Research of the innovative development of the Russian Federation regions and its impact on the eco-friendliness of the economy based on neural network cluster analysis for the purpose of economic security

Abstract

This article is devoted to the assessment of innovative development of the Russian Federation regions using self-organizing Kohonen maps. The relevance of this paper is due to the need to develop various criteria for making decisions on state support for regions, the use of which will allow to conduct a comprehensive assessment of regional development. Its findings should serve as a reliable, high-quality source of information about the feasibility and type of support for a particular region. The study provides a justification for a set of indicators that are used in conducting cluster analysis. The methodology developed by the authors provides an opportunity to divide the regions into clusters, conduct their quantitative and qualitative analysis, and further predict the key indicators of the regions based on their belonging to different clusters. All this allows to study regional innovative development in dynamics. The authors draw a conclusion about the uneven innovative development of the Russian regions and the ambiguity of connections between the indicators of the share of organizations engaged in technological innovations and the degree of environmental friendliness of the economy. The findings of this study will be useful to public authorities when making decisions on the allocation of budgetary funds for the development of territories.