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

  • Unobserved Heterogeneity
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Schmalenbach Business Review Aims and scope

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.

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Authors and Affiliations

  1. Institute for Market-Based Management, Ludwig-Maximilians-University Munich, Kaulbachstr. 45 / I, 80539, Munich, USA

    Marko Sarstedt & Manfred Schwaiger

  2. Institute for Marketing and Brand Management, University of Cologne, Albertus-Magnus-Platz 1, 50923, Cologne, Germany

    Jan-Michael Becker

  3. Institute for Human Resource Management and Organizations, TUHH - Hamburg University of Technology, Schwarzenbergstraße 95 (D), D-21073, Hamburg, Germany

    Christian M. Ringle

  4. Centre for Management and Organisation Studies (CMOS), University of Technology Sydney (UTS), City Campus, Building 5, 1-59 Quay Street, Haymarket, NSW, 2001, Australia

    Christian M. Ringle

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  1. Marko Sarstedt
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  2. Jan-Michael Becker
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  4. Manfred Schwaiger
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Correspondence to Marko Sarstedt.

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The authors would like to thank the anonymous reviewers and the area editor for their helpful comments on prior versions of the manuscript.

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Sarstedt, M., Becker, JM., Ringle, C.M. et al. Uncovering and Treating Unobserved Heterogeneity with FIMIX-PLS: Which Model Selection Criterion Provides an Appropriate Number of Segments?. Schmalenbach Bus Rev 63, 34–62 (2011). https://doi.org/10.1007/BF03396886

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