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Multicriterion clusterwise regression for joint segmentation settings: an application to customer value
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 an SA heuristic solution strategy based on simulated annealing and examine trade-offs in the recovery of multiple true cluster structures for 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. Although the SA heuristic provides a viable approach for multicriterion clustering, additional research regarding efficient implementation of multicriterion data analysis methods is clearly in order. Important research directions include the development and testing of procedures for establishing starting solutions and conducting efficient searches of the massive solutions spaces for problems with three or more objective criteria..Printed
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| PSB lt.dasar - Pascasarjana | 1 |
| Penerbit | American Marketing Association., |
|---|---|
| Edisi | - |
| Subjek | Mathematical models Market segmentation Regression analysis Models Telecommunications industry heuristic studies |
| ISBN/ISSN | 222437 |
| Klasifikasi | - |
| Deskripsi Fisik | - |
| Info Detail Spesifik | - |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas | Tidak Ada Data |