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Artificial Intelligence-Based Human Resource Performance Assessment for Good University Governance: Meta-Analysis and Systematic Literature Review Shinta Ratnawati; Miftachul Mujib; Ikhwan Alfath Nurul Fathony; Khairul Ikhwan; Dewi Anggraeni; Bagus Fauzan Azhari
Annals of Human Resource Management Research Vol. 6 No. 1 (2026): March
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/ahrmr.v6i1.3640

Abstract

Purpose: This study examines the role of Artificial Intelligence (AI)-based Human Resource (HR) performance evaluation in enhancing Good University Governance (GUG), particularly in improving accountability, transparency, efficiency, and responsiveness in higher education institutions. Research Methodology: A Systematic Literature Review (SLR) and meta-analysis were conducted on 65 peer-reviewed articles published between 2015 and 2025, sourced from Scopus, Web of Science, and ScienceDirect. The effect sizes were calculated, and heterogeneity tests were performed to ensure the robustness of the findings. Results: The results reveal that AI-based HR performance evaluation has a moderate to strong positive relationship with governance effectiveness (r = 0.45) and a moderate positive relationship with governance transparency (r = 0.33). These findings indicate that AI enhances data accuracy, reduces subjective bias, and supports more efficient and consistent decision-making in higher education governance. Conclusions: This study concludes that AI integration in HR performance evaluation significantly contributes to the implementation of GUG principles. It offers both theoretical contributions to digital governance literature and practical implications for university leaders and policymakers. Limitations: This study is limited by the scope of the 65 selected articles, which may not fully represent all existing research on AI-based HR evaluation in higher education contexts.
Analysis of Entrepreneurship-Based Human Resource Management Integration to Improve Business Ecosystem Sustainability in a Dynamic Market Era: A Study in Magelang Regency Hanung Eka Atmaja; Ipuk Widayanti; Khairul Ikhwan; Raina Dewi Aldianti
Amkop Management Accounting Review Vol. 5 No. 2 (2025): July - December
Publisher : Yayasan Vifada Cendikia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/amar.v5i2.3205

Abstract

The increasingly dynamic business environment requires business actors, especially MSMEs, to adapt quickly and strategically to remain sustainable. Human resource management that is not only administrative but also oriented towards entrepreneurial values is believed to be the key to strengthening competitiveness in an era of rapidly changing markets. This study aims to analyse the effect of entrepreneurial human resource management integration on business ecosystem sustainability, with the dynamic market era as a mediating variable. This study employs an explanatory quantitative approach to examine MSMEs in Magelang Regency, Central Java. The study population consists of all active MSME actors, and through the proportionate stratified random sampling method, 71 respondents were obtained as the study sample. Primary data were collected using a Likert scale questionnaire and analysed using Partial Least Squares-Structural Equation Modelling (PLS-SEM) with SmartPLS version 4.0. The results show that integrating entrepreneurial human resource management has a positive effect on market adaptability, which significantly improves the sustainability of the business ecosystem. Furthermore, the dynamic market era was found to mediate the relationship between entrepreneurial human resource management and business sustainability. This confirms that successful innovative human resource management must be accompanied by the ability to cope with changes in the external environment. These findings have important implications for strengthening MSME development strategies based on human capabilities and sustainable market adaptation.