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PLS-SEM: Indeed a Silver Bullet

2011; Taylor & Francis; Volume: 19; Issue: 2 Linguagem: Inglês

10.2753/mtp1069-6679190202

1944-7175

Joe F. Hair, Christian M. Ringle, Marko Sarstedt,

Technology Adoption and User Behaviour

Abstract Structural equation modeling (SEM) has become a quasi-standard in marketing and management research when it comes to analyzing the cause-effect relations between latent constructs. For most researchers, SEM is equivalent to carrying out covariance-based SEM (CB-SEM). While marketing researchers have a basic understanding of CB-SEM, most of them are only barely familiar with the other useful approach to SEM-partial least squares SEM (PLS-SEM). The current paper reviews PLS-SEM and its algorithm, and provides an overview of when it can be most appropriately applied, indicating its potential and limitations for future research. The authors conclude that PLS-SEM path modeling, if appropriately applied, is indeed a "silver bullet" for estimating causal models in many theoretical models and empirical data situations. This article is part of the following collections: Celebrating the Impactful Articles from Journal of Marketing Theory and Practice