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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

A group decision approach for supplier categorization based on hesitant fuzzy and ELECTRE TRI

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Autor(es):
Galo, Nadya Regina [1] ; Del Rosso Calache, Lucas Daniel [1] ; Ribeiro Carpinetti, Luiz Cesar [1]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Sao Carlos Sch Engn, Prod Engn Dept, Av Trabalhador Sancarlense 400, BR-13566590 Sao Carlos, SP - Brazil
Número total de Afiliações: 1
Tipo de documento: Artigo Científico
Fonte: INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS; v. 202, p. 182-196, AUG 2018.
Citações Web of Science: 8
Resumo

Supplier evaluation and categorization is an important decision process in supplier management. It relies on judgements by multiple decision makers about the performance of a supplier on a set of criteria. Uncertainty of judgements, non-compensation between criteria and group decision are the main requirements of the decision process that have to be considered. However, none of the studies found in the literature presents a solution that contemplates all this requirements at the same time. Therefore, aiming to bridge this gap, this paper proposes an approach to supplier categorization based on the use of ELECTRE TRI combined with hesitant fuzzy. ELECTRE TRI is a non-compensatory multicriteria decision making method specific for categorization. Hesitant fuzzy is used prior to it to aggregate linguistic judgements of multiple decision makers. The decision process model is detailed and implemented in Matlab(C). Analyses of the results of an illustrative case of application in the automotive industry show consistent categorization results, particularly using the pessimistic ELECTRE TRI categorization procedure. But, when there is too much discordance, negotiation techniques may be a better option. Also, test with different criteria weights showed no change in the categorization results, confirming the non-compensatory effect of the technique. (AU)

Processo FAPESP: 16/14618-4 - Gestão de desempenho de fornecedores: estudo de técnicas multicritério e de inteligência artificial para decisão em grupo
Beneficiário:Luiz Cesar Ribeiro Carpinetti
Modalidade de apoio: Auxílio à Pesquisa - Regular