Clustering of regional innovation systems using statistical analysis methods

Abstract

The main methodological postulates of clusterization of regional innovation systems (RIS) are highlighted: goals, tasks, clusterization algorithm, basic principles for selecting indicators for clusterization. Design/methodology/approach: Methodologically, all these approaches can be divided into two different directions. One of them is based on the so-called case studies, that is, the study of the static state of individual regions, mainly the regions that are leaders of European countries. As a result of using the case study approach, several typologies are obtained. Findings: The main groups of distinctive characteristics of RIS are proposed and new indicators that were not previously used in identifying the types of regional innovation systems, but are important for their characteristics are updated: the share of secondary and tertiary sectors of the economy in gross value added; the share of the cost of fixed assets in the secondary and tertiary sectors (as indicators of the progressiveness of the sectoral structure of the economy of the region); total revenues of consolidated budgets without gratuitous transfers per capita (financial potential); population density and density of public roads with paved surface (taking into account the agglomeration factor). Originality/value: Clusterization of regional innovation systems using statistical methods was carried out and 14 types of RIS were identified