Determining the key factors of the innovation gap between EU countries


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Innovation plays a crucial role in ensuring economic growth and competitiveness of national economies, creating conditions for their sustainable development. By focusing on supporting innovation, the EU is particularly helping to accelerate the development of those member states that lag far behind the EU average. This requires the selection of the indicators reflecting the development of innovation that determine the differences between member countries to the greatest extent. Therefore, the aim of the study is to identify the key factors of the innovation gap (FIG) between EU countries based on a comparison of indicators characterizing the national innovation systems (NIS).
For this purpose, 22 relative indicators were selected from the indicators included in the Global Innovation Index to form an array of empirical data. At the first stage, the EU countries were divided into four clusters using the k-means method. At the second stage, using the decision tree method, a group of indicators was identified that together distinguish the obtained clusters to the greatest extent and, accordingly, determine the differences between EU countries and can be considered as FIG, namely: “Researchers”, “GERD financed by business”, “Joint venture/strategic alliance deals”, “Software spending”, and “High-tech manufacturing”. This allows individual member states to prioritize the development of those indicators (i.e. FIG) that most determine their position in the EU and therefore improve their NIS. At the EU level, this will contribute to the complementarity of the NIS, overcome differences between member states and increase the overall level of convergence in innovation.

view full abstract hide full abstract
    • Table 1. List of key indicators characterizing the innovation systems of EU countries (2022)
    • Table 2. Minimum (min), average (aver.) and maximum (max) values of the indicators identified as FIG for the obtained clusters of EU countries
    • Table A1. Clusters of EU countries by indicators characterizing their innovation systems (2022 data)
    • Conceptualization
      Maxim Polyakov, Igor Khanin, Gennadiy Shevchenko, Vladimir Bilozubenko, Maxim Korneyev
    • Formal Analysis
      Maxim Polyakov, Gennadiy Shevchenko, Vladimir Bilozubenko, Maxim Korneyev
    • Project administration
      Maxim Polyakov, Igor Khanin
    • Supervision
      Maxim Polyakov, Igor Khanin, Gennadiy Shevchenko, Maxim Korneyev
    • Writing – review & editing
      Maxim Polyakov, Igor Khanin
    • Investigation
      Igor Khanin, Vladimir Bilozubenko, Maxim Korneyev
    • Data curation
      Gennadiy Shevchenko, Vladimir Bilozubenko
    • Methodology
      Gennadiy Shevchenko, Vladimir Bilozubenko
    • Software
      Gennadiy Shevchenko
    • Writing – original draft
      Gennadiy Shevchenko, Vladimir Bilozubenko, Maxim Korneyev
    • Validation
      Vladimir Bilozubenko, Maxim Korneyev
    • Resources
      Maxim Korneyev