Logistics performance can be affected by the presence of uncertainties in the decision making process. To reduce decision making uncertainties, a topology of sources of supply chain ({SC)} uncertainty is proposed, in order to identify different types of uncertainty. A conceptual framework is developed for the analysis of decision making uncertainty sources in {SC’s}, providing the basis for the design and selection of improved {SC} scenarios. A case study is presented to illustrate the potential of simulation techniques in modeling scenarios for the Supply Chain: a set of performance measures is proposed, and results are obtained based on a predetermined selection criterion.
Supply chains (SCs) may experience instability induced by disturbances such as extreme climate conditions or accidents. These events can cause severe negative effects on SCs, jeopardising the on-time delivery of products and services to customers. This paper proposes a mapping framework to improve SC resilience to such events, avoiding possible failure modes. The proposed mapping framework allows identification of the current SC operation and possible transition states, together with points of vulnerability. An illustrative example of the framework applied to a real-life wine SC is presented.
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