IDEAS home Printed from https://ideas.repec.org/a/taf/tjmaxx/v11y2024i3p389-444.html
   My bibliography  Save this article

Linguistic hesitant fuzzy interactive multi-attribute group decision making for enterprise resource planning selection

Author

Listed:
  • Shu-Ping Wan
  • Chun-yan Zeng
  • Jiu-ying Dong
  • Si-shi Hu

Abstract

Enterprise resource planning (ERP) system selection involves multiple evaluation attributes with interaction. It can be attributed to a type of interactive multi-attribute group decision making (MAGDM). Linguistic hesitant fuzzy sets (LHFSs) are powerful tools to represent the uncertainty, hesitancy, and inconsistency of decision makers’ (DMs’) preference. This article proposes two new methods for interactive MAGDM with LHFSs based on comprehensive cloud (CC) power geometric (PG) aggregation operators. First, the CC of LHFS is defined and a distance measure between two CCs is offered. Considering the interaction among the aggregated LHFSs, we develop some CC PG aggregation operators of LHFSs. An uncertainty degree of LHFS is defined. Then, an approach is developed to derive the weights of DMs. An approach is proposed to derive the comprehensive attribute weights. Thus two new methods are presented for interactive MAGDM with LHFSs. An ERP selection example is provided to validate the proposed methods.

Suggested Citation

  • Shu-Ping Wan & Chun-yan Zeng & Jiu-ying Dong & Si-shi Hu, 2024. "Linguistic hesitant fuzzy interactive multi-attribute group decision making for enterprise resource planning selection," Journal of Management Analytics, Taylor & Francis Journals, vol. 11(3), pages 389-444, July.
    • Handle: RePEc:taf:tjmaxx:v:11:y:2024:i:3:p:389-444
    DOI: 10.1080/23270012.2024.2371517
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23270012.2024.2371517
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/23270012.2024.2371517?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.

    More about this item

    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:taf:tjmaxx:v:11:y:2024:i:3:p:389-444. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjma .

    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.