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All Journal Journal of Accounting and Management Innovation Jurnal Ekonomi Integra Ecobisma (Jurnal Ekonomi, Bisnis dan Manajemen) Journey : Journal of Tourismpreneurship, Culinary, Hospitality, Convention and Event Management Journal of Accounting and Management Innovation Jurnal Paradigma Akuntansi Jurnal Indonesia Sosial Teknologi AHKAM : Jurnal Hukum Islam dan Humaniora Ranah Research : Journal of Multidisciplinary Research and Development Journal of Chemistry Education and Integration SCIENTIA JOURNAL : Jurnal Ilmiah Mahasiswa
Vivi Vivi, Vivi
Fakultas Farmasi Universitas Ahmad Dahlan Yogyakarta, Jl. Prof. Dr. Soepomo, Janturan, Umbulharjo, Yogyakarta 55164
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Transportation Other

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INTEGRATING EMOTION AI IN HR DECISION-MAKING FOR EMPLOYEE WELL-BEING AND PERFORMANCE Taslim, Wui San; Vivi, Vivi
ECOBISMA (JURNAL EKONOMI, BISNIS DAN MANAJEMEN) Vol 13, No 1 (2026): ECOBISMA
Publisher : Published by the Faculty of Economics and Business, University of Labuhanbatu, North Sumat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/ecobi.v13i1.8207

Abstract

PURPOSE - This study examines how Emotion Artificial Intelligence (Emotion AI) influences the quality of Human Resource (HR) decision-making through the mediating role of Emotionally Aware AI Decision Making (EA-AIDM). EA-AIDM is introduced as a socio-technical construct that reflects AI systems, capacity to detect, interpret, and respond to human emotions in HR contexts.METHODOLOGY - Using a quantitative design, the study applied Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze responses from 122 HR professionals representing technology, manufacturing, and financial sectors. Participants were selected through purposive and stratified sampling, with inclusion criteria such as managerial roles and experience using AI-driven HR systems. Analyses included reliability, validity, factor loadings, and mediation testing.FINDING - Results reveal that AI adoption has no direct impact on HR decision-making (β = 0.178, p = 0.085) but exerts a significant indirect influence through EA-AIDM (β = 0.364, p < 0.001), indicating partial mediation. Among EA-AIDM indicators, context awareness and risk aversion showed the strongest effects, while emotion detection was weakest (mean = 2.69). These findings underscore the importance of designing emotionally aware AI that balances analytical precision with empathy to achieve ethical and effective HR decisions
Co-Authors Aini, Lutfiah Asmawaty, Asmawaty Daniel Cassa Augustinus, Daniel Cassa Fajriyan Hakimi Lukman, Fajriyan Hakimi Hakki, Tandry Halim, Deddy Kurniawan Hikmah Hikmah Hollandina, Ni Putu Darla Jefiza, Iqbal Junardi Junardi Marmaiyatno Mulia, Victor Bangun Pangoloan Soleman Ritonga R. Rusli Ratnah, St. Rusdiaman, Rusdiaman Sihombing, L. Alfies Sugianto Sugianto Taslim, Wui San Vanessa, Delicia Widyasari Widyasari, Widyasari Wiwik Handayani Yanti Yanti Yeni Nuraeni, Yeni