IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v349y2025i2d10.1007_s10479-019-03456-z.html
   My bibliography  Save this article

A novel fuzzy reference-neighborhood rough set approach for green supplier development practices

Author

Listed:
  • Chunguang Bai

    (University of Electronic Science and Technology of China)

  • Kannan Govindan

    (University of Southern Denmark)

  • Ahmet Satir

    (Concordia University)

  • Hong Yan

    (The Hong Kong Polytechnic University)

Abstract

Green supplier development (GSD) is an important operational strategy that significantly contributes to environmental performance of the supply chain. However, green supplier evaluation for development, the first step in green supplier development, has not been widely reported in the literature. This article aims to develop a green supplier evaluation methodology for supplier development. Poor suppliers set and weak areas of each supplier are identified so that green supplier development practices can be implemented. This study proposes an environmental evaluation methodology based on environmental performance and environmental practices and use of development priority number to effectively assess suppliers’ green capability. A novel interval-valued intuitionistic fuzzy numbers based reference-neighborhood rough set approach is then used to identify the poor supplier set and suppliers’ weak areas. The feasibility of this methodology is illustrated through a case study in a large chemical company. The methodology proposed can guide organizations when developing more specific GSD plans through identifying the poor suppliers and the weak areas.

Suggested Citation

  • Chunguang Bai & Kannan Govindan & Ahmet Satir & Hong Yan, 2025. "A novel fuzzy reference-neighborhood rough set approach for green supplier development practices," Annals of Operations Research, Springer, vol. 349(2), pages 731-765, June.
    • Handle: RePEc:spr:annopr:v:349:y:2025:i:2:d:10.1007_s10479-019-03456-z
    DOI: 10.1007/s10479-019-03456-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-019-03456-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-019-03456-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    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:spr:annopr:v:349:y:2025:i:2:d:10.1007_s10479-019-03456-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.