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Uncovering and Treating Unobserved Heterogeneity with Fimix-Pls: Which Model Selection Criterion Provides an Appropriate Number of Segments?

Schmalenbach Business Review, Vol. 63, pp. 34-62, January 2011

29 Pages Posted: 5 Jul 2011  

Marko Sarstedt

University of Magdeburg; University of Magdeburg; University of Newcastle (Australia)

Jan-Michael Becker

University of Cologne - Department of Marketing and Brand Management

Christian M. Ringle

Hamburg University of Technology (TUHH); University of Newcastle (Australia)

Manfred Schwaiger

Ludwig Maximilian University of Munich - Faculty of Business Administration (Munich School of Management)

Date Written: January 1, 2011

Abstract

Since its first introduction in the Schmalenbach Business Review, Hahn et al.’s (2002) finite mixture partial least squares (FIMIX-PLS) approach to response-based segmentation in variance-based structural equation modeling has received much attention from the marketing and management disciplines. When applying FIMIX-PLS to uncover unobserved heterogeneity, the actual number of segments is usually unknown. As in any clustering procedure, retaining a suitable number of segments is crucial, since many managerial decisions are based on this result. In empirical research, applications of FIMIX-PLS rely on information and classification criteria to select an appropriate number of segments to retain from the data. However, the performance and robustness of these criteria in determining an adequate number of segments has not yet been investigated scientifically in the context of FIMIX-PLS. By conducting computational experiments, this study provides an evaluation of several model selection criteria’s performance and of different data characteristics’ influence on the robustness of the criteria. The results engender key recommendations and identify appropriate model selection criteria for FIMIX-PLS. The study’s findings enhance the applicability of FIMIX-PLS in both theory and practice.

Keywords: FIMIX-PLS, finite mixture modeling, model selection, partial least squares (PLS), segmentation, structural equation modeling

JEL Classification: C39, M31

Suggested Citation

Sarstedt, Marko and Becker, Jan-Michael and Ringle, Christian M. and Schwaiger, Manfred, Uncovering and Treating Unobserved Heterogeneity with Fimix-Pls: Which Model Selection Criterion Provides an Appropriate Number of Segments? (January 1, 2011). Schmalenbach Business Review, Vol. 63, pp. 34-62, January 2011. Available at SSRN: https://ssrn.com/abstract=1879141

Marko Sarstedt (Contact Author)

University of Magdeburg ( email )

Universitätspl. 2
PSF 4120
Magdeburg, D-39106
Germany

University of Magdeburg ( email )

Universitätspl. 2
PSF 4120
Magdeburg, D-39106
Germany

University of Newcastle (Australia) ( email )

University Drive
Callaghan, NSW 2308
Australia

Jan-Michael Becker

University of Cologne - Department of Marketing and Brand Management ( email )

Albertus-Magnus-Platz 1
Cologne, 50931
Germany

Christian M. Ringle

University of Newcastle (Australia) ( email )

University Drive
Callaghan, NSW 2308
Australia

Hamburg University of Technology (TUHH) ( email )

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

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

Manfred Schwaiger

Ludwig Maximilian University of Munich - Faculty of Business Administration (Munich School of Management) ( email )

Kaulbachstrasse 45
Munich, 80539
Germany

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