Research & Innovation (R&I) policy initiatives employed by the European Union (EU) across its regional economies are important instruments to ensure the scientific and technological progress along with the associated benefits. One relevant aspect in this regard is to encourage and enable collaboration between regional partners to enhance potential learning opportunities and to ensure cohesive long-term development patterns. Furthermore, frequently these initiatives are also targeted at specific technology sectors, such as the EU R&I policy actions towards nanotechnology. Based on an advance theoretical framework and data from the official EU project databases as well as regionalized European Patent Office data, the present study develops a methodological tool through which it is possible to identify effective collaboration settings, while providing policymakers and evaluators with a practical tool that will enable them to predict the possible outcomes of such critical EU-funded R&I projects from the onset.

Calignano, G., Lee, J., Kogler, D.F. (2024). Nanotechnology and knowledge relatedness: how to identify optimal regional partners in EU innovation networks?. SCIENCE & PUBLIC POLICY, 51(5), 879-894 [10.1093/scipol/scae032].

Nanotechnology and knowledge relatedness: how to identify optimal regional partners in EU innovation networks?

Calignano, Giuseppe
Primo
;
2024

Abstract

Research & Innovation (R&I) policy initiatives employed by the European Union (EU) across its regional economies are important instruments to ensure the scientific and technological progress along with the associated benefits. One relevant aspect in this regard is to encourage and enable collaboration between regional partners to enhance potential learning opportunities and to ensure cohesive long-term development patterns. Furthermore, frequently these initiatives are also targeted at specific technology sectors, such as the EU R&I policy actions towards nanotechnology. Based on an advance theoretical framework and data from the official EU project databases as well as regionalized European Patent Office data, the present study develops a methodological tool through which it is possible to identify effective collaboration settings, while providing policymakers and evaluators with a practical tool that will enable them to predict the possible outcomes of such critical EU-funded R&I projects from the onset.
2024
Calignano, G., Lee, J., Kogler, D.F. (2024). Nanotechnology and knowledge relatedness: how to identify optimal regional partners in EU innovation networks?. SCIENCE & PUBLIC POLICY, 51(5), 879-894 [10.1093/scipol/scae032].
Calignano, Giuseppe; Lee, Junmin; Kogler, Dieter F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/990595
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