Mirror, Mirror on the Wall: A Comparative Evaluation of Composite-Based Structural Equation Modeling Methods

Journal of the Academy of Marketing Science, Forthcoming

Posted: 13 Jun 2017

See all articles by Joseph F. Hair

Joseph F. Hair

Kennesaw State University

G. Tomas M. Hult

Michigan State University

Christian M. Ringle

Hamburg University of Technology (TUHH); Waikato Management School

Marko Sarstedt

Otto-von-Guericke-Universität Magdeburg; Otto-von-Guericke-Universität Magdeburg; University of Newcastle (Australia)

Kai Thiele

Hamburg University of Technology

Date Written: July 7, 2016

Abstract

Composite-based structural equation modeling (SEM), and especially partial least squares path modeling (PLS), has gained increasing dissemination in marketing. To fully exploit the potential of these methods, researchers must know about their relative performance and the settings that favor each method’s use. While numerous simulation studies have aimed to evaluate the performance of composite-based SEM methods, practically all of them defined populations using common factor models, thereby assessing the methods on erroneous grounds. This study is the first to offer a comprehensive assessment of composite-based SEM techniques on the basis of composite model data, considering a broad range of model constellations. Results of a large-scale simulation study substantiate that PLS and generalized structured component analysis are consistent estimators when the underlying population is composite model-based. While both methods outperform sum-scores regression in terms of parameter recovery, PLS achieves slightly greater statistical power.

Keywords: Composite, Generalized structured component analysis, GSCA, Partial least squares, PLS, SEM, Simulation, Structural equationmodeling, Sumscores regression

Suggested Citation

Hair, Joseph F. and Hult, G. Tomas M. and Ringle, Christian M. and Sarstedt, Marko and Thiele, Kai, Mirror, Mirror on the Wall: A Comparative Evaluation of Composite-Based Structural Equation Modeling Methods (July 7, 2016). Journal of the Academy of Marketing Science, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2984764

Joseph F. Hair

Kennesaw State University ( email )

1000 Chastain Rd
Kennesaw, GA 30144
United States

G. Tomas M. Hult (Contact Author)

Michigan State University ( email )

East Lansing, MI 48824-1121
United States

Christian M. Ringle

Hamburg University of Technology (TUHH) ( email )

Schwarzenbergstr. 95 (D)
Hamburg, D-21071
Germany

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

Waikato Management School ( email )

Te Raupapa
Private Bag 3105
Hamilton, 3240
New Zealand

Marko Sarstedt

Otto-von-Guericke-Universität Magdeburg ( email )

Universitätspl. 2
PSF 4120
Magdeburg, D-39106
Germany

Otto-von-Guericke-Universität Magdeburg ( email )

Universitätspl. 2
PSF 4120
Magdeburg, D-39106
Germany

University of Newcastle (Australia) ( email )

University Drive
Callaghan, NSW 2308
Australia

Kai Thiele

Hamburg University of Technology ( email )

Schwarzenbergstrasse 95
Hamburg, DE Hamburg 21073
Germany

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