Options
Common beliefs and reality about PLS : comments on Rönkkö and Evermann (2013)
Citation Link: https://doi.org/10.15480/882.1565
Publikationstyp
Journal Article
Publikationsdatum
2014-04
Sprache
English
Enthalten in
Volume
17
Issue
2
Start Page
182
End Page
209
Citation
Organizational Research Methods 2 (17): 182-209 (2014)
Publisher DOI
Scopus ID
Publisher
Sage Publ.
This article addresses Ro¨nkko¨ 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 Ro¨nkko¨ 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 Ro¨nkko¨ 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.
problems with the technique, but instead to three problems with Ro¨nkko¨ 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 Ro¨nkko¨ 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.
Schlagworte
quantitative research
multivariate analysis
structural equation modeling
linear techniques
partial least squares path modeling
composite factor model
DDC Class
330: Wirtschaft