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[학술저널]

  • 학술저널

Hamid Bekamiri(Ferdowsi University of Mashhad) Mohammad Mehraeen (Lagzian)(Ferdowsi University of Mashhad) Alireza Pooya(Ferdowsi University of Mashhad) Hossein Sharif(Sharif University of Technology)

DOI : 10.7232/iems.2020.19.4.744

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This study provides a stochastic dynamic programming model with a Markov chain that explicitly focuses on the customer as well as a new model for valuing the customers in the banking industry. The proposed framework calculates individual customer’s lifetime value dynamically. The study follows a stochastic dynamic programming model that is based on the Markov chain. The deduced findings are illustrated with supplementary context from an outstanding case study. The findings underline the importance of the stochastic model for calculating customer lifetime value based on customer behavior. The presented framework provides a beneficial way for future research and valuable insight for allocating promotional marketing strategies to customer groups. The presented framework provides a dynamic model for calculating the individual customer’s lifetime value. The main contribution of the study is the explicit calculation of individual customer’s lifetime value in the banking industry. Thus, this study provides a stochastic framework for customer segmentation and allocates appropriate marketing promotion strategies. Furthermore, the results of this study were supported by real customer data of one of the largest banks in the MENA region.

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ABSTRACT
1. INTRODUCTION
2. REVIEW OF LITERATURE
3. METHODOLOGY: A STOCHASTIC MODEL FOR CALCULATING CLV
4. INDIVIDUAL CLV EQUATION
5. LIMITING PROBABILITY
6. A CASE OF STUDY IN MENA REGION BANKING INDUSTRY
7. DATA PREPARATION
8. BUILDING THE ONE-STEP TRANSITION MATRIX
9. REWARD VECTOR OF CUSTOMER I
10. LIFETIME VALUE OF CUSTOMER I
11. THE PRACTICAL SIDE OF RESEARCH
13. LIMITATIONS AND SCOPE OF FURTHER RESEARCH
14. CONCLUSION
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