Rethinking some of the rethinking of partial least squares
University of South Alabama · Otto-von-Guericke-Universität Magdeburg · +3 more institutions
Abstract
Purpose Partial least squares structural equation modeling (PLS-SEM) is an important statistical technique in the toolbox of methods that researchers in marketing and other social sciences disciplines frequently use in their empirical analyses. The purpose of this paper is to shed light on several misconceptions that have emerged as a result of the proposed “new guidelines” for PLS-SEM. The authors discuss various aspects related to current debates on when or when not to use PLS-SEM, and which model evaluation metrics to apply. In addition, this paper summarizes several important methodological extensions of PLS-SEM researchers can use to improve the quality of their analyses, results and findings.…
Citation impact
- FWCI
- 161.92
- Percentile
- 100%
- References
- 146
Authors
3Topics & keywords
- Partial least squares regression
- Structural equation modeling
- Computer science
- Toolbox
- Management science
- Economics
- Machine learning