Increasing the Scientific Potential in the Russian Regions - the Strategic National Priorities of Russia

Abstract

The article analyzes the theoretical approaches to the concept of "scientific potential", provides an overview of foreign and domestic methodological approaches to assessing the scientific potential of national and regional economies. For a comparative assessment of the scientific potential of a number of Russian regions-analogues, a methodology based on an integrated approach has been formed, which includes elements of leading author's and institutional methods. Five modules of indicators have been identified: material and technical equipment, the level of education of scientific personnel, the volume and structure of scientific research and development, amount of funding, organizational structure of the scientific sphere. The relationship between the socio-economic development of the region and the actual and probabilistic level of the scientific potential of the territory is proved. In addition, it has been proven that the main factors are the level of funding and the quantity and quality of scientific personnel. This approach has been tested in some Russian regions of the Volga Federal District and the Ural Federal District. The center of comparison in the article is the Perm Territory. Regression analysis was applied to predict the development of the scientific potential of the analyzed region. To build a qualitative model, an effective indicator and factors explaining it were chosen: advanced production technologies developed, the number of scientific organizations, the number of scientificpersonnel, internal costs for research and development, the number of researchers with scientific degrees, the number of university students, the number of patents issued, the average salary researcher, the amount of funding from the federal budget. Regression analysis showed that the developed advanced manufacturing technologies are more affected by changes in the size of internal costs for research and development, as well as the number of researchers with scientific degrees. Thanks to the regression model, it was revealed that active financing of scientific activities in the region contributes to the emergence of highly qualified scientific personnel.