Aim. The work aimed to develop an approach to solving import substitution problems and achieving the technological sovereignty in Russia based on the activation of interorganizational interaction.
Objectives. The work seeks to analyze the directions and results of the impact of sanctions of the collective West on the Russian economy; to reveal the relationship between sanctions and import substitution, as well as the achievement of technological sovereignty; to develop an organizational mechanism for solving import substitution problems using the opportunities of interorganizational interaction and creating strategic alliances of companies.
Methods. The study is based on theoretical developments in the field of management theory, the economic integration theory, as well as on the study of the possibilities of practical application of management tools for import substitution and achieving technological sovereignty under sanctions. The empirical analysis was performed taking into account the Federal State Statistics Service data. The authors used methods of institutional analysis, content analysis, organizational design, index method, special methods for assessing efficiency, as well as expert and situational approaches.
Results. It was established that, in addition to the traditional method of solving import substitution problems from above, which has largely exhausted its potential, import substitution from below is becoming more productive, which is based on the activation of entrepreneurial initiative by creating intercompany alliances focused on import substitution and technological sovereignty. This approach does not exclude state participation through partnerships with intercompany alliances, which can take on the role of a collective private partner in projects aimed at solving import substitution problems and achieving technological sovereignty.
Conclusions. In the context of geopolitical tension and geoeconomic instability caused by sanctions, the current state of production chains in the Russian economy poses a threat to the sustainability of economic development and national economic security. Taking measures to ensure import substitution and achieve technological sovereignty in this regard is becoming a priority. However such measures initiated by the state are not always sufficiently effective, since they are not supported by initiatives from the private sector, which is determined by the conflict of economic interests of the state (public interest) and business (private interest). Under these conditions, the projects to localize key stages of production chains in the country can only be implemented with guarantees of stable financing and future procurements of import-substituting products through the activation of inter-organizational interaction.

Aim. The work aimed to determine the advantages and disadvantages of the models used in Russian and international practice to assess the effects of implementing state regional policy.

Objectives. The work seeks to analyze Russian and international practice of applying economic and mathematical approaches to assessing the effects of implementing state policy (econometric models, input-output balance models, computable general equilibrium models), as well as to identify the specifics and limitations of these approaches.

Methods. The study employed general scientific methods (classification and comparative analysis) to obtain the scientific provisions formulated in the article.

Results. The basic economic and mathematical models used to assess the effects of implementing state regional policy are econometric models (systems of simultaneous equations and models of cause-and-effect relationships), input-output balance models, and computable general equilibrium models. Simultaneous equation systems are used to construct an interval forecast of endogenous variables of the model based on known or assumed values of exogenous variables characterizing the economic policy implemented. Econometric models of cause-and-effect relationships enable to identify and justify the effects of economic decisions on the model endogenous variables. In the input-output balance models, the estimates of effects are mainly associated with the production field; they are calculated for gross output and added value. Such models are easily reproduced, but are limited by the mathematical specification of the economy production structure. The advantages of computable general equilibrium models include a high level of detailed elaboration of the economic system, the ability to calculate effects for various institutional sectors and spatial objects.

Conclusions. Computable general equilibrium models are the most informative for analyzing structural changes in the regional economy when implementing public policy measures. In this regard, the authors recommend the development and use of models of this class in the formation of financial and economic justification and assessment of the consequences of the developed and implemented measures of state regional policy.

Aim. The work aimed to develop an algorithm for forming a digitalization strategy for the business ecosystem of an industrial enterprise.
Objectives. The work seeks to perform critical analysis of previous studies and approaches to digitalization of economic ecosystems; synthesize key principles of digital transformation capable to ensure the possibility of applying the strategy at enterprises with different levels of the ecosystem digital maturity; justify the proposed universal algorithm for the digitalization of business ecosystems based on the author’s approach to the stages of their evolution.
Methods. The study employed a comprehensive bibliographic and system analysis, comparative analysis and synthesis in the process of studying approaches to digitalization of business ecosystems. The informational background was published articles indexed in international scientific databases (Web of Science, Scopus, Russian Science Citation Index). For structuring the result, the authors’ development of the logic and stages of the evolution of business ecosystems in B2B was used, as well as the author’s integral approach to assessing their efficiency based on five criteria.
Results. The key principles of digitalization include ecosystemacity, co-evolution, adaptability, joint value creation, a hybrid approach to platforms, and consideration of organizational and cultural aspects. A standardized algorithm for forming a digitalization strategy for an industrial enterprise business ecosystem has been developed, consisting of successive stages, namely diagnostics of digital readiness, setting strategic goals, designing digital architecture, implementing digital solutions, developing a digital culture and monitoring with adaptive management.
Conclusions. The authors focus on the need for a comprehensive approach to digital transformation that takes into account financial, technical, operational, as well as organizational, cultural, and market-related aspects of the enterprise. The approach novelty consists in the formation of a unified algorithm applicable to various stages of the evolution of digital business ecosystems and the development of a model linking the strategic principles of digitalization with specific performance criteria. The proposed approach allows companies to approach digital transformation systematically and adapt successfully to the changing conditions of the digital economy.

