Supply Chain Challenges with Complex Adaptive System Perspective

  • Abla Chaouni Benabdellah
  • Imane Bouhaddou
  • Asmaa Benghabrit
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 745)

Abstract

At first glance, a supply chain is a complex system, since a slight change in one activity may cause tremors everywhere. In fact, the system is an interconnected autonomous entity that makes choices to survive, to evolve, and to be self-organized over time. Within a dynamic environment, several disciplines have adopted the Complex Adaptive System (CAS) perspective. Hence, the main purpose of this paper is to explore the supply chain as a CAS. In addition, using the complexity theory, the knowledge gained from this matching can be beneficial for supply chain to move from the static and the isolated field to dynamic and connected one.

Keywords

Supply chain complexity Complex adaptive system (CAS) Organizational approach Analytic and simulation models 

References

  1. 1.
    Christopher, M.: Logistics and Supply Chain Management. Pearson, UK (2016)Google Scholar
  2. 2.
    Pathak, S.D., et al.: Complexity and adaptivity in supply networks: building supply network theory using a complex adaptive systems perspective. Decis. Sci. 38(4), 547–580 (2007)CrossRefGoogle Scholar
  3. 3.
    Cooper, M.C., Ellram, L.M.: Characteristics of supply chain management and the implications for purchasing and logistics strategy. Int. J. Logist. Manag. 4(2), 13–24 (1993)CrossRefGoogle Scholar
  4. 4.
    Van der Vorst, J.G.A.J., Beulens, A.J.M.: Identifying sources of uncertainty to generate supply chain redesign strategies. Int. J. Phys. Distrib. Logist. Manag. 32(6), 409–430 (2002)CrossRefGoogle Scholar
  5. 5.
    Isik, F.: Complexity in supply chains: a new approach to quantitative measurement of the supply-chain-complexity. In: Supply chain management. InTech (2011)Google Scholar
  6. 6.
    Bouhaddou, I., Benabdelhafid, A.: Product Lifecycle Management (PLM): a key to manage supply chain complexity. In: First Complex Systems Digital Campus World E-Conference 2015. Springer, Cham (2017)Google Scholar
  7. 7.
    Perera, S.S., Bell, M., Bliemer, M.: Modelling supply chains as complex networks for investigating resilience: an improved methodological framework. In: Proceedings of the 37th Australasian Transport Research Forum (ATRF), Sydney, Australia, vol. 30 (2015)Google Scholar
  8. 8.
    Protopappa-Sieke, M., Thonemann, U.W. (eds.): Supply Chain Segmentation: Best-in-Class Cases, Practical Insights and Foundations. Springer, Heidelberg (2017)Google Scholar
  9. 9.
    Cheng, C.-Y., Chen, T.-L., Chen, Y.-Y.: An analysis of the structural complexity of supply chain networks. Appl. Math. Model. 38(9), 2328–2344 (2014)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Serdarasan, S.: A review of supply chain complexity drivers. Comput. Ind. Eng. 66(3), 533–540 (2013)CrossRefGoogle Scholar
  11. 11.
    Vogel, W., Lasch, R.: Complexity drivers in manufacturing companies: a literature review. Logist. Res. 9(1), 25 (2016)CrossRefGoogle Scholar
  12. 12.
    Calinescu, A., et al.: Complexity in manufacturing: an information theoretic approach. In: Proceedings of the International Conference on Complex Systems and Complexity in Manufacturing, vol. 19. Warwick University (2000)Google Scholar
  13. 13.
    Efthymiou, K., et al.: Manufacturing systems complexity review: challenges and outlook. Procedia CIRP 3, 644–649 (2012)CrossRefGoogle Scholar
  14. 14.
    Manuj, I., Sahin, F.: A model of supply chain and supply chain decision-making complexity. Int. J. Phys. Distrib. Logist. Manag. 41(5), 511–549 (2011)CrossRefGoogle Scholar
  15. 15.
    Vanpoucke, E., et al.: Leveraging the impact of supply chain integration through information technology. Int. J. Oper. Prod. Manag. 37(4), 510–530 (2017)CrossRefGoogle Scholar
  16. 16.
