Abstract
This paper is aimed and formalizing an objective method to analyze and assess operational risk in supply chain. The proposed approach consist of exploiting the analogy among logistic networks and dynamical systems; in particular, it proposes to identify the risky events characterizing a generic supply chain by studying its attributed Petri net and the corresponding coverability graph, whereas it suggests to assess the risky events effects by building the logistic network simulation model, experimenting on it and applying ANOVA to analyze the results and, then, define the order of importance among the risky events previously figured out. Finally, the method has been applied to a single-item, 3-stages supply chain to show how it can be practically used.