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The article addresses the issue of measuring the degree of digitalization in European Union countries using the Digital Economy and Society Index (DESI). The aim is to analyze the impact of selected normalization algorithms on the DESI ranking and to identify the algorithm that is least sensitive to unusual indicator values. An analysis of eleven selected normalization algorithms was conducted using computer programs in Python, specifically developed for this study. The findings indicate that the linear normalization sum-based algorithm is the most effective, providing the most stable ranking where changes in the DESI index of some countries are minimally affected by changes in the indicator values of other countries in the ranking. The authors’ main contribution is the analysis of data normalization algorithms and the identification of the most suitable one for DESI.

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The Role of Data Normalization Algorithm in Measuring of EU Countries Digitalization Degree

  • 会议论文

  • 发表日期：

    2025年

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  • Anna Borawska,
  • Mariusz Borawski,
  • Małgorzata Łatuszyńska

摘要

The article addresses the issue of measuring the degree of digitalization in European Union countries using the Digital Economy and Society Index (DESI). The aim is to analyze the impact of selected normalization algorithms on the DESI ranking and to identify the algorithm that is least sensitive to unusual indicator values. An analysis of eleven selected normalization algorithms was conducted using computer programs in Python, specifically developed for this study. The findings indicate that the linear normalization sum-based algorithm is the most effective, providing the most stable ranking where changes in the DESI index of some countries are minimally affected by changes in the indicator values of other countries in the ranking. The authors’ main contribution is the analysis of data normalization algorithms and the identification of the most suitable one for DESI.