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Abstract

Supply Chain Network (SCN) is one of the most important elements of Logistic nowadays. One of the aspects, which is not covered very well in literature, is the one concerned to the mechanisms behind the connections that are established among players. In this work it was analysed the impact of the variation in the probabilities in being a member of a network, the relation of players with risk and respective effect on the SCN, the individualism versus collaborative approach of players and the problem solving effect. For that, it was developed a multi-agent based system. The obtained results demonstrate that experienced members prefer to establish links with other experienced members or repeated partners when the SCN are built for important businesses. The results also show the critical role of companies’ risk aversion conceiving a SCN.

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References

  1. Harland, C.M.: Supply chain management: relationships, chains and networks. Br. J. Manag. 7(s1), S63–S80 (1996)

    Article  Google Scholar 

  2. Guimerà, R., Uzzi, B., Spiro, J., Amaral, L.A.: Team assembly mechanisms determine collaboration network structure and team performance. Science 308(5722), 697–702 (2005). https://doi.org/10.1126/science.1106340

    Article  Google Scholar 

  3. Vitasek, K.: Supply Chain and Logistics: Terms and Glossary. Supply Chain Visions, Bellevue (2006)

    Google Scholar 

  4. Webster, S.: Principles and Tools for Supply Chain Management. McGraw-Hill Irwin, Boston (2008)

    Google Scholar 

  5. Slack, N., Chambers, S., Johnston, R.: Operations and Process Management: Principles and Practice for Strategic Impact. Prentice Hall/Financial Times, Upper Saddle River (2009). ISBN 9780273718512

    Google Scholar 

  6. Chopra, S., Meindl, P.: Supply Chain Management. Pearson International Edition, Thousand Oaks (2007)

    Google Scholar 

  7. Klibi, W., Martel, A.: Scenario-based supply chain network risk modeling. Eur. J. Oper. Res. 223(3), 644–658 (2012). https://doi.org/10.1016/j.ejor.2012.06.027

    Article  Google Scholar 

  8. Watson, M., Lewis, S., Cacioppi, P., Jayaraman, J.: Supply Chain Network Design: Applying Optimization & Analytics to Global Supply Chain, p. 1. Pearson Education, Inc., Thousand Oaks (2013). ISBN 978–0-13-301737-3

    Google Scholar 

  9. Wang, F., Lai, X., Shi, N.: A multi-objective optimization for green supply chain network design. Decis. Support Syst. 51, 262–269 (2011)

    Article  Google Scholar 

  10. Fattahi, M., Govindan, K., Keyvanshokooh, E.: Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers. Transp. R. Part E: Logistics Transp. Rev. 101, 176–200 (2017)

    Article  Google Scholar 

  11. Trkman, P., McCormack, K.: Supply chain risk in turbulent environments: a conceptual model for managing supply chain network risk. Int. J. Prod. Econ. 119(2), 247–258 (2009). https://doi.org/10.1016/j.ijpe.2009.03.002

    Article  Google Scholar 

  12. Pishvaee, M., Razmi, J.: Environmental supply chain network design using multi-objective fuzzy mathematical programming. Appl. Math. Model. 36(8), 3433–3446 (2012). https://doi.org/10.1016/j.apm.2011.10.00

    Article  MathSciNet  MATH  Google Scholar 

  13. Guide Jr., V., Van Wassenhove, L.: The reverse supply chain. Harvard Business Review (2002)

    Google Scholar 

  14. Pishvaee, M.S., Torabi, S.A.: A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy Sets Syst. Theme: Games Optim. Discrete Struct. 161(20), 2668–2683 (2010). https://doi.org/10.1016/j.fss.2010.04.010

    Article  MathSciNet  MATH  Google Scholar 

  15. Lonsdale, C.: Effectively managing vertical supply relationships: a risk management model for outsourcing. Supply Chain Manag.: Int. J. 4(4), 176–183 (1999)

    Article  Google Scholar 

  16. Wilensky, U.: NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL (1999). http://ccl.northwestern.edu/netlogo/

  17. Bakshy, E., Wilensky, U.: NetLogo Team Assembly Model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL (2007). http://ccl.northwestern.edu/netlogo/models/TeamAssembly

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Correspondence to Nuno Trindade Magessi .

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Magessi, N.T., Antunes, L. (2019). The Supply Chain Network Integration. In: De La Prieta, F., et al. Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection. PAAMS 2019. Communications in Computer and Information Science, vol 1047. Springer, Cham. https://doi.org/10.1007/978-3-030-24299-2_4

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  • DOI: https://doi.org/10.1007/978-3-030-24299-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24298-5

  • Online ISBN: 978-3-030-24299-2

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