IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-04549059.html
   My bibliography  Save this paper

Explainable Analytics for Operational Research

Author

Listed:
  • K. de Bock

    (Audencia Business School)

  • K. Coussement
  • A. de Caigny

Abstract

This paper introduces the feature cluster on "Explainable AI for Operational Research". Its main purpose is to provide summaries for the 15 contributing research papers that were accepted for inclusion in this feature cluster. To guide the presentation of individual contributions, we refer to the XAIOR framework, or Explainable AI for OR, which is presented in a review paper featured in this feature cluster. XAIOR is defined as the conceptualization and application of advanced methods for transforming data into insights that are simultaneously performant, attributable, and responsible for solving OR problems and enhancing decision-making. This paper zooms in on the underlying dimensions of XAIOR linked to three types of analytics, i.e. performance analytics, attributable analytics and responsible analytics. We discuss the feature cluster contributions' linkage to the XAIOR framework. In particular, contributing papers are categorized along along two dimensions depending on whether the research paper introduces a new XAIOR method that is applicable across OR domains, or whether the paper zooms in on XAIOR aspects of a particular OR application field.

Suggested Citation

  • K. de Bock & K. Coussement & A. de Caigny, 2024. "Explainable Analytics for Operational Research," Post-Print hal-04549059, HAL.
  • Handle: RePEc:hal:journl:hal-04549059
    DOI: 10.1016/j.ejor.2024.04.015
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:hal:journl:hal-04549059. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.