE, and TBQ, emphasizing its role in enhancing operational efficiency, stakeholder trust, and market confidence. However, short- and long-term debt and cash ratio exhibit a negative impact on all financial metrics, highlighting inefficiencies linked to excessive leverage and liquidity. Firm size positively influences ROA and ROE but negatively affects TBQ, indicating challenges in market perception of growth potential for larger firms. Conversely, firm age positively impacts ROA, reflecting stability and operational experience, but presents mixed effects on ROE and TBQ due to innovation inertia and equity inefficiencies. Robustness checks using Difference GMM validate these findings, confirming the relationships between ESGP, financial metrics, and control variables. This study offers insights for corporate managers and policymakers, advocating for sustainable financial practices, optimal capital structures, and innovation-driven strategies to maximize profitability and market valuation. It contributes to the literature on sustainable finance by providing empirical evidence from an emerging market perspective and aligns with Thailand’s national sustainability agenda. JEL Classification: G32, G34, Q56, M14, C33

This research delves into the interplay between Human Resource Management Practices (HRMPs) and job autonomy concerning faculty job performance within private universities in the United Arab Emirates (UAE) while considering the moderating role of faculty experience. The research explores how job autonomy and supportive HRMPs enhance job performance. The primary objective is to address the research gap concerning the functional independence of HRMPs and their impact on faculty job performance within higher education, specifically focusing on institutions in the (UAE). The significance of this research lies in the pivotal role of Human Resource Management (HRM) in higher education, as HRM has evolved from simply executing decisions to shaping strategic directions, making it a crucial factor in the success of universities through HRMPs related to finding and developing teaching staff to drive educational excellence. The HRMPs under scrutiny encompass recruitment, service ending, training, performance appraisal, promotion, and compensation as a cluster. A survey collected data from 225 faculty members, and statistical analysis was conducted using SPSS and SmartPLS software. The results reached through tests show a significant and positive impact of HRMPs and job independence on faculty performance. In addition, faculty members' experience affects the relationship between HRMPs, job independence, and faculty job performance as a moderating variable. This study has tremendous implications for tertiary institutions seeking to enhance the job performance of faculty members. It provides fresh insights into higher education and the specific context of the private tertiary sector in the UAE.

This study examines how leadership capacity drives digital transformation in higher education institutions in the United Arab Emirates (UAE), guided by the Advance HE (2025) framework for leading in higher education (HE). Using a quantitative, cross-sectional survey design supplemented by structured multiple-response items, the authors surveyed 283 academic staff and leaders and analyzed the data with partial least squares-structural equation modelling. Leadership knowledge and digital literacy, leadership values and mindsets, and institutional digital strategies and support significantly predicted faculty willingness to adopt technology. Faculty willingness mediated the association between leadership capacity and digital curriculum transformation, which in turn related to stronger student engagement and learning outcomes. Structured section 8 responses highlighted workload pressures, infrastructure constraints, and data-privacy concerns, as well as the importance of vision-led leadership and sustained institutional support. The findings suggest that sustainable digital transformation depends less on technology availability alone than on coherent leadership, faculty readiness, and curriculum-centered reform. The study offers practical implications for aligning governance, professional development, and policy in UAE HE.