2782-6015 18 1 2025 1-195

RAR RUS 7-20 57190260598 0000-0001-6888-1981 V.I. Vernadsky Crimean Federal University Kirilchuk Svetlana skir12@yandex.ru

Prospekt Vernadskogo 4 , Simferopol, Republic of Crimea, 295007

Nalivaychenko Ekaterina The relationship of industrial digitalization with dynamic changes in the labor economy of the region in the context of Industry 4.0 and 5.0 The objective of the study: to reveal the relationship between industrial digitalization and dynamic changes in the labor economy in the context of the introduction of Industry 4.0 and 5.0 technologies in the Republic of Crimea, as well as to identify the impact of these changes on production processes, employment and qualifications of the workforce. Research methodology: logical, systemic and functional-differential approaches, as well as statistical analysis and synthesis. These methods allow for a deeper understanding of the impact of digitalization on the industrial sector and its relationship to the world of work. Research results: the first part of the study examines the effectiveness of digitalization of the industrial sector of the Crimean region in the context of Industry 4.0, the second part of the study provides a description of dynamic changes in the labor economy of the Crimean region in the context of Industry 5.0. The focus is on the impact of digitalization on production processes, employment and qualifications of the workforce in the context of the transition to the sixth and seventh technological paradigms. The results of the analysis show that, despite the positive trends in increasing the importance of the contribution of human capital to economic growth, the development of high-performance jobs and the implementation of digital technologies, there are significant challenges, such as declining labor productivity and lagging behind the pace of nominal wage growth. In general, the dynamics of industrial development performance indicators in the Crimean region is lower than the Russian average. Recommendations: The existing problems can be overcome by activating the possibilities of industrial digitalization, which requires increased investment in fixed assets, ensuring access to modern technologies and production tools, effective use of digital resources, and the development of a digital culture of employees. The originality of the research and the author's contribution: the imbalances in the industries of the Crimean region were identified and recommendations were formulated to improve the efficiency of the industry through the development of infrastructure for digital transformation and key technologies. 10.18721/JE.18101 industrial digitalization labor economics Industry 4.0 Industry 5.0 Republic of Crimea labor productivity labor force qualifications high-performance workplaces digital technologies innovation https://economy.spbstu.ru/article/2025.111.1/ 01_Kirilchuk.pdf

RAR RUS 21-56 V-1094-2019 56968223000 0000-0002-0941-6358 Peter the Great St.Petersburg Polytechnic University Babkin Alexander babkin@spbstu.ru

Russia, 195251, St.Petersburg, Polytechnicheskaya, 29

Liberman Irina iliberman@kantiana.ru Klachek Pavel PKlachek@mail.ru Q-4229-2017 57195759467 0000-0003-3644-4239 Voronezh State Technical University Shkarupeta Elena 9056591561@mail.ru

20 letiya Oktyabrya st., 84, Voronezh, Russia

Industry 6.0: methodology, tools, practice The concept of Industry 6.0 is considered as a qualitatively new phase of industrial and socio-economic development, characterized by comprehensive intellectual and technological immersive hyperconnectivity and physical-cognitive-emotional fusion of virtual twins of man and machine within the framework of symbiotic interaction. The methodology of Industry 6.0 is disclosed through a comprehensive system of views on the essence, content, core, object, goals, distinctive technologies of Industry 6.0, covering the entire spectrum of processes of creation, implementation and development of emotional-intellectual cybersocial meta-ecosystems obtained on the basis of ChIME convergence (ChIME means “Chelovek” (“man”) – “Iskusstvennyi sverkhintellekt” (“artificial superintelligence”) – “metaekosistema” (“meta-ecosystem”)). By analogy with genetic algorithms (where inheritance, mutation, selection, crossing over, etc. are used), the methodology and technology of DNA engineering of cybersocial metaecosystems include approaches of genetic engineering in an expanded synergetic, interdisciplinary format, which allows using the principles of convergent evolution and NBIC convergence. The toolkit for implementing Industry 6.0 includes the development of a periodic table of system-target elements of the polysystem tetrad of cybersocial metaecosystems (PTSTE-PTCM) (by analogy with the periodic table of chemical elements), generalized versions of polysystem proteins, amino acids and codons, as well as a cognitive genetic model of the polysystem genome in the form of a heterogeneous gene-neural network. The practice of deploying Industry 6.0 is demonstrated using the example of creating a test version of the “Polysystem Tetrad of the Cybersocial Metaecosystem of Industry 5.0/6.0” at “Techno Tube” LLC and during the development of the GН1G structure – a polysystem protein that ensures the research and technological development of the Starbase metaecosystem within the Starship HLS project. To prove the effectiveness of the polysystem protein GН1G, a model of economic coevolution of the Starbase metaecosystem was created, which showed high efficiency and significant scientific and technological potential of the presented tools. One of the directions of further research of the Industry 6.0 concept, which the authors would like to note, is the development of a table of analogies between the electron configurations of atoms of chemical elements and complexes of relations of the fundamental categorical cores of the system-target elements of the PTSTE-PTCM, especially configurations 6p, 1d and higher. The development of elements of these configurations will allow us to move on to the creation of anthropogenic systems. 10.18721/JE.18102 330.322.012 Industry 6.0 artificial intelligence innovation management technological paradigms cybersocial metaecosystems technologies synergetic technologies genetic engineering https://economy.spbstu.ru/article/2025.111.2/ 02_Babkin%2C-Liberman%2C-Klachek%2C-Shkarupeta.pdf

