The interdisciplinary nature of AI and human resource management: A bibliometric analysis

BACKGROUND: This study investigates the evolving relationship between artificial intelligence [AI] and human resource management [HRM] over the past two decades through a comprehensive analysis of 392 articles published between 2012 and 2023. OBJECTIVE: The study aims to provide a systematic understanding of this relationship by employing a rigorous three-stage methodology involving RStudio, VOSviewer, and Excel. METHODS: The methodology encompasses overall performance assessment, citation analysis, and network and content analysis to identify evolving research priorities, influential authors and publications, and underlying connections within the academic literature. RESULTS: The systematic approach reveals clusters of future research trends, including leveraging AI and big data for HRM advancements, enhancing employee engagement through machine learning, and investigating neural networks and procedural justice in HRM. IMPLICATIONS: This research agenda offers a roadmap for academics and HR professionals, identifying key areas for future exploration to ensure continued understanding of the dynamic interplay between AI and HRM.

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Publication Details

Journal
Human Systems Management
Published
2024-11-01
DOI
https://doi.org/10.1177/01672533241305173
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.53
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article

The interdisciplinary nature of AI and human resource management: A bibliometric analysis

Husni Samara, Ghaith Abualfalayeh, Tareq Abu Orabi, Abeer Madi Mohammad Alahewat
1 citations
Human Systems Management
Big Data and Business Intelligence
0.53
article

The interdisciplinary nature of AI and human resource management: A bibliometric analysis

Husni Samara, Ghaith Abualfalayeh, Tareq Abu Orabi, Abeer Madi Mohammad Alahewat
article en
1 citations

Abstract

BACKGROUND: This study investigates the evolving relationship between artificial intelligence [AI] and human resource management [HRM] over the past two decades through a comprehensive analysis of 392 articles published between 2012 and 2023. OBJECTIVE: The study aims to provide a systematic understanding of this relationship by employing a rigorous three-stage methodology involving RStudio, VOSviewer, and Excel. METHODS: The methodology encompasses overall performance assessment, citation analysis, and network and content analysis to identify evolving research priorities, influential authors and publications, and underlying connections within the academic literature. RESULTS: The systematic approach reveals clusters of future research trends, including leveraging AI and big data for HRM advancements, enhancing employee engagement through machine learning, and investigating neural networks and procedural justice in HRM. IMPLICATIONS: This research agenda offers a roadmap for academics and HR professionals, identifying key areas for future exploration to ensure continued understanding of the dynamic interplay between AI and HRM.

Human Systems ManagementVol. 43(6)
Applied Science Private University (JO), Universitat de València (ES), Al-Balqa Applied University (JO), Universitat Politècnica de València (ES)
Decent work and economic growth
Openalex Percentile: Top 22%
Big Data and Business Intelligence
0.53
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The interdisciplinary nature of AI and human resource management: A bibliometric analysis — Husni Samara, Ghaith Abualfalayeh, et al. · Human Systems Management (2024) | TGRS Research Map | TGRS