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Customer Segmentation Model for Internet Banking using Self-organizing Neural Networks and Hierarchical Gustering Method  

Shin, Taek-Soo (연세대학교 원주캠퍼스 경영학부)
Hong, Tae-Ho (부산대학교 경영학부)
Publication Information
Asia pacific journal of information systems / v.16, no.3, 2006 , pp. 49-65 More about this Journal
Abstract
This study proposes a model for customer segmentation using the psychological characteristics of Internet banking customers. The model was developed through two phased clustering method, called SONN-HC by integrating self-organizing neural networks (SONN) and hierarchical clustering (HC) method. We applied the SONN-HC method to internet banking customer segmentation and performed an empirical analysis with 845 cases. The results of our empirical analysis show the psychological characteristics of Internet banking customers have significant differences among four clusters of the customers created by SONN-HC. From these results, we found that the psychological characteristics of Internet banking customers had an important role of planning a strategy for customer segmentation in a financial institution.
Keywords
Customer Segmentation; Internet Banking; Self-organizing Neural Networks; Hierarchical Clustering;
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Times Cited By KSCI : 2  (Citation Analysis)
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