1 SUPPLY NETWORK TOPOLOGY AND ROBUSTNESS AGAINST DISRUPTIONS – AN INVESTIGATION USING MULTIAGENT MODEL

In this study we examine the relationship between supply network's topology and its robustness in the presence of random failures and targeted attacks. The agent based model developed in this paper uses the basic framework and parameters in the experimental game presented in Sterman (1989) for modeling adaptive managerial decision making in an inventory management context. The study extends the linear supply chain context to a complex supply network and undertakes a rigorous examination of robustness of these supply networks that are characterized by distinct network characteristics. We theorize that network characteristics such as average path length, clustering coefficient, size of the largest connected component in the network and the maximum distance between nodes in the largest connected component are related to the robustness of supply networks, and test the research hypotheses using data from several simulation runs. Simulations were carried out using twenty distinct network topologies where ten of these topologies were generated using preferential attachment approach (based on the theory of scale-free networks) and the remaining ten topologies were generated using random attachment approach (using random graph theory as a foundation). These twenty supply networks were subjected to random demand and their performances were evaluated by considering varying probabilities of random failures of nodes and targeted attacks on nodes. We also consider the severity of these disruptions by considering the downtime of the affected nodes. Using the data collected from a series of simulation experiments, we test the research hypotheses by means of binomial logistic regression analysis. The results point towards a significant association between network characteristics and supply network robustness assessed using multiple performance measures. We discuss the implications of the study and present directions for future research.

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