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

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.

Publication DOI: https://doi.org/10.1108/pr-04-2023-0296
Divisions: College of Business and Social Sciences > Aston Business School > Work & Organisational Psychology
College of Business and Social Sciences > Aston Business School > Aston India Centre for Applied Research
College of Business and Social Sciences > Aston Business School > Aston India Foundation for Applied Research
College of Business and Social Sciences > Aston Business School
Aston University (General)
Additional Information: 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 permissions@emerald.com
Uncontrolled Keywords: E-HRM,HRM,Bibliometric analysis,Artificial Intelligence,Big Data,Technology,Advanced Statistical
Publication ISSN: 1758-6933
Last Modified: 06 Nov 2024 08:18
Date Deposited: 23 Aug 2024 13:33
Full Text Link:
Related URLs: https://www.eme ... -0296/full/html (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2024-08-26
Published Online Date: 2024-08-26
Accepted Date: 2024-07-19
Authors: Narzary, Srumita
Makhecha, Upam Pushpak
Budhwar, Pawan (ORCID Profile 0000-0001-8915-6172)
Malik, Ashish
Kumar, Satish

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