A Comparative Analysis of Clustering Methodology and Application for Market Segmentation: K-Means, SOM and a Two-Level SOM

  • Sang-Chul Lee
  • Ja-Chul Gu
  • Yung-Ho Suh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4203)


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.


Structural Equation Model Variable Selection Customer Loyalty Virtual Community Market Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sang-Chul Lee
    • 1
  • Ja-Chul Gu
    • 2
  • Yung-Ho Suh
    • 2
  1. 1.Department of Management Information SystemsKorea Christian UniversityKangseo-Ku, SeoulSouth Korea
  2. 2.School of Business AdministrationKyung Hee UniversityDongdaemoon-Gu, SeoulSouth Korea

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