Poly-scale evaluation of the knowledge-based economy

Abstract

Cities and urban agglomerations are increasingly becoming a focus in knowledge and innovation studies as the nodes where the major part of regional intellectual capital being generated and accumulated. With that, a region is generally conceived as an optimal scale for capturing the holistic structure of a territorial innovation system. Regional level studies dominate the research design on knowledge-based and innovation-driven economies, providing input for state policies. In this study, we test the hypothesis that the aggregate regional level data obscures the great variety of knowledge nodes, being dominated by the major knowledge hub-generally the administrative centre of the region. The research design is focused on assessing the knowledge-generation domain at a poly-scale level-city and region, using the method of spatial scientometrics. The Russian Federation is chosen as an interesting case study, as due to the great length of the country its centres of knowledge production are geographically distributed and remote from each other. This fact determines the high degree of heterogeneity both at the intra- A nd inter-regional levels of the national innovation system. The research results reveal a strong correlation between the knowledge profile of the regions and its primary knowledge-generating cities (KGCs). In the cases of the strong centre-peripheral structure of the regional knowledge production system, the regional profile is fully aligned with the profile of its primary KGC. The capacity of secondary tier cities remains hidden. The poly-scale city-region approach enables to grasp local specificity and diversity by capturing the entire set of elements of the regional knowledge production system. The study concludes with policy recommendations on knowledge management at poly-scale level.