A new application of clustering for segmentation of banks’ e-payment services based on profitability

Farokhi, S.; Teimourpour, B.; Shekarriz, F.; Masoudi, M.

Growing Science » Uncertain Supply Chain Management » A new application of clustering for segmentation of banks’ e-payment services based on profitability

Journals

USCM Volumes

Volume 1 (22)
- Issue 1 (4)
- Issue 2 (6)
- Issue 3 (6)
- Issue 4 (6)

Volume 2 (32)
- Issue 1 (7)
- Issue 2 (5)
- Issue 3 (10)
- Issue 4 (10)

Volume 3 (39)
- Issue 1 (9)
- Issue 2 (13)
- Issue 3 (10)
- Issue 4 (7)

Volume 4 (31)
- Issue 1 (10)
- Issue 2 (6)
- Issue 3 (6)
- Issue 4 (9)

Volume 5 (26)
- Issue 1 (6)
- Issue 2 (6)
- Issue 3 (8)
- Issue 4 (6)

Volume 6 (25)
- Issue 1 (7)
- Issue 2 (6)
- Issue 3 (6)
- Issue 4 (6)

Volume 7 (57)
- Issue 1 (8)
- Issue 2 (19)
- Issue 3 (14)
- Issue 4 (16)

Volume 8 (82)
- Issue 1 (20)
- Issue 2 (15)
- Issue 3 (17)
- Issue 4 (30)

Volume 9 (117)
- Issue 1 (25)
- Issue 2 (26)
- Issue 3 (32)
- Issue 4 (34)

Volume 10 (150)
- Issue 1 (28)
- Issue 2 (32)
- Issue 3 (44)
- Issue 4 (46)

Volume 11 (190)
- Issue 1 (42)
- Issue 2 (45)
- Issue 3 (50)
- Issue 4 (53)

Volume 12 (244)
- Issue 1 (55)
- Issue 2 (59)
- Issue 3 (63)
- Issue 4 (67)

Countries

Uncertain Supply Chain Management

ISSN 2291-6830 (Online) - ISSN 2291-6822 (Print) Quarterly Publication Volume 4 Issue 1 pp. 55-60 , 2016

A new application of clustering for segmentation of banks’ e-payment services based on profitability Pages 55-60 Download PDF

Authors: Sorour Farokhi, Babak Teimourpour, Fatemeh Shekarriz, Maryam Masoudi

DOI: 10.5267/j.uscm.2015.7.004

Keywords: Clustering, K-Means, Kohonen, Point of Sales

Abstract: In today' s extremely competitive environment, customers are the most important asset of any business and success of any organization depends on loyal customer retention. Therefore, it is important to learn more about different groups of customers and propose appropriate plans to take care of them. Customer segmentation is one of the most common methods to analyze customer’s behavior. The market can be divided into several smaller homogeneous groups, which helps organizations deliver targeted marketing techniques and provides optimized techniques for resource allocation. This paper uses the information gathered from Point of Sales (POS) in one of Iranian private banks and using two methods of K-Means and Kohonen, customers are clustered into four segments to detect the most profitable customers.

How to cite this paper

 Farokhi, S., Teimourpour, B., Shekarriz, F & Masoudi, M. (2016). A new application of clustering for segmentation of banks’ e-payment services based on profitability.Uncertain Supply Chain Management, 4(1), 55-60.

Refrences

Baradwaj, B. K., & Pal, S. (2011). Mining Educational Data to Analyze Students & apos; Performance. International Journal of Advanced Computer Science & Applications, 2(6), 63-69.

Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Sherer, C., & Wirth, R. (2000). Cross industry standard process for data mining (CRISP-DM) 1.0.

Dunn, J. C. (1973). A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters. Journal of Cybernetics, 3, 32-57

Garcia-Murillo, M., & Annabi, H. (2002). Customer knowledge management. Journal of the Operational Research society, 53(8), 875-884.

Golmah, V., & Mirhashemi, G. (2012). Implementing a data mining solution to customer segmentation for decayable products-A case study for a textile firm. International Journal of Database Theory & Application, 5(3), 73-89.

Pang-Ning, T., Steinbach, M., & Kumar, V. (2006). Introduction to data mining. In Library of Congress (p. 74).

Profeta, A., Balling, R., & Roosen, J. (2012). The relevance of origin information at the point of sale. Food Quality and Preference, 26(1), 1-11.

Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53-65.

?chiopu, D. (2010). Applying TwoStep cluster analysis for identifying bank customers & apos; profile. Buletinul, 62, 66-75.