A comparative analysis of clustering methodology and application for market segmentation: K-means, SOM and a two-level SOM

Authors:
Sang-Chul Lee;Ja-Chul Gu;Yung-Ho Suh
Affiliations:
Department of Management Information Systems, Korea Christian University, Kangseo-Ku, Seoul, South Korea;School of Business Administration, Kyung Hee University, Dongdaemoon-Gu, Seoul, South Korea;School of Business Administration, Kyung Hee University, Dongdaemoon-Gu, Seoul, South Korea
Venue:
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Year:
2006

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Abstract

The purpose of our research is to identify the critical variables, to evaluate the performance of variable selection, to evaluate the performance of a two-level SOM and to implement this methodology into Asian online game market segmentation. Conclusively, our results suggest that weight-based variable selection is more useful for market segmentation than full-based and SEM-based variable selection. Additionally, a two-level SOM is more accurate in classification than K-means and SOM. The critical segmentation variables and the characteristics of target customers were different among countries. Therefore, online game companies should develop diverse marketing strategies based on characteristics of their target customers using research framework we propose.