IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v353y2025i1d10.1007_s10479-024-06449-9.html
   My bibliography  Save this article

Criteria definition for digital requirements using hesitant fuzzy linguistic terms sets: an application to the automotive industry

Author

Listed:
  • Pietro Fronte

    (ESADE Business School - Ramon Llull University
    CUPRA)

  • Núria Agell

    (ESADE Business School - Ramon Llull University)

  • Marc Torrens

    (ESADE Business School - Ramon Llull University)

  • Diana Mesa

    (CUPRA
    SEAT CODE)

Abstract

Managing a portfolio of digital products is challenging, particularly in a context of limited economic resources and workforce. Therefore, prioritization of activities and new developments is crucial. In Software Development environment, almost all well-known prioritization techniques are based on experts’ knowledge and opinion, leaving little room for a data-driven, objective approach. In this paper, we propose a methodology that adopts the Delphi framework and Hesitant Fuzzy Linguistic Term Sets for collecting experts’ opinions, evaluating perceived importance, and computing group consensus. The objective is to provide a framework to define a group-consensual set of relevant criteria that would represent the basis for a data-driven prioritization process for digital requirements. Implementation and results from a real case application in a European automotive company are presented to understand the relevance of criteria and suggest their inclusion or exclusion for prioritization purposes.

Suggested Citation

  • Pietro Fronte & Núria Agell & Marc Torrens & Diana Mesa, 2025. "Criteria definition for digital requirements using hesitant fuzzy linguistic terms sets: an application to the automotive industry," Annals of Operations Research, Springer, vol. 353(1), pages 147-169, October.
    • Handle: RePEc:spr:annopr:v:353:y:2025:i:1:d:10.1007_s10479-024-06449-9
    DOI: 10.1007/s10479-024-06449-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-024-06449-9
    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/s10479-024-06449-9?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:annopr:v:353:y:2025:i:1:d:10.1007_s10479-024-06449-9. 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.