Skip to main content
Log in

Pricing Decisions in a Fuzzy Supply Chain System Considering Different Duopolistic Retailers’ Competitive Behavior

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

Abstract

This paper characterizes the pricing decisions in a two-echelon supply chain composed of one manufacturer and two retailers. A Stackelberg structure is supposed between the two echelons with a manufacturer acting as the leader and two retailers acting as followers in the supply chain. Specifically, both customer demand and manufacturing cost of products are represented as triangular fuzzy variables, and expected value models are developed to discuss the pricing decisions, and the influence of three different types of competitive behavior of the two retailers, namely Stackelberg (Model S), Bertrand (Model B) and Collusion (Model C), using the global cooperation model (Model G) as a reference. Further, a numerical experiment is conducted to illustrate that different types of competitive behavior have different effects on the optimal profits of chain members, where the maximal expected profit of the supply chain system and the manufacturer are all positively associated with the fuzzy degrees of parameters in all three situations, while those of the retailers are associated negatively.

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.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. Type-1 fuzzy numbers are used to solve the general problem of uncertainty, while type-2 fuzzy numbers are used to solve complex or high-order uncertainties [36, 37].

References

  1. Yang, S.L., Zhou, Y.W.: Two-echelon supply chain models: considering duopolistic retailers’ different competitive behaviors. Int. J. Prod. Econ. 103(1), 104–116 (2006)

    Article  Google Scholar 

  2. Wei, J., Zhao, J.: Pricing decisions for substitutable products with horizontal and vertical competition in fuzzy environments. Ann. Oper. Res. 242(2), 505–528 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  3. Zhao, J., Tang, W., Zhao, R., Wei, J.: Pricing decisions for substitutable products with a common retailer in fuzzy environments. Eur. J. Oper. Res. 216(2), 409–419 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  4. Yang, D., Xiao, T.: Pricing and green level decisions of a green supply chain with governmental interventions under fuzzy uncertainties. J. Clean. Prod. 149, 1174–1187 (2017)

    Article  Google Scholar 

  5. Giri, B.C., Bardhan, S., Maiti, T.: Coordinating a three-layer supply chain with uncertain demand and random yield. Int. J. Prod. Res. 54(8), 1–20 (2015)

    Google Scholar 

  6. Cardoso, S.R., Barbosa-Póvoa, A.P., Relvas, S., Novais, A.Q.: Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty. Omega 56(1), 53–73 (2015)

    Article  Google Scholar 

  7. Kaya, O., Bagci, F., Turkay, M.: Planning of capacity, production and inventory decisions in a generic reverse supply chain under uncertain demand and returns. Int. J. Prod. Res. 52(1), 270–282 (2014)

    Article  Google Scholar 

  8. Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)

    Article  MATH  Google Scholar 

  9. Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1, 3–28 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  10. Guo, S., Yu, L., Li, X., Kar, S.: Fuzzy multi-period portfolio selection with different investment horizons. Eur. J. Oper. Res. 254(3), 1026–1035 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  11. Xu, Z., Liao, H.: A survey of approaches to decision making with intuitionistic fuzzy preference relations. Knowl. Based Syst. 80(5), 131–142 (2015)

    Article  Google Scholar 

  12. Peng, J., Wang, J., Wu, X., Zhang, H., Chen, X.: The fuzzy cross-entropy for intuitionistic hesitant fuzzy sets and their application in multi-criteria decision-making. Int. J. Syst. Sci. 46(13), 2335–2350 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  13. Qin, J., Liu, X., Witold, P.: Hesitant fuzzy maclaurin symmetric mean operators and its application to multiple-attribute decision making. Int. J. Fuzzy Syst. 17(4), 509–520 (2015)

    Article  MathSciNet  Google Scholar 

  14. Yu, S.M., Wang, J., Wang, J.Q.: An interval type-2 fuzzy likelihood-based MABAC approach and its application in selecting hotels on a tourism website. Int. J. Fuzzy Syst. 19(1), 1–15 (2016)

    MathSciNet  Google Scholar 

  15. Sang, S.: Optimal models in price competition supply chain under a fuzzy decision environment. J. Intell. Fuzzy Syst. 27(1), 257–271 (2014)

    MathSciNet  MATH  Google Scholar 

  16. Choi, S.C.: Price competition in a channel structure with a common retailer. Mark. Sci. 10(4), 271–296 (1991)

    Article  Google Scholar 

  17. Yue, J., Austin, J., Wang, M.C., Huang, Z.: Coordination of cooperative advertising in a two-level supply chain when manufacturer offers discount. Eur. J. Oper. Res. 168(1), 65–85 (2006)

