Consensus Building in a Group Decision-Making Process

Zamora, Yankiel Blanco

doi:10.1590/0101-7438.2020.040.00235350

Cited by 1 publication

(1 citation statement)

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“…To generate a final ranking regarding the most characteristic risks of the supply chain studied, the next step is to aggregate the six individual rankings, which are obtained for the decision-makers of each company. Based on the literature, there are several methods to measure the consensus and stability of a group of decision-makers (Zamora, 2020). However, this study presents a differential approach when exploring the outcome of the prioritisation of each decision-maker by the CPP method as input to the aggregation procedure and formulation of the final risk ranking, which is obtained using the result of Kendall's W coefficient of agreement.…”

Section: Numerical Applicationmentioning

confidence: 99%

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

Casado

Silva

2022

IJQRM

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PurposeThe paper aims to propose a multi-criteria model for risk prioritisation associated to supply chain management involving multiple decision-makers.Design/methodology/approachThe 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.FindingsContrary 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/implicationsThe focus was restricted to the use of only internal chain risks.Practical implicationsThe 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/valueEstablishing 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.

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Section: Numerical Applicationmentioning

confidence: 99%