The regional dimension of digital skills research

Author:

Popov Evgeniy V.1

Affiliation:

1. HSE University

Abstract

The main research problem underlying the article is the bias in the results of analysing the level of digital skills when approximating variables are used. It is noted that this strategy is common in the Russian digitalisation researchers academic community. Instead of the approximating tactic, the article uses the established methodology of calculating the level of digital literacy by Eurostat used until the year 2021. The empirical basis of the study is Rosstat data. By analysing it the author demonstrates the differentiation of the Russian regions by key components of the digital literacy level: information and communication competences, the ability to solve everyday tasks and the ability to work with software. The cluster model developed in the course of the analysis allowed to identify three groups of regions differing in these components: leaders (21 regions), middle-ranking regions (43 regions) and lagging behind (21 regions). The leading regions include the Omsk and Murmansk Regions and the city of Moscow, while the lagging regions include the Republic of North Ossetia, the Magadan and Jewish Autonomous Regions. It was revealed that the overall level of digital literacy in the regions is influenced by economic indicators: the average index of the physical volume of GRP, the average size of wages, as well as the value component – a positive assessment of the impact of digital technologies on life in particular.

Publisher

The Russian Academy of Sciences

Reference24 articles.

1. Abdrahmanova G. I., Vasilkovskiy S. A. (eds) (2022) Indicators of the Digital Economy: 2022: Statistical Collection. Moscow: VSHE. (In Russ.)

2. Aissaoui N. (2022) The digital divide: a literature review and some directions for future research in light of COVID-19. Global Knowledge, Memory and Communication. No. 8/9: 686–708.

3. Dmitriev Ya.V., Alyabin I. A. et al. (2021) Development of Digital Skills among University Students: De Jure vs De Facto. University Management: praktika i analiz [University Management: Practice and Analysis.]. No. 2: 59–79. (In Russ.)

4. Fedorova N. V., Minchenkova O. Yu., Makeeva V. G. (2020). Possibilities and risks of digitalization of the economy and society. Nauka I iskusstvo upravlenia [Science and art of management]. No. (3/4): 25–37. (In Russ.)

5. Fedoseeva S. S., Glezman L. V., Yelkin S. A. (2022) Digital literacy of the population as the basis for the development of digital economy in Russia and the regions. Upravlencheskii uchet [Management Accounting]. No. 11: 948–955.

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