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

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  • 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
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    References listed on IDEAS

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    1. Tadeusz Trzaskalik, 2023. "Vectors of indicators and pointer function in the Multistage Bipolar Method," 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. 31(3), pages 791-816, September.
    2. Nazanin Vafaei & Rita A. Ribeiro & Luis M. Camarinha-Matos, 2018. "Data normalisation techniques in decision making: case study with TOPSIS method," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 10(1), pages 19-38.
    3. Eleni Laitsou & Antonios Kargas & Dimitris Varoutas, 2020. "Digital Competitiveness in the European Union Era: The Greek Case," Economies, MDPI, vol. 8(4), pages 1-33, October.
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    Cited by:

    1. Péter Biró & Sándor Bozóki & Tamás Király & Alexandru Kristály, 2024. "Optimization methods and algorithms," 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 1-9, March.

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