2782-6015 18 2 2025 1-200

RAR RUS 7-29 LI Rong Measuring and comparing the development of the digital economy of the SCO member states With the implementation and further development of the Digital Silk Road initiative, the countries along the route have gradually formed common interests in the field of digital economy. The active development of the digital economy within the framework of the implementation of the Belt and Road initiative in these countries contributes to their socio-economic development, increasing the level of trade and openness, accelerating the growth of the green economy and forming a new development model both at the domestic and international levels. Most of the countries participating in the Belt and Road initiative and the Eurasian Economic Union (EAEU) are members or observers of the Shanghai Cooperation Organization (SCO). Economic ties between these countries are constantly strengthening, and the SCO has become an important regional economic and strategic platform. Since 2015, when the SCO began to develop cooperation in the field of digital economy, there has been insufficient research on the development of the digital economy and cooperation between China and the SCO member states. This article analyzes the current situation and development problems of the SCO member states from the perspective of the digital economy. By comparing the existing digital economy development index systems, a digital economy development index system for the SCO was developed, including six dimensions: digital infrastructure; digital connectivity; digital industry development; digital innovation competitiveness; digital economic environment; digital governance. The entropy method was used to measure the degree of digital economy development of China and the SCO member states, as well as the level of cooperation between them. The digital economy development indices of China and the SCO member states for the period from 2005 to 2022, as well as bilateral digital economy cooperation indices, were measured and compared. The comparative analysis shows that the SCO member countries have made rapid progress in the development of digital infrastructure, digital applications, digital development and digital innovation competitiveness. However, the level of digitalization has not grown so fast. China has an absolute advantage in the digital economy, but its development pace has slowed down at present. The level and speed of digital economy development of Russia, Belarus and India are above average, while the level of digital economy development of Uzbekistan and Pakistan is relatively low. In recent years, the digital development of the SCO member countries has grown rapidly, and economic and trade cooperation has become closely related to digital cooperation. In the future, the SCO member countries are expected to further strengthen cooperation in the digital economy, especially in building digital infrastructure, empowering digital innovation, promoting digital trade, cross-border e-commerce, digital finance, etc., as well as in digital security and privacy protection, helping to solve the problem of “digital inequality” and digital economic governance. All this is expected to further promote economic prosperity and sustainable development of the SCO member countries. 10.18721/JE.18201 339.9 digital economy digital inequality digital economic development entropy method SCO https://economy.spbstu.ru/article/2025.112.1/ 01_Li-Zhun.pdf

RAR RUS 30-48 Melnikov Alexandr melnikov4work@gmail.com Kalabina. Elena kalabina@mail.ru Analysis of the distribution of digital tools in the activities of russian enterprises The relevance of the research is due to the increased interest of enterprises in digitalization and the use of digital technologies and tools in business processes. Enterprises are increasingly faced with the need to use digital technologies such as artificial intelligence, cloud services, big data analysis technologies, etc. The effectiveness of using these technologies directly affects the quality and speed of business processes, which directly affects the competitiveness. The main purpose of the work is to analyze the spread of digital tools in the activities of enterprises in the Russian Federation. The scientific novelty of the study lies in the assessment of the use of digital tools and technologies by enterprises in the Russian Federation in 2019–2023. The authors conducted a quantitative analysis of statistics on the use of digital technologies and the cost of their implementation. Subsequently, the dynamics of the introduction and application of digital technologies and tools in industries were revealed. The theoretical and methodological basis of the study were research materials on the digitalization of business processes, on improving the digital competencies of enterprise employees, as well as on assessing the impact of digital technologies on the activities of enterprises. Quantitative data analysis, expert and comparative analyses were used as research methods. The information base was statistical data on the use of digital technologies by enterprises, as well as research on trends and management methods in the context of digital transformation. The result of the work was the formation of an assessment of the current state of the spread of digital technologies in the activities of enterprises in the Russian Federation. The results can be used to develop digital transformation strategies and improve enterprise management in the digital economy. The data obtained also allows businesses and government agencies to monitor the process of digitalization and adjust plans for digital development. The main conclusion of the study is that enterprises in the Russian Federation mainly meet basic needs using digital technologies, while there is potential for the development of more complex solutions. In the future, research areas may focus on in-depth analysis of barriers associated with the digital skills of employees, as well as on the development of hybrid models of digital maturity suitable for Russian realities. 10.18721/JE.18202 338.24 digital transformation digital technologies digitalization digital economy https://economy.spbstu.ru/article/2025.112.2/ 02_Melnikov%2C-Kalabina.pdf

