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Digital Human Resource Management: Emerging Technologies in Talent Identification and Development and Their Strategic Adoption

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Dissertation(670.69 KB)

Date

2025

Authors

Supervisor

Smollan, Roy

Item type

Dissertation

Degree name

Master of Business

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Publisher

Auckland University of Technology

Abstract

In the rapidly evolving field of Human Resource Management (HRM), organisations must stay relevant in the business environment by following recent trends and best practices. Further, with abundant workforce data, especially in large organisations, embracing emerging technologies and having a competent system for managing the HR processes is essential. Based on resource-based, human capital theories and high-commitment HR strategies, this research focuses on identifying and developing valuable HR processes to gain a competitive advantage for organisations. The study begins by analysing the gaps in the previous literature and discusses the two main objectives drawn from it. The first objective was to understand how digitalisation is influencing the talent management processes of talent identification and development, and the second was to explore ways for successfully adopting digital human resource strategies within an organisation. Based on these objectives, two research questions were designed: RQ1: How is digitalisation influencing organisations' talent identification and development processes and their effectiveness? RQ2: How can digital human resource strategies be adopted successfully? A flexible narrative literature review research method was employed to merge academic and practical insights from recent literature published since 2019. The findings of the study were derived from thematic analysis to uncover the role of emerging technologies, like AI, HR analytics, and VR/AR technologies, with their unique strengths, positively transforming talent identification and development processes, providing a clear roadmap for organisations to decide which technologies to leverage to earn maximum return on investment. Additionally, this study demonstrates how digital HR strategies can be successfully adopted, considering the barriers to technological adoption. Against this backdrop, the study proposes a 4C model comprising four interconnected elements of commitment, culture, change management and collaboration, derived from previous research studies. Then, the discussion section analyses the findings and identifies theoretical and practical implications. The analysis highlighted several limitations, including the scope of the study, lack of empirical studies in AR/VR, HR analytics, AI, and selection bias. Consequently, proposed future studies focus on robust ethical systems, employee well-being, and the need for more empirical evidence to evaluate and develop AI, HR analytics and AR/VR technologies in HR. Lastly, this dissertation provides actionable recommendations for employees, HR practitioners, and organisations, and it discusses the key contributions to theoretical knowledge and implementation within HR digitalisation and beyond.

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http://hdl.handle.net/10292/19246

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Masters Dissertations