Latent Variable Models for Integrated Analysis of Credit and Point Usage History Data on Rewards Credit Card System


  •  Ryotaro Shimizu    
  •  Haruka Yamashita    
  •  Masao Ueda    
  •  Ranna Tanaka    
  •  Tetsuya Tachibana    
  •  Masayuki Goto    

Abstract

Recently, credit cards with point rewards functions (rewards credit cards) are widely used. Credit card companies can collect the users’ usage log data of various stores in multiple industries. The purposes of possessing a credit card varies depending on each user such as to use only the credit function, to use both the credit and point rewards functions, etc. Moreover, credit cards can be used in various situations in users’ lives, and the purchase history of each user is diverse. Focusing on the diversity of both card possessing purposes and purchasing behavior for each user, we propose two latent class models representing these diversities in this research.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-9004
  • ISSN(Online): 1913-9012
  • Started: 2008
  • Frequency: monthly

Journal Metrics

Google-based Impact Factor (2019): 0.86

h-index (December 2019): 64

i10-index (December 2019): 529

h5-index (December 2019): 24

h5-median(December 2019): 35

( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )

Contact