    Article  MATH  Google Scholar 

  18. Hua, G., Wang, S., Cheng, T.C.E.: Price and lead time decisions in dual-channel supply chains. Eur. J. Oper. Res. 205(1), 113–126 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  19. Hsieh, C.C., Chang, Y.L., Wu, C.H.: Competitive pricing and ordering decisions in a multiple-channel supply chain. Int. J. Prod. Econ. 154(4), 156–165 (2014)

    Article  Google Scholar 

  20. Zhu, S.X.: Integration of capacity, pricing, and lead-time decisions in a decentralized supply chain. Int. J. Prod. Econ. 164, 14–23 (2015)

    Article  Google Scholar 

  21. Shafiee-Gol, S., Nasiri, M.M., Taleizadeh, A.A.: Pricing and production decisions in multi-product single machine manufacturing system with discrete delivery and rework. OPSEARCH 53(4), 873–888 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  22. Liu, L., Wang, Z., Xu, L., Hong, X., Govindan, K.: Collection effort and reverse channel choices in a closed-loop supply chain. J. Clean. Prod. 144, 492–500 (2017)

    Article  Google Scholar 

  23. Giri, R.N., Mondal, S.K., Maiti, M.: Bundle pricing strategies for two complementary products with different channel powers. Ann. Oper. Res. (2017). https://doi.org/10.1007/s10479-017-2632-y

  24. Lau, A.H.L., Lau, H.S.: Effects of a demand-curve’s shape on the optimal solutions of a multi-echelon inventory/pricing model. Eur. J. Oper. Res. 147(3), 530–548 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  25. Wu, C.H., Chen, C.W., Hsieh, C.C.: Competitive pricing decisions in a two-echelon supply chain with horizontal and vertical competition. Int. J. Prod. Econ. 135(1), 265–274 (2011)

    Article  Google Scholar 

  26. Cao, E., Wan, C., Lai, M.: Coordination of a supply chain with one manufacturer and multiple competing retailers under simultaneous demand and cost disruptions. Int. J. Prod. Econ. 141(1), 425–433 (2013)

    Article  Google Scholar 

  27. Jena, S.K., Sarmah, S.P.: Price competition and co-operation in a duopoly closed-loop supply chain. Int. J. Prod. Econ. 156(5), 346–360 (2014)

    Article  Google Scholar 

  28. Roy, A., Sana, S.S., Chaudhuri, K.: Optimal pricing of competing retailers under uncertain demand-a two layer supply chain model. Ann. Oper. Res. (2015). https://doi.org/10.1007/s10479-015-1996-0

  29. Luo, Z., Chen, X., Chen, J., Wang, X.: Optimal pricing policies for differentiated brands under different supply chain power structures. Eur. J. Oper. Res. 259(2), 437–451 (2017)

    Article  MathSciNet  Google Scholar 

  30. Giannoccaro, I., Pontrandolfo, P., Scozzi, B.: A fuzzy echelon approach for inventory management in supply chains. Eur. J. Oper. Res. 149(1), 185–196 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  31. Wang, J., Shu, Y.F.: Fuzzy decision modeling for supply chain management. Fuzzy Sets Syst. 150(1), 107–127 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  32. Chen, C.T., Lin, C.T., Huang, S.F.: A fuzzy approach for supplier evaluation and selection in supply chain management. Int. J. Prod. Econ. 102(2), 289–301 (2006)

    Article  Google Scholar 

  33. Kumar, D., Singh, J., Singh, O.P.: A fuzzy logic based decisionsupport system for evaluation of suppliers in supply chain management practices. Math. Comput. Model. 58(11–12), 1679–1695 (2013)

    Article  MATH  Google Scholar 

  34. Shen, J., Zhu, K.: Uncertain supply chain problem with price and effort. Int. J. Fuzzy Syst. (2017). https://doi.org/10.1007/s40815-017-0407-x

  35. McGuire, T., Staein, R.: An industry equilibrium analyses of downstream vertical integration. Mark. Sci. 2(2), 161–191 (1983)

    Article  Google Scholar 

  36. Qin, J.D., Liu, X.W., Witold, P.: An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. Eur. J. Oper. Res. 258(2), 626–638 (2017)

    Article  MathSciNet  Google Scholar 

  37. Qin, J.D., Liu, X.W.: Multi-attribute group decision making using combined ranking value under interval type-2 fuzzy environment. Info. Sci. 297, 293–315 (2015)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant No. 71672071).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xianpei Hong.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhong, Q., Wang, Z. & Hong, X. Pricing Decisions in a Fuzzy Supply Chain System Considering Different Duopolistic Retailers’ Competitive Behavior. Int. J. Fuzzy Syst. 20, 1592–1605 (2018). https://doi.org/10.1007/s40815-017-0437-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-017-0437-4

Keywords

Navigation