Multi-criteria decision model for risk prioritisation involving multiple decision-makers: an application of composition of probabilistic preferences combined with FMEA in the supply chain

Abstract

Purpose

The paper aims to propose a multi-criteria model for risk prioritisation associated to supply chain management involving multiple decision-makers.

Design/methodology/approach

The model integrates the composition of probabilistic preferences (CPP) on the failure modes analysis and its effects (FMEA) criteria. First, the authors carried out a probabilistic transformation of the numerical evaluations of the multiple decision-makers on the FMEA criteria regarding the internal risks that affect the chain of clothing pole in the Agreste region of Pernambuco. Then, the authors proposed the use of the Kendall's concordance coefficient W to aggregate these evaluations.

Findings

Contrary to expectations, the two main risks to be investigated as a model suggestion was related to the context of supply chain suppliers and not related to the raw material costs. Besides, a simulation with the traditional FMEA was carried out, and comparing with the model result, the simulation is worth highlighting seven consistent differences along the two rankings.

Research limitations/implications

The focus was restricted to the use of only internal chain risks.

Practical implications

The proposed model can contribute to the improvement of the decisions within organisations that make up the chains, thus guaranteeing a better quality in risk management.

Originality/value

Establishing a more effective representation of uncertain information related to traditional FMEA treatment involving multiple decision-makers means identifying in advance the potential risks, providing a better supply chain control.

Citation

Casado, R.S.G.R., Silva, M.M. and Silva, L.C. (2023), "Multi-criteria decision model for risk prioritisation involving multiple decision-makers: an application of composition of probabilistic preferences combined with FMEA in the supply chain", International Journal of Quality & Reliability Management, Vol. 40 No. 3, pp. 709-726. https://doi.org/10.1108/IJQRM-03-2020-0065