DOI QR코드

DOI QR Code

Derivation and utilization of probability distribution of credit card usage behavior

신용카드 이용행태의 확률분포 도출과 활용

  • 이찬경 (홍익대학교 대학원 경영학과) ;
  • 노형봉 (홍익대학교 경영대학)
  • Received : 2018.01.03
  • Accepted : 2018.02.23
  • Published : 2018.03.31

Abstract

Purpose: To find out the appropriate probability distribution of credit card usage behavior by considering the relationship among income, expenditure and credit card usage amount. Such relationship is enabled by Korea's especially high penetration of credit card. Method: Goodness-of-fit test and effect size statistic W were used to identify the distribution of income and credit card usage amount. A simulation model is introduced to generate the credit card transactions on individual user level. Result: The three data sets for testing had either passed the chi-square test or showed low W values, meaning they follow the exponential distribution. And the exponential distribution turned out to fit the data sets well. The r values were very high. Conclusion: The credit card usage behavior, denoted as the counts of users by usage amount band, follows the exponential distribution. This distribution is easy to manipulate, has a variety of applications and generates important business implications.

Keywords

References

  1. Bank of Korea(BOK). 2016. "A research on payment method usage behaviors and its implications."
  2. Bentler, P.M., and Bonnet, Douglas G. 1980. "Significance tests and goodness of fit in the analysis of covariance structure." Psychological Bulletin 88(3):588-606. https://doi.org/10.1037/0033-2909.88.3.588
  3. Champernowne, D.G. 1953. "A model of income distribution." The Economic Journal 63(250):18-351.
  4. Cohen, Jacob. 1988. Statistical Power Analysis for the Behavioral Sciences: Erlbaum Associates 2nd ed.
  5. Credit Finance Association(CREFIA). 2014. "Credit Card Business Report September."
  6. Diacon, Paula-Elena, and Maha, Liviu-George. 2014. "The relationship between Income, Consumption and GDP." Procedia Economics and Finance 23:1535-1543.
  7. Dragulescu, A., and Yakovenko, V.M. 2001. "Evidence for the exponential distribution of income in the USA." European Physical Journal B 20: 585-589.
  8. Fan, Yuhao Jeremy. 2016. "Examining credit card consumption pattern." Washington University:4-12.
  9. Heggestuen, John. 2014. "Low Credit Card Usage Means Carrier Billing Could Catch on in Emerging Markets." Business Insider Australia.
  10. Jung. H.M., Cho, S.J., and Chung, Justin. 2013. "An Empirical Study on Credit Card Usage." Journal of Economic Research 18:103-124.
  11. Keynes, John Maynard. 1936. The General Theory of Employment, Interest and Money, Palgrave Macmillan.
  12. Kim, K.G., and Yeom, M.B. 2015. "A Study on consumption of credit cards as surrogate economic index and characteristics of local consumption." Journal of Economic Research 33(1):121-141.
  13. Lee, G.C., Jung, N.S., and Shin, G,S. 2002. "An Artificial Intelligence-based Data Mining Approach to Extracting Strategies for Reducing the Churning date in Credit Card Industry." Journal of intelligent information systems 8(2):15-35.
  14. Lee, Seung-Hwan. 2014. "Credit Card Payment Ratio is 51%." Financial News.
  15. Lee, Y.J., Lee, S.H., and Lee, J.S. 2014. "KB's marketing activities and big data utilization." KBR 18(1).
  16. Reliability Analysis Center. 2003. "The Chi Square: A large sample goodness-of-fit test." START 10(4).
  17. Schmittlein, Daivd C., Morrison, Donald G., Colombo, Richard. 1987. "Counting Your Customers: Who are they and what will they do next?" Management Science 33(1): 3-11.
  18. So, Meko M.C., and Thomas, Lyn C. 2011. "Modeling the profitability of credit cards by Markov decision processes." European Journal of operational research 212:123-130 https://doi.org/10.1016/j.ejor.2011.01.023
  19. Song, H.J., and Sung, M.J. 2012. "Analysis of the effect of credit card deduction." Journal of Finance Research 5(2):157-194.
  20. Till, Robert, and Hand, David. 2003. "Behavioural models of credit card usage." Journal of Applied statistics, 30(10):1201-1220. https://doi.org/10.1080/0266476032000107196