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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Combining SCOR (R) model and fuzzy TOPSIS for supplier evaluation and management

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Author(s):
Lima-Junior, Francisco Rodrigues [1] ; Ribeiro Carpinetti, Luiz Cesar [1]
Total Authors: 2
Affiliation:
[1] Univ Sao Paulo, Sch Engn Sao Carlos, Dept Prod Engn, Ave Trabalhador Sancarlense 400, BR-13566590 Sao Carlos, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS; v. 174, p. 128-141, APR 2016.
Web of Science Citations: 30
Abstract

Evaluating suppliers and supporting their continuous improvement have become critical for supply chain (SC) performance management. Since the performance of an organization in a SC depends on the performance of its suppliers, it is desirable that the evaluation of a supplier can be integrated to the evaluation of the SC. Few studies propose decision making models to aid the supplier evaluation for development. However, these studies adopt criteria similar to ones used in supplier selection, which can lead to a mismatch between supplier and SC performance evaluations. Therefore, to overcome this lack of alignment, this article presents a new approach that uses the performance metrics of the SCOR (R) (Supply Chain Operations Reference) model to evaluate the suppliers in the dimensions cost and delivery performance. It combines two fuzzy TOPSIS models for evaluating and categorizing the suppliers in four groups depending on their performance evaluation. According to their categorization, directives for action plans are proposed. An illustrative application was developed based on a manufacturing context. The combination between the SCOR (R) and fuzzy TOPSIS brings several benefits when compared with other approaches, such as: it facilitates the integration of the processes of performance evaluation of the suppliers and the SC; it enables benchmarking against other SCs; the fuzzy TOPSIS requires few judgments to parameterization, which contributes to the agility of the decision process; it does not limit the number of alternatives simultaneously evaluated; it does not cause the ranking reversal problem when a new supplier is included in the evaluation process. (C) 2016 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 11/10241-0 - Quality management of suppliers: segmentation and analysis of performance indicators to supplier management
Grantee:Luiz Cesar Ribeiro Carpinetti
Support Opportunities: Regular Research Grants