The asymmetric game of production technology in a manufacturing supply chain network: the influence of number of manufacturing partners

  • Zhendong Li
  • Huiying Zhang
  • Ke JiangEmail author
  • Mitchell Mainstone


We consider the influence of the number of manufacturing partners on the game of production technologies, which takes place between two manufacturers with different production technologies in a two-echelon manufacturing supply chain network. Firstly, this study analyzes the influence of the number of manufacturing partners on the bilateral production cooperative relation between upstream and downstream manufacturers, finding that the number of manufacturing partners significantly influences bilateral cost-sharing proportion caused by “eliminating production technology differences between them.” Furthermore, we explore corresponding conditions for reaching different evolutionary stable strategy of the two parties in the game of production technology, concluding that manufacturers would not have better performance and either they have more and more or fewer and fewer manufacturing partners. Instead, there exists a critical interval in the number of manufacturing partners in which manufacturers regularly choose certain evolutionary stable strategies all the time. Finally, according to the example analysis on evolutionary stable states in the game and the sensitivity analysis on relevant parameters that affect the game relationship, it is shown that whether the “collaborate” strategy would eventually be chosen by the manufacturer was correlated negatively with its cost coefficient for eliminating production technology differences, but positively with the other party’s cost coefficient and extra profit in bilateral cooperation.


Production technologies Cooperative production Manufacturing partner Supply chain Evolutionary game 


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The authors gratefully acknowledge TJCoST (research project: TJGL15-004); we are also very grateful to the Fundamental Research Funds for the Central Universities (research project: No.2016zzts005)


