Research on Prediction Model of the Impact of New Telecom Services Tariff Based on the Customer Choice Behavior

Abstract:

This paper studies the impact of new telecom services tariff on the customers inside (customers who have ever chosen the original telecom service packages) and the revenue variation from the perspective of utility and customer choice behavior. On the basis of the quantification of telecom services tariff, a measurement model is built through multi-nominal logit (MNL) choice rule to predict the impact. Important indicators such as utility of service packages, transfer probability of the customers inside and expected change of revenue are obtained, which are useful for market orientation, revenue prediction and optimization management of the new telecom services tariff.

• Periodical: Advanced Materials Research (Volumes 765-767)
• Pages: 3249-3252
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.765-767.3249
• Online since: September 2013
• Authors: Xin Kuang Jiang, Xu Chen
• Keywords: Customer Choice Behavior, MNL, Telecom Services Tariff, Utility of Service Packages

References

[1] Shin-Yuan Hung, David C. Yen, Hsiu-Yu Wang. Applying data mining to telecom churn management, J. Expert Systems with Applications. 31(3) (2006) 515-524.

DOI: 10.1016/j.eswa.2005.09.080

[2] D Jia, R Wang, P Wang. Research on prediction method of the amount of customers in telecom services tariff preview, J. Telecommunications Science. 27(8) (2011) 25-32.

[3] Hyunchul Ahn, Jae Joon Ahn, Kyong Joo Oh, Dong Ha Kim. Facilitating cross-selling in a mobile telecom market to develop customer classification model based on hybrid data mining techniques, J. Expert Systems with Applications. 38(5) (2011).

DOI: 10.1016/j.eswa.2010.09.150

[4] Y Hou, S Hou. Analysis of the mobile telephone customers forecast model and error, J. Computer and Telecom. 5 (2011) 68-69.

[5] Y Liu, Z Chen. Research and application of data mining in package preview of telecom enterprise, J. Computer Engineering and Design. 29(15) (2008) 4032-4039.

[6] T Zhang, L Cai, X Luo, J Tang. Framework model of telecom suite design based on customer lifetime value, J. Systems Engineering. 30(2) (2012) 15-21.

[7] B Mu, Y Xiao, J Chen. Pricing and inventory decisions for substitutable products based on MNL customer choice model, J. Chinese Journal of Management Science. 18(3) (2010) 25-32.

[8] Xu, S., Akcay,Y. Joint dynamic pricing of multiple perishable products under consumer choice, Z. Working Paper, Smeal College of Business, The Pennsylvania State University, (2008).