Estimating vulnerability to risks: an application in a biofuel supply chain |
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Authors: | Silvio Francisco dos Santos Humberto Siqueira Brandi Suzana Borschiver Vanderléa de Souza |
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Affiliation: | 1.Instituto Nacional de Metrologia,Qualidade e Tecnologia (Inmetro),Duque de Caxias,Brazil;2.Escola de Química,Universidade Federal do Rio de Janeiro (UFRJ),Rio de Janeiro,Brazil |
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Abstract: | In the present work, we propose a theoretical model to identify and prioritize risks involved in a biofuel supply chain. We adopt a set of indicators associated with determinant factors of the supply chain to identify risks that are characterized through a risk matrix. We consider the five largest world biodiesel producers and included China due to its global market importance and potential impacts of its growth on the environment and society. To determine the impacts and the probability of occurrence of risks, we use the Canberra distance, as metrics. To facilitate the analysis and interpretation, a convenient manner is to express the results in terms of matrices. To exemplify the potentiality of the scheme and for the sake of simplicity, a more comprehensive discussion is focused on the Brazilian case, restricted to the Technology and Innovation, and Integration, Logistics and Infrastructure determining factors (dimensions) of the biodiesel supply chain. Concerning these determining factors, the Brazilian biodiesel chain shows strong vulnerability when compared with developed and developing countries, despite that the evolution of the data over recent years indicates small improvements in Integration, Logistics and Infrastructure dimension. Although in this work the calculations are restricted to the Canberra distance, the present approach may be applied to other distances to compare or validate the results. This work presents a contribution to model vulnerability to risks, providing to policy makers and stakeholders a tool to design, analyze and improve sustainability system by measuring its risks. The study of the contribution of each indicator suggests corrections to be taken and which indicators should be prioritized. |
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