RAR RUS 57-79 Mukhacheva Anna Tools for ensuring digital quality of life of the population in the national economy The relevance of the study is determined by the need to satisfy the vital, social and moral interests of the population through the use of information and communication technologies, i.e. the formation of a digital quality of life, in the context of the development of the digital economy and the data economy. The term “digital quality of life” remains conceptually and definitionally unexplored, and the foundations of its formation are still practically not considered by researchers. Digital technologies determine the development of education, healthcare, social protection, law enforcement, environmental safety, labor market, public consumption, and the implementation of social and spiritual needs. Digital twins act as a catalyst for territorial development in the digital world within the framework of ecosystem provision of quality of life. More and more examples of their effective application can be found in Russian regions and cities. At present, the state has developed many information and analytical systems, some of which can form elements of a single socio-economic digital space, a digital twin of the territory. Digitalization of the social ecosystem for ensuring quality of life also has disadvantages. Among them, it is worth noting the increasing speed of change in the modern VUCA world, previously unknown to man and capable of causing negative psychological states (stress, frustration, psychological disorders), as well as cyber risks associated with the possibility of malicious use of personal data, and the standardization of public life. At the same time, digitalization of the social sphere, economy and public life is an objective and inevitable reality, the advantages of which are significantly greater for maintaining the quality of life of the population, and the disadvantages can be leveled by the same digital tools and the proper degree of attention of state and municipal authorities. The purpose of the study is to develop the theoretical and conceptual foundations of the category “digital quality of life”, to determine the tools for its formation, development and assessment. Research objectives are as follows: to form the theoretical and conceptual foundations of the category “digital quality of life”; to develop framework groups of indicators for assessing the digital quality of life of the population; to analyze the implementation of digital tools for the implementation of various interests of citizens; to consider existing information and analytical systems for managing the digital quality of life of the population. The research methods are the standard methods of description, comparison, system analysis, synthesis, economic and statistical assessment, and study of research on the topic. The practical significance of the research results is the possibility of using recommendations for the formation of the digital quality of life of the population to increase the degree of satisfaction of various interests of citizens at the federal and regional levels. 10.18721/JE.18103 332.14 digital tools digital quality of life digital region digitalization information system https://economy.spbstu.ru/article/2025.111.3/ 03_Muhachyova.pdf

RAR RUS 80-92 Viktorova Natalia viknata@mail.ru Lyu Lingli Assessing the impact of social factors on the sustainable economic development of China and its regions This study examines the extent and nature of the impact of social factors on the sustainable economic development of China and its regions. Thus, based on the entropy method, the integral index of China's sustainable economic development was calculated, which became an explanatory variable in the regression analysis. The regression analysis of panel data of 30 Chinese provincial-level administrative regions covering the period from 2012 to 2021 resulted in the construction of three fixed-effect models showing the relationship between each of the socially-oriented dependent variables, as well as their totality, and sustainable economic development. The type of models was selected using the Hausman test and, to ensure reliability, an analysis of both the overall sample and its regional heterogeneity was carried out in addition to the reliability tests. According to the results of the study, one of the social factors (aging of the population) can contribute significantly to China's economic stability. At the same time, the second social factor – the growing participation of the population in pension insurance – has a negative impact on the Chinese economy. The combination of these factors does not have a significant impact on China's sustainable economic development. The study also shows that the impact of the social factors analyzed on economic sustainability differs in the eastern, central and western provinces of China. Based on the empirical results of the study, the following recommendations are proposed for China's sustainable economic development in the face of social challenges (aging of the population): to expand the use of the consumer potential of the senior population, and to develop this group as human resources; to promote the rational distribution of the factors of production among provinces by coordination of the state's regional policies. These recommendations can be used by the government to formulate a strategy for the sustainable economic development of China and its provinces. The research results will also be beneficial for businesses aiming to adapt their corporate environment to emerging realities and trends. 10.18721/JE.18104 332.1 sustainable economic development state region social factors https://economy.spbstu.ru/article/2025.111.4/ 04_Viktorova%2C-Lyuy.pdf

