Multicriterion Clusterwise Regression for Joint Segmentation Settings: An Application to Customer Value
Department
Marketing and Professional Sales
Document Type
Article
Publication Date
5-2003
Abstract
The authors present a multicriterion clusterwise linear regression model that can be applied to a joint segmentation setting. The model enables the consideration of segment homogeneity, as well as multiple dependent variables (segmentation bases), in a weighted objective function. The authors propose a heuristic solution strategy based on simulated annealing and examine trade-offs in the recovery of multiple true cluster structures for several synthetic data sets. They also propose an application of the model to a joint segmentation problem in the telecommunications industry, which addresses important issues pertaining to the selection of the objective function weights and the number of clusters.
Journal Title
Journal of Marketing Research
Journal ISSN
0022-2437
Volume
40
First Page
225
Last Page
234
Digital Object Identifier (DOI)
10.1509/jmkr.40.2.225.19227