RAR RUS 49-72 Razmanova Svetlana s.razmanova@sng.vniigaz.gazprom.ru Omysheva Tatiana Tatyanaomysheva2009@yandex.ru Chernova Elena e.chernova@spbu.ru Russian market of engineering services in oil and gas industry: fundamentals and state of the art Today, the domestic engineering market in the Russian Federation is growing twice as fast as the global one. The field of engineering services provided in the oil and gas industry is characterized as the most dynamic with a wide range of opportunities for Russian engineering companies if they take on functions previously performed by Western EPC contractors. This article analyzes the formation of the modern market for engineering and construction services, starting from the second half of the 19th century to the present. While the first approach to such concepts as engineering and engineering services was formulated during the Soviet period with its state funding, it has been significantly transformed but over the past decades. The paper considers the specifics of Russian terminology and conceptual framework describing engineering and engineering activities. We touch upon such issue as the lack of a unified approach to the definition of engineering activities in Russian legislative practice. It is noted that the conceptual framework for engineering activities should be unified at the legislative level in the future. The dynamics of value volumes (from 2013 to 2023) as well as current and future trends in the development of the Russian market of engineering services are considered. The authors emphasize that the main drawback of Russian and foreign companies hindering the creation of a balanced domestic market for engineering services is the lack of appropriate competencies at the project management stage. It is observed that the market for engineering services directly depends on the situation in the oil and gas exploration and production market. 10.18721/JE.18203 338.012 engineering oil and gas industry competitiveness market of engineering services https://economy.spbstu.ru/article/2025.112.3/ 03_Razmanova%2C-Omisheva%2C-CHernova.pdf

REV RUS 73-86 Afanasev Kirill k-i-r-i-l-l-a@mail.ru Kalinin Aleksandr kalinal@yandex.ru Tools for forecasting regional economic growth using big data and business intelligence technologies The significance of the study is due to the increasing complexity of regional economic growth forecasting in the context of digital transformation and the limitations of traditional analysis methods. According to research, the volume of generated data on regional socio-economic development increases by 40–50% annually, requiring fundamentally new approaches to their processing and analysis. Existing forecasting methods do not effectively account for nonlinear relationships and synergetic effects between various regional development factors. The goal of the study is to construct comprehensive tools for forecasting regional economic growth based on integration of big data technologies and modern business analytics methods. The research methodology includes modified machine learning algorithms specifically adapted for regional data analysis, using both structured and unstructured information sources. The developed tools were tested on data from 76 Russian regions for 2015–2023 using distributed computing systems. The novel findings of this study is that we created integrated tools for detecting nonlinear effects and synergetic interactions between growth factors, as well as quantifying factor thresholds and lag effects of their influence. A methodology for comprehensive assessment of digital transformation's impact on regional development has been proposed for the first time, considering the relationships between technological, social, and institutional factors. The practical significance is confirmed by successful implementation in regional governance, providing a 20–25% increase in management efficiency through more accurate forecasting and comprehensive consideration of growth factors. The developed tools were implemented in strategic planning practices of several Russian regions, showing high effectiveness in developing socio-economic development programs. Further research directions include expanding the analyzed indicators through IoT data and digital platforms, improving machine learning algorithms for economic instability conditions, adapting tools for municipal governance level and developing integration mechanisms with existing regional management information systems. 10.18721/JE.18204 332 big data economic growth regional development forecasting machine learning business analytics synergetic effects digital transformation regional governance strategic planning https://economy.spbstu.ru/article/2025.112.4/ 04_Afanasev%2C-Kalinin.pdf