RAR RUS 93-106 Tsetsiarynets Tatsiana Correlation of indicators of scientific potential and intensity of human capital accumulation in the territorial-sectoral projection of the Republic of Belarus he article, based on official statistical data of the Republic of Belarus for 2015–2023, provides an assessment of the interrelation between the level of development of the territorial-industrial segment of the national economy, investment provision of the food sector and the intensity of human capital accumulation. The peculiarities of the formation of the latter are due to the significant influence of natural, climatic, ecological and socio-cultural factors. Given the versatility of human capital, the specifics of its formation and development in the territorial-industrial section, the methodology of scientific search is based on acmeological approaches that reveal its essence in the process of continuous development. This fact allows us to theoretically and practically substantiate the influence of indicators of scientific sphere development on the intensity of human capital accumulation in the territorial-industrial projection of the Republic of Belarus. This makes it possible to comprehensively study the relationship between the trends in the development trends of the scientific sphere and human capital from the position of quantitative and qualitative parameters, including the gross value added (GVA) of agriculture, fisheries and forestry, the volume of investment in fixed capital in this sphere, productivity and capitalization of the food sector. The analysis of qualitative characteristics of the scientific potential of Belarus allows us to note its significant reduction in 2015–2023. The Republic of Belarus is characterized by a decrease in the qualitative composition of scientific personnel, expressed by negative trends in such indicators as the ratio of admitted to and successfully mastered scientifically oriented educational programs, the number of researchers, the number of doctors and candidates of science in various fields of science, and an intensive increase in the number of scientific workers over 60 years old. Labor productivity is considered as a qualitative indicator characterizing the relationship between the intensity of development of the scientific sphere and the rate of human capital accumulation. This indicator compiles the influence of investment and technological impact on the development of the food sector and socio-economic factors that determine the creation of GVA. Empirical research proves that a very high capital equipment of the agricultural segment acts as a restraining factor in the accumulation of human capital and causes a decrease in productivity in the sector. 10.18721/JE.18105 332.01 human capital territorial-industry projection scientific potential investment in fixed capital productivity capital formation Republic of Belarus https://economy.spbstu.ru/article/2025.111.5/ 05_Teterinets.pdf

RAR RUS 107-123 Vasilyeva Anzhelika vavangel@mail.ru An algorithm for selecting competing regions based on localization coefficients (using the example of the Amur region) The assessment of the competitiveness of regions is preceded by the stage of formation of the statistical set of the assessed entities. Each author approaches this stage in his own way. Some authors assess the competitiveness of all regions of the country, skipping the selection stage. Others consider regions of the same federal district as objects of comparison. Still others focus on neighboring regions, also within a federal district. The weak validity of such approaches can lead to distortion of the results of assessing the competitiveness of the constituent entities of the Russian Federation and the formulation of incorrect conclusions about the competitive advantages of the regions. In order to minimize representativeness errors, it is necessary to formalize the selection procedure for competing regions. The purpose of the study is to improve the algorithm for forming a statistical set of competing regions using localization coefficients. The information base of the study is the Federal State Statistics Service data for 2022. Statistical methods were used to perform the calculations, as well as methods for analyzing the regional economy. The result of the work is an improved algorithm for the formation of a statistical set of competing regions, which makes it possible to select homogeneous regions with minimal differences in the contribution of different types of activities to the regional economy. The algorithm is based on the calculation of localization coefficients, which makes it possible to make a representative sample. The use of the proposed algorithm for selecting competing regions will help strengthen the competitive positions of the assessed regions by using the experience of the regional policy of the compared entities of the Russian Federation. The algorithm was tested on the statistical data of the country's entities. As a result, a representative sample of the competing regions of the Amur Region has been formed, which should be used to assess the competitiveness of the region and identify its competitive advantages and weaknesses. The methods of selecting competing regions depend on the number of dominant types of activities and the purpose of the study. In it is necessary to consider competitors by all types of competitive specialization, the number of competing regions of the Amur Region will include 68 entities in 2022. If we select regions by industrial activity, the statistical set of competing regions will consist of 46 entities. 10.18721/JE.18106 303.717; 311.15; 332.133.44 (571.61) algorithm representative sample competing regions localization coefficients https://economy.spbstu.ru/article/2025.111.6/ 06_Vasileva.pdf

