A Temporal Evolution of Human Resource Management and Technology Research: A Retrospective Bibliometric Analysis

Srumita Narzary, Upam Pushpak Makhecha, Pawan Budhwar, Ashish Malik*, Satish Kumar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Research on human resource management (HRM) and technology has gained momentum recently. This review aims to create a bibliographic profile of the field of HRM and technology using bibliometric techniques, complemented by qualitative analysis, examining 239 articles published in the four key human resource (HR) journals. Design/methodology/approach: First, using VOSviewer software, we analysed the research productivity by identifying authors, journals and influential articles, followed by insights on research themes and their evolution. Next, integrating bibliometric and qualitative approaches, we conducted a hybrid inquiry of the field to analyse current theories, methods and variables. Findings: The bibliometric analysis highlighted the intellectual structure, key themes and distinctive developments categorised under four temporal phases that have shaped research in this field. In addition, qualitative analysis presents significant theoretical perspectives, the methods employed and the nomological framework of variables. Originality/value: Our study advances the extant literature on HRM and technology by quantifying the leading bibliometric performance indicators complemented by qualitative evaluation of the field, which entails exploring the possible research strands and related trends that have emerged in the past two decades.

Original languageEnglish
JournalPersonnel Review
Early online date26 Aug 2024
DOIs
Publication statusE-pub ahead of print - 26 Aug 2024

Bibliographical note

Copyright © 2024, Emerald Publishing Limited. This author's accepted manuscript is deposited under a Creative Commons Attribution Non-commercial 4.0 International (CC BY-NC) licence. This means that anyone may distribute, adapt, and build upon the work for non-commercial purposes, subject to full attribution. If you wish to use this manuscript for commercial purposes, please contact [email protected]

Keywords

  • E-HRM
  • HRM
  • Bibliometric analysis
  • Artificial Intelligence
  • Big Data
  • Technology
  • Advanced Statistical

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