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Customer segmentation using unobserved heterogeneity in the perceived-value–loyalty–intentions link


  • Floh, Arne
  • Zauner, Alexander
  • Koller, Monika
  • Rusch, Thomas


Multiple facets of perceived value perceptions drive loyalty intentions. However, this value–loyalty link is not uniform for all customers. In fact, the present study identifies three different segments that are internally consistent and stable across different service industries, using two data sets: the wireless telecommunication industry (sample size 1122) and the financial services industry (sample size 982). Comparing the results of a single-class solution with finite mixture results confirms the existence of unobserved customer segments. The three established segments are “rationalists”, “functionalists” and “value maximizers”. These results point the way for value-based segmentation in loyalty initiatives and reflect the importance of a multidimensional conceptualization of perceived value, comprising cognitive and affective components. The present results substantiate the fact that assuming a homogeneous value–loyalty link provides a misleading view of the market. The paper derives implications for marketing research and practice in terms of segmentation, positioning, loyalty programs and strategic alliances.

Suggested Citation

  • Floh, Arne & Zauner, Alexander & Koller, Monika & Rusch, Thomas, 2014. "Customer segmentation using unobserved heterogeneity in the perceived-value–loyalty–intentions link," Journal of Business Research, Elsevier, vol. 67(5), pages 974-982.
  • Handle: RePEc:eee:jbrese:v:67:y:2014:i:5:p:974-982
    DOI: 10.1016/j.jbusres.2013.08.003

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    References listed on IDEAS

    1. Kamakura, Wagner A & Wedel, Michel, 2004. "An Empirical Bayes Procedure for Improving Individual-Level Estimates and Predictions from Finite Mixtures of Multinomial Logit Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 121-125, January.
    2. Leisch, Friedrich, 2004. "FlexMix: A General Framework for Finite Mixture Models and Latent Class Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i08).
    3. Sheth, Jagdish N. & Newman, Bruce I. & Gross, Barbara L., 1991. "Why we buy what we buy: A theory of consumption values," Journal of Business Research, Elsevier, vol. 22(2), pages 159-170, March.
    4. Ruth N. Bolton, 1998. "A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction," Marketing Science, INFORMS, vol. 17(1), pages 45-65.
    5. Babin, Barry J. & Babin, Laurie, 2001. "Seeking something different? A model of schema typicality, consumer affect, purchase intentions and perceived shopping value," Journal of Business Research, Elsevier, vol. 54(2), pages 89-96, November.
    6. David Martín Ruiz & Carmen Barroso Castro & Enrique Martín Armario, 2007. "Explaining Market Heterogeneity in Terms of Value Perceptions," The Service Industries Journal, Taylor & Francis Journals, vol. 27(8), pages 1087-1110, December.
    7. Cortiñas, Mónica & Chocarro, Raquel & Villanueva, María Luisa, 2010. "Understanding multi-channel banking customers," Journal of Business Research, Elsevier, vol. 63(11), pages 1215-1221, November.
    8. Ko, Eunju & Taylor, Charles R. & Sung, Heewon & Lee, Jooyeon & Wagner, Udo & Navarro, David Martin-Consuegra & Wang, Fanghua, 2012. "Global marketing segmentation usefulness in the sportswear industry," Journal of Business Research, Elsevier, vol. 65(11), pages 1565-1575.
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    Cited by:

    1. Al-Qeisi, Kholoud & Dennis, Charles & Alamanos, Eleftherios & Jayawardhena, Chanaka, 2014. "Website design quality and usage behavior: Unified Theory of Acceptance and Use of Technology," Journal of Business Research, Elsevier, vol. 67(11), pages 2282-2290.
    2. repec:eee:joreco:v:22:y:2015:i:c:p:107-116 is not listed on IDEAS
    3. Hiep-Hung Pham & Sue Ling Lai & Quan-Hoang Vuong, 2017. "The impacts of value, disconfirmation and satisfaction on loyalty: Evidence from international higher education setting," Working Papers CEB 17-035, ULB -- Universite Libre de Bruxelles.
    4. Dolnicar, Sara & Grün, Bettina & Leisch, Friedrich, 2016. "Increasing sample size compensates for data problems in segmentation studies," Journal of Business Research, Elsevier, vol. 69(2), pages 992-999.
    5. repec:eee:joreco:v:36:y:2017:i:c:p:124-136 is not listed on IDEAS
    6. repec:ksb:journl:v:10:y:2017:p:21-56 is not listed on IDEAS
    7. repec:gam:jsusta:v:9:y:2017:i:10:p:1918-:d:116074 is not listed on IDEAS


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