Digitalization of the Russian Economy: Trends, personnel, platforms, and challenges to the state

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Abstract

The article analyzes the relationship between the index describing the capability of the Russian economy to compete globally and different digital indices based on the distribution polygon method. At the macro level, correlation and regression statistical data analysis techniques are used to calculate the relationship between the basic indicators of economy digitalization and to reveal the key trends. Within the framework of K. Schwab's Industry 4.0 concept interpreting the interdependence of technological, social, cultural and political changes, the authors examine staff training in Russia's leading universities. In conclusion, the authors state that the curricula should be adjusted so as to include disciplines reflecting employers' demand for the digitalization of business processes. The article provides an analysis of a Yandex.taxi case through the prism of changing business processes and transformation of the value chain. The study describes the role of platforms, marketplaces and 'big data' in creating the network effect. The authors point to an evolutionary ("creeping") character of macro economy digitalization, social sphere in modern Russia and possible revolutionary ("galloping") changes in a separate market segment. Digital transformations of the business processes lead to considerable changes in the Five Forces model by M. Porter. Conventional concepts, such as demand, offer, clients, suppliers, competitors, borrow a number of important characteristics from each other creating a new market situation. The authors highlight that certain government efforts, budget policies and legal regulations are needed to tackle external negative effects of digitalization.

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APA

Rastorguev, S. V., & Tyan, Y. S. (2019). Digitalization of the Russian Economy: Trends, personnel, platforms, and challenges to the state. Monitoring Obshchestvennogo Mneniya: Ekonomicheskie i Sotsial’nye Peremeny, 153(5), 136–161. https://doi.org/10.14515/monitoring.2019.5.08

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