Customer lifetime value prediction by a Markov chain based data mining model: application to an auto repair and maintenance company in Taiwan | |
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學年 | 100 |
學期 | 2 |
出版(發表)日期 | 2012-06-01 |
作品名稱 | Customer lifetime value prediction by a Markov chain based data mining model: application to an auto repair and maintenance company in Taiwan |
作品名稱(其他語言) | |
著者 | Cheng, C. J.; Chiu, S. W.; Cheng, C.B; Wu, J. Y. |
單位 | 淡江大學資訊管理學系 |
出版者 | Tehran: Sharif University of Technology |
著錄名稱、卷期、頁數 | Scientia Iranica 19(3), pp.849-855 |
摘要 | The present study attempts to establish a framework for computing customer lifetime values for a company in the auto repair and maintenance industry. The customer lifetime value defined in this study consists of the current and future values of a customer, which involve an estimation of lifetime length, future purchasing behavior and the profit associated with each behavior of the customer. The proposed framework contains three groups of techniques to obtain these estimates from historical customer transactions. The first group includes a logistic regression model and a decision tree model to estimate the churn probability of a customer and to, further, predict the lifetime length of the customer. The second group comprises a regression analysis to identify the critical variables that affect a customer’s purchasing behavior, and a Markov chain to model the transition probabilities of behavior change. Finally, the third group contains two neural networks to predict the profits contributed by a customer under various purchasing behaviors. The proposed framework is demonstrated with the historical customer transactions of an auto repair and maintenance company in Taiwan. |
關鍵字 | Customer lifetime value;Auto repair and maintenance industry;Data mining;Markov chain;Decision tree;Neural networks |
語言 | en |
ISSN | 1026-3098 |
期刊性質 | 國外 |
收錄於 | SCI |
產學合作 | |
通訊作者 | |
審稿制度 | 否 |
國別 | IRN |
公開徵稿 | |
出版型式 | ,紙本 |
相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/73531 ) |
SDGS | 產業創新與基礎設施 |