Six additional questions about smart specialization: implications for regional innovation policy 4.0

2020 ◽  
Vol 28 (8) ◽  
pp. 1667-1684 ◽  
Author(s):  
Maximilian Benner
2016 ◽  
pp. 65-81 ◽  
Author(s):  
S. Zemtsov ◽  
V. Barinova

The article substantiates the need for regionally differentiated innovation policy based on the principles of smart specialization. It provides an extensive review of international experience and literature and proposes guidelines for a new policy relating to the conservation of the human capital, the formation of innovative businesses and the intensification of horizontal connections. Using the cluster analysis, the authors develop a typology of regions and cities for innovation policy goals. The article suggests support tools for each type of regions, which are different in the potential of creation and implementation of new technologies, technological and industrial specialization.


Economies ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 48 ◽  
Author(s):  
Mona Roman ◽  
Henry Varga ◽  
Vladimir Cvijanovic ◽  
Alasdair Reid

Prior research has emphasized the importance of bringing together quadruple helix (QH) actors (academia, industry, government and civil society) to strengthen regional innovation. The QH model forms an integral part of European innovation policy, which aims to create sustainable and inclusive growth in Europe. As part of this policy, European Union (EU) regions are to design and implement research and innovation strategies for smart specialization (RIS3) through the participatory entrepreneurial discovery process (EDP). Despite the strong emphasis on the QH model, the model is still far from a well-established concept in innovation research and policy, and civil society participation in RIS3 has remained low. Our paper aims to support regional governments to engage with and facilitate the participation of civil society in a territorial EDP based on two case studies from Finland and Sweden. It contributes to the literature on regional innovation systems through identifying mechanisms to foster the QH model and suggests lessons learnt for the operationalization of the QH model as part of RIS3.


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