{"title":"基于生存分析的顾客忠诚研究","authors":"Linghui Jin, Lisha Guo","doi":"10.1109/DCABES.2017.45","DOIUrl":null,"url":null,"abstract":"In this paper, we study the customer loyalty based on survival analysis. We regard the time of using product as the survival time, and utilize the AFT model to analysis the influencing factors of the customer loyalty. The results of simulation show that our method is more effective than commonly regression method. A real example is also provided as an illustration.","PeriodicalId":446641,"journal":{"name":"2017 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Customer Loyalty Research Based on Survival Analysis\",\"authors\":\"Linghui Jin, Lisha Guo\",\"doi\":\"10.1109/DCABES.2017.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we study the customer loyalty based on survival analysis. We regard the time of using product as the survival time, and utilize the AFT model to analysis the influencing factors of the customer loyalty. The results of simulation show that our method is more effective than commonly regression method. A real example is also provided as an illustration.\",\"PeriodicalId\":446641,\"journal\":{\"name\":\"2017 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCABES.2017.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCABES.2017.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Customer Loyalty Research Based on Survival Analysis
In this paper, we study the customer loyalty based on survival analysis. We regard the time of using product as the survival time, and utilize the AFT model to analysis the influencing factors of the customer loyalty. The results of simulation show that our method is more effective than commonly regression method. A real example is also provided as an illustration.