    Kirwan, J., Maye, D., Brunori, G.: Acknowledging complexity in food supply chains when assessing their performance and sustainability. J. Rural Stud. 52, 21–32 (2017)CrossRefGoogle Scholar
  17. 17.
    Morin, E.: Restricted complexity, general complexity. In: Science and us: Philosophy and Complexity, pp. 1–25. World Scientific, Singapore (2007)Google Scholar
  18. 18.
    Gell-Mann, M.: Complex adaptive systems, pp. 17–45 (1994)Google Scholar
  19. 19.
    Blecic, I., Cecchini, A., Trunfio, G.A.: A decision support tool coupling a causal model and a multi-objective genetic algorithm. Appl. Intell. 26(2), 125–137 (2007)CrossRefGoogle Scholar
  20. 20.
    Surana, A., et al.: Supply-chain networks: a complex adaptive systems perspective. Int. J. Prod. Res. 43(20), 4235–4265 (2005)CrossRefGoogle Scholar
  21. 21.
    Luo, J., Hessami, A.G.: Emergent properties and requirements evolution in engineering systems and a roadmap. In: 2015 Third World Conference on Complex Systems (WCCS). IEEE (2015)Google Scholar
  22. 22.
    DeMattos, P.C., Miller, D.M., Park, E.H.: Decision making in trauma centers from the standpoint of complex adaptive systems. Manag. Decis. 50(9), 1549–1569 (2012)CrossRefGoogle Scholar
  23. 23.
    Chan, S.: Complex adaptive systems. In: ESD. 83 Research Seminar in Engineering Systems, vol. 31 (2001)Google Scholar
  24. 24.
    Niazi, M.A.: Complex adaptive systems modeling: a multidisciplinary roadmap. Complex Adapt. Syst. Model. 1(1), 1 (2013)CrossRefGoogle Scholar
  25. 25.
    Scott, W.R., Davis, G.F.: Organizations and Organizing: Rational, Natural and Open Systems Perspectives. Routledge, Abingdon (2015)Google Scholar
  26. 26.
    Prokopenko, M.: Guided self‐organization, pp. 287–289 (2009)CrossRefGoogle Scholar
  27. 27.
    Arthur, W.B.: Out-of-equilibrium economics and agent-based modeling. Handb. Comput. Econ. 2, 1551–1564 (2006)CrossRefGoogle Scholar
  28. 28.
    Newman, M.E.J.: Complex systems: a survey. arXiv preprint arXiv:1112.1440 (2011)
  29. 29.
    Sayama, H.: Introduction to the Modeling and Analysis of Complex Systems. Open SUNY Textbooks, Geneseo (2015)Google Scholar
  30. 30.
    Cindy, E., et al.: Understanding complex systems: somme core challenges. J. Learn. Sci. 5, 53–61 (2013)Google Scholar
  31. 31.
    Barrat, A., Barthelemy, M., Vespignani, A.: Dynamical Processes on Complex Networks. Cambridge University Press, Cambridge (2008)CrossRefGoogle Scholar
  32. 32.
    Johnson, D.S.: The NP-completeness column: an ongoing gulde. J. Algorithms 3(4), 381–395 (1982)MathSciNetCrossRefGoogle Scholar
  33. 33.
    Moore, C., Mertens, S.: The Nature of Computation. OUP Oxford, Oxford (2011)CrossRefGoogle Scholar
  34. 34.
    Szathmáry, E., Smith, J.M.: The major evolutionary transitions. Nature 374(6519), 227–232 (1995)CrossRefGoogle Scholar
  35. 35.
    Gould, S.J.: The Structure of Evolutionary Theory. Harvard University Press, Cambridge (2002)Google Scholar
  36. 36.
    Dawkins, R.: The Selfish Gene. Oxford University Press, Oxford (1976)Google Scholar
  37. 37.
    Gintis, H.: The Bounds of Reason: Game Theory and the Unification of the Behavioral Sciences. Princeton University Press, Princeton (2014)CrossRefGoogle Scholar
  38. 38.
    Schelling, T.C.: Dynamic models of segregation. J. Math. Sociol. 1(2), 143–186 (1971)CrossRefGoogle Scholar
  39. 39.
    Ray, T.S.: An approach to the synthesis of life, pp. 371–408 (1991)Google Scholar
  40. 40.
    Epstein, J.M., Axtell, R.L.: Growing Artificial Societies: Social Science from the Bottom Up. MIT Press, Cambridge (1996)Google Scholar
  41. 41.
    Grimm, V., Railsback, S.F.: Individual-based Modeling and Ecology. Princeton University Press, Princeton (2013)MATHGoogle Scholar
  42. 42.
    Gilbert, N.: Agent-Based Models, vol. 153. Sage, Thousand Oaks (2008)CrossRefGoogle Scholar
  43. 43.
    Boccaletti, S., et al.: Complex networks: structure and dynamics. Phys. Rep. 424(4), 175–308 (2006)MathSciNetCrossRefGoogle Scholar
  44. 44.
