Forecasting Prospects for Regional Economic Systems’ Development in Digital Economy

The study discussed in this article addresses a topic that is highly relevant to the Russian Federation’s regional development as well as the need for accurate forecasting. It also looks at how regional economic systems are gradually becoming more digital. Forecasting neural networks, Bayesian intelligent measurements, cluster analysis, correlation-regression analysis, and other models are used to evaluate the potential for digital transformations at the regional management level. A crucial aspect of these methodologies is the adaptation of all indicators and criteria to the conditions of digitalization, taking into account the significant and substantive changes occurring in all elements of regional economic systems. The purpose of this article is to provide a scientific foundation and test methodological tools for assessing the development of regional economic systems within the digital economy. For forecasting this process, an algorithm for mathematical and statistical modeling was developed, distinguishing four evaluation groups: financial-economic, investment-innovative, intellectual-digital, and sociocentric indicators. As a result of calculating integral criteria for these groups of indicators, an aggregated general criterion was established to assess the level of development of regional economic systems in the context of digitalization. The simulation results were evaluated using the regional economic systems of the Southern Federal District of the Russian Federation as a case study. Consequently, trend models for the digital development of these regions were established, identifying both leading and lagging regions. The findings underscore the importance of considering all factors associated with the digitalization of regional economic systems. Additionally, it is essential to employ adaptive forecasting models that can calculate multiple alternatives for the implementation of events or phenomena within the digital economy. Authors’ contribution. Yu.P. Maydanevych – formation of a concept, analysis of scientific methods and approaches, development assessment of regional economic systems in the digital economy, and scientific editing of the text of the article; M.M. – formation of a modeling algorithm and testing of tools for development assessment of regional economic systems in the context of digitalization, collection and analysis of data, generalization of research results, and preparation of the article text.