Trends and trajectories in Human Resource Analytics: A scopus-based bibliometric study of knowledge domains and research evolution

Alainati, S.; Senathirajah, A.R. S.; Al-Hunaiyyan, A.; Alameeri, M.

doi:10.22034/IJHCUM.2026.02.07

Trends and trajectories in Human Resource Analytics: A scopus-based bibliometric study of knowledge domains and research evolution

https://doi.org/10.22034/IJHCUM.2026.02.07

Volume 11, Issue 2
Spring 2026

Pages 323-342

International Journal of Human Capital in Urban Management

Document Type : ORIGINAL RESEARCH ARTICLE

Authors

S. Alainati ¹

A.R. S. Senathirajah ²^{, 3}

A. Al-Hunaiyyan ⁴

M. Alameeri ⁵

¹ Management Department, College of Business Studies, Public Authority for Applied Education and Training (PAAET), Ardiya, Kuwait

² Faculty of Business and Communication, INTI International University, Nilai, Malaysia

³ Faculty of Management, Shinawatra University, Pathum Thani, Thailand

⁴ Computing Department, College of Business Studies, Public Authority for Applied Education and Training (PAAET), Ardiya, Kuwait

⁵ Office Training Department, College of Business Studies, Public Authority for Applied Education and Training (PAAET), Ardiya, Kuwait

Abstract

BACKGROUND AND OBJECTIVES: Human Resource Analytics has become a strategic enabler in modern workforce management, particularly amid digital transformation. However, scholarly research in Human Resource Analytics remains fragmented across regions and disciplines. This study employs bibliometric analysis to map global research output in Human Resource Analytics from 2012 to 2024, identifying trends, influential contributors, thematic concentrations, and underexplored areas.
METHODS: A bibliometric analysis approach was applied using data retrieved from the Scopus database. The dataset covered publication metadata, including authorship, institutional affiliation, geographic origin, keywords, sources, and citation counts. VOSviewer software was used to construct visual maps illustrating keyword co-occurrence, co-authorship networks, and citation clusters, enabling a comprehensive overview of research activity and intellectual structure in the Human Resource Analytics.
FINDINGS: A total of 211 publications are identified and analysed over 13 years, involving 602 contributors. The analysis highlights 2,674 citations, with an average of 12.67 citations per paper. The corresponding h-index and g-index are 24 and 47, respectively. The results reveal three research themes. They present an increasing global interest, with leading contributions from high-income countries. The three core themes are workforce analytics, Artificial Intelligence in Human Resource Management, and strategic decision-making. Notably, low representation from developing regions and limited use of advanced predictive analytics highlight critical research gaps.
CONCLUSION: This study provides a comprehensive quantitative overview of the evolution of Human Resource Analytics scholarship. It guides future research by identifying emerging priorities, regional disparities, and methodological developments, offering valuable insights for advancing data-driven human resource practices and fostering more strategic, evidence-based decision-making in HR management and policy development globally.

Keywords

Artificial Intelligence

Bibliometric analysis

Human Resource Analytics

Human Resource Management

Scopus database

Subjects

Human capital in urban management

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