Why researchers should be cautious about using PLS-SEM

A recent contribution to Industrial Marketing Management by Guenther, Guenther, Ringle, Zaefarian, and Cartwright (2023) aims at “[i]mproving PLS-SEM use.” It assumes that the use of PLS-SEM could be improved by more strictly following existing PLS-SEM guidelines and using advanced techniques. Unfortunately, such “improved” use of PLS-SEM does not necessarily translate into more rigorous scientific analyses. In this commentary, we show that the PLS-SEM guidelines themselves are problematic and that using PLS-SEM can lead to erroneous conclusions. It is, therefore, not so much the use of PLS-SEM that needs improvement, but the literature on PLS-SEM itself, particularly its guidelines. The commentary concludes with recommendations for analysts and questions for PLS-SEM proponents to stimulate further research on PLS-SEM.

Authors

Publication Details

Journal
Industrial Marketing Management
Published
2025-05-26
DOI
https://doi.org/10.1016/j.indmarman.2024.01.017
Citations
8
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
15.99

Funders

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article

Why researchers should be cautious about using PLS-SEM

Jörg Henseler, Nick J. Lee, Florian Schuberth, Ildikó Kemény
8 citations
Industrial Marketing Management
Big Data and Business Intelligence
15.99
article

Why researchers should be cautious about using PLS-SEM

Jörg Henseler, Nick J. Lee, Florian Schuberth, Ildikó Kemény
article en
8 citations

Abstract

A recent contribution to Industrial Marketing Management by Guenther, Guenther, Ringle, Zaefarian, and Cartwright (2023) aims at “[i]mproving PLS-SEM use.” It assumes that the use of PLS-SEM could be improved by more strictly following existing PLS-SEM guidelines and using advanced techniques. Unfortunately, such “improved” use of PLS-SEM does not necessarily translate into more rigorous scientific analyses. In this commentary, we show that the PLS-SEM guidelines themselves are problematic and that using PLS-SEM can lead to erroneous conclusions. It is, therefore, not so much the use of PLS-SEM that needs improvement, but the literature on PLS-SEM itself, particularly its guidelines. The commentary concludes with recommendations for analysts and questions for PLS-SEM proponents to stimulate further research on PLS-SEM.

Industrial Marketing ManagementVol. 128
Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 1%
Big Data and Business Intelligence
15.99
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