An approach for green supplier selection in the automobile manufacturing industry

Qian Yu, Fujun Hou

    Research output: Contribution to journalArticlepeer-review

    70 Citations (Scopus)

    Abstract

    Purpose – The purpose of this paper is to study a modified multiplicative analytic hierarchy process (MMAHP) method, which is combined with multi-criteria decision making (MCDM) and applied MMAHP model for solving green supplier selection problem. Design/methodology/approach – Supplier selection is typically a MCDM problem including both qualitative and quantitative factors that has to be taken into consideration. To select the best green suppliers with the highest potential for meeting a firm’s needs consistently, the MMAHP is utilized in this study. Then a green supplier selection problem of a well-known automobile manufacturing company in Qingdao is investigated. The authors also make a comparison of the results with that of the traditional AHP, during which the authors observe that the MMAHP is an effective approach for the considered problem and potential rank reversals can be avoided, that is, when a new supplier is added, the ranking of suppliers does not change and maintains its original relative ratio. Findings – A numerical example of green supplier selection is utilized to verify the proposed approach. The results show that the MMAHP is an effective approach for the considered problem and potential rank reversals can be avoided. Practical implications – The proposed approach can be used to solving green supplier selection problems and can avoid the rank reversal. Originality/value – The paper introduces the MMAHP method to help researchers to choose more effective approach for green supplier selection.

    Original languageEnglish
    Pages (from-to)571-588
    Number of pages18
    JournalKybernetes
    Volume45
    Issue number4
    DOIs
    Publication statusPublished - 4 Apr 2016

    Keywords

    • Green supply chain management
    • Modelling
    • Modified multiplicative AHP (MMAHP)
    • Operational research
    • Supplier selection

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