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A fuzzy multicriteria approach for evaluating environmental performance of suppliers

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  • Awasthi, Anjali
  • Chauhan, Satyaveer S.
  • Goyal, S.K.
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    Abstract

    In this paper, we present a fuzzy multicriteria approach for evaluating environmental performance of suppliers. The proposed approach consists of three steps. The first step involves identification of criteria for assessing environmental performance of suppliers. In step 2, the experts rate the selected criteria and the various alternatives (suppliers) against each of the criteria. Linguistic assessments are used to rate the criteria and the alternatives. These linguistic ratings are then combined through fuzzy TOPSIS to generate an overall performance score for each alternative. The alternative with the highest score is chosen as the one with highest environmental performance. The advantage of using fuzzy TOPSIS is that it distinguishes between Benefit (the more the better) and the Cost (the less the better) category criteria and selects solutions that are close to the positive ideal solutions and far from negative ideal solutions. In step 3, sensitivity analysis is conducted to evaluate the influence of criteria weights on the environmental performance evaluation of suppliers. The strength of the proposed approach is its practical applicability and ability to provide solution under partial or lack of quantitative information. A numerical application is provided to demonstrate the proposed approach.

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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 126 (2010)
    Issue (Month): 2 (August)
    Pages: 370-378

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    Handle: RePEc:eee:proeco:v:126:y:2010:i:2:p:370-378

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    Web page: http://www.elsevier.com/locate/ijpe

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    Keywords: Multicriteria decision making Fuzzy theory TOPSIS Supplier selection Environmental performance;

    References

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    1. Handfield, Robert & Walton, Steven V. & Sroufe, Robert & Melnyk, Steven A., 2002. "Applying environmental criteria to supplier assessment: A study in the application of the Analytical Hierarchy Process," European Journal of Operational Research, Elsevier, vol. 141(1), pages 70-87, August.
    2. Degraeve, Zeger & Labro, Eva & Roodhooft, Filip, 2000. "An evaluation of vendor selection models from a total cost of ownership perspective," European Journal of Operational Research, Elsevier, vol. 125(1), pages 34-58, August.
    3. Ho, William & Xu, Xiaowei & Dey, Prasanta K., 2010. "Multi-criteria decision making approaches for supplier evaluation and selection: A literature review," European Journal of Operational Research, Elsevier, vol. 202(1), pages 16-24, April.
    4. Bai, Chunguang & Sarkis, Joseph, 2010. "Integrating sustainability into supplier selection with grey system and rough set methodologies," International Journal of Production Economics, Elsevier, vol. 124(1), pages 252-264, March.
    5. Liang, Gin-Shuh, 1999. "Fuzzy MCDM based on ideal and anti-ideal concepts," European Journal of Operational Research, Elsevier, vol. 112(3), pages 682-691, February.
    6. Weber, Charles A. & Current, John R. & Benton, W. C., 1991. "Vendor selection criteria and methods," European Journal of Operational Research, Elsevier, vol. 50(1), pages 2-18, January.
    7. Chen, Chen-Tung & Lin, Ching-Torng & Huang, Sue-Fn, 2006. "A fuzzy approach for supplier evaluation and selection in supply chain management," International Journal of Production Economics, Elsevier, vol. 102(2), pages 289-301, August.
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    Cited by:
    1. Ageron, Blandine & Gunasekaran, Angappa & Spalanzani, Alain, 2012. "Sustainable supply management: An empirical study," International Journal of Production Economics, Elsevier, vol. 140(1), pages 168-182.
    2. Xu, Jiuping & Ding, Can, 2011. "A class of chance constrained multiobjective linear programming with birandom coefficients and its application to vendors selection," International Journal of Production Economics, Elsevier, vol. 131(2), pages 709-720, June.
    3. Liu, Dehai & Li, Hongyi & Wang, Weiguo & Dong, Yucheng, 2012. "Constructivism scenario evolutionary analysis of zero emission regional planning: A case of Qaidam Circular Economy Pilot Area in China," International Journal of Production Economics, Elsevier, vol. 140(1), pages 341-356.
    4. Osiro, Lauro & Lima-Junior, Francisco R. & Carpinetti, Luiz Cesar R., 2014. "A fuzzy logic approach to supplier evaluation for development," International Journal of Production Economics, Elsevier, vol. 153(C), pages 95-112.
    5. Lo, Chris K.Y. & Yeung, Andy C.L. & Edwin Cheng, T.C., 2011. "Meta-standards, financial performance and senior executive compensation in China: An institutional perspective," International Journal of Production Economics, Elsevier, vol. 129(1), pages 119-126, January.
    6. Golmohammadi, Davood, 2011. "Neural network application for fuzzy multi-criteria decision making problems," International Journal of Production Economics, Elsevier, vol. 131(2), pages 490-504, June.
    7. Gold, Stefan & Hahn, Rüdiger & Seuring, Stefan, 2013. "Sustainable supply chain management in “Base of the Pyramid” food projects—A path to triple bottom line approaches for multinationals?," International Business Review, Elsevier, vol. 22(5), pages 784-799.
    8. Doukas, Haris, 2013. "Modelling of linguistic variables in multicriteria energy policy support," European Journal of Operational Research, Elsevier, vol. 227(2), pages 227-238.
    9. Huiru Zhao & Sen Guo, 2014. "Selecting Green Supplier of Thermal Power Equipment by Using a Hybrid MCDM Method for Sustainability," Sustainability, MDPI, Open Access Journal, vol. 6(1), pages 217-235, January.
    10. Du, Yuxian & Gao, Cai & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2014. "A new method of identifying influential nodes in complex networks based on TOPSIS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 57-69.
    11. Garcia, Fernanda A. & Marchetta, Martin G. & Camargo, Mauricio & Morel, Laure & Forradellas, Raymundo Q., 2012. "A framework for measuring logistics performance in the wine industry," International Journal of Production Economics, Elsevier, vol. 135(1), pages 284-298.

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