Abstract
A clusterwise regression method is proposed in the case of binary variables. Its objective is to improve the marketing operationality of the procedure by optimizing clusters’ predictivity under constraints of homogeneity and differentiation. The algorithm is a hybrid of genetic algorithm (GA) and of learning vector quantization (LVQ). GA is used for optimizing predictivity under constraints of cluster homogeneity. Specific LVQ rules are implemented for speeding up the process. In an empirical test, based on actual marketing data, the hybrid LVQ/GA compared satisfactorily with Kohonen’s original LVQ (OLVQ).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Aurifeille JM, Bergmann J. Segmentation de marchés: une méthode fondée sur l’optimisation contrainte d’un réseau de neurones. Proceedings of the 27th Journées Internationales de Statistique. A.S.U. S.S.F, Paris, 1995; 42–47.
Aurifeille J.M, Valette-Florence P. Determination of the Dominant Chains. International Journal of Research in Marketing 1995; 12: 267–278.
DeSarbo WL, Cron WL. A Maximum Likelihood Methodology for Clusterwise Linear Regression. Journal of Classification 1988; 5: 249–282.
DeSarbo W, Oliver RL, Rangaswamy A. A Simulated Annealing Methodology for Clusterwise Linear Regression. Psychometrika 1989; 54, 4: 707–736.
Grossberg S. Studies of the Mind and Brain. Drodrecht, Holland: Reidel Press, 1982.
Gutman J. A Means-End Chain Model Based on Consumer Categorization Processes. Journal of Marketing, 1982; 46: 60–72.
Holland JH. Adaptation in natural and artificial systems. Ann Harbor: The University of Michigan Press, 1975.
Howard JA. Consumer Behavior: Application of Theory. New York: McGraw-Hill, 1977. Kohonen T. Self-Organization and Associative Memory. Berlin: Springer, 1987.
Olson JC, Reynolds TJ. “Understanding Consumers’ Cognitive Structures: Implications for Advertising Strategy.” in Advertising and Consumer Psychology, Lexington; Lexington Books, 1983; 77–90.
Reynolds TJ, Gutman J. Laddering Theory, Method, Analysis and Interpretation. Journal of Advertising Research, 1988; 28: 11–31.
Wedel M, Steenkamp J-B. A Fuzzy Clusterwise Regression Approach to Benefit Segmentation. International Journal of Research in Marketing, 1989; 6: 241–258.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Aurifeille, JM. (1998). A Bio-Mimetic Clusterwise Regression Algorithm for Consumer Segmentation. In: Aurifeille, JM., Deissenberg, C. (eds) Bio-Mimetic Approaches in Management Science. Advances in Computational Management Science, vol 1. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2821-7_11
Download citation
DOI: https://doi.org/10.1007/978-1-4757-2821-7_11
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-4791-8
Online ISBN: 978-1-4757-2821-7
eBook Packages: Springer Book Archive