A novel customer scoring model to encourage the use of mobile value added services

被引:8
作者
Ahn, Hyunchul [2 ]
Ahn, Jae Joo [1 ]
Byun, Hyun Woo [1 ]
Oh, Kyong Joo [1 ]
机构
[1] Yonsei Univ, Dept Informat & Ind Engn, Seoul 120749, South Korea
[2] Kookmin Univ, Sch Management Informat Syst, Seoul 136702, South Korea
关键词
Customer scoring model; Value-added services; Classification; Data mining; MARKET;
D O I
10.1016/j.eswa.2011.03.054
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Following deregulation and liberalization of the mobile telecommunications sector, the mobile telecommunication market is becoming increasingly saturated. Mobile operators are confronted with a sluggish user growth rate and a fall in the average revenue per user (ARPU). Mobile value-added services (VAS) are expected to form mobile operators' strategy to compensate dwindling revenues. However, not only is it difficult to analyze which types of customers are willing to use VAS, but it is equally difficult to understand the diversified customer preferences on VAS. This study proposes an integrated scoring model that includes multiple classification models. It analyzes and distinguishes the potential prospects of VAS. We applied our model to the case of a mobile operator in Korea to validate its usefulness. We explored the prospects for melody bells for that company. We found that our proposed scoring model produces better results than other comparative models. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:11693 / 11700
页数:8
相关论文
共 28 条
[1]  
Anckar B., 2002, J INFORM TECHNOLOGY, V4, P43
[2]  
ANITA S, 2007, INT J MOB COMMUN, V5, P68
[3]  
Berry MichaelJ., 1997, DATA MINING TECHNIQU
[4]  
Berson A., 1999, Building data mining applications for CRM
[5]   Competition in Korean mobile telecommunications market: business strategy and regulatory environment [J].
Choi, SK ;
Lee, MH ;
Chung, GH .
TELECOMMUNICATIONS POLICY, 2001, 25 (1-2) :125-138
[6]  
Coursaris C, 2003, CAN J ADM SCI, V20, P54
[7]  
Cox DR., 1989, Analysis of Binary Data, V2nd ed.
[8]  
Davis F., 1996, MARK INTELL PLAN, V14, P26, DOI [DOI 10.1108/02634509610110778, 10.1108/02634509610110778]
[9]   The use of data mining and neural networks for forecasting stock market returns [J].
Enke, D ;
Thawornwong, S .
EXPERT SYSTEMS WITH APPLICATIONS, 2005, 29 (04) :927-940
[10]  
Flagg J.C., 1991, Review of Financial Economics, V1, P67