IDEAS home Printed from https://ideas.repec.org/a/spr/cejnor/v32y2024i1d10.1007_s10100-023-00876-y.html
   My bibliography  Save this article

Sensitivity of TOPSIS ranks to data normalization and objective weights on the example of digital development

Author

Listed:
  • Zoltán Bánhidi

    (Budapest University of Technology and Economics)

  • Imre Dobos

    (Budapest University of Technology and Economics)

Abstract

The European Commission's Digital Economy and Social Index (DESI) is a composite index that aims to measure the state of digital transformation in the European Union (EU) and its member states based on five principal dimensions. For each dimension, the Commission assigns predefined weights to determine the ranking of countries. The following paper ranks the member states using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. TOPSIS is based on two data transformations. First, it normalizes the data according to a chosen procedure and second, it assigns weights to the criteria. The aim of the study is to evaluate how the countries of the European Union can be ranked according to the five principal dimensions of the DESI but using objective weights instead of the arbitrary predefined weights of the European Commission, testing the robustness of the ranking and its sensitivity to the methods of normalization and weighting.

Suggested Citation

  • Zoltán Bánhidi & Imre Dobos, 2024. "Sensitivity of TOPSIS ranks to data normalization and objective weights on the example of digital development," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 32(1), pages 29-44, March.
  • Handle: RePEc:spr:cejnor:v:32:y:2024:i:1:d:10.1007_s10100-023-00876-y
    DOI: 10.1007/s10100-023-00876-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10100-023-00876-y
    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/s10100-023-00876-y?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:cejnor:v:32:y:2024:i:1:d:10.1007_s10100-023-00876-y. 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.