Java Code of thesis (Customer Knowledge Management of a bank by data mining techniques )




Increasing level of competition between the markets, made the managemers and organization analysts to seek solutions that bring a competitive advantage for organizations. According to literature, using customer knowledge to adopt strategies, for customer satisfaction, direct organizations toward this goal. On the other, expand taking advantage of update technologies in information and communication, in particular, in banks cause to staying large amounts of data that analyze and make decisions based on their with conventional methods of reporting and statistical methods, is not possible. Data mining is a powerful and update tool that is proposed for data analysis to extract customer knowledge in this thesis.

The purpose of this study that titled as “Knowledge management of the Mehr Eghtesad bank customers using data mining techniques”, is segmentation of the customers of the Mehr Eghtesad bank, aimed to discover the similar behavioral characteristics, for help the managers in banks to facilitate the adoption of appropriate strategies for each cluster and consequently preserve, strengthen and develop relationships with customers and ultimately profitability for the bank.  Raw data for this study were extracted from the database of Mehr Eghtesad bank.

Key words:

Customer Knowledge Management, Data Mining, Knowledge Discovery, Customers Clustering.

References :

[18] Bosjank,z. , “Credit users segmentation for improved customer relationship management in banking”, Applied Computational Intelligence and Informatics (SACI), IEEE , 2011, pp. 379 – 384.

[19] Nie, Guangli, et al. “Credit card churn forecasting by logistic regression and decision tree.” Expert Systems with Applications 38.12 (2011) : 15273-15285.

[20] Lin, Chiun-Sin, Gwo-Hshiung Tzeng, and Yang-Chieh Chin. “Combined rough set theory and flow network graph to predict customer churn in credit card accounts.” Expert Systems with Applications 38.1 (2011) : 8-15.

[21] Madhoushi, Mehrdad and et al., “Survey of Customer Knowledge Management Impact on Customer Relationship Management: (Iranian study)”, International Journal of Business and Social Science, Vol. 2, No. 20, November 2011.

[22] Lee, Byungtae and et al., “Empirical analysis of online auction fraud: Credit card phantom transactions”, Expert Systems with Applications, vol 37, pp. 2991–2999, 2010.

[23] Hosseini, Seyed Mohammad Seyed, Anahita Maleki, and Mohammad Reza Gholamian. “Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty.” Expert Systems with Applications 37.7 (2010): pp. 5259-5264.

[24] Chen, Fei-Long and et al., “Combination of feature selection approaches with SVM in credit scoring“, Expert Systems with Applications, vol 37, pp. 4902–4909, 2010.

[25] Ngai, Eric WT, Li Xiu, and D. C. K. Chau. “Application of data mining techniques in customer relationship management: A literature review and classification.” Expert Systems with Applications 36.2 (2009): 2592-2602.

[26] Nisbet, Robert, John Fletcher Elder, and Gary Miner. Handbook of statistical analysis and data mining applications. Academic Press, 2009.

[27] Rezvani, Zeinab, New Product Development Based on Customer Knowledge Management, Master Thesis, Luleå University of Technology,  pp.25-35, 2009.

[28] Xie, Yaya, et al. “Customer churn prediction using improved balanced random forests.” Expert Systems with Applications 36.3 (2009) : 5445-5449.

[29] Abdou, Hussein et al., “Neural nets versus conventional techniques in credit scoring in Egyptian banking”, Expert Systems with Applications, vol 35, pp. 1275–1292, 2008.

[30] Ranjan, Jayanthi, A Review of Data Mining Tools In Customer Relationship Management ,Journal of Knowledge Management Practice, Vol. 9, No. 1, March 2008.

[31] Han, Jiawei, and Micheline Kamber. Data mining: concepts and techniques. Morgan Kaufmann, 2006.

[32] Paquette, Scott. “Customer knowledge management.” Encyclopedia of Knowledge Management (2006): 90.

[33] Rollins, Minna, and Aino Halinen. “Customer knowledge management competence: towards a theoretical framework.” System Sciences, 2005. HICSS’05. Proceedings of the 38th Annual Hawaii International Conference on. IEEE, 2005.

