Project information
Evaluating Regional Innovation Capacity for Selected European Regions

Project Identification
Project Period
1/2024 - 12/2024
Investor / Pogramme / Project type
Masaryk University
MU Faculty or unit
Faculty of Economics and Administration

The differences between global or world cities and peripheral areas can be attributed to differences in knowledge, talent, qualified labour force, production concentration, location of multination corporations, major suppliers, dedicated research institutions and the ease of access to information and knowledge outside the region (Brodzicki & Golejewska, 2019; Ciołek et al., 2021). The need for uniqueness in planning policies, missions and visons apply to high innovation performance regions as well as low-innovation-performance regions (Berna Sezen ÖZen & Tüzin Baycan, 2022; B. S. Özen & T. Baycan, 2022). Literature on Regional Innovation systems often emphasizes the localization of knowledge flows, geographical proximity, and the importance of regions in promoting innovation processes (Ciołek et al., 2021). The RIS concept which was initially based on the success stories of some industrial clusters and agglomerations has allowed for a better understanding of the uneven geography of innovation. The research will focus on mainly highly innovative NUTS regions in the Netherlands, Sweden, Denmark, Belgium, Germany, France, Austria, and Finland based on their performance ranking in the European and Regional Innovation Index. In order to examine changes in the RIS features, the years: 2016 – a time of a fairly good economic situation and the start of available data to 2023 – the most current year with data available will be used. This study will contribute to the literature by; (i)focusing on the regions that are diverse and highly innovative in various capacities, as an example of other similar regions and countries, (ii) covering the NUTS-2 level which helps in highlighting local knowledge and regional dynamics, and (iii) assessing the transitions of regions with the Markov Chains and Shorrocks indices and Panel Regressions including different time periods, and finally (iv) evaluating the regional performances of the following indicators - Population with tertiary education; Innovation expenditures per person employed; SMEs introducing product innovations; SMEs introducing business process innovations; Sales of new-to-market and new-to-firm innovations; Innovative SMEs collaborating with others; PCT patent applications; Trademark applications; Design applications; Employment in innovative enterprises, which serve as varying challenges to innovation.

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