Name
Abstract | ||
|---|---|---|
To compete successfully in today's global online game markets, a cross-national analysis for market segmentation is becoming a more important issue, by which companies are able to understand their domestic and foreign loyal customers and concentrate their limited resources into the target customers. However, previous research methodologies for market segmentation were difficult to be conducted on a cross-national analysis because they were performed within a nation. Additionally, the traditional clustering methodologies have not provided a unique clustering nor determined the precise number of clusters. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1016/j.eswa.2004.06.001 | Expert Systems with Applications |
Keywords | Field | DocType |
Self-organizational map,Cross-national analysis,Online game,Market segmentation | Data mining,Market segmentation,Computer science,Confirmatory factor analysis,Game industry,Artificial intelligence,Cluster analysis,Machine learning | Journal |
Volume | Issue | ISSN |
27 | 4 | 0957-4174 |
Citations | PageRank | References |
25 | 1.19 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sang-Chul Lee | 1 | 287 | 24.04 |
| Yung-Ho Suh | 2 | 164 | 7.41 |
| Jae Kyeong Kim | 3 | 1011 | 52.32 |
| Kyoung Jun Lee | 4 | 156 | 20.53 |