2024/05/28 by Joe F. Hair, Marko Sarstedt, Christian M. Ringle +4
Business, Management and Accounting · Decision Sciences · #Customer Service Quality and Loyalty #Technology Adoption and User Behaviour
paper · pdf · doi:10.1108/ejm-08-2023-0645
openalex publication_date 2024/05/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
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.