Hruschka, Harald and Natter, M. (1999) Comparing performance of feedforward neural nets and K-means for cluster-based market segmentation. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 114 (2). pp. 346-353. ISSN 0377-2217,
Full text not available from this repository.Abstract
We compare the performance of a specifically designed feedforward artificial neural network with one layer of hidden units to the K-means clustering technique in solving the problem of cluster-based market segmentation. The data set analyzed consists of usages of brands (product category: household cleaners) in different usage situations. The proposed feedforward neural network model results in a two Segment solution that is confirmed by appropriate tests. On the other hand, the K-means algorithm Fails in discovering any somewhat stronger cluster structure. Classification of respondents on the basis of external criteria is better for the neural network solution. We also demonstrate the managerial interpretability of the network results. (C) 1999 Elsevier Science B.V. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | NETWORKS; neural networks; marketing; K-means; cluster analysis; market segmentation |
| Subjects: | 600 Technology > 650 Management & auxiliary services |
| Divisions: | Business, Economics and Information Systems > Institut für Betriebswirtschaftslehre > Lehrstuhl für Marketing (Prof. Dr. Harald Hruschka) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 07 Nov 2022 10:00 |
| Last Modified: | 07 Nov 2022 10:00 |
| URI: | https://pred.uni-regensburg.de/id/eprint/48319 |
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