  1. 1.
    Ashayeri J, Tuzkaya G, Tuzkaya UR (2012) Supply chain partners and configuration selection: an intuitionistic fuzzy Choquet integral operator based approach. Expert Syst Appl 39(3):3642–3649Google Scholar
  2. 2.
    Bakos JY, Brynjolfsson E (1993) Information technology, incentives, and the optimal number of suppliers. J Manag Inf Syst 10(2):37–53Google Scholar
  3. 3.
    Besen SM, Farrell J (1991) The role of the ITU in standardization: pre-eminence, impotence or rubber stamp?. Telecomm Policy 15(4):311–321Google Scholar
  4. 4.
    Braunstein YM, White LJ (1985) Setting technical compatibility standards: an economic analysis. Antitrust Bull 30:337Google Scholar
  5. 5.
    Chang CW, Chiang DM, Pai FY (2012) Cooperative strategy in supply chain networks. Ind Mark Manag 41(7):1114–1124Google Scholar
  6. 6.
    Chen IJ, Paulraj A (2004) Towards a theory of supply chain management: the constructs and measurements. J Oper Manag 22(2):119–150Google Scholar
  7. 7.
    Cooper RG, Kleinschmidt EJ (1986) An investigation into the new product process: steps, deficiencies, and impact. J Product Innov Manag Int Publ Product Dev Manag Assoc 3(2):71–85Google Scholar
  8. 8.
    Dong M, Chen FF (2001) Process modeling and analysis of manufacturing supply chain networks using object-oriented Petri nets. Robot Comput-Integr Manuf 17(1-2):121–129Google Scholar
  9. 9.
    ElMaraghy H, Azab A, Schuh G, Pulz C (2009) Managing variations in products, processes and manufacturing systems. CIRP Ann 58(1):441–446Google Scholar
  10. 10.
    Faria A, Fenn P, Bruce A (2002) Determinants of adoption of flexible production technologies: evidence from Portuguese manufacturing industry. Econ Innov Technol 11(6):569–580Google Scholar
  11. 11.
    Friedman D (1991) Evolutionary games in economics. Econometrica 59(3):637–666MathSciNetzbMATHGoogle Scholar
  12. 12.
    Gargiulo M, Benassi M (2000) Trapped in your own net? Network cohesion, structural holes, and the adaptation of social capital. Organ Sci 11(2):183–196Google Scholar
  13. 13.
    Golder PN, Tellis GJ (2004) Growing, growing, gone: cascades, diffusion, and turning points in the product life cycle. Mark Sci 23(2):207–218Google Scholar
  14. 14.
    Hagedoorn J (1993) Understanding the rationale of strategic technology partnering: Nterorganizational modes of cooperation and sectoral differences. Strateg Manag J 14(5):371–385Google Scholar
  15. 15.
    Halley A, Beaulieu M (2009) Mastery of operational competencies in the context of supply chain management. Supply Chain Manag Int J 14(1):49–63Google Scholar
  16. 16.
    Harland CM (1996) Supply chain management: relationships, chains and networks. Br J Manag 7:S63–S80Google Scholar
  17. 17.
    Huang B, Gao C, Chen L (2011) Partner selection in a virtual enterprise under uncertain information about candidates. Expert Syst Appl 38(9):11305–11310Google Scholar
  18. 18.
    Inman RR, Blumenfeld DE (2014) Product complexity and supply chain design. Int J Prod Res 52 (7):1956–1969Google Scholar
  19. 19.
    Jiao JR, You X, Kumar A (2006) An agent-based framework for collaborative negotiation in the global manufacturing supply chain network. Robot Comput-Integr Manuf 22(3):239–255Google Scholar
  20. 20.
    Johanson J, Mattsson LG (1987) Interorganizational relations in industrial systems: a network approach compared with the transaction-cost approach. Int Stud Manag Organ 17(1):34–48Google Scholar
  21. 21.
    Kanda A, Deshmukh SG (2008) Supply chain coordination: perspectives, empirical studies and research directions. Int J Prod Econ 115(2):316–335Google Scholar
  22. 22.
    Khan RA, Anand A, Wani MF (2018) A holistic framework for environment conscious based product risk modeling and assessment using multi criteria decision making. J Clean Prod 174:954–965Google Scholar
  23. 23.
    Ko CS, Kim T, Hwang H (2001) External partner selection using tabu search heuristics in distributed manufacturing. Int J Prod Res 39(17):3959–3974zbMATHGoogle Scholar
  24. 24.
    Lambert DM, Emmelhainz MA, Gardner JT (1996) Developing and implementing supply chain partnerships. Int J Logist Manag 7(2):1–18Google Scholar
  25. 25.
    Lee WB, Lau HCW (1999) Multi-agent modeling of dispersed manufacturing networks. Expert Syst Appl 16(3):297–306Google Scholar
  26. 26.
    Long Q (2015) Three-dimensional-flow model of agent-based computational experiment for complex supply network evolution. Expert Syst Appl 42(5):2525–2537Google Scholar
  27. 27.
    Mailath GJ (1998) Do people play Nash equilibrium? Lessons from evolutionary game theory. J Econ Lit 36(3):1347–1374Google Scholar
  28. 28.
    Melnyk SA, Narasimhan R, DeCampos HA (2014) Supply chain design: issues, challenges, frameworks and solutionsGoogle Scholar
  29. 29.
    Nagurney A (2010) Supply chain network design under profit maximization and oligopolistic competition. Transp Res Part E: Log Transp Rev 46(3):281–294Google Scholar
  30. 30.
    Petersen KJ, Handfield RB, Ragatz GL (2005) Supplier integration into new product development: coordinating product, process and supply chain design. J Oper Manag 23(3-4):371–388Google Scholar
  31. 31.
    Roca CP, Cuesta JA, Sánchez A (2009) Evolutionary game theory: temporal and spatial effects beyond replicator dynamics. Phys Life Rev 6(4):208–249Google Scholar
  32. 32.
    Sha DY, Che ZH (2006) Supply chain network design: partner selection and production/distribution planning using a systematic model. J Oper Res Soc 57(1):52–62zbMATHGoogle Scholar
  33. 33.
    Shipilov AV (2009) Firm scope experience, historic multimarket contact with partners, centrality, and the relationship between structural holes and performance. Organ Sci 20(1):85–106Google Scholar
  34. 34.
    Shukla SK, Tiwari MK, Wan HD, Shankar R (2010) Optimization of the supply chain network: Simulation, Taguchi, and Psychoclonal algorithm embedded approach. Comput Ind Eng 58(1):29–39Google Scholar
  35. 35.
    Stuart TE (1998) Network positions and propensities to collaborate: an investigation of strategic alliance formation in a high-technology industry. Adm Sci Q 43(3):668–698Google Scholar
  36. 36.
    Sun DH, He W, Zheng LJ, Liao XY (2014) Scheduling flexible job shop problem subject to machine breakdown with game theory. Int J Prod Res 52(13):3858–3876Google Scholar
  37. 37.
    Tatikonda MV, Stock GN (2003) Product technology transfer in the upstream supply chain. J Product Innov Manag 20(6):444–467Google Scholar
  38. 38.
    Tian Y, Govindan K, Zhu QA (2014) System dynamics model based on evolutionary game theory for green supply chain management diffusion among Chinese manufacturers. J Clean Prod 80:96–105Google Scholar
  39. 39.
    Wiendahl HP, ElMaraghy HA, Nyhuis P, Zäh MF, Wiendahl HH, Duffie N, Brieke M (2007) Changeable manufacturing-classification, design and operation. CIRP Ann 56(2):783–809Google Scholar
  40. 40.
    Yu Z, Yan H, Edwin Cheng TC (2001) Benefits of information sharing with supply chain partnerships. Ind Manag Data Syst 101(3):114–121Google Scholar
  41. 41.
    Zaheer A, Bell GG (2005) Benefiting from network position: firm capabilities, structural holes, and performance. Strateg Manag J 26(9):809–825Google Scholar
  42. 42.
    Zhang S, Lee CKM, Wu K, Choy KL (2016) Multi-objective optimization for sustainable supply chain network design considering multiple distribution channels. Expert Syst Appl 65:87–99Google Scholar
  43. 43.
    Zsidisin GA, Smith ME (2005) Managing supply risk with early supplier involvement: a case study and research propositions. J Supply Chain Manag 41(4):44–57Google Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Zhendong Li
    • 1
  • Huiying Zhang
    • 1
  • Ke Jiang
    • 2
    • 3
    Email author
  • Mitchell Mainstone
    • 4
  1. 1.College of Management and EconomicsTianjin UniversityTianjinChina
  2. 2.Business SchoolCentral South UniversityChangshaChina
  3. 3.Manchester Institute of Innovation ResearchThe University of ManchesterManchesterUK
  4. 4.Hertford CollegeUniversity of OxfordOxfordUK

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