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Fuzzy principal-agent model for optimal supplier switching with asymmetric information

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Abstract

This paper studies a fuzzy principal-agent problem for supplier switching with taking into account the asymmetric information and the competition effect where the buying firm’s assessment to the entrant supplier’s cost is described as a fuzzy variable. The supplier switching model is set up to minimize the buying firm’s total procurement cost which includes the transfer payment to the entrant supplier, the payment to the incumbent supplier and the switching cost. Through the analysis of the participation constraint, the incentive compatibility constraint and the objective function, the equivalent model of the fuzzy principal-agent problem for supplier switching is proposed, and the optimal supplier switching strategy is obtained. It is shown that the competition effect would lead to a partial switching strategy. Additionally, the supplier switching decision under the symmetric information is also studied. Finally, an example is given to illustrate the effectiveness of the proposed model and the supplier switching strategy.

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References

  1. Amid A, Ghodsypour SH, O’Brien C (2006) Fuzzy multiobjective linear model for supplier selection in a supply chain. Int J Prod Econ 104(2):394–407

    Article  Google Scholar 

  2. Berman O, Wang J, Sapna KP (2005) Optimal management of cross-trained workers in services with negligible switching costs. Eur J Oper Res 167(2):349–369

    Article  MATH  MathSciNet  Google Scholar 

  3. Burke GJ, Carrillo JE, Vakharia AJ (2007) Single versus multiple supplier sourcing strategies. Eur J Oper Res 182(1):95–112

    Article  MATH  MathSciNet  Google Scholar 

  4. Burnham TA, Frels JK, Mahajan V (2003) Consumer switching costs: a typology, antecedents, and consequences. J Acad Mark Sci 31(2):109–126

    Article  Google Scholar 

  5. Chou SY, Dat LQ, Yu VF (2011) A revised method for ranking fuzzy numbers using maximizing set and minimizing set. Comput Ind Eng 61(4):1342–1348

    Article  Google Scholar 

  6. Cui LX, Zhao RQ, Tang WS (2007) Principal-agent problem in a fuzzy environment. IEEE Trans Fuzzy Syst 15(6):1230–1237

    Article  Google Scholar 

  7. Friebel L, Friebelová J (2012) Stochastic analysis of maintenance process costs in the IT industry: a case study. Cent Eur J Oper Res 20(3):393–408

    Google Scholar 

  8. Heide JB, Weiss AM (1995) Vendor consideration and switching behavior for buyers in high-technology markets. J Mark 59(3):30–43

    Article  Google Scholar 

  9. Hu F, Lim CC, Lu Z, Sun XC (2013) Coordination in a single-retailer two-supplier supply chain under random demand and random supply with disruption. Discret Dyn Nat Soc 1–12:2013

    MathSciNet  Google Scholar 

  10. Hu M (2011) The supplier switching of retail enterprise. In: Industrial Engineering and Engineering Management (IE and EM), 2011 IEEE 18th International Conference pp 277–280.

  11. Hu M, Tang W, Zhang J (2012) Optimization of supplier switching with asymmetric information. Trans Tianjin Univ 18(2):149–156

    Article  MathSciNet  Google Scholar 

  12. Ivanov D, Sokolov J, Kaeschel B (2011) Integrated supply chain planning based on a combined application of operations research and optimal control. Cent Eur Oper Res 19(3):299–317

    Article  MathSciNet  Google Scholar 

  13. Ju CH, Chen TG (2012) Simplifying multiproject scheduling problem based on design structure matrix and its solution by an improved ainet algorithm. Discret Dyn Nat Soc 1–22:2012

    MathSciNet  Google Scholar 

  14. Kamrad B, Siddique A (2004) Supply contracts, profit sharing, switching, and reaction options. Manag Sci 50(1):64–82

    Article  Google Scholar 

  15. Klemperer P (1995) Competition when consumers have switching costs: an overview with applications to industrial organization, macroeconomics, and international trade. Rev Econ Stud 62(4):515–539

    Article  MATH  Google Scholar 

  16. Lan Y, Zhao R, Tang W (2011) Minimum risk criterion for uncertain production planning problems. Comput Ind Eng 61(3):591–599

    Article  MathSciNet  Google Scholar 

  17. Lan YF, Zhao RQ, Tang WS (2011) A bilevel fuzzy principal-agent model for optimal nonlinear taxation problems. Fuzzy Optim Decision Mak 10(3):211–232

