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Economic Analysis: Theory and Practice
 

Studying the innovative development of regional economy as an imperative of sustainable socio-economic growth in Russia, using neural network modeling

Vol. 20, Iss. 8, AUGUST 2021

Received: 19 July 2021

Received in revised form: 25 July 2021

Accepted: 4 August 2021

Available online: 30 August 2021

Subject Heading: Innovation

JEL Classification: С45, O30, R11

Pages: 1394–1414

https://doi.org/10.24891/ea.20.8.1394

Nikolai P. LYUBUSHIN Voronezh State University (VSU), Voronezh, Russian Federation
lubushinnp@mail.ru

https://orcid.org/0000-0002-4493-2278

Elena N. LETYAGINA National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
len@fks.unn.ru

ORCID id: not available

Valentina I. PEROVA National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
perova_vi@mail.ru

ORCID id: not available

Subject. The article deals with the innovative potential of Russian regions in light of the national goal of the Russian Federation development, reflecting decent and productive work.
Objectives. The purpose is to study the innovation activity in Russian regions, using neural networks, to ensure breakthrough innovative development of the Russian economy.
Methods. We employ a cluster analysis on the basis of neural network modeling, using information technologies. For the research, we selected neural networks (Kohonen self-organizing maps), which are focused on unsupervised learning and are a promising tool for clustering and visualization of multidimensional statistical data.
Results. The result of neural network modeling was the ranking of 85 regions of the Russian Federation into 5 compact groups (clusters) regardless of their affiliation to federal districts of the Russian Federation. The study shows that there is a strong differentiation of the number of regions in these clusters. We obtained average values of indicators in the clusters and compared them with all-Russian indicators.
Conclusions. Breakthrough in the socio-economic growth of the Russian Federation is associated with a set of measures that involve stimulating innovation activities in regions, which are characterized by different level of innovation development. Such measures will increase the interest of the real sector of the economy in using scientific development, advanced production technologies, higher-productivity employment opportunities, and, as a result, will encourage socio-economic growth and people's quality of life.

Keywords: innovation activity, cluster analysis, neural network, Kohonen self-organizing map

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