Proposal of a supply risk prioritization method based on the application of fuzzy techniques and cognitive maps for group decision making

Abstract

Supply Chain Risk Management (SCRM) is an issue that has received importance in the literature in recent years. In SCRM, supply risk assessment attracts the largest volume of research, where five major research opportunities have been identified: (1) adequately deal with the imprecision present in human assessments due to their uncertainties or lack of data, (2) using a suitable technique for the decision process to be in a group, (3) appropriately addressing compensation and non-compensation between criteria, (4) estimating risks through cause and effect dependencies between them and (5) use real data for the application of risk management models in the supply chain. To contemplate these opportunities, the present project aims to propose a decision-making model that combines the Fuzzy Delphi technique to obtain a consensus of the experts opinions during the group judgment process; Fuzzy Inference System, to find the degree of importance for each risk assessed in a compensatory and non-compensatory approach; and Fuzzy Cognitive Maps, to update the risks' importance based on the influence between them. The project also includes the computational modeling of the proposal and the implementation of a pilot application to prioritize the supply risks that have the greatest impact on the evaluation of decision makers. Thus, the advantages, difficulties and limitations identified during the pilot application of the proposed model will be analyzed. This master's project is related to another project financed by FAPESP (process 2016/14618-4), which is liked to the project INCT - INSID - Instituto Nacional de Sistemas de Informação e Decisão. (AU)