A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling

By Mikko Rönkkö, Joerg Evermann. 2013

422 citations recorded by the source corpus.

Subfields: Management Information Systems, Organizational Behavior and Human Resource Management, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/a2a7ee16e6375f1e9efac8b2d9f079d1da1a1b20

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Citations in the corpus

Comparison Between CB-SEM and PLS-SEM: Testing and Confirming the Maqasid Syariah Quality of Life Measurement Model (2019, methodology): “According to Rönkkö and Evermann (2013), the factor loading produced by PLS-SEM is always biased upwards or overestimated due to the presence of measurement error which could affect the parameter estimates and eventually lead to the committing of type I error.”
Using PLS path modeling in new technology research: updated guidelines (2016, background): “Scholars have discussed the conceptual underpinnings (Rigdon, 2012, 2014; Sarstedt et al., 2014) as well as the strengths and weaknesses (Rönkkö and Evermann, 2013; Henseler et al., 2014; Aguirre-Urreta and Marakas, 2013; Rigdon et al., 2014).”
Partial Least Squares Structural Equation Modeling with R. (2016, methodology): “For more studies regarding the advantageous and disadvantageous of PLS-SEM respected readers are referred to Rigdon (2012; in press), Henseler et al. (2014), Rönkkö and Evermann (2013), and McIntosh, Edwards, and Antonakis, (2014).”
Partial least squares structural equation modeling in HRM research (2020, methodology): “…2014) and the controversy regarding its advantages and limitations (e.g. Goodhue, Lewis, & Thompson, 2012; Marcoulides, Chin, & Saunders, 2012; Rönkkö & Evermann, 2013; Sarstedt, Hair, Ringle, Thiele, & Gudergan, 2016) call for a critical review of the way the method is used in the HRM field.”
Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling (2018, background): “Some researchers even claim that PLS-SEM does not allow endogeneity to be addressed at all (e.g., Antonakis et al. 2010; McIntosh, Edwards, and Antonakis 2014; Rönkkö and Evermann 2013).”
An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research (2017, methodology): “…Dijkstra, T.K., Sarstedt, M., Ringle, C.M., Diamantopoulos, A., Straub, D.W., Ketchen, D.J., Hair, J.F., Hult, G.T.M. and Calantone, R.J. (2014), "Common Beliefs and Reality about Partial Least Squares: Comments on Rönkkö & Evermann (2013)", Organizational Research Methods, Vol. 17, pp. 182-209.”
Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods (2017, background): “While this study is not the first to question PLS’s performance in this regard (Goodhue et al. 2012a; Rönkkö and Evermann 2013), it is the first to do so on the grounds of an approriately specified (i.e., composite model) population.”
On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations (2017, methodology): “Studies that dramatize differences in the methods (Rönkkö et al., 2016; Rönkkö & Evermann, 2013), thereby inflating the relevance of method choice, have contributed to this development.”
Big Data and Predictive Analytics and Manufacturing Performance: Integrating Institutional Theory, Resource‐Based View and Big Data Culture (2019, neutral): “However, in recent years some scholars have raised concerns over the use of PLS technique (see, Ronkko and Evermann, 2013; Guide and Ketokivi, 2015; Ronkko et al., 2016).”