Artikel

How efficiently does the EU support research and innovation in SMEs?

The European Regional Development Fund devoted around 66 billion Euros to the financial support of innovation and productivity in European enterprises over the 2014-2020 programming period. In this framework, we assessed the implementation of the Operational Programmes dedicated to fostering research and innovation, particularly in small and medium-sized enterprises. With this aim, we used a network slack-based data envelopment analysis model paired with cluster analysis that encompasses a multitude of performance framework indicators to assess 53 Operational Programmes from 19 countries. Our findings suggest that compared to transition and less developed regions, more developed regions present a higher room for improvement. Also, less developed regions present a better performance when they employ their funding against more developed regions, suggesting that further funding should be channelled for leveraging research and innovation in the former regions. Finally, Operational Programme managers should focus on solving the problems both inherent to the poor outcomes in terms of enhancing the number of researchers working in improved research infrastructures and promoting the technology transfer between research institutions and enterprises.

Sprache
Englisch

Erschienen in
Journal: Journal of Open Innovation: Technology, Market, and Complexity ; ISSN: 2199-8531 ; Volume: 8 ; Year: 2022 ; Issue: 2 ; Pages: 1-36

Klassifikation
Management
Thema
cluster analysis
ERDF
EU regions
research and innovation
slack-based measure
SMEs

Ereignis
Geistige Schöpfung
(wer)
Henriques, Carla Oliveira
Viseu, Clara
Neves, Maria
Amaro, Ana
Gouveia, Maria
Trigo, António
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2022

DOI
doi:10.3390/joitmc8020092
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Henriques, Carla Oliveira
  • Viseu, Clara
  • Neves, Maria
  • Amaro, Ana
  • Gouveia, Maria
  • Trigo, António
  • MDPI

Entstanden

  • 2022

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