RAR RUS 87-99 Yanenko Marina myanenko@mail.ru Ianenko Mikhail Transformational changes in the economy in the context of the development of digital business models: influence factors, problems, prospects Transformation of economic management processes has become a crucial direction against the background of fierce competition and explosive rise of digital technologies in various industries. The significance of this problem in the context of the development of digital business models radically changing the situation in a number of economic sectors is linked with the demand for new approaches to improve enterprise management, create and develop innovative tools ensuring competitiveness in the digital economy. The goal of the study is to generate new approaches to management of transformational changes within the framework of modern business models, offering practical recommendations for the development of competitive strategies. The work uses methods of system analysis, structural and logical analysis, content analysis, as well as economic and statistical methods, methods of comparative analysis, forecasting and expert assessments. The classification of digital business models developed by the authors allows to formulate recommendations for using the concept of digital business models in managing the digital transformation of enterprise activities. The directions proposed for constructing the concept of managing the transformation of activities in the digital economy allow to account for: potentially providing consumers with additional free services in exchange for receiving data on their consumer behavior; network effects; role of digital technologies as a source of innovation. Recommendations are given for using digital business models together with marketing tools in the activities of the enterprise associated with promoting material, digital and virtual products, including in metaspatial business entities. The scientific novelty of the work lies in combining the concept of digital business models with marketing tools when analyzing the processes occurring in the digital economy. Specific examples illustrate the transformations occurring under the influence of digital business models, recommendations are given for the formation of strategies in a changing competitive environment. It is confirmed that the development and implementation of innovative business models requires engaging marketing specialists and integrating marketing tools. Further research is expected to focus in-depth analysis of the impact of digital business models on the improvement of product and pricing policies, sales systems and product promotion in the context of the development of artificial intelligence. 10.18721/JE.18205 332.05 competitiveness innovation consumer behavior technology transformation management digital business models https://economy.spbstu.ru/article/2025.112.5/ 05_Yanenko%2C-Yanenko.pdf

REV RUS 100-120 Kuchumov Artur arturspb1@yandex.ru Eremicheva Polina eremicheva2000@outlook.com Features of formation of industrial cluster policy in developing countries of Asia The article considers the features of development, formation and application of cluster policy of the industrial complex within the borders of developing Asian countries. The purpose of the article is to identify the characteristic features of the model of development of industrial cluster policy in the conditions of the Asia-Pacific region through a comparative analysis of individual countries. The authors set a number of tasks for conducting the study of the designated issue taking into account the available information, including determining the main stages in the chronology of development of industrial cluster policy in China, Thailand and the Republic of Korea; identifying the role of government agencies in the formation and practical implementation of industrial cluster policy; identifying the main patterns in the practice of applying the results of designing industrial cluster policy within the borders of China, Thailand and the Republic of Korea; studying the factors influencing the development of industrial cluster policy and the course of its practical implementation in Asian countries; analyzing and assessing the degree of influence of the implementation of measures within the framework of cluster policy on the development of the industrial complex of the countries presented in the review. Among the methods that were used in the process of writing the article, the authors applied ontological analysis, system analysis, content analysis, specification and comparison. As an example, the authors turned to the experience of developing industrial cluster policy in China, Thailand and South Korea. In the course of the study, the main indicators were identified that reflect progress within the framework of the considered area of development of the countries, the main intersections in the structure of industrial cluster policy of the three developing economies were identified, and the key patterns of their development were studied in a private manner. The authors conducted a retrospective analysis of the stages of formation of industrial cluster policy in China, Thailand and South Korea, and identified the characteristic features of the current level of development of the countries. As a result of the study, it was possible to compile in chronological order the stages of development of industrial cluster policy in Asian countries, identify key conceptual features in its reform, trace a number of intersections and analogies in matters of development and implementation of industrial cluster policy using the example of large economies. 10.18721/JE.18206 332.1 cluster approach clusters industrial cluster cluster policy Asia-Pacific region market state institutional management public-private partnership https://economy.spbstu.ru/article/2025.112.6/ 06_Kuchumov%2C-Eremicheva.pdf

RAR RUS 121-133 7005476276 0000-0002-8228-3109 Peter the Great St.Petersburg Polytechnic University Glukhov Vladimir vicerector.me@spbstu.ru

