Skip to main content
Log in

Stackelberg game models between two competitive retailers in fuzzy decision environment

  • Published:
Fuzzy Optimization and Decision Making Aims and scope Submit manuscript

Abstract

In this paper, we study the pricing problem in a fuzzy supply chain that consists of a manufacturer and two competitive retailers. There is a single product produced by a manufacturer and then sold by two competitive retailers to the consumers. The manufacturer acting as a leader determines the wholesale price, and the retailers acting as the followers set their sale prices independently. Both the manufacturing cost and the demand for product are characterized as fuzzy variables, we analyze how the manufacturer and the retailers make their pricing decisions with the duopolistic retailers’ different behaviors: competition strategy and collusion strategy, and develop the expected value models in this paper. Finally, numerical examples illustrate the effectiveness of the proposed two-echelon models using fuzzy set theory.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102, 289–301.

    Article  Google Scholar 

  • Chen, S. P., & Ho, Y. H. (2011). Analysis of the newsboy problem with fuzzy demands and incremental discounts. International Journal of Production Economics, 129, 169–177.

    Article  Google Scholar 

  • Choi, S. C. (1991). Price competition in a channel structure with a common retailer. Marketing Science, 10, 271–296.

    Article  Google Scholar 

  • Choi, S. C. (1996). Price competition in a duopoly common retailer channel. Journal of Retailing, 72, 117–134.

    Article  Google Scholar 

  • Ertek, G., & Griffin, P. M. (2003). Supplier-and buyer-driven channels in a two-stage supply chain. IIE Transaction, 34, 691–700.

    Google Scholar 

  • Handfield, R., Warsing, D., & Wu, X. (2009). \(\left( q, r \right)\) inventory policies in a fuzzy uncertain supply chain environment. European Journal of Operational Research, 197, 609–619.

    Article  MATH  MathSciNet  Google Scholar 

  • Huang, Z. M., & Li, S. X. (2005). Coordination and cooperation in manufacturer-retailer supply chains. Lecture Notes in Computer Science, 3327, 174–186.

    Article  Google Scholar 

  • Ingene, C. A., & Parry, M. E. (1995). Channel cooperation when retailers compete. Management Science, 41, 360–377.

    Article  Google Scholar 

  • Jeuland, A., & Shugan, S. (1983). Managing channel profits. Marketing Science, 2, 239–272.

    Article  Google Scholar 

  • Jeuland, A., & Shugan, S. (1988). Channel of Distribution Profits When Channel Members Form Conjectures. Marketing Science, 7, 202–210.

    Article  Google Scholar 

  • Kumar, M., Vrat, P., & Shankar, R. (2004). A fuzzy goal programming approach for vendor selection problem in a supply chain. Computer and Industrial Engineering, 46, 69–85.

    Article  Google Scholar 

  • Li, L., & Huo, J. Z. (2010). Pricing competition and order coordination of supply chain with duopolistic retailers. International Conference on Logistics Systems and Intelligent Management, pp: 873–878.

  • Li, J., Wang, S. Y., & Cheng, T. (2010). Competition and cooperation in a single-retailer Two-supplier supply chain with supply disruption. International Journal of Production Economics, 124, 137–150.

    Article  Google Scholar 

  • Liang, G. S., Lin, L. Y., & Liu, C. F. (2008). The optimum output quantity of a duopoly market under a fuzzy decision environment. Computers and Mathematics with Applications, 56, 1176–1187.

    Article  MATH  MathSciNet  Google Scholar 

  • Liu, B. (2002). Theory and practice of uncertain programming. Heidelberg: Physica-Verlag.

    Book  MATH  Google Scholar 

  • Liu, B., & Liu, Y. (2002). Excepted value of fuzzy variable and fuzzy expected value models. IEEE Transactions on Fuzzy Systems, 10, 445–450.

    Article  Google Scholar 

  • Mcguire, T. W., & Staelin, R. (1984). An approach for developing an optimal quantity discount pricing policy. Marketing Science, 2, 161–190.

    Article  Google Scholar 

  • Nahmias, S. (1978). Fuzzy variables. Fuzzy Sets and Systems, 1, 97–110.

    Article  MATH  MathSciNet  Google Scholar 

  • Pedrycz, W. (1994). Why triangular membership functions? Fuzzy Sets and Systems, 64, 21–30.