Aim. The work aimed to determine the socio-economic effects of the introduction of artificial intelligence technologies (hereinafter referred to as AI) in the emerging Russian digital economy, as well as to identify problematic aspects of the use of AI in the future.
Objectives. The work seeks to analyze priority fields of AI application in the economy, including automation of production processes, data mining, development of digital platforms and services, as well as the introduction of AI in public administration; to assess the socio-economic effects of AI application, in particular to study the impact on labor productivity growth, changes in the employment structure, redistribution of jobs, increased efficiency of business processes and improved quality of services provided; to analyze possible risks associated with technological unemployment, increased social inequality and ethical aspects of AI application.
Methods. The research methods are based on the basic economic concepts of the digital economy, the use of a risk-oriented approach to considering the problem, as well as the use of general scientific methods for studying socio-economic phenomena and approaches.
Results. The work proposed strategic directions of public policy aimed at stimulating innovative activity, developing digital infrastructure, and ensuring inclusive socio-economic growth in the context of active implementation of AI technologies.
Conclusions. AI is becoming an integral component of the economy and public administration system at the current stage. Its implementation speeds up processes, including in cases of decision-making, reduces costs, and improves the quality of services. However, technological progress requires a sound approach, as it is necessary to develop simultaneously the legal framework, institutional mechanisms, and culture of responsible use of AI.

Aim. The work aimed to develop a balanced scorecard of quantitative indicators of the efficiency of strategic human resource management in IT companies of the Russian Federation (RF).
Objectives. The work seeks to analyze existing methodological approaches to assessing the efficiency of human resource management; to identify key factors and goals of human resource management in IT companies in a specific scorecard; to compile a balanced scorecard of human resource management efficiency for IT companies.
Methods. The study employed methods of comparative analysis of approaches to assessing efficiency, as well as methods of system analysis of strategic human resource management processes.
Results. A critical analysis of existing approaches and indicators of human resource management efficiency was performed. It determined the key results and goals of human resource management in IT companies in the context of a balanced scorecard. A balanced scorecard of quantitative indicators of human resource management efficiency in IT companies of the Russian Federation was developed, structured according to four perspectives, namely finance, clients, processes, training and development.
Conclusions. The work revealed the absence of universal methodological approaches and systems of indicators of the human resource management efficiency. The list of balanced indicators of efficiency developed in the course of this study takes into account the specifics of the manifestation of intellectual human resources and can be recommended for use in IT companies of the Russian Federation for strategic management of human resources in order to obtain competitive advantages under a shortage of highly qualified personnel.

Aim. The work aimed to identify the main problems and aspects of small entrepreneurship development in modern Russia.
Objectives. The work seeks to analyze the current state of small business development; reveal the key problems and features of the development of small and medium-sized business entities (SMEs) in Russia; identify the functions and main differences between small entrepreneurship and medium-sized and large businesses; reveal the content of new national projects and initiatives for state support of small businesses.
Methods. The authors used general scientific methods (analysis, synthesis, systematization), as well as institutional and comparative approaches, to substantiate the provisions and conclusions. 
Results. The article analyzes the key problems and aspects of the development of small businesses in Russia. The authors revealed that the latter face a number of challenges. The most significant of them are limited access to financial resources, including difficulties associated with raising of credit funds due to high interest rates and complex collateral security requirements; difficulties in overcoming bureaucratic obstacles; a high level of competition from large corporations with significant financial and technological resources.
Conclusions. The authors came to the general conclusion that small businesses contribute to the creation of a competitive environment and are flexible in accordance with market changes; they perform an important social function, absorbing surplus labor and thereby contributing to the expansion of employment. Small businesses optimize the use of local resources, increasing their economic efficiency.

