People Analytics in HRM: A Bibliometric Study

Abstract

This study examines the development and intellectual structure of people analytics within human resource management using a bibliometric approach. Drawing on data from a selected academic database, the analysis maps publication trends, influential sources, and the relationships among key concepts through co-occurrence, network, overlay, and density visualizations. The findings identify people analytics as the central construct that connects technological domains such as artificial intelligence, machine learning, and predictive analytics with strategic HR practices, including talent management and decision making. The results reveal an evolutionary trajectory in which early studies focused on data infrastructure and workforce analytics, followed by a phase of integration into HR functions, and more recent work emphasizing predictive and decision-oriented applications. Despite this progress, the field remains partially fragmented, with limited integration between analytical techniques and strategic HR outcomes. This study contributes by clarifying the intellectual landscape of people analytics and highlighting opportunities for future research to develop more integrative and theory-informed approaches that link analytics capabilities with organizational value creation.