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Success Factors of Startups in the EU—A Comparative Study

Author

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  • Eulalia Skawińska

    (Department of Economy and Management, University of Zielona Góra; 65-417 Zielona Góra, Poland)

  • Romuald I. Zalewski

    (Department of Economy and Management, University of Zielona Góra; 65-417 Zielona Góra, Poland)

Abstract

The paper focuses on key success factors of startups in the European Union. Startup companies have a massive potential to boost the level of innovation and competitiveness of national economies. They are also uniquely equipped to provide extremely effective and flexible ways of meeting both existing and emerging market needs. However, the development of these microventures differs from country to country. Hence, we put forth a hypothesis that strategic success factors in the development of startups vary in highly developed and catching-up countries. Our main goal was to determine the key success factors of startups in the EU, and to classify the gap between developed and lagging Member States. For this purpose, we applied the method of component analysis on startup data available for selected the EU states. We managed to isolate 5 components explaining 72% of data variability, all of which can be linked to human capital as well as to formal and informal economic institutions. The results confirmed the validity of our hypothesis. We established that more developed countries offer an institutional competitive advantage to startups, while the gap in success factors between highly developed and catching-up countries can be attributed to human capital and to institutions. Based on our findings, we offer suggestions how to reduce this gap by improving formal and informal institutions via innovative public policy and by supporting education.

Suggested Citation

  • Eulalia Skawińska & Romuald I. Zalewski, 2020. "Success Factors of Startups in the EU—A Comparative Study," Sustainability, MDPI, vol. 12(19), pages 1-28, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8200-:d:423911
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    Cited by:

    1. Lele Cao & Vilhelm von Ehrenheim & Sebastian Krakowski & Xiaoxue Li & Alexandra Lutz, 2022. "Using Deep Learning to Find the Next Unicorn: A Practical Synthesis," Papers 2210.14195, arXiv.org, revised Jun 2024.
    2. Gianni Onesti & Eleonora Monaco & Riccardo Palumbo, 2022. "Assessing the Italian Innovative Start-Ups Performance with a Composite Index," Administrative Sciences, MDPI, vol. 12(4), pages 1-18, December.
    3. Lele Cao & Gustaf Halvardsson & Andrew McCornack & Vilhelm von Ehrenheim & Pawel Herman, 2023. "Beyond Gut Feel: Using Time Series Transformers to Find Investment Gems," Papers 2309.16888, arXiv.org, revised Jun 2024.

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