European Journal of Marketing· 2019Q1
Rethinking some of the rethinking of partial least squares
- 1,600citations
- Q1SCImago
- 2019year
Short summary
This paper offers a counter-perspective to recent 'new guidelines' for Partial Least Squares Structural Equation Modeling (PLS-SEM), clarifying misconceptions and providing guidance on its appropriate use and evaluation.
AI-generated from the title and abstract; the full text is not read.
Key points
- Challenges recent 'new guidelines' for PLS-SEM, arguing some claims lack substantiation.
- Clarifies misconceptions regarding the application and evaluation metrics of PLS-SEM.
- Provides guidance on situations favoring PLS-SEM use and handling endogeneity.
- Opposes characterizing established PLS-SEM practices as outdated without offering concrete alternatives.
AI-generated from the title and abstract; the full text is not read.
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. Design/methodology/approach The paper merges literature from various disciplines, including marketing, strategic management, information systems, accounting and statistics, to present a state-of-the-art review of PLS-SEM. Based on these findings, the paper offers a point of orientation on how to consider and apply these latest developments when executing or assessing PLS-SEM-based research. Findings This paper offers guidance regarding situations that favor the use of PLS-SEM and discusses the need to consider certain model evaluation metrics. It also summarizes how to deal with endogeneity in PLS-SEM, and critically comments on the recent proposal to adjust PLS-SEM estimates to mimic common factor models that are the foundation of covariance-based SEM. Finally, this paper opposes characterizing common concepts and practices of PLS-SEM as “out-of-date” without providing well-substantiated alternatives and solutions. Research limitations/implications The paper paves the way for future discussions and suggests a way forward to reach consensus regarding situations that favor PLS-SEM use and its application. Practical implications This paper offers guidance on how to consider the latest methodological developments when executing or assessing PLS-SEM-based research. Originality/value This paper complements recently proposed “new guidelines” with the aim of offering a counter perspective on some strong claims made in the latest literature on PLS-SEM. It also clarifies some misconceptions regarding the application of PLS-SEM.
The authors' abstract, as published at the source. European Journal of Marketing, 2019 · DOI ↗
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Field: Organizational Behavior and Human Resource Management
Organizational Behavior and Human Resource ManagementBusiness, Management and Accounting