Pricing and Remanufacturing Decisions of a Decentralized Fuzzy Supply Chain

The optimal pricing and remanufacturing decisions problem of a fuzzy closed-loop supply chain is considered in this paper. Particularly, there is one manufacturer who has incorporated a remanufacturing process for used products into her original production system, so that she can manufacture a new product directly from raw materials or from collected used products. The manufacturer then sells the new product to two different competitive retailers, respectively, and the two competitive retailers are in charge of deciding the rates of the remanufactured products in their consumers’ demand quantity. The fuzziness is associated with the customer’s demands, the remanufacturing and manufacturing costs, and the collecting scaling parameters of the two retailers. The purpose of this paper is to explore how the manufacturer and the two retailers make their own decisions about wholesale price, retail prices, and the remanufacturing rates in the expected value model. Using game theory and fuzzy theory, we examine each firm’s strategy and explore the role of the manufacturer and the two retailers over three different game scenarios. We get some insights into the economic behavior of firms, which can serve as the basis for empirical study in the future.

[1]  Juite Wang,et al.  Fuzzy decision modeling for supply chain management , 2005, Fuzzy Sets Syst..

[2]  S. C. Choi,et al.  Price competition in a duopoly common retailer channel , 1996 .

[3]  Yongjian Li,et al.  Retail service for mixed retail and E-tail channels , 2010, Annals of Operations Research.

[4]  Wansheng Tang,et al.  Pricing decision for substitutable products with retail competition in a fuzzy environment , 2012 .

[5]  S. Mondal,et al.  Multi-item fuzzy EOQ models using genetic algorithm , 2003 .

[6]  S. Dowlatshahi,et al.  A strategic framework for the design and implementation of remanufacturing operations in reverse logistics , 2005 .

[7]  Samar K. Mukhopadhyay,et al.  Joint procurement and production decisions in remanufacturing under quality and demand uncertainty , 2009 .

[8]  Avinash Dixit,et al.  A MODEL OF DUOPOLY SUGGESTING A THEORY OF ENTRY BARRIERS , 1978 .

[9]  A. Kaufmann,et al.  Introduction to fuzzy arithmetic : theory and applications , 1986 .

[10]  Dobrila Petrovic,et al.  Simulation of supply chain behaviour and performance in an uncertain environment , 2001 .

[11]  V. Daniel R. Guide,et al.  Building contingency planning for closed-loop supply chains with product recovery , 2003 .

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

[13]  Jing Zhao,et al.  Reverse channel decisions for a fuzzy closed-loop supply chain , 2013 .

[14]  Caroline M. Eastman,et al.  Review: Introduction to fuzzy arithmetic: Theory and applications : Arnold Kaufmann and Madan M. Gupta, Van Nostrand Reinhold, New York, 1985 , 1987, Int. J. Approx. Reason..

[15]  Ioannis Konstantaras,et al.  Optimal policy and holding cost stability regions in a periodic review inventory system with manufacturing and remanufacturing options , 2007, Eur. J. Oper. Res..

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

[17]  Luk N. Van Wassenhove,et al.  Closed - Loop Supply Chain Models with Product Remanufacturing , 2004, Manag. Sci..

[18]  Hans-Jürgen Zimmermann,et al.  An application-oriented view of modeling uncertainty , 2000, Eur. J. Oper. Res..

[19]  X. Vives,et al.  Price and quantity competition in a differentiated duopoly , 1984 .

[20]  Michael E. Ketzenberg,et al.  Value of Information in Closed Loop Supply Chains , 2006 .

[21]  Albert Corominas,et al.  Optimal manufacturing-remanufacturing policies in a lean production environment , 2008, Comput. Ind. Eng..

[22]  Xavier Vives,et al.  On the efficiency of Bertrand and Cournot equilibria with product differentation , 1985 .

[23]  Sridhar Moorthy,et al.  Managing a distribution channel under asymmetric information with performance requirements , 1997 .

[24]  Yian-Kui Liu,et al.  Expected value of fuzzy variable and fuzzy expected value models , 2002, IEEE Trans. Fuzzy Syst..

[25]  Baoding Liu,et al.  A survey of credibility theory , 2006, Fuzzy Optim. Decis. Mak..

[26]  M. Parry,et al.  Channel Coordination When Retailers Compete , 1995 .