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Digital Transformation of the Regions of the Central Federal District: Dynamics, Clusters and Economic Effects (2018–2025)

https://doi.org/10.37791/2687-0657-2026-20-2-102-121

EDN: GFVAGC

Abstract

The article is devoted to a comprehensive analysis of the digital maturity of 18 constituent entities of the Central Federal District based on the integral rating "Digital Maturity of Russian Regions" (April 2025). Unlike existing studies that either limit themselves to describing sectoral indicators or do not verify composite indices with objective statistical data, the authors, for the first time for the CFD, apply a nine-component index structure (digital infrastructure, e-government services, smart city, healthcare, education, artificial intelligence projects, open data, economy and innovation, communications) and conduct empirical verification using Rosstat indicators (patent activity, innovation activity, share of organizations with broadband access) and the CNews Analytics ICT budgets rating. The distribution of regions by digital maturity level is analyzed, revealing a persistent polarization: the gap between the leader (Moscow, 95 points) and the laggards (Tambov and Tver oblasts, 36 points) is 59 points, which is 2.6 times. Using k-means clustering based on the nine components, four typological groups are identified: leaders (cluster A), innovation-active (cluster B), catching-up (cluster C), and lagging (cluster D). Spearman's correlation coefficient between the digital maturity index and GRP per capita was 0.89 (p < 0.001), and with net migration – 0.71 (p = 0.001). Regression analysis (OLS, R2 = 0.86) showed that a one-point increase in the index is associated with a 3.56% increase in GRP per capita, controlling for investment and population size. Comparison with the Digital Russia index (SKOLKOVO, 2018) revealed high rank stability (ρ = 0.85), indicating the persistence of structural digital inequality over seven years. The article has practical significance, as the proposed regional policy measures (differentiated by cluster) can be directly used by public authorities in developing and adjusting digital transformation programs for the constituent entities of the Russian Federation, as well as in the allocation of intergovernmental transfers.

About the Authors

Nataliya V. Yakovenko
Voronezh State University of Forestry and Technologies named after G. F. Morozov
Russian Federation

Dr. Sci. (Geography), Full Professor; Chief Researcher at Directorate of the Research Institute of Innovative Technologies and the Forestry Complex (Voronezh State University of Forestry and Technologies named after G. F. Morozov)



Anna Yu. Nebesnaya
Voronezh State University of Forestry and Technologies named after G. F. Morozov
Russian Federation

Cand. Sci. (Economics); Associate Professor at Global and National Economy Department (Voronezh State University of Forestry and Technologies named after G. F. Morozov)



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Review

For citations:


Yakovenko N.V., Nebesnaya A.Yu. Digital Transformation of the Regions of the Central Federal District: Dynamics, Clusters and Economic Effects (2018–2025). Journal of Modern Competition. 2026;20(2):102-121. (In Russ.) https://doi.org/10.37791/2687-0657-2026-20-2-102-121. EDN: GFVAGC

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