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Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013)

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Henseler, Jörg, Dijkstra, Theo K., Sarstedt, Marko, Ringle, Christian M., Diamantopoulos, Adamantios, Straub, Detmar W., Ketchen, David J., Hair, Joseph F., Hult, G. Tomas M., Calantone, Roger J.·2014·Organizational Research Methods

DOI 10.1177/1094428114526928

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Abstract

This article addresses Rönkkö and Evermann’s criticisms of the partial least squares (PLS) approach to structural equation modeling. We contend that the alleged shortcomings of PLS are not due to problems with the technique, but instead to three problems with Rönkkö and Evermann’s study: (a) the adherence to the common factor model, (b) a very limited simulation designs, and (c) overstretched generalizations of their findings. Whereas Rönkkö and Evermann claim to be dispelling myths about PLS, they have in reality created new myths that we, in turn, debunk. By examining their claims, our article contributes to reestablishing a constructive discussion of the PLS method and its properties. We show that PLS does offer advantages for exploratory research and that it is a viable estimator for composite factor models. This can pose an interesting alternative if the common factor model does not hold. Therefore, we can conclude that PLS should continue to be used as an important statistical tool for management and organizational research, as well as other social science disciplines.

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Authors: Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J.
Affiliations: Radboud University Nijmegen (NL)
University of Groningen (NL)
University of Newcastle Australia (AU)
University of Vienna (AT)
University System of Georgia (US)
Auburn University (US)
Kennesaw State University (US)
Michigan State University (US)
Corresponding author: Henseler, Jörg
ORCID: Henseler, Jörg
Sarstedt, Marko
Ringle, Christian M.
Diamantopoulos, Adamantios
Straub, Detmar W.
Ketchen, David J.
Hair, Joseph F.
Hult, G. Tomas M.
Calantone, Roger J.
Venue: Organizational Research Methods
Publisher: SAGE Publications
Published: 2014-04
Volume: 17
Issue: 2
Pages: 182-209
ISSN: 1094-4281 (ISSN-L)
1552-7425
DOI: 10.1177/1094428114526928
OpenAlex: W2100739170
Cited by: 3,332
References: 111
Citations by year: 2026: 327 · 2025: 396 · 2024: 433 · 2023: 458 · 2022: 424 · 2021: 349 · 2020: 261 · 2019: 230 · 2018: 177 · 2017: 116 · 2016: 106 · 2015: 40 · 2014: 14
FWCI: 115.87
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Organizational Research Methods (publishedVersion, cc-by-nc)
University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, cc-by-nc)
University of Twente Research Information (publishedVersion, cc-by)
DigitalCommons - Kennesaw State University (Kennesaw State University) (submittedVersion)
Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
DigitalCommons - Kennesaw State University (Kennesaw State University) (submittedVersion, cc-by-nc)
Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion, cc-by-nc)
Radboud Repository (Radboud University) (submittedVersion)
University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by-nc)
University of Twente Research Information (submittedVersion, cc-by)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
Keywords: partial least squares, structural equation modeling, common factor model, simulation study, exploratory research, methodological considerations

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