Supply chain simulation integrating agent-based modeling with social network analysis: A conceptual framework

This paper proposes a conceptual framework for modeling and simulating dynamic behaviors of supply chain by using agent-based modeling (ABM) and social network analysis (SNA). Conventional approaches for simulation in Supply Chain Management (SCM) usually have focused on decision-making problems about controlling the flow of materials through physical relationships between firms. In SCM, however, many different types of decision-making problems can occurr, as well as the scope of interactions should be extended. Therefore, we propose a conceptual model of the framework to support the simulation with wide applicability to all sorts of different problems and interactions in SCM. By adopting the concept of ABM-based SNA, the scope of interactions are extended to the social relationships, which is included as one of modeling components for the supply chain network. In the proposed framework, dynamic behaviors of firms in supply chain are simulated by making interdependent decisions, and then they interact by influencing on each other. Finally, we can analyze the influencing of their decisions and interactions on the overall performance of supply chain. Thus, the proposed framework can provide guidelines for re-engineering of the supply chain by expecting how the dynamics of each firm's status, behavior, propensity, policy and strategy impact with the supply chain. ICIC International © 2012.