Abstract
Market segmentation is inherently a multicriterion problem even though it has often been modeled as a single-criterion problem in the traditional marketing literature and in practice. This paper discusses the multicriterion nature of market segmentation and develops a new mathematical model that addresses this issue. A new method for market segmentation based on multiobjective evolutionary algorithms, called MMSEA, is developed. It complements existing segmentation methods by optimizing multiple objectives simultaneously, searching for globally optimal solutions, and approximating a set of Pareto-optimal solutions. We have applied and evaluated this method in two empirical studies for two firms from distinct industries: descriptive segmentation of the cell phone service market from a dual-value creation perspective and predictive segmentation of retail customers based on profit and customer sociodemographic attributes. The results provide decision makers with compelling alternatives and enhanced flexibility currently missing in existing market segmentation methods.
Original language | English (US) |
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Pages (from-to) | 880-894 |
Number of pages | 15 |
Journal | Marketing Science |
Volume | 29 |
Issue number | 5 |
DOIs | |
State | Published - Sep 2010 |
Keywords
- Descriptive market segmentation
- Multicriterion market segmentation
- Multiobjective clustering
- Multiobjective evolutionary algorithms
- Multiobjective optimization
- Pareto-optimal solution set
- Predictive market segmentation
ASJC Scopus subject areas
- Business and International Management
- Marketing