Testing Measurement Invariance of Composites Using Partial Least Squares

International Marketing Review, Vol. 33, No. 3, pp. 405-431, 2016

Posted: 14 Jun 2017

See all articles by Jörg Henseler

Jörg Henseler

Institute for Management Research, Radboud University Nijmegen; Instituto Superior de Estatística e Gestão de Informação, Universidade Nova de Lisboa

Christian M. Ringle

Hamburg University of Technology (TUHH)

Marko Sarstedt

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

Date Written: September 19, 2014

Abstract

Purpose – Research on international marketing usually involves comparing different groups of respondents. When using structural equation modeling (SEM), group comparisons can be misleading unless researchers establish the invariance of their measures. While methods have been proposed to analyze measurement invariance in common factor models, research lacks an approach in respect of composite models. The purpose of this paper is to present a novel three-step procedure to analyze the measurement invariance of composite models (MICOM) when using variance-based SEM, such as partial least squares (PLS) path modeling.

Design/methodology/approach – A simulation study allows us to assess the suitability of the MICOM procedure to analyze the measurement invariance in PLS applications.

Findings – TheMICOMprocedure appropriately identifies no, partial, and full measurement invariance.

Research limitations/implications – The statistical power of the proposed tests requires further research, and researchers using the MICOM procedure should take potential type-II errors into account.

Originality/value – The research presents a novel procedure to assess the measurement invariance in the context of composite models. Researchers in international marketing and other disciplines need to conduct this kind of assessment before undertaking multigroup analyses. They can use MICOM procedure as a standard means to assess the measurement invariance.

Keywords: Methodology, Structural equation modelling, Measurement, Measurement invariance, Partial least squares, MICOM, Multigroup, Variance-based SEM, Composite models, Permutation test, Path modelling

Suggested Citation

Henseler, Jörg and Ringle, Christian M. and Sarstedt, Marko, Testing Measurement Invariance of Composites Using Partial Least Squares (September 19, 2014). International Marketing Review, Vol. 33, No. 3, pp. 405-431, 2016, Available at SSRN: https://ssrn.com/abstract=2985327

Jörg Henseler

Institute for Management Research, Radboud University Nijmegen ( email )

Thomas van Aquinostraat 3
P.O. Box 9108
Nijmegen, 6500HK
Netherlands
+31 24 3611854 (Phone)
+31 24 3611933 (Fax)

HOME PAGE: http://www.ru.nl/fm/henseler

Instituto Superior de Estatística e Gestão de Informação, Universidade Nova de Lisboa ( email )

Campus de Campolide
Lisbon, 1070-312
Portugal

HOME PAGE: http://www.henseler.com

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

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

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
700
PlumX Metrics