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<p>This study examines the impact of blockchain technology on human resource management (HRM) through a systematic literature review (SLR) and bibliometric analysis. Drawing on 96 peer-reviewed articles indexed in Scopus between 2016 and April 2024, the study applies the SPAR-4-SLR protocol and employs RStudio and VOSviewer to map thematic structures and research trajectories. The findings indicate that blockchain adoption in HRM enhances transparency, data security, and operational efficiency, particularly in recruitment, payroll, employee verification, and performance management. However, the effects are conditioned by organizational size, technological readiness, and institutional context. Bibliometric clustering reveals three dominant research streams: (1) foundational blockchain applications in HRM, (2) technological convergence with artificial intelligence and Industry 4.0, and (3) data-driven and predictive HR ecosystems integrating big data, IoT, and machine learning. The study moves beyond descriptive theme identification by translating clusters into evolutionary research trajectories and anchoring them within the TCM (theory–context–method) and ADO (antecedents–decisions–outcomes) frameworks. This structured interpretation provides conceptual clarity and highlights the uneven maturity of blockchain–HRM scholarship. The findings offer theoretical insights into digital transformation in HRM and provide practical guidance for managers and policymakers seeking staged and context-sensitive blockchain adoption strategies.</p>

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The impacts of blockchain on human resource management: a systematic literature review and bibliometric analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月27日

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  • Elma Noorain Momo,
  • Md. Nazmus Sakib

摘要

This study examines the impact of blockchain technology on human resource management (HRM) through a systematic literature review (SLR) and bibliometric analysis. Drawing on 96 peer-reviewed articles indexed in Scopus between 2016 and April 2024, the study applies the SPAR-4-SLR protocol and employs RStudio and VOSviewer to map thematic structures and research trajectories. The findings indicate that blockchain adoption in HRM enhances transparency, data security, and operational efficiency, particularly in recruitment, payroll, employee verification, and performance management. However, the effects are conditioned by organizational size, technological readiness, and institutional context. Bibliometric clustering reveals three dominant research streams: (1) foundational blockchain applications in HRM, (2) technological convergence with artificial intelligence and Industry 4.0, and (3) data-driven and predictive HR ecosystems integrating big data, IoT, and machine learning. The study moves beyond descriptive theme identification by translating clusters into evolutionary research trajectories and anchoring them within the TCM (theory–context–method) and ADO (antecedents–decisions–outcomes) frameworks. This structured interpretation provides conceptual clarity and highlights the uneven maturity of blockchain–HRM scholarship. The findings offer theoretical insights into digital transformation in HRM and provide practical guidance for managers and policymakers seeking staged and context-sensitive blockchain adoption strategies.