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Capturing Customer Heterogeneity Using A Finite Mixture Pls Approach

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  • Carsten Hahn
  • Michael D. Johnson
  • Andreas Herrmann
  • Frank Huber
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    Abstract

    An approach for capturing unobserved customer heterogeneity in structural equation modeling is proposed based on partial least squares. The method uses a modified finite-mixture distribution approach. An empirical analysis using quality, customer satisfaction and loyalty data for convenience stores illustrates the advantages of the new method vis-à-vis a traditional market segmentation scheme based on well known grouping variables. The results confirm the assumption of heterogeneity in the individuals’ perception of the antecedents and consequences of satisfaction and their relationships. The results also illustrate how the finite-mixture approach complements and provides insights over and above a traditional segmentation scheme.

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    Bibliographic Info

    Article provided by LMU Munich School of Management in its journal Schmalenbach Business Review.

    Volume (Year): 54 (2002)
    Issue (Month): 3 (July)
    Pages: 243-269

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    Handle: RePEc:sbr:abstra:v:54:y:2002:i:3:p:243-269

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    Cited by:
    1. Esposito Vinzi, Vincenzo & Ringle, Christian M. & Squillacciotti, Silvia & Trinchera, Laura, 2007. "Capturing and Treating Unobserved Heterogeneity by Response Based Segmentation in PLS Path Modeling. A Comparison of Alternative Methods by Computational Experiments," ESSEC Working Papers DR 07019, ESSEC Research Center, ESSEC Business School.
    2. Ringle, Christian M. & Sarstedt, Marko & Schlittgen, Rainer & Taylor, Charles R., 2013. "PLS path modeling and evolutionary segmentation," Journal of Business Research, Elsevier, vol. 66(9), pages 1318-1324.
    3. Sarstedt, Marko & Wilczynski, Petra & Melewar, T.C., 2013. "Measuring reputation in global markets—A comparison of reputation measures’ convergent and criterion validities," Journal of World Business, Elsevier, vol. 48(3), pages 329-339.
    4. Luca Zanin, 2013. "Detecting Unobserved Heterogeneity in the Relationship Between Subjective Well-Being and Satisfaction in Various Domains of Life Using the REBUS-PLS Path Modelling Approach: A Case Study," Social Indicators Research, Springer, vol. 110(1), pages 281-304, January.
    5. Eurico, Sofia & Valle, Patrícia & Silva, João Albino & Marques, Catarina, 2012. "Segmenting Graduate Consumers of Higher Education in Tourism: An Extension of the ECSI Model," Spatial and Organizational Dynamics Discussion Papers 2012-7, CIEO-Research Centre for Spatial and Organizational Dynamics, University of Algarve.
    6. Ringle, Christian M., 2006. "Segmentation for path models and unobserved heterogeneity: The finite mixture partial least squares approach," MPRA Paper 10734, University Library of Munich, Germany.
    7. Sarstedt, Marko & Ringle, Christian M. & Smith, Donna & Reams, Russell & Hair, Joseph F., 2014. "Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers," Journal of Family Business Strategy, Elsevier, vol. 5(1), pages 105-115.

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