Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Self-Organization in Biological Systems
Self-Organization in Biological Systems
Supply chain modeling: past, present and future
Computers and Industrial Engineering - Supply chain management
Emergent Supply Networks: System Dynamics Simulation of Adaptive Supply Agents
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 3 - Volume 3
Emergent Structures in Supply Chains " A Study Integrating Agent-Based and System Dynamics Modeling
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 3 - Volume 3
Proceedings of the 35th conference on Winter simulation: driving innovation
Global supply network health: Analysis and visualization
Information-Knowledge-Systems Management - Enterprise Transformation: Manufacturing in a Global Enterprise
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A supply network (SN) is a complex adaptive system, and its structure and collaboration mechanism evolves over time. However, most literature views SN as a static system and the study on the evolution of SNs is very limited. Based on complex adaptive system and fitness landscape theory, this paper first proposes an evolution model of SNs in order to understand the general principle of SN evolution. Then the paper conducts a multi-agent simulation on the evolution model, and discloses that the SN emerges and evolves from firms' dynamic interaction under the dynamic environment. Dominated by the environment and firms' internal mechanism, the evolution is highly sensitive to the initial condition, and it is path-dependent and difficult to predict precisely. Although the dynamics of environments is different, a SN enjoys the stable structure in different environments. Higher level of structure stability and fitness of the SN are achieved when the firms in the SN adopt the long-term collaboration strategy rather than the short-term strategy. Finally, a China case is explored which validates the self-organization evolution of SNs.