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A Unified Market Segmentation Method for Generating Pareto Optimal Solutions Sets

6 Pages Posted: 22 Feb 2006  

Ying Liu

University of Arizona - Eller College of Management

Sudha Ram

University of Arizona - Department of Management Information Systems

Robert Lusch

University of Arizona - Department of Marketing

Abstract

Market segmentation is an important issue in today's intensely ompetitive environment. While many methods have been proposed for market segmentation, they can be classified into two categories: descriptive and predictive. Descriptive methods are optimized for segment identifiability while predictive methods are optimized for segment responsiveness. Most existing segmentation methods cannot effectively address both identifiability and responsiveness goals of market segmentation due to their focus on only one aspect of the multiobjective problem. This paper proposes a new market segmentation method that unifies descriptive and predictive methods by simultaneously optimizing multiple objectives. The unified market segmentation method overcomes the limitations of existing segmentation methods and generates Pareto optimal solution sets. It also suggests the optimal number-of-segments and the best solution based on the characteristics of the Pareto front. As a result, the method presents a unified view of possible segmentation solutions and automatically selects the best solution(s) by balancing the tradeoffs. We demonstrate the benefits of our method by empirically evaluating it using data from a cell phone service provider.

Keywords: market segmentation, Pareto optimal solutions, multiple objective optimization

Suggested Citation

Liu, Ying and Ram, Sudha and Lusch, Robert, A Unified Market Segmentation Method for Generating Pareto Optimal Solutions Sets. 15th Annual Workshop on Information Technolgies & Systems (WITS) Paper. Available at SSRN: https://ssrn.com/abstract=882884 or http://dx.doi.org/10.2139/ssrn.882884

Ying Liu (Contact Author)

University of Arizona - Eller College of Management ( email )

McClelland Hall
P.O. Box 210108
Tucson, AZ 85721-0108
United States

Sudha Ram

University of Arizona - Department of Management Information Systems ( email )

McClelland Hall
Tucson, AZ 85721-0108
United States
520-621-4113 (Phone)

Robert Lusch

University of Arizona - Department of Marketing ( email )

McClelland Hall
P.O. Box 210108
Tucson, AZ 85721-0108
United States

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