The European research landscape under the Horizon 2020 Lenses: the interaction between science centers, public institutions, and industry

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Abstract

This research analyses the European landscape of innovation in small and medium-sized enterprises (SMEs). To achieve this objective, data collected from the Horizon 2020 strategy is extracted, which includes 1055 research projects that focus on innovation in SMEs. A complex network analysis is carried out at three levels: (1) at aggregated level by participating European countries, (2) at aggregated level according to the actors of the Triple Helix model, and (3) at disaggregated level according to the individual entities participating in the program. The results allow us to understand the European environment that drives innovation in SMEs. First, this study provides a descriptive overview of the relationships between European countries that favor innovation, and it also describes the positioning of each of them in the joint network. Second, this analysis is able to identify the most relevant agents in the network, the Big Science Centers, and their relationships with industry and public institutions. This study can be used as an analytical tool to improve knowledge transfer in complex ecosystems.

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This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10961-020-09816-3

Bibliographic citation

Ferrer-Serrano, M., Latorre-Martínez, M.P. & Fuentelsaz, L. The European research landscape under the Horizon 2020 Lenses: the interaction between science centers, public institutions, and industry. J Technol Transf 46, 828–853 (2021). https://doi.org/10.1007/s10961-020-09816-3

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Spanish Ministry of Economy and Competitiveness and FEDER (project ECO2017-85451-R)
Regional Government of Aragón and European Social Fund (project S64_20R and projects S42_17R)
Pre-doctoral grant BOAIIU/1408/2018

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Attribution-NoDerivatives 4.0 International