    Cohen, R., Havlin, S.: Complex Networks: Structure, Robustness and Function. Cambridge University Press, Cambridge (2010)CrossRefGoogle Scholar
  45. 45.
    Cossentino, M., Potts, C.: A CASE tool supported methodology for the design of multi-agent systems. In: International Conference on Software Engineering Research and Practice (SERP 2002) (2002)Google Scholar
  46. 46.
    Newman, M.: Networks: An Introduction. Oxford University Press, Oxford (2010)CrossRefGoogle Scholar
  47. 47.
    Nicolis, G., Prigogine, I., Nocolis, G.: Exploring complexity (1989)Google Scholar
  48. 48.
    Gardner, M.: Mathematical games: the fantastic combinations of John Conway’s new solitaire game “life”. Sci. Am. 223(4), 120–123 (1970)CrossRefGoogle Scholar
  49. 49.
    Feigenbaum, M.J.: Quantitative universality for a class of nonlinear transformations. J. Stat. Phys. 19(1), 25–52 (1978)MathSciNetCrossRefGoogle Scholar
  50. 50.
    Ilachinski, A.: Cellular Automata: A Discrete Universe. World Scientific Publishing Co Inc, Singapore (2001)CrossRefGoogle Scholar
  51. 51.
    Shannon, C.E.: Communication theory of secrecy systems. Bell Labs Techn. J. 28(4), 656–715 (1949)MathSciNetCrossRefGoogle Scholar
  52. 52.
    Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley, Hoboken (2012)MATHGoogle Scholar
  53. 53.
    Badii, R., Politi, A.P., Strogatz, S.H.: Complexity: hierarchical structures and scaling in physics. Nature 387(6635), 771 (1997)CrossRefGoogle Scholar
  54. 54.
    Akaike, H.: Information theory and an extension of the maximum likelihood principle. In: Selected Papers of Hirotugu Akaike, pp. 199–213. Springer, New York (1998)Google Scholar
  55. 55.
    Zhou, L., Naim, M.M., Disney, S.M.: The impact of product returns and remanufacturing uncertainties on the dynamic performance of a multi-echelon closed-loop supply chain. Int. J. Prod. Econ. 183, 487–502 (2017)CrossRefGoogle Scholar
  56. 56.
    Zhang, W.-B.: Theory of complex systems and economic dynamics. Nonlinear Dyn. Psychol. Life Sci. 6(2), 83–101 (2002)CrossRefGoogle Scholar
  57. 57.
    Grussenmeyer, R., Blecker, T.: Complexity and robustness influence on production performance – a theoretical framework. In: Kompetenz, Interdisziplinarität und Komplexität in der Betriebswirtschaftslehre, pp. 57–69. Springer Fachmedien, Wiesbaden (2013)CrossRefGoogle Scholar
  58. 58.
    Caridi, M., et al.: Do virtuality and complexity affect supply chain visibility? Int. J. Prod. Econ. 127(2), 372–383 (2010)MathSciNetCrossRefGoogle Scholar
  59. 59.
    Blome, C., Schoenherr, T., Rexhausen, D.: Antecedents and enablers of supply chain agility and its effect on performance: a dynamic capabilities perspective. Int. J. Prod. Res. 51(4), 1295–1318 (2013)CrossRefGoogle Scholar
  60. 60.
    Gerschberger, M., Hohensinn, R.: Supply chain configuration–comparison of supplier evaluation attempts. Logist. Sustain. Transp. 4(1), 12–17 (2013)Google Scholar
  61. 61.
    Feynman, R.P., et al.: Elementary Particles and the Laws of Physics: The 1986 Dirac Memorial Lectures. Cambridge University Press, Cambridge (1987)CrossRefGoogle Scholar
  62. 62.
    Choi, T.Y., Dooley, K.J., Rungtusanatham, M.: Supply networks and complex adaptive systems: control versus emergence. J. Oper. Manag. 19(3), 351–366 (2001)CrossRefGoogle Scholar
  63. 63.
    Cossentino, M., et al.: ASPECS: an agent-oriented software process for engineering complex systems. Auton. Agent. Multi-Agent Syst. 20(2), 260–304 (2010)CrossRefGoogle Scholar
  64. 64.
    Koestler, A.: Beyond atomism and holism—the concept of the holon, pp. 192–232 (1969)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Abla Chaouni Benabdellah
    • 1
  • Imane Bouhaddou
    • 1
  • Asmaa Benghabrit
    • 2
  1. 1.LM2I Laboratory ENSAMMoulay Ismail UniversityMeknesMorocco
  2. 2.LMAID Laboratory, ENSMRMohamed V UniversityRabatMorocco

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