Clustering of the Russian regions by information and communication technologies indicators – infrastructure and Internet access

Author:

Kuznetsov N. V.1ORCID,Pershina T. A.1ORCID,Sychev A. A.1ORCID,Savostitsky A. S.1ORCID

Affiliation:

1. State University of Management

Abstract

In the context of the digitalization of the economy, it is important to systematize indicators that will fully assess the work of the regions of the Russian Federation in the direction of the country’s information development. The article presents a system for assessing state entities within the framework of infrastructure and access to the Internet network throughout the country. The authors analyze the heterogeneity of the regional structure of Russia in terms of digitalization indicators. The use of advanced statistical parametric and non-parametric methods made it possible to determine the stratification of regions. The paper compares the level of development of information and communication technologies in groups (layers) of regions according to the indicators included in the block “information and communication technologies infrastructure and access”, obtained as a result of monitoring the development of the information society in the Russian Federation. Researchers conduct a factor analysis to identify the main components that affect the level of development of information and communication technologies in the Russian regions.

Publisher

State University of Management

Subject

General Medicine

Reference10 articles.

1. Bakumenko L.P., Minina E.A. International index of digital economy and society (I-DESI): Trends in the development of digital technologies. Statistics and Economics. 2020;17(2):40–54 https://doi.org/10.21686/2500-3925-2020-2-40-54 (in Russian).

2. Rosstat. Russian information society development monitoring. https://rosstat.gov.ru/folder/154882 (accessed 22.02.2023). (In Russian).

3. Bashina O.E., Tsaregorodtsev Yu.N., Serebrovskaya T.B. Influence of information technologies on the development of educational institutions programs and training of modern personnel. Vestnik Akademii. 2020;1:34–42. (In Russian).

4. Bekbergeneva D.E. Characteristics of digital economy development indices. Actual issues of the modern economics. 2020;6:211– 216. https://doi.org/10.34755/IROK.2020.57.55.054 (in Russian).

5. Matraeva L.V., Vasiutina E.S., Korolkova N.A., Kaurova O.V., Maloletko A.N. Digital transformation of the economy: Dividends and threats. Сooperation and Sustainable Development: Conference proceedings, Моscow, dewcember 15–16, 2020. Cham: Springer Nature Switzerland; 2022:19–26. https://doi.org/10.1007/978-3-030-77000-6_3

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