RAR RUS 124-138 Samaybekova. Zeynegul Study of factors influencing the development of innovations and labor potential in the economy of Kyrgyzstan In the context of a dynamically changing global market and high rates of external migration of the population of Kyrgyzstan, strategic management of innovations in the processes of development of labor potential is of particular importance, which generally contributes to the improvement of the general standard of living of the population. In Kyrgyzstan, innovation activities began to develop relatively recently, facing a number of challenges and opportunities caused by both internal economic changes and global trends. Therefore, the purpose of the study is to analyze the key factors influencing the development of innovations and labor potential in the economy of Kyrgyzstan. The study is based on an extensive review of scientific works of Russian and Kyrgyz researchers. The information base also included socio-economic indicators of the National Statistical Committee of Kyrgyzstan, the humanitarian portal of the Center for Humanitarian Technologies and other Internet resources. This paper provides a comparative analysis of strategic management of innovations and development of labor potential in Russia, Kyrgyzstan, Kazakhstan and Uzbekistan in international rankings. The main attention is paid to the analysis of key factors, such as R&D investments, scientific potential and research funding, migration processes, changes in the labor market, state support and others, affecting the effective strategic management of innovations in the processes of development of labor potential of Kyrgyzstan. The results of the study show that effective strategic management of innovations in Kyrgyzstan is possible subject to flexibility and innovative response to the dynamics of trends, as well as active interaction of all participants in the innovation ecosystem. A conclusion is made on the need for: development of innovation management strategies aimed at strengthening the interaction of science and business, attracting investment and developing research infrastructure; strategic management of innovations aimed at preserving and effectively using human capital, as well as focused on the development of labor potential. Further research should be aimed at developing a system of indicators for measuring the contribution of labor potential and methods for assessing the effectiveness of strategic management of innovations. 10.18721/JE.18107 330.3 actors and trends innovation labor potential scientific potential migration labor market strategic management of innovation https://economy.spbstu.ru/article/2025.111.7/ 07_Samaybekova.pdf

RAR RUS 139-159 Veretyokhin Andrei v_a_v_crimea@mail.ru Assessment of the industrial enterprise digital development level based on fuzzy logic method In modern turbulent conditions of digital ecosystem formation, it is important to promptly make informed managerial decisions on the development of an industrial enterprise. To maintain competitiveness, an enterprise must follow the trend towards digital transformation. In doing so, the use of ESG approach allows the manager to make strategically informed decisions on digital change. In the context of the importance of assessment in the management process, widely recognized by the scientific and expert community, scholars have so far developed many diverse and varied methods and models for assessing the digital transformation of enterprises. Scientists and practitioners use different sets of indicators and assessment methodologies. However, despite the numerous proposals, scholars have paid insufficient attention to the self-assessment of the digital development of an enterprise, taking into account its ESG sustainability. The purpose of this paper is to develop a universal toolkit for assessing the level of digital development of an industrial enterprise that is applicable in practice. The main research methods are analysis and synthesis, as well as methods of expert assessments and fuzzy logic, and the theory of fuzzy sets. The main results of the study are as follows: the requirements that the assessment of the level of digital development and its information and analytical tools must meet for suitability for practical use by enterprises are determined; a corresponding information and analytical tool for assessing the level of digital development; the testing of the tool for assessment of the level of digital development. The reliability of the proposed information and analytical tool is ensured by the following: this study is based on scientific and practical experience accumulated in the field of assessing the level of digital development of an industrial enterprise; the assessment uses a quantitatively limited set of easily definable indicators based on open data; the assessment uses detailed, tested and well-proven methods of hierarchy of indicators and fuzzy logic; the original software product DigInfoLogicTool has been verified on the data of industrial enterprises of the Crimean region. The use of this proprietary development will allow management to promptly make informed decisions on digital development, taking into account the ESG indicators of the enterprise. The results of this work can be the basis for future research aimed at developing methodological recommendations for selecting the direction of digital development and industrial enterprise digital transformation. 10.18721/JE.18108 338 management of organization industrial enterprise digital development digital transformation digitalization fuzzy logic ESG https://economy.spbstu.ru/article/2025.111.8/ 08_Veretyohin.pdf

