Visualising components of regional innovation systems using self-organizing maps—Evidence from European regions

Petr Hajek, Roberto Henriques and Veronika Hajkova

Technological Forecasting and Social Change, 2014, vol. 84, issue C, 197-214

Abstract: Regional innovation systems are regarded as complex systems in which components are strongly dependent on each other. Such relationships can have both linear and nonlinear character. One of the ways to investigate the structure of regional innovation systems is to use a self-organizing map resulting from an unsupervised learning process. In this paper we employed this procedure to visualize and study the patterns present in the individual components of European regional innovation systems. Our findings suggest that there is a similar level of diversity in individual regional innovation systems' components due to their strong intercorrelations. Additionally, the visualisation of the components in geographical maps shows on a positive effect of the Knowledge intensive regions on the spatially close Catching up regions. Finally, the economic growth of the European regions appears to be associated to European economic integration (for lagging behind regions) and the level of innovative and entrepreneurial activity (for knowledge intensive regions).

Keywords: regional innovation system; self-organizing map; economic growth; research and development (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:84:y:2014:i:c:p:197-214

DOI: 10.1016/j.techfore.2013.07.013

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