Aim. The work is aimed to determine the impact of Big Data technologies on the transformation of mechanisms for forecasting sports events, managing financial risks, and the forming business strategies in sports betting.
Objectives. The work seeks to formulate priority fields for the use of Big Data technologies in the financial system of sports betting; to assess the impact of Big Data on methods for forecasting the outcomes of sports events and the financial risk management system; to substantiate the regulatory and ethical aspects of using Big Data in the financial system of sports betting; to make a forecast of the development of analytical systems based on Big Data in the sports betting.
Methods. The authors reviewed scientific literature, studied the cases Big Data influence on the financial system of sports betting, as well as expert assessments from open sources.
Results. The study identifies the key fields of Big Data in the financial system of sports betting, namely outcome forecasting, risk management, and personalization of client strategies. The work also substantiates the facts of increasing the accuracy of forecasts and reducing the time of odds generation. Ethical and regulatory risks were identified. The work proposes development directions, namely hybrid analytics model, adaptive margin, and algorithmic transparency standards.
Conclusions. The impact of Big Data digital technologies on the financial system of sports betting is manifested in their ability to radically transform the betting industry, including key business processes and financial models. The use of Big Data technologies has a systemic impact on the betting industry, while transforming its key business processes. These technologies ensure a high level of forecasting accuracy, increase economic efficiency, and adapt strategic management in the context of digital competition. Thus, Big Data is becoming not only an analytical tool, but also a factor in restructuring the entire financial architecture of the industry. The implementation of Big Data requires institutional and regulatory support, which is an important condition for the sustainable development of the sports betting market.

Aim. The work aimed to determine priority fields of digitalization of tax administration in relation to entities of the agricultural sector of the Russian Federation (RF), including an analysis of problems of the current functioning of the unified agricultural tax (UAT) mechanism, and to develop proposals for the implementation of digital solutions aimed at increasing transparency, automating interaction with tax authorities, and reducing the administrative load on agricultural producers.
Objectives. The work seeks to analyze the current level of digitalization of tax administration in the agro-industrial complex; to identify organizational, infrastructural and legal barriers to the implementation of digital technologies in the tax policy of the unified agricultural tax; to study the current digital tools used by the Federal Tax Service (FTS of Russia), and assess their applicability to agricultural entities; to develop models of digital administration of the unified agricultural tax taking into account interdepartmental integration and the level of digital maturity of agricultural organizations; to propose a set of measures for the implementation of digital services, mobile applications and training platforms for agricultural workers; to define digital benchmarks for the transformation of tax administration in the industry.
Methods. The study employed systemic and comparative legal approaches which enabled to identify structural relationships between tax regulation entities and digital platforms; as well as an economic and statistical analysis of official reporting data from the Federal Tax Service of Russia, the Ministry of Agriculture of Russia, and the Ministry of Digital Development of Russia for 2019–2024 was performed. The project method was used to create a digital administration model for the unified agricultural tax, including a description of the platform functional architecture and an assessment of the expected results. The graphical method is used to visualize the integration links between participants in tax interactions, as well as to compile a comparative table of the current and target state of digital transformation in the industry.
Results. It was established that the level of digitalization of tax administration in agriculture remains fragmentary, namely less than 40% of entities use electronic document management; and integration with the information systems of tax authorities is difficult due to the lack of standardized solutions and weak digital infrastructure in a number of regions. Key barriers were identified. These include insufficient digital literacy of taxpayers, low level of Internet access, and poor adaptation of existing digital platforms to the specifics of the unified agricultural tax. A digital administration model was developed, including the creation of a single digital platform for the unified agricultural tax, the implementation of a mobile application, integration with accounting cloud systems, as well as interaction with banks and cadastral authorities. Measures were proposed for the phased implementation of digital solutions with an assessment of their effect by key indicators, namely reporting processing times, the share of digital document flow, and the degree of automation of calculations. The results are systematized in tabular and graphical ways, indicating the promising architecture of tax interaction.
Conclusions. The theoretical and regulatory aspects of digitalization of tax administration in the agricultural sector were analyzed with an emphasis on the unified agricultural tax. A need was identified to adapt the system of interaction between tax authorities and agricultural producers to industry specifics, eliminate digital inequality, and optimize information exchange. The scientific novelty consists in the development of a model for the unified agricultural tax digitalization, which includes information exchange, automation of tax calculations, and digital services. Measures for regulation, training, information security, and monitoring with cost assessment were proposed. The results confirmed the model efficiency for successful digitalization of tax administration in the field of agricultural business. The proposed measures can be used in programs for digitalization of tax administration and support of the agro-industrial complex.

