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All Journal JBMP (Jurnal Bisnis, Manajemen dan Perbankan) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Mantik Jurnal Informatika Ekonomi Bisnis Journal of Management - Small and Medium Enterprises (SME's) JOURNAL SCIENTIFIC OF MANDALIKA (JSM) Jurnal Pengabdian kepada Masyarakat Journal of Tourism Economics and Policy Jurnal Informatika Ekonomi Bisnis Journal of Mandalika Literature Journal of Practical Management Studies Jurnal Pengabdian Sosial Jurnal Pengabdian Masyarakat dan Riset Pendidikan E-Amal: Jurnal Pengabdian Kepada Masyarakat Asian Journal of Management, Entrepreneurship and Social Science Journal of Management and Business Innovation (JOMBINOV)
Anderias U. T. Anabuni
Department Of Business Administration, Politeknik Nenegeri Kupang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Artificial Intelligence and the Ethical Boundaries of Managerial Judgment: Insights from a Systematic Literature Review Irience R. A. Manongga; Andrias U. T. Anabuni
Journal of Management and Business Innovation Journal of Management and Business Innovation (JOMBINOV): Volume 02, No 01, March 2026
Publisher : CV. Vocezmi Learnov

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65792/jombinov.v2i01.33

Abstract

This research aims to systematically analyze the utilization of Artificial Intelligence (AI) in various Human Resource Management (HRM) functions, evaluate the theoretical foundations used in previous studies, summarize key empirical findings, and identify research gaps and emerging ethical-managerial implications. The research uses a Systematic Literature Review (SLR) design with a PRISMA approach. Data was collected from the Scopus, Web of Science, and Google Scholar databases for reputable journal articles published between 2015 and 2025. The selection process was conducted through the stages of identification, screening, and eligibility based on strict inclusion and exclusion criteria, resulting in 52 articles that were analyzed using thematic analysis and conceptual synthesis. Theoretically, this research enriches the technology-based HRM literature by presenting a typology of AI utilization in HRM functions and revealing the limitations of the theoretical framework, which is still partial and fragmented in previous studies. The research findings have strategic implications for practitioners and policymakers in ethically, responsibly, and sustainably integrating AI into HRM practices, particularly in the context of recruitment and selection, performance analytics, talent management, and data-driven HR decision-making. The limitations of this study lie in its reliance on secondary data sources and the dominance of studies focused on developed country contexts. This situation opens opportunities for further research that is empirical, longitudinal, and contextual, particularly in developing countries.
Determinants of QRIS User Information: The Role of Usage Barriers, Value Barriers, Risk Barriers, Initial Trust, and Perceived Usefulness Septia S. Dioh; Taqwa Sultan; Irience R. A. Manongga; Maria S. Lou Kelen; Wihelmina Muni; Andrias U. T. Anabuni
Journal of Practical Management Studies Vol. 4 No. 1 (2026): JPMS - March (2026)
Publisher : CV. Jala Berkat Abadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61106/jpms.v1i1.143

Abstract

This study examines the determinants of QRIS user information by integrating innovation resistance and technology acceptance perspectives within Indonesia’s nationally standardized digital payment system. Using a quantitative explanatory design, data were collected from 105 QRIS users in Kupang City through a structured questionnaire. Multiple linear regression analysis was employed to test the effects of usage barrier, value barrier, risk barrier, initial trust, and perceived usefulness on user information, following validity, reliability, and classical assumption testing. The results show that usage barriers negatively influence QRIS user information, whereas value barriers, risk barriers, initial trust, and perceived usefulness have significant positive effects. Among all predictors, risk barrier emerges as the most dominant determinant, indicating that security and uncertainty perceptions play a critical role in shaping users’ informational engagement. The proposed model explains 65.8% of the variance in user information, demonstrating strong explanatory power. This study adopts a cross-sectional design and focuses on a single geographic context, which may limit generalizability. Future research may employ longitudinal or comparative approaches to capture dynamic and contextual variations. This study advances digital payment and information systems literature by repositioning user information as a central cognitive outcome of user–technology interaction rather than merely an antecedent of adoption, offering an information-centric framework for evaluating the effectiveness of standardized digital payment systems.
Co-Authors Aman, Dominikus K.T Aman, Dominikus K.T. Arthana, I Komang Bunga, Markus Cornelia Amelia Thonak de Rozari, Petrus E. Dewiaty, Irma Linda Dikky Mooy Dominikus K.T.Aman Dominikus Kopong T. Aman Fanggidae, Apriana H.J. Foenay, Christien C. Himpi, Plafianto jono karjo Irience R.A. Manongga Kellen, Maria Sisilia Lou Klaasvakumok Jehezkielomi Kamuri Makatita, Reyner F. Maria S. Lou Kelen Marianus S. Neno Marianus S.Neno Natonis, Sari Angriany Neno, Marianus S Pane, Ayu Sartika Petrus E de Rosari Septia S. Dioh Siahaan, Moni Y. Taqwa Sultan Wehelmina Ndoen Wehelmina Ndoen Wihelmina Muni Yonas F Riwu Yonas F. Riwu Yosefina Dhae Yosefina K.I.D.D Dhae Yuri S. Fa’ah Yuri Sandra Fa’ah Yuri.S.Fa’ah