    Article  MathSciNet  Google Scholar 

  • Petrovic, D., Roy, R., & Petrovic, R. (1998). Modeling and simulation of a supply chain in an uncertain environment. European Journal of operational Research, 109, 299–309.

    Article  MATH  Google Scholar 

  • Petrovic, D., Roy, R., & Petrovic, R. (1999). Supply chain modeling using fuzzy sets. International Journal of Production Economics, 59, 443–453.

    Article  Google Scholar 

  • Raul, R., Paz, P., & Rainer, L. (2011). From competitive to collaborative supply networks: A simulation study. Applied Mathematical Modelling, 35, 1054–1064.

    Article  MATH  Google Scholar 

  • Ryu, K., & Yücesan, E. (2010). A fuzzy newsvendor approach to supply chain coordination. European Journal of Operational Research, 200, 421–438.

    Article  MATH  Google Scholar 

  • Sasien, M. W. (1986). Competition and cooperation between manufacturer and retailer. IMA Journal of Management Mathematics, 1, 33–38.

    Article  Google Scholar 

  • Selim, H., Araz, C., & Ozkarahan, I. (2008). Collaborative production-distribution planning in supply chain: A fuzzy goal programming approach. Transportation Research Part E, 44, 396–419.

    Article  Google Scholar 

  • Shugan, S. (1985). Implicit understandings in channels of distribution. Management Science, 31, 435–460.

    Article  Google Scholar 

  • Sinha, S., & Sarmah, S. P. (2008). An application of fuzzy set theory for supply chain coordination. International Journal of Management Science and Engineering Management, 3, 19–32.

    Google Scholar 

  • Torabi, S. A., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 159, 193–214.

    Article  MATH  MathSciNet  Google Scholar 

  • Wang, C., Tang, W., & Zhao, R. (2007). On the continuity and convexity analysis of the expected value function of a fuzzy mapping. Journal of Uncertain Systems, 1, 148–160.

    Google Scholar 

  • Wang, S. D., Wang, J., & Zhou, Y. W. (2012). Channel coordination with different competitive duopolistic retailers’ behavior and non-linear demand. International Journal of Management Science and Engineering Management, 7, 119–127.

    Google Scholar 

  • Xie, Y., Petrovic, D., & Burnham, K. (2006). A heuristic procedure for the two-level control of serial supply chains under fuzzy customer demand. International Journal Production Economics, 102, 37–50.

    Article  Google Scholar 

  • Xu, J. P., He, Y. N., & Gen, M. (2009). A class of random fuzzy programming and its application to supply chain design. Computer and Industrial Engineering, 56, 937–950.

    Article  Google Scholar 

  • Yang, S. L., & Zhou, Y. W. (2006). Two-echelon supply chain models: Considering duopolistic retailers’ different competitive behaviors. International Journal of Production Economics, 103, 104–116.

    Article  Google Scholar 

  • Yu, Y., & Jin, T. D. (2011). The return policy model with fuzzy demands and asymmetric information. Applied Soft Computing, 11, 1669–1678.

    Article  Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 18, 338–353.

    Article  MathSciNet  Google Scholar 

  • Zadeh, L. (1978). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 3–28.

    Article  MATH  MathSciNet  Google Scholar 

  • Zhao, J., Tang, W., & Wei, J. (2012a). Pricing decision for substitutable products with retail competition in a fuzzy environment. International Journal of Production Economics, 139, 144–153.

    Article  Google Scholar 

  • Zhao, J., Tang, W. S., Zhao, R., & Wei, J. (2012b). Pricing decisions for substitutable products with a common retailer in fuzzy environments. European Journal of Operational Research, 216, 409–419.

    Article  MATH  MathSciNet  Google Scholar 

  • Zimmermann, H. (2000). An application-oriented view of modelling uncertainty. European Journal of Operational Research, 122, 190–198.

    Article  MATH  Google Scholar 

Download references

Acknowledgments

The authors are very grateful to the anonymous reviewers for their insightful and constructive comments and suggestions that have led to an improved version of this paper. The work was supported by the National Natural Science Foundation of China (Nos. 71071161 and 61273209).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zeshui Xu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Liu, S., Xu, Z. Stackelberg game models between two competitive retailers in fuzzy decision environment. Fuzzy Optim Decis Making 13, 33–48 (2014). https://doi.org/10.1007/s10700-013-9165-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10700-013-9165-x

Keywords

Navigation