[34] Feng, Tian-Xue, and Jin-Xin Tian. “Customer knowledge management and condition analysis of successful CKM implementation.” Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on. Vol. 4. IEEE, 2005.

]35[ Hsieh, Nan-Chen. “An integrated data mining and behavioral scoring model for analyzing bank customers.” Expert Systems with Applications 27.4 (2004): 623-633.

[36] Bose, Ranjit, and Vijayan Sugumaran. “Application of knowledge management technology in customer relationship management.” Knowledge and process management 10.1 (2003): 3-17.

[37] Gebert, Henning, et al. “Knowledge-enabled customer relationship management: integrating customer relationship management and knowledge management concepts [1].” Journal of knowledge management 7.5 (2003): 107-123.

 [38] Gibbert, Michael, Marius Leibold, and Gilbert Probst. “Five styles of customer knowledge management, and how smart companies use them to create value.” European Management Journal 20, no 5 , pp 459-469 ,2002.

[39] Bose, Ranjit. “Customer relationship management: key components for IT success.” industrial management & data systems 102.2 (2002): 89-97.

[40] Dyche, Jill. The CRM handbook: a business guide to customer relationship management. Addison-Wesley Professional, 2002.

[41] Garcia-Murillo, Martha, and Hala Annabi. “Customer knowledge management.” Journal of the Operational Research Society , pp. 875-884 ,2002.

[42] Rowley J. Eight Enhancing Questions for Customer Knowledge Management in e-Business. Journal of Knowledge Management 2002; 6(5): 500-511.

[43] Rowley, Jennifer E. “Reflections on customer knowledge management in e-business.” Qualitative Market Research: An International Journal 5.4 (2002): 268-280.

[44] Zack, Michael H. “Developing a knowledge strategy.” The strategic management of intellectual capital and organizational knowledge (2002): 76-255.

[45] Bhatt, Ganesh D. “Knowledge management in organizations: examining the interaction between technologies, techniques, and people.” Journal of knowledge management 5.1, pp. 68-75, 2001.

[46] Ling, Raymond, and David C. Yen. “Customer relationship management: An analysis framework and implementation strategies.” Journal of Computer Information Systems 41.3 (2001): 82-97.

[47] Davenport, Thomas H., Jeanne G. Harris, and Ajay K. Kohli. “How do they know their customers so well?.” MIT Sloan Management Review 42.2 (2001): 63-73.

[48] Davenport, Thomas H., and Laurence Prusak. Working knowledge: How organizations manage what they know. Harvard Business Press, 2000.

[49] Mårtensson, Maria. “A critical review of knowledge management as a management tool.” Journal of knowledge management 4, no 3 (2000): 204-216.

[50] Wirth, Rüdiger, and Jochen Hipp. “CRISP-DM: Towards a standard process model for data mining.” Proceedings of the 4th International Conference on the Practical Applications of Knowledge Discovery and Data Mining. 2000.

 [51] uit Beijerse, Roelof P. “Questions in knowledge management: defining and conceptualizing a phenomenon.” Journal of Knowledge Management 3.2 (1999): 94-110.

 [52] Chen, Ming-Syan, Jiawei Han, and Philip S. Yu. “Data mining: an overview from a database perspective.” Knowledge and data Engineering, IEEE Transactions on 8.6 (1996): 866-883.

 [53] Fayyad, Usama and et al., “From Data Mining to Knowledge Discovery in Databases”, AI Magazine, Vol. 17, Number 3, 1996.

 [54] Szulanski, Gabriel. “Exploring internal stickiness: Impediments to the transfer of best practice within the firm.” Strategic management journal 17 (1996): 27-43.

 [55] Nonaka, Ikujiro, and Hirotaka Takeuchi. The knowledge-creating company: How Japanese companies create the dynamics of innovation. Oxford University Press, USA, 1995.


There are no reviews yet.

Be the first to review “Java Code of thesis (Customer Knowledge Management of a bank by data mining techniques )”

Your email address will not be published. Required fields are marked *