From naive supply chain risk concepts to computable risk-curves

Resource type
Iris Heckmann
The literature on supply chain risk analysis is mostly of anecdotal or case-based nature and only few authors present empirical research. Quantitative, systematic and reliable analyses are scarce. Mathematical optimization approaches focus on a small number of variables and, therefore, are less suitable to model numerous interacting characteristics, which prevail in nowadays supply chain systems. Additionally, supply chain risk definitions are scarce and neglect the need for quantitative assessment. Instead, simulation is more appropriate as a method to model and analyze complex systems. In this talk we present our definition of supply chain risk (Heckmann et al. 2015) and a simulation-based approach for the analysis of supply chain risk. The main goal of the presented simulation model is to provide the user with valid and credible implications on the dynamics that drive the underlying supply chain and that potentially make supply chain risk effective when disturbances occur. In order to demonstrate the operationalization of the newly derived supply chain risk definition by the simulation approach we introduce and present risk-curves. For the sake of conceptual and methodological consistency the approach models and respects the defining entities of supply chain risk.
Research focus
Logistics and Supply Chain Optimisation
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