Abstract

Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate analysis technique that human resource management (HRM) researchers frequently use. While most disciplines undertake regular critical reflections on the use of important methods to ensure rigorous research and publication practices, the use of PLS-SEM in HRM has not been analyzed so far. To address this gap in HRM literature, this paper presents a critical review of PLS-SEM use in 77 HRM studies published over a 30-year period in leading journals. By contrasting the review results with state-of-the-art guidelines for use of the method, we identify several areas that offer room of improvement when applying PLS-SEM in HRM studies. Our findings offer important guidance for future use of the PLS-SEM method in HRM and related fields.

Keywords

Partial least squares regressionStructural equation modelingHuman resource managementKnowledge managementComputer scienceManagement scienceProcess managementBusinessEngineeringMachine learning

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Publication Info

Year
2018
Type
article
Volume
31
Issue
12
Pages
1617-1643
Citations
1582
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

1582
OpenAlex
175
Influential

Cite This

Christian M. Ringle, Marko Sarstedt, Rebecca Mitchell et al. (2018). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management , 31 (12) , 1617-1643. https://doi.org/10.1080/09585192.2017.1416655

Identifiers

DOI
10.1080/09585192.2017.1416655

Data Quality

Data completeness: 81%