IDEAS home Printed from https://ideas.repec.org/a/ids/ijores/v35y2019i1p1-19.html
   My bibliography  Save this article

Application of fuzzy ANP method to select the best supplier in the supply chain

Author

Listed:
  • Habibollah Danai
  • Shahram Hashemnia
  • Rokhshad Ahmadi
  • Seyed Hojjat Bazazzadeh

Abstract

Positive performance of the purchase department has a direct impact on reducing cost and increasing profitability, and survival of the supply chain. One of the major tasks of the purchase department in the supply chain is to evaluate and select suppliers. The process of selecting a suitable supplier among different options and variables is an important task. Inappropriate selection of supplier in addition to imposing more costs will have devastating impacts on the organisation's performance. The main objective of this study is to provide a useful approach to fuzzy ANP for evaluation of issues related to supplier selection. Many quantitative and qualitative concerns may be brought by the issues related to supplier selection, they are complicated issues. In this study, an ANP model was designed in fuzzy environment; through which the best accessories suppliers in HivaSanat Company are identified and prioritised.

Suggested Citation

  • Habibollah Danai & Shahram Hashemnia & Rokhshad Ahmadi & Seyed Hojjat Bazazzadeh, 2019. "Application of fuzzy ANP method to select the best supplier in the supply chain," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 35(1), pages 1-19.
    • Handle: RePEc:ids:ijores:v:35:y:2019:i:1:p:1-19
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=99540
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pankaj Dutta & Bharath Jaikumar & Manpreet Singh Arora, 2022. "Applications of data envelopment analysis in supplier selection between 2000 and 2020: a literature review," Annals of Operations Research, Springer, vol. 315(2), pages 1399-1454, August.
    2. Aquib Irteza Reshad & Tasnia Biswas & Renu Agarwal & Sanjoy Kumar Paul & Abdullahil Azeem, 2023. "Evaluating barriers and strategies to sustainable supply chain risk management in the context of an emerging economy," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4315-4334, November.

    More about this item

    Keywords

    fuzzy ANP; supply chain.;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijores:v:35:y:2019:i:1:p:1-19. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=170 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.