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

Yucheng Zhang, Shan Xu, Long Zhang and Mengxi Yang

Journal of Business Research, 2021, vol. 133, issue C, 34-50

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.

Keywords: Human resource management research; Big data; Integrative review; Inductive and deductive paradigms (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:133:y:2021:i:c:p:34-50

DOI: 10.1016/j.jbusres.2021.04.019

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