195251, St.Petersburg, Polytechnicheskaya, 29

Kolomysova Mariya km@spbstu.ru Methodology for assessing the business activity index of an enterprise based on the analysis of the business environment An overview of common business activity indices is presented, methods for their calculation are given, a generalized method for calculating the consolidated business activity index is presented, the role of business activity as an indicator of economic system development is shown; indicators for assessing business activity are systematized in relation to the specifics of entrepreneurial activity. The concept of business activity is defined, a method for calculating business activity indices of industrial enterprises is proposed. The work identifies the characteristic features of the existing framework for assessing the level of business activity of an industrial enterprise, discusses the methodological experience of developed countries and the Russian Federation, and provides quantitative values of the business activity index. The proposed method for assessing the business activity index of enterprises is constructed by calculating a set of qualitative and quantitative indicators. The directions of the enterprise’s activities are taken into account and a generalized characteristic of these activities is proposed, areas of application of the business activity index in managerial strategic decisions are detected. The elements of the methodology are described: the choice of the composition of indicators, the algorithm for calculating the consolidated index of enterprises, the algorithm for calculating the business activity index of a group of enterprises; interpretation of the results. The system of proposed indices allows to analyze and compare economic indicators of different periods, to determine trends and to forecast further development of the market, providing an important tool for developing business plans, helping business and investors to make decisions based on objective data on the economic situation. The authors systematized the indicators of business activity assessment with respect to the specifics of entrepreneurial activity; developed algorithms for calculating the quantitative and diffusion aggregate index of business activity of the enterprise; the relationship between the entrepreneurial situation assessed by business activity indices and recommended management decisions is shown. The developed methodology for assessing the index of business activity of the enterprise can be developed within the scope of application by top management of industrial and regional associations of manufacturers and entrepreneurs. The framework developed allows to reasonably characterize the results of the activities of enterprises that are members of associations, choose the necessary forms of support for their commercial activities, lobby their interests before government bodies. 10.18721/JE.18207 658 business activity index PMI index business environment enterprise https://economy.spbstu.ru/article/2025.112.7/ 07_Gluhov%2C-Kolomisova.pdf

RAR RUS 134-149 Baushev Sergey 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

Volokitina Irina Galeev Eduard Formation of integrated corporate structures in the defense-industrial complex of Russia in the conditions of global challenges The article analyzes the integration processes in the military–industrial complex (MIC) of Russia, characterizing the development of production and technological ties, structural transformation, as well as the interaction of MIC enterprises in the course of formation and implementation of different consolidation strategies. The significance of the study is associated with the need for structural reform of MIC in the context of geopolitical tensions. Sustainable development of MIC can be achieved by introducing strategic changes in the structure of production, with the integrated corporate structures entering new markets for civilian products. The specific consolidation strategy for MIC enterprises is chosen based on the objective features of various types of integration. In general, this should help reach the key objective of integration, which is to achieve the synergistic effect, expressed in increasing production efficiency, reducing costs, accelerating technological development and strengthening competitive positions in the market. The goal of the study is to systematically analyze and identify the key factors that determine the strategy for consolidation of MIC enterprises focused on the combination of civil and defense production, which should contribute to effective modernization of the national MIC by improving its investment attractiveness. A classification of types of integrated corporate structures devised by the authors is proposed to plan integration processes. The prerequisites for combining enterprises in hard and soft forms are substantiated, the effects of integration are determined. The novelty of the study is in the formation of a set of factors taken into account when choosing a consolidation strategy in modern conditions. The practical experience of existing scientific and production associations was used to determine the real risks arising in the formation of integrated corporate structures. The authors note that the association of enterprises in integrated corporate structures is a popular strategy for economic growth of MIC in Russia in the conditions of tension of world and national markets. Given the fact that integration is an expensive process with high risks, targeted government support measures are needed to solve this problem. As the directions for further research into the integration processes in the military–industrial complex of Russia, the authors see the development of a model for assessing financial stability based on stochastic simulation modeling. 10.18721/JE.18208 658.5 defense-industrial complex development strategies organization of production integration of enterprises risks of formation of integrated structures https://economy.spbstu.ru/article/2025.112.8/ 08_Baushev%2C-Babkin%2CVolokitina%2C-Galeev.pdf

RAR RUS 150-163 Tatarovsky Yury Formation of a risk-based monitoring indicators system for the activities of backbone enterprises  The domestic economy is currently under great pressure from external and internal factors. To solve its tasks, the state needs not only a short-term mobilization of financial resources at the current moment, but also the creation of a reliable, strategic foundation for growth and sustainable development. Backbone enterprises are socially and economically significant business entities, act as guides and main subjects of the state's economic policy, and form the basis of the economic security of the entire country. This leads to the need for monitoring (systematic collection and analysis) of information about the activities of these enterprises. The purpose of the study was to develop a methodology that helps identify key risks of backbone enterprises. The author's approach to the formation of a risk-based monitoring system for the company's activities differs from those methods used by relevant government agencies. In particular, it takes into account the specific risks inherent only to backbone enterprises. The object of the study was the main aspects of the activities of backbone enterprises, reflected in the indicators of financial condition and trends. The monitoring methodology was tested at strategic enterprises of the Samara region. The research conducted by the author is based on quantitative methods of analyzing the activities of enterprises. Thus, the coefficient method was included in the basis, as well as the analysis of dynamics and identification of trends occurring in backbone enterprises. As a result of the conducted research, the practical possibility of applying the proposed methodology and the sufficiency of information openness of backbone enterprises were proved. The practical significance of the conducted research is that during testing, the key risks of backbone enterprises were identified (using the example of strategic backbone enterprises in the Samara region), as well as the trends in the economic activity of backbone enterprises were analyzed, on the basis of which conclusions were formulated regarding the economic security of these enterprises. The direction of further work is to study a larger number of backbone enterprises (not included in the list of strategic ones) in order to identify common trends, threats and risks of the development of these economic entities. 10.18721/JE.18209 332.1 backbone enterprises financial condition financial analysis monitoring risk analysis economic security https://economy.spbstu.ru/article/2025.112.9/ 09_Tatarovskiy.pdf

RAR RUS 164-178 Saranin Zakhar Skhvediani Angi shvediani_ae@spbstu.ru Econometric modelling of oil export countries development The Organization of the Petroleum Exporting Countries (OPEC) brings together the largest oil exporters from around the world, which determine the volumes of supplies and prices of hydrocarbons on the global market. However, their income directly depends on demand, which is influenced by the economic conditions and growth rates of the world’s leading economies. Therefore, the purpose of this study is to analyze the relationship between macroeconomic indicators and the GDP of OPEC members. For this analysis, data from 11 OPEC countries for the period from 1990 to 2023 were collected. The relationships between variables were estimated using pooled regression models, as well as models with random and fixed effects. The Hausman test was used to choose between fixed and random effects models. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to choose between models in the same group. Additionally, the likelihood ratio test (LR test) was used to test the models are nested. The dependent and independent variables were logarithmized. Furthermore, the squares of independent variables were incorporated into the model to detect nonlinear dependencies. Significant nonlinear relationships were identified between the economic development of OPEC countries, expressed in GDP and several indicators, including daily oil production, population, daily world demand for oil, exchange rate, spot price of the mail oil brand, unemployment. At the same time, a J-shaped dependence was observed only for the population of oil-exporting countries, while an inverse J-shaped dependence was observed for daily world demand for oil. The latter may potentially suggest symptoms of Dutch disease in the countries under study during periods of high world demand for oil. The findings of the study could be used to improve the economic policies of OPEC countries. 10.18721/JE.18210 332.1 econometric modeling economic growth oil-exporting countries socio-economic factors oil https://economy.spbstu.ru/article/2025.112.10/ 10_Saranin%2C-Shvediani.pdf

RAR RUS 179-200 Shkanov Bulat bulat.shkanov@mail.ru A comprehensive approach to portfolio optimization based on modern mathematical modeling methods  In this study, an integrated approach to portfolio optimization is presented, combining modern time series forecasting methods and flexible settings for portfolio optimization. In conditions of high volatility in the digital asset market, traditional models such as Markowitz and CAPM lose their effectiveness without accurate return forecasts, as they do not account for dynamically changing market conditions. In this work, an approach is proposed that includes the adaptive selection of forecasting models for each asset and the optimization of portfolio weights based on forecast data. For asset price forecasting, ARIMA, Chronos Forecasting, GMDH, and LSTM models are employed, which allows various aspects of market dynamics to be taken into account. Based on the forecasts, a covariance matrix of returns is calculated and portfolio optimization is performed considering different strategies: allowing short positions, risk minimization, and achieving a predetermined level of return. The approach was tested on data from yfinance with various parameter configurations, including the number of assets, forecast horizon, and data scaling approaches. The experimental results show that the proposed approach yields an average realized portfolio return of 55.2%, with the proportion of portfolios achieving positive returns reaching 83.3%. Using the median as the scaling strategy increases the average return to 66.9%, with 92.6% of the portfolios being successful. This approach serves as a tool for investors, allowing strategies to be adapted to changing market conditions and enhancing the efficiency of digital asset portfolio management. Furthermore, the proposed approach demonstrates a high degree of flexibility due to the ability to adjust various optimization parameters. For example, varying the forecast horizon allows both short-term and long-term market trends to be taken into account, while the choice of scaling strategy influences prediction accuracy. Portfolio optimization is carried out considering various metrics, making the approach applicable to both conservative and aggressive investment strategies. Further research may include expanding the set of forecasting models, integrating alternative optimization strategies, and applying the proposed approach to traditional financial markets. This would enhance forecasting accuracy and the effectiveness of investment management under conditions of high uncertainty and volatility in digital assets. 10.18721/JE.18211 336.767.2 investment portfolio optimization machine learning returns prediction price prediction time series https://economy.spbstu.ru/article/2025.112.11/ 11_Shkanov.pdf