RAR RUS 160-177 Dunskaia Lada dunskaia.l@edu.kubsau.ru Popova Elena Adaptation of k-means to automated forecasting of poorly structured time series of economic dynamics With the growing volume of data and increasing complexity of economic interactions, more advanced analysis methods and interdisciplinary approaches should be applied to study of systems with mixed behavior. Data mining methods used in machine learning or deep learning allow to take into account complex patterns and nonlinear dependencies in the data. Applied statistics methods provide reliable approaches to hypothesis testing, model parameter estimation and interpretation of results. It was established for different systems with complex behavior that economic processes are often characterized by nonlinearity, instability, and the presence of hidden dependencies. Furthermore, machine learning and deep data analysis methods allow not only to improve the forecasting accuracy but also to identify hidden patterns that may be overlooked by traditional statistical approaches. This is especially important in the study of financial markets, where the dynamics of change can be extremely unstable and influenced by many external factors. Such methods help to increase the effectiveness of decision-making in conditions of uncertainty, serving as indispensable tools for modern economic research. Thus, research in this area is urgent, as confirmed not only by the nature of the series, but also by the need to find more advanced methods of analysis and forecasting. The article provides preliminary analysis, additionally constructing a forecast based on a linear cellular automaton. Applied statistics and data mining tools were used for time series analysis as well as for adaptation of clustering methods as a means for automating the predictive model. We confirmed that use and integration of well-known clustering methods into the linear cellular automaton algorithm allows to identify patterns and improve the quality of the forecast. The object of the study is the time series of the financial market, since these economic series are influenced by a variety of factors that are hard to detect (in terms of their influence), such as external shocks, seasonal fluctuations and long-term trends. Our findings indicate that data mining algorithms make it possible to automate the process of translating numerical indicators of a time series into a linguistic equivalent to obtain predictive values without loss of quality. 10.18721/JE.18109 330.4 forecasting data mining methods of applied statistics linear cellular automaton https://economy.spbstu.ru/article/2025.111.9/ 09_Dunskaya%2C-Popova.pdf

RAR RUS 178-198 Krasyuk Tatyana actualbil@gmail.com Formation of an investment channel: determination, financial policy factors and strategic approach The relevance of this research is substantiated by the fact that the integrated management approach will help to unite and focus the heterogeneous instrumental mechanism of regulatory influence on investment processes to achieve strategic goals, in particular, the development of the supply-side economy in Russia. Without a radical change in investment policy, an increase in the volume of investment in the real sector of the economy, in particular, an increase in the production of means of production, a decrease in the level of depreciation of fixed assets, the most important problems of restructuring the economy and industry, the competitiveness of products and the technological level of production cannot be solved. A tight monetary policy does not objectify the investment channel, and the measures implemented within its framework do not lead to an increase in supply and competitiveness of the economy, do not develop investment demand. The relevance of forming an investment channel is justified by the goal of changing the vector of development and the formation of a supply-side economy, as well as adapting to external economic shocks. The purpose of the research is to develop an integrated management approach to identifying investment triggers, the most complete range of factors for the formation of an investment channel in the main production capital of the economy. The paper presents for the first time the definitions of integrated strategic investment management, investment channel, and investment trigger. The analysis of scientific views on the impact of financial and monetary policy on the supply-side economy and investment processes, taking into account different periods and levels of economic development, is carried out. An economic and mathematical analysis of individual factors of the sources of investment in fixed assets and the production base of the supply-side economy and their interrelations is carried out. Conclusions are made that the level and stage of economic development, the institutional structure and the structure of the financial system play a fundamental role in the formation of the relationship between the firm's leverage and investments in the economy, and the current set of endogenous and exogenous factors leads to the need to abandon the standard previously used patterns of monetary policy and methods for the development of the economy and investment potential. A structural model for the formation of an investment channel for the supply economy has been developed. The proposed approach forms the conceptual basis for the investment impulses and triggers search and the development of methodological solutions based on the integration of strategic, investment and financial management tools. 10.18721/JE.18110 330.322, 330.341, 334.02, 336.6 investment channel investment triggers monetary policy fixed production assets strategic approach supply-side economics production of means of production depreciation of fixed assets https://economy.spbstu.ru/article/2025.111.10/ 10_Krasyuk.pdf