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  4. Going beyond the untold facts in PLS–SEM and moving forward
 
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Going beyond the untold facts in PLS–SEM and moving forward

Citation Link: https://doi.org/10.15480/882.13068
Publikationstyp
Journal Article
Date Issued
2024-05-28
Sprache
English
Author(s)
Hair, Joseph F.  
Sarstedt, Marko  
Ringle, Christian M.  orcid-logo
Management und Entscheidungswissenschaften W-9  
Sharma, Pratyush Nidhi  
Liengaard, Benjamin Dybro  
TORE-DOI
10.15480/882.13068
TORE-URI
https://hdl.handle.net/11420/47894
Journal
European journal of marketing  
Volume
58
Issue
13
Start Page
81
End Page
106
Citation
European Journal of Marketing 58 (13): 81-106 (2024)
Publisher DOI
10.1108/EJM-08-2023-0645
Scopus ID
2-s2.0-85195178252
Publisher
Emerald
Purpose: This paper aims to discuss recent criticism related to partial least squares structural equation modeling (PLS-SEM). Design/methodology/approach: Using a combination of literature reviews, empirical examples, and simulation evidence, this research demonstrates that critical accounts of PLS-SEM paint an overly negative picture of PLS-SEM’s capabilities. Findings: Criticisms of PLS-SEM often generalize from boundary conditions with little practical relevance to the method’s general performance, and disregard the metrics and analyses (e.g., Type I error assessment) that are important when assessing the method’s efficacy. Research limitations/implications: We believe the alleged “fallacies” and “untold facts” have already been addressed in prior research and that the discussion should shift toward constructive avenues by exploring future research areas that are relevant to PLS-SEM applications. Practical implications: All statistical methods, including PLS-SEM, have strengths and weaknesses. Researchers need to consider established guidelines and recent advancements when using the method, especially given the fast pace of developments in the field. Originality/value: This research addresses criticisms of PLS-SEM and offers researchers, reviewers, and journal editors a more constructive view of its capabilities.
Subjects
Composite-based modeling
Partial least squares
Path modeling
Structural equation modeling
DDC Class
330: Economics
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
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