The return policy model with fuzzy demands and asymmetric information

Return policy, by offering the retailer some reimbursements for the leftover products, is one of the most efficient mechanisms for channel coordination. This paper considers a supplier-retailer channel to design the optimal return policy for the supplier. It is assumed that the supply chain operates under uncertain demands, which is represented by fuzzy sets. We first study the return policy in a supply chain with symmetric channel information, i.e. the channel information is completely shared between the supplier and the retailer. Further we assume the retailer keeps retail price information private, i.e. the channel information is asymmetric. Thus, the supplier makes the return policy on the basis of estimated retail price which is described as a fuzzy number. We formulate an inventory model with fuzzy demand and fuzzy retail price for the supplier to make a suitable return policy so that the retailer could be motivated to make the optimal order decision to improve the overall supply chain performance. Finally, some characteristics of the return policy are discussed, and numerical examples are presented to demonstrate the model applicability.

[1]  Wen-June Wang,et al.  A simple computation of MIN and MAX operations for fuzzy numbers , 2002, Fuzzy Sets Syst..

[2]  Kunhiraman Nair,et al.  Fuzzy models for single-period inventory problem , 2002, Fuzzy Sets Syst..

[3]  D. Dubois,et al.  Operations on fuzzy numbers , 1978 .

[4]  Radko Mesiar,et al.  Fuzzy Interval Analysis , 2000 .

[5]  Jing-Shing Yao,et al.  Ranking fuzzy numbers based on decomposition principle and signed distance , 2000, Fuzzy Sets Syst..

[6]  Hon-Shiang Lau,et al.  Some two-echelon supply-chain games: Improving from deterministic-symmetric-information to stochastic-asymmetric-information models , 2005, Eur. J. Oper. Res..

[7]  Hon-Shiang Lau,et al.  A stochastic and asymmetric-information framework for a dominant-manufacturer supply chain , 2007, Eur. J. Oper. Res..

[8]  Ronald R. Yager,et al.  A procedure for ordering fuzzy subsets of the unit interval , 1981, Inf. Sci..

[9]  Jin Yi-hui Buy Back Policy under Asymmetric Information in Two-stage Supply Chain , 2003 .

[10]  Didier Dubois,et al.  Gradual elements in a fuzzy set , 2008, Soft Comput..

[11]  Eugene Kandel The Right to Return , 1996, The Journal of Law and Economics.

[12]  Jing-Shing Yao,et al.  A fuzzy stochastic single-period model for cash management , 2006, Eur. J. Oper. Res..

[13]  C. Kao,et al.  A single-period inventory model with fuzzy demand , 2002 .

[14]  S. Gilbert,et al.  Note. the Role of Returns Policies in Pricing and Inventory Decisions for Catalogue Goods , 1998 .

[15]  Barry Alan Pasternack,et al.  Optimal Pricing and Return Policies for Perishable Commodities , 2008, Mark. Sci..

[16]  Yong-Wu Zhou,et al.  A comparison of different quantity discount pricing policies in a two-echelon channel with stochastic and asymmetric demand information , 2007, Eur. J. Oper. Res..

[17]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.