The russian area digitalization index to assess digitalization vectors in the program-targeted administration model

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Abstract

Foreign and domestic methods, indices and indicators used to assess the level of development of the digital economy are considered. Their critical analysis in terms of regional scalability is provided. The authors present the approach to building the digitalization index of Russian regions. The index measures the level of digitalization in a region by 48 parameters, grouped into three main groups: “perception of the processes of digital transformation of the subject of the Russian Federation,” “preparedness of the digital environment,” and “effects of digital transformation for the economy and social sphere of the region.” The rating provides monitoring, evaluation of development, manageability, efficiency, and effectiveness in the context of interests and involvement of the main participants in the digital transformation process. The main participants in the digital transformation process are the following: authorities (states); representatives of the business community; citizens of the Russian Federation. A feature of the proposed approach is the accounting, when determining subject areas and composition of indicators and strategic priorities of Russia in the field of digitalization. The authors assume that the Index will be used by regional authorities to specify the provisions of regional projects conducted in the framework of federal projects of the national program “Digital Economy of the Russian Federation.” Furthermore, the Index will be used to monitor its progress in the field of digital development and analyze problematic issues in the implementation of the digitalization strategy in the constituent entities of the Russian Federation.

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Matraeva, L. V., Korolkova, N. A., Kaurova, O. V., Maloletko, A. N., & Bashina, O. E. (2021). The russian area digitalization index to assess digitalization vectors in the program-targeted administration model. In Studies in Systems, Decision and Control (Vol. 316, pp. 197–207). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-57831-2_21

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