HUMAN DIGITAL TWIN IN ELECTRONIC HUMAN RESOURCE MANAGEMENT: A CONCEPTUAL FRAMEWORK FOR PERSONALIZED TALENT MANAGEMENT IN INDUSTRY 5.0

M. Alfis Nor Abdi (Master of Management Program, Postgraduate Program, Universitas Islam Kalimantan Muhammad Arsyad Al Banjari (UNISKA MAB), Banjarmasin, Indonesia)
Syahrial Shaddiq (Faculty of Economics and Business, Universitas Lambung Mangkurat (ULM), Banjarmasin, Indonesia)
Khuzaini (Master of Management Program, Postgraduate Program, Universitas Islam Kalimantan Muhammad Arsyad Al Banjari (UNISKA MAB), Banjarmasin, Indonesia)
Zakky Zamrudi (Master of Management Program, Postgraduate Program, Universitas Islam Kalimantan Muhammad Arsyad Al Banjari (UNISKA MAB), Banjarmasin, Indonesia)

Jurnal Riset Multidisiplin Edukasi
Vol. 3 No. 7 (2026): Jurnal Riset Multidisiplin Edukasi (Juli 2026)

The rapid advancement of Industry 5.0 has transformed the strategic role of Human Resource Management (HRM), shifting organizational priorities from technology-driven automation toward human-centered innovation and sustainable workforce development. While Electronic Human Resource Management (e-HRM) has significantly improved the efficiency of human resource processes through digital technologies, current e-HRM systems often lack personalization, predictive intelligence, and continuous adaptation to employees' dynamic capabilities. This conceptual paper introduces the concept of the Human Digital Twin (HDT) as an innovative framework for enhancing e-HRM practices within the Industry 5.0 paradigm. The proposed framework integrates artificial intelligence, real-time workforce analytics, competency mapping, digital behavior analysis, predictive career development, and employee well-being monitoring into a unified digital representation of individual employees. Through an extensive review of recent literature on e-HRM, Industry 5.0, digital twins, artificial intelligence, and talent management, this study develops a comprehensive conceptual model demonstrating how Human Digital Twins can support personalized talent management throughout the employee lifecycle, including recruitment, training and development, performance management, succession planning, career development, and employee retention. The framework emphasizes ethical artificial intelligence, data governance, employee privacy, transparency, and human-centered decision-making as fundamental principles for successful implementation. Furthermore, the study argues that Human Digital Twins have the potential to strengthen organizational resilience, enhance employee experience, foster workforce agility, and improve strategic decision-making in increasingly digital organizations. This paper contributes to the emerging literature by extending the application of Digital Twin technology beyond industrial operations into strategic human resource management, offering both theoretical insights and practical guidance for organizations preparing for Industry 5.0.