Estimation Issues with PLS and CBSEM: Where the Bias Lies!

Posted: 13 Jun 2017

See all articles by Marko Sarstedt

Marko Sarstedt

Otto-von-Guericke-Universität Magdeburg

Joseph F. Hair

Kennesaw State University

Christian M. Ringle

Hamburg University of Technology (TUHH)

Kai Thiele

Technical University Hamburg-Harburg (TUHH)

Siggi Gudergan

Newcastle Business School

Date Written: March 31, 2016

Abstract

Discussions concerning different structural equation modeling methods draw on an increasing array of concepts and related terminology. As a consequence,misconceptions about the meaning of terms such as reflective measurement and common factor models as well as formative measurement and composite models have emerged. By distinguishing conceptual variables and their measurement model operationalization from the estimation perspective,we disentangle the confusion between the terminologies and develop a unifying framework.

Results from a simulation study substantiate our conceptual considerations, highlighting the biases that occur when using:

(1) composite-based partial least squares path modeling to estimate common factor models, and

(2) common factor-based covariance-based structural equation modeling to estimate composite models.

The results show that the use of PLS is preferable, particularly when it is unknown whether the data's nature is common factor- or composite-based.

Keywords: Common factor models, Composite models, Reflective measurement, Formative measurement, Structural equation modeling, Partial least squares

Suggested Citation

Sarstedt, Marko and Hair, Joseph F. and Ringle, Christian M. and Thiele, Kai and Gudergan, Siggi, Estimation Issues with PLS and CBSEM: Where the Bias Lies! (March 31, 2016). Journal of Business Research, Vol. 69, No. 10, 2016, Available at SSRN: https://ssrn.com/abstract=2984816

Marko Sarstedt (Contact Author)

Otto-von-Guericke-Universität Magdeburg ( email )

Universitätspl. 2
PSF 4120
Magdeburg, D-39106
Germany

Joseph F. Hair

Kennesaw State University ( email )

1000 Chastain Rd
Kennesaw, GA 30144
United States

Christian M. Ringle

Hamburg University of Technology (TUHH) ( email )

Am Schwarzenberg-Campus 4
Hamburg, 21073
Germany

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

Kai Thiele

Technical University Hamburg-Harburg (TUHH) ( email )

Schwarzenbergstrasse 95
Hamburg, DE Hamburg 21073
Germany

Siggi Gudergan

Newcastle Business School ( email )

City Campus East – 231
Newcastle-Upon-Tyne NE1 8ST, NE1 8ST
Australia

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