Abstract
Purpose (limit 100 words) 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 (limit 100 words) First, using Vosviewer software, we analyzed 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 analyze current theories, methods, and variables. Findings (limit 100 words) 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 present significant theoretical perspectives, the methods employed, and nomological framework of variables. Originality/value (limit 100 words) 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 language | English |
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Journal | Personnel Review |
DOIs | |
Publication status | Accepted/In press - 19 Jul 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