Combined rough set theory and flow network graph to predict customer churn in credit card accounts

Expert Systems with Applications

Volumn 38, Issue 1, 2011, Pages 8-15

  Lin, Chiun Sin ^a   Tzeng, Gwo Hshiung ^a,b   Chin, Yang Chieh ^c  

^a KAINAN UNIVERSITY   (Taiwan)

^b NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

^c ASIA UNIVERSITY   (Taiwan)

Author keywords

Credit card; Customer churn; Flow network graph; Marketing strategy; Rough set theory

Indexed keywords

CREDIT CARDS; CUSTOMER CHURN; FLOW NETWORK; MARKETING STRATEGY; ROUGH SET;

CUSTOMER SATISFACTION; DECISION MAKING; DECISION THEORY; RISK ANALYSIS; RISK MANAGEMENT; SALES; STRATEGIC PLANNING;

ROUGH SET THEORY;

EID: 77956612708     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.05.039     Document Type: Article

References (32)

1. M.J. Beyon, B. Curry, and P. Morgan Knowledge discovery in marketing - An approach through rough set theory European Journal of Marketing 35 1 2001 915 933
2. J. Burez, and D. Vand den Poel Separating financial from commercial customer churn: A modeling step towards resolving the conflict between the sales and credit department Expert Systems with Applications 35 1 2008 497 514
3. D.A. Chiang, Y.F. Wang, S.L. Lee, and C.J. Lin Goal-oriented sequential pattern for network banking churn analysis Expert Systems with Applications 25 3 2003 293 302
4. B.H. Chu, M.S. Tsai, and C.S. Ho Toward a hybrid data mining model for customer retention Knowledge-Based Systems 20 1 2007 703 718
5. P.A. Estevez, C.M. Held, and C.A. Perez Subscription fraud prevention in telecommunications using fuzzy rules and neural networks Expert Systems with Applications 31 1 2006 337 344
6. L.R. Ford, and D.R. Fulkerson Flows in networks 1962 Princeton University Press Princeton, New Jersey
7. C. Goh, and R. Law Incorporating the rough sets theory into travel demand analysis Tourism Management 24 5 2003 511 517
8. J.L. Heskett, T.O. Jones, G.W. Loveman, W.E. Sasser Jr., and L.A. Schlesinger Putting the service-profit chain to work Harvard Business Review 72 2 1994 164 175
9. H. Hwang, T. Jung, and E. Suh An LTV model and customer segmentation based on customer value: A case study on the wireless telecommunication industry Expert Systems with Applications 26 1 2004 181 188
10. N. Japkowicz, and S. Stephen The class imbalance problem: A systematic study Intelligent Data Analysis 6 1 2002 429 449
11. B. Karakostas, D. Kardaras, and E. Papathanassiou The state of CRM adoption by the financial services in the UK: An empirical investigation Information & Management 42 1 2005 853 863
12. S. Kim, K.S. Shin, and K. Park An application of support vector machines for customer churn analysis: Credit card case Lecture Notes in Computer Science 3611 1 2005 636 647
13. J. Komorowski, and J. Zytkow Principles of data mining and knowledge discovery 1997 Springer-Verlag New York
14. D.A. Kumar, and V. Ravi Predicting credit card customer churn in banks using data mining International Journal of Data Analysis Techniques and Strategies 1 1 2008 4 28
15. K.C. Lee, N.H. Chung, and J.K. Kim A fuzzy cognitive map approach to integrating explicit knowledge and tacit knowledge: Emphasis on the churn analysis of credit card holders Information Systems Review 11 4 2001 113 133
16. K.C. Lee, N.H. Chung, and K.S. Shin An artificial intelligence-based data mining approach to extracting strategies for reducing the churning rate in credit card industry Journal of Intelligent Information Systems 8 2 2002 15 35
17. P. Lingras, M. Hogo, M. Snorek, and C. West Temporal analysis of clusters of supermarket customers: Conventional versus interval set approach Information Sciences 172 1 2005 215 240
18. L. Modisette Milking wireless churn for profit, telecommunications Dedham 33 2 1999 73 74
19. Ou Yang, Y. P., Shieh, H. M., Tzeng, G. H., Yen, L., & Chan, C. C. (2008). Business aviation decision-making using rough sets. In C.-C. Chan et al. (Eds.), RSCTC 2008, LNAI 5306 (pp. 329-338).
20. Z. Pawlak Rough set International Journal of Computer and Information Sciences 11 1 1982 341 356
21. Z. Pawlak Rough classification International Journal of Man-Machine Studies 20 5 1984 469 483
22. Z. Pawlak Rough sets, decision algorithms and Bayes' theory European Journal of Operational Research 136 1 2002 181 189
23. Z. Pawlak Decision rules and flow networks European Journal of Operation research 154 1 2004 184 190
24. Z. Pawlak Flow graphs and intelligent data analysis Fundamenta Informaticae 64 1 2005 369 377
25. Z. Pawlak, and A. Skowron Rudiments of rough sets Information Science 117 1 2007 3 27
26. F.F. Reichheld, and W.E. Sasser Jr. Zero defections: Quality comes to service Harvard Business Review 68 5 1990 105 111
27. J.J. Shyng, H.M. Shieh, G.H. Tzeng, and S.H. Hsieh Using FSBT technique with rough set theory for personal investment portfolio analysis European Journal of Operational Research 201 2 2009 601 607
28. J.J. Shyng, F.K. Wang, G.W. Tzeng, and K.S. Wu Rough set theory in analyzing the attributes of combination values for the insurance market Expert Systems with Applications 32 1 2007 56 64
29. T.L. Tseng, and C.C. Huang Rough set-based approach to feature selection in customer relationship management The International Journal of Management Science 35 1 2007 365 383
30. D. Van den Poel, and B. Lariviere Customer attrition analysis for financial services using proportional hazard models European Journal of Operational Research 157 1 2004 196 217
31. B. Walczak, and D.L. Massart Rough set theory Chemometrics and Intelligent Laboratory Systems 47 1 1999 1 16
32. C.P. Wei, and I.T. Chiu Turning telecommunications call details to churn prediction: A data mining approach Expert Systems with Applications 23 1 2002 103 112