Big data and human resource management research: an integrative review and new directions for future research

Zhang, Yucheng, Xu, Shan, Zhang, Long and Yang, Mengxi (2021) Big data and human resource management research: an integrative review and new directions for future research. Journal of Business Research, 133, 34-50. (doi:10.1016/j.jbusres.2021.04.019).

Abstract

The lack of sufficient big data-based approaches impedes the development of human resource management (HRM) research and practices. Although scholars have realized the importance of applying a big data approach to HRM research, clear guidance is lacking regarding how to integrate the two. Using a clustering algorithm based on the big data research paradigm, we first conduct a bibliometric review to quantitatively assess and scientifically map the evolution of the current big data HRM literature. Based on this systematic review, we propose a general theoretical framework described as “Inductive (Prediction paradigm: Data mining/Theory building) vs. Deductive (Explanation paradigm: Theory testing)”. In this framework, we discuss potential research questions, their corresponding levels of analysis, relevant methods, data sources and software. We then summarize the general procedures for conducting big data research within HRM research. Finally, we propose a future agenda for applying big data approaches to HRM research and identify five promising HRM research topics at the micro, meso and macro levels along with three challenges and limitations that HRM scholars may face in the era of big data.

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Contributors

Author: Yucheng Zhang

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