The evolutionary complexity of complex adaptive supply networks: A simulation and case study
A supply chain should be treated not just as a supply chain but also as a complex adaptive supply network (CASN). However, the literature on supply chain management has given little attention to the evolutionary complexity of the network structure and collaboration mechanism of CASNs. In this paper, we first model and simulate the evolution of CASNs based on complex adaptive system and fitness landscape theory. The simulation results indicate the evolutionary complexities such as emergence, quasi-equilibrium, chaos, and lock-in of CASNs. Then, a case study of the evolution of the LVEA (low voltage equipment apparatus) supply network in the emerging Chinese market has been explored to validate the findings from the simulation and develop a better understanding of the general principles influencing the emergence, adaptation and evolution of CASNs in the real world. Based on the simulation and the case study, we propose some propositions about the factors and principles influencing the evolutionary complexity of CASNs. The external environment factors and firm-internal mechanisms appear to be the dominant forces that shape the gradual evolution of CASNs. Factors in the external environment, such as government regulation, market demand and market structure appear to have a long-term impact on the evolution, while a firm's strategies, product structure, technology, and organization appear to be the internal factors that exert an immediate influence on the evolution of CASNs. Among these factors, cost and quality considerations appear to be the primary forces that influence the structure complexity, centralization and formalization of CASNs.
Year of publication: |
2010
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Authors: | Li, Gang ; Yang, Hongjiao ; Sun, Linyan ; Ji, Ping ; Feng, Lei |
Published in: |
International Journal of Production Economics. - Elsevier, ISSN 0925-5273. - Vol. 124.2010, 2, p. 310-330
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Publisher: |
Elsevier |
Keywords: | Supply chain management Operation strategy Case study research Simulation Complex adaptive system Complexity |
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