Stochastic Models for Optimal Assessment of Control Relationship Management with Customer.

Stochastic Models for Optimal Assessment of Control Relationship Management with Customer.

BubaBajo(Buba Bajo)

指導教授 ： 陳雲岫

元智大學/工程學院/工業工程與管理學系/碩士(2011年)

https://doi.org/10.6838/YZU.2011.00372

摘要

ABSTRACT
In any service system, one of the challenges in assessing customer lifetime value or more is the Classification of customers. Running a successful business is to maintain a good relationship with the customers. Classification of customers (i.e. a company should identify the profitable customers and keep them with an acceptable effort) plays an important role in promotion planning and budget setting.
Promotion budget allocation is designed to attract and keep customers. In this thesis we applied stochastic dynamic programming models with the Markov chain techniques for capturing the customer behavior. The model can be implemented using dual simplex method in a Microsoft Excel worksheet, and precise implementation is also demonstrated and discussed in details.
Furthermore, a higher-order Markov chain model is a further way of capturing the dynamics of practical data. The practical data from Telecommunication Company is used to illustrate the effectiveness of the higher-order Markov Model thereby observed the improvement in predicting the customer behavior.
Keywords: Customer lifetime value, stochastic dynamic programming models, Markov chain, dual simplex method

關鍵字

Customer lifetime value ； stochastic dynamic programming models ； Markov chain ； dual simplex method

並列摘要

ABSTRACT
In any service system, one of the challenges in assessing customer lifetime value or more is the Classification of customers. Running a successful business is to maintain a good relationship with the customers. Classification of customers (i.e. a company should identify the profitable customers and keep them with an acceptable effort) plays an important role in promotion planning and budget setting.
Promotion budget allocation is designed to attract and keep customers. In this thesis we applied stochastic dynamic programming models with the Markov chain techniques for capturing the customer behavior. The model can be implemented using dual simplex method in a Microsoft Excel worksheet, and precise implementation is also demonstrated and discussed in details.
Furthermore, a higher-order Markov chain model is a further way of capturing the dynamics of practical data. The practical data from Telecommunication Company is used to illustrate the effectiveness of the higher-order Markov Model thereby observed the improvement in predicting the customer behavior.
Keywords: Customer lifetime value, stochastic dynamic programming models, Markov chain, dual simplex method

並列關鍵字

Customer lifetime value ； stochastic dynamic programming models ； Markov chain ； dual simplex method

參考文獻

Altman, E. (1994). "Denumerable Constrained Markov Decision Processes and Finite Approximations." Mathematics of operations research 19(1): 169-191.

Berger, P. (2001). "The allocation of promotion budget to maximize customer equity." Omega (Oxford) 29(1): 49-61.

Blattberg, R. a. D. (1996). "Manage marketing by the customer equity test." Harvard business review 74: 136-144.

Ching, W.-K. (2004). "Customer lifetime value: stochastic optimization approach." The Journal of the Operational Research Society 55(8): 860-868.

Ching, W.-K. Z., S. Jiao, Y. Akutsu and Wong (2009). "Optimal control policy for probabilistic Boolean networks with hard constraints." IET system biology 3(2): 90-99.