Abstract
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.
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.
| Original language | English |
|---|---|
| Journal | European Journal of Marketing |
| Volume | 58 |
| Issue | 13 |
| Pages (from-to) | 81-106 |
| Number of pages | 26 |
| ISSN | 0309-0566 |
| DOIs | |
| Publication status | Published - May 2024 |
Keywords
- Path modeling
- Structural equation modeling
- composite-based modeling
- partial least squares
- Composite-based modeling
- Partial least squares