    Article  MATH  MathSciNet  Google Scholar 

  18. Lan YF, Zhao RQ, Tang WS (2012) A fuzzy supply chain contract problem with pricing and warranty. J Intell Fuzzy Syst. doi:10.3233/IFS-130836

  19. Liu B, Liu YK (2002) Expected value of fuzzy variable and fuzzy expected value models. IEEE Trans Fuzzy Syst 10(4):445–450

    Article  Google Scholar 

  20. Martínez-Soto R, Castillo O, Aguilar LT, Rodriguez A (2013) A hybrid optimization method with pso and ga to automatically design type-1 and type-2 fuzzy logic controllers. Int J Mach Learn Cybern. doi:10.1007/s13042-013-0170-8

  21. Mu R, Lan YF, Tang WS (2013) An uncertain contract model for rural migrant workers employment problems. Fuzzy Optim Decision Mak 12(1):29–39

    Article  MathSciNet  Google Scholar 

  22. Myerson RB (1979) Incentive compatibility and the bargaining problem. Econometrica. J Econom Soc 47(1):61–73

    Article  MATH  MathSciNet  Google Scholar 

  23. Saen RF (2007) A new mathematical approach for suppliers selection: accounting for non-homogeneity is important. Appl Math Comput 185(1):84–95

    Article  MATH  MathSciNet  Google Scholar 

  24. Sawik T (2011) Supplier selection in make-to-order environment with risks. Math Comput Model 53(9–10):1670–1679

    Article  MATH  MathSciNet  Google Scholar 

  25. Shugan SM (1980) The cost of thinking. J Consum Res 7(2):99–111

    Article  MathSciNet  Google Scholar 

  26. Taylan O, Darrab IA (2011) Determining optimal quality distribution of latex weight using adaptive neuro-fuzzy modeling and control systems. Comput Ind Eng 61(3):686–696

    Google Scholar 

  27. Wagner SM (2010) Supplier traits for better customer firm innovation performance. Ind Mark Manag 39(7):1139–1149

    Article  Google Scholar 

  28. Wagner SM, Friedl G (2007) Supplier switching decisions. Eur J Oper Res 183(2):700–717

    Article  MATH  Google Scholar 

  29. Wang C, Tang WS, Zhao RQ (2007) On the continuity and convexity analysis of the expected value function of a fuzzy mapping. J Uncertain Syst 1(2):148–160

    MathSciNet  Google Scholar 

  30. Wang XZ, Chen B, Qian GL, Ye F (2000) On the optimization of fuzzy decision trees. Fuzzy Sets Syst 112(1):117–125

    Article  MathSciNet  Google Scholar 

  31. Wang XZ, Hong JR (1999) Learning optimization in simplifying fuzzy rules. Fuzzy Sets Syst 106(3):349–356

    Article  MATH  MathSciNet  Google Scholar 

  32. Wei J, Pang GY, Liu YJ, Ma Q (2013) Pricing decisions of a two-echelon supply chain in fuzzy environment. Discret Dyn Nat Soc 1–11:2013

    MathSciNet  Google Scholar 

  33. Xue F, Tang WS, Zhao RQ (2008) The expected value of a function of a fuzzy variable with a continuous membership function. Comput Math Appl 55(6):1215–1224

    Article  MATH  MathSciNet  Google Scholar 

  34. Yang YQ, Wang GJ, Yang Y (2014) Parameters optimization of polygonal fuzzy neural networks based on ga-bp hybrid algorithm. Int J Mach Learn Cybern. doi:10.1007/s13042-013-0224-y

  35. Yu H, Zeng AZ, Zhao L (2009) Single or dual sourcing: decision-making in the presence of supply chain disruption risks. OMEGA Int J Manag Sci 37(4):788–800

    Article  Google Scholar 

  36. Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353

    Article  MATH  MathSciNet  Google Scholar 

  37. Zimmermann HJ (1985) Applications of fuzzy set theory to mathematical programming. Inf Sci 36(1–2):29–58

    Article  MATH  Google Scholar 

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Acknowledgments

This work was supported by Doctor Foundation of Hubei University of Automotive Technology No. BK201301 and the thousand people plan of Hubei Educational Department No. BK XD2012404.

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Correspondence to Mingmao Hu.

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Hu, M., Guo, B. & Liu, H. Fuzzy principal-agent model for optimal supplier switching with asymmetric information. Int. J. Mach. Learn. & Cyber. 6, 7–15 (2015). https://doi.org/10.1007/s13042-014-0246-0

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  • DOI: https://doi.org/10.1007/s13042-014-0246-0

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