PLS-SEM: Indeed a Silver Bullet

Journal of Marketing Theory and Practice, Vol. 19, No. 2, 2011, pp. 139-152

Posted: 4 Nov 2011 Last revised: 4 Feb 2014

See all articles by Joseph F. Hair

Joseph F. Hair

Kennesaw State University

Christian M. Ringle

Hamburg University of Technology (TUHH)

Marko Sarstedt

Otto-von-Guericke-Universität Magdeburg

Date Written: November 4, 2011

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.

Keywords: partial least squares, path modeling, PLS, structural equation modeling, SEM, marketing

JEL Classification: A00

Suggested Citation

Hair, Joseph F. and Ringle, Christian M. and Sarstedt, Marko, PLS-SEM: Indeed a Silver Bullet (November 4, 2011). Journal of Marketing Theory and Practice, Vol. 19, No. 2, 2011, pp. 139-152, Available at SSRN: https://ssrn.com/abstract=1954735

Joseph F. Hair

Kennesaw State University ( email )

1000 Chastain Rd
Kennesaw, GA 30144
United States

Christian M. Ringle (Contact Author)

Hamburg University of Technology (TUHH) ( email )

Am Schwarzenberg-Campus 4
Hamburg, 21073
Germany

HOME PAGE: http://www.tuhh.de/hrmo

Marko Sarstedt

Otto-von-Guericke-Universität Magdeburg ( email )

Universitätspl. 2
PSF 4120
Magdeburg, D-39106
Germany

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