Aim. The work aimed to identify distinctive methods of business acceleration, applied to accelerate the development of technology entrepreneurs in Russia.
Objectives. The work seeks to characterize the methods used in Russian acceleration programs; to evaluate the effectiveness of the methods for supporting technology entrepreneurs, used by business accelerators; and to classify the methods of acceleration programs based on the instruments used.
Methods. The work employed comparative analysis, generalization, classification, as well as systemic and structural approaches. Data from secondary expert interviews and statistical reports on the results of graduate clients of Russian accelerators were used. The work also analyzed the works of Russian and international scientists studying acceleration programs.
Results. It was established that the startup development in acceleration programs is accelerated due to seven distinctive methods that form the business acceleration methodology. These include constant external support, rapid hypothesis testing, expansion of social bonds, increase in effective working hours, provision of a ready-made methodology, access to capital sources, and increased availability of other resources. The methodology helps entrepreneurs save time, optimize business processes, and focus on the growth points of their business. Based on the study results, an expanded classification of support methods used in Russian acceleration programs was created based on the tools used.
Conclusions. Acceleration of startup development in accelerators occurs due to a specific methodology that helps reduce time expenditures on business processes and increase operational efficiency. According to the results of acceleration programs in 2015–2020, the technology companies increased the value of a number of business indicators such as revenue, average receipt amount, and number of clients, as well as accelerated the transaction cycle, employed the capital, and reached quickly the break-even point relative to natural market conditions. The study results have not only scientific but also practical value for organizers and participants of acceleration programs. In order to implement the research potential of the Russian acceleration program market, it becomes necessary to study further their methodology and effectiveness in 2022–2025. Future studies plan to evaluate the application of the identified methods in various types of acceleration programs (state, university, corporate), as well as compare the methodology applied in the Russian and international acceleration backgrounds.

Aim. The work aimed to determine the gender influencing factors on the choice of financial products.
Objectives. The work seeks to study of consumer groups with characteristic differences in demand for financial products based on gender; review the groups of financial products most in demand among men and women; analyze the nature of the influence of gender on the choice and consumption of financial products.
Methods. The work employed a methodological approach that includes a review and comparative analysis of Russian and international publications; quantitative analysis of data from the All-Russian household survey on consumer finances.
Results. The work identified clusters with distinctive characteristics of demand for financial products by combining the gender factor with the age group and marital status. The study selected groups of financial products, with the demand for them having different characteristics for the clusters specified. The gender factor influence in combination with the age group and marital status on the demand for a number of financial products was analyzed.
Conclusions. The gender factor is a significant driver of demand for financial products. Gender is one of the key demographic variables that determine consumer interest in using financial market products, as well as quantitative and qualitative indicators of this demand. The nature of the gender factor influence largely depends on other social and demographic characteristics.

Aim. The work aimed to reveal the mechanisms of the social credit rating in China and evaluate its effectiveness.
Objectives. The work seeks to determine the economic problems that social credit rating system is able to solve in China; to identify the main advantages and disadvantages of this tool in managing the state economy; to consider how this system is used to resolve the issue of interaction between the state and business to ensure economic security.
Methods. The study employed general methods of scientific cognition to discuss the policy of China in the field of digitalization of economic management and the processes of interaction between the state and private business in various aspects.
Results. The corporate credit rating system is an effective tool for tracking potential fraudulent schemes and economic crimes. It also helps to provide targeted subsidies to promising companies that meet the necessary requirements from the state for the purpose of economic growth and innovation, thereby reducing the risk of ineffective investments.
Conclusions. The introduction of a corporate social credit rating enables to systematize the information about companies in the People’s Republic of China (PRC) and increase transparency in monitoring of state subsidies. Such an initiative allows for more targeted allocation of budget funds, which helps to achieve greater results with less resource expenditure.

Aim. The work aimed to develop new instruments of state policy for sustainable development that meet modern challenges and are aimed at increasing the efficiency of renewable energy projects in Russia and China.
Objectives. The work seeks to identify the main differences in the state policy for sustainable development of Russia and China; determine the promising areas of cooperation between these countries in the field of renewable energy; substantiate the possibility of developing