Use of Logistics Regression Model in Credit Evaluation for Mobile Subscribers
As mobile communication market appears to be saturated, the customer relationship management has become a key element for revenue stabilization for mobile communication network operators. In order to reduce bad debt, operators often set credit limits for subscribers, but for those customers who are not defaulting intentionally, the incorrect credit limit will result to decreasing customer satisfaction and losing revenue directly. In this paper, logistics regression model is applied to resolve the problem. At first we select effective possible explanatory variables from those possible variables based on the information about customer behavior through chisquare test and contingency test, and then establish the credit evaluation model for mobile subscribers include 6 variables, at last we verify the efficiency and stability of the model by comparison test. With the help of this model deployed in IT system, operators can not only assign credit ratings and set credit limits for subscribers automatically, but also enhance customer satisfaction and improve profit margins.
Credit evaluation Logistics regression model Mobile communication Statistical analysis
Jian SUN Wan-hua QIU Xiao-jing JIA
School of Economic & Management,Beihang University,Beijing,P.R.China,100191 Central University of Finance and Economics,Beijing,P.R.China,100081
国际会议
The 2nd International Conference on Vale Engineering and Vale Management(2009)(2009年北京价值工程与价值管理国际会议)
北京
英文
148-152
2009-10-16（万方平台首次上网日期，不代表论文的发表时间）