A Customer Identification Method based on Genetic Algorithm and Customer Value Model: Theoretical Model and Empirical Application
Customer value (CV) identification is the basis for customer relationship retention strategic decision-making, and both variables and criteria for value identification need to reflect strategic intentions of enterprise customer resources. In this paper, we analyzed the limitations of one of the widely-used methods, K-means cluster method. Then, we proposed a modified method for customer value identification, and this method combined the technique of selecting the optimal K-value based on genetic algorithm with the technology of setting weights for customer value variables. This paper also systematically described the key methodologies and implementation procedures for design of evaluation system, index weight setup, value measurement and evaluation, and genetic cluster analysis. Furthermore, we used a data set related to customer relationship retention collected from a real-life enterprise to demonstrate the application of the proposed method. Finally, we compared the solutions of genetic cluster algorithm with K-means.
customer identification value evaluation system genetic algorithm cluster analysis
Wan Yinghong Cao Xiaopeng Jiang Liquan
School of management, Xian Jiaotong University,Experiment Center for Management Teaching & Learning School of management Xian Jiaotong University Xian, China
国际会议
成都
英文
687-693
2010-07-09（万方平台首次上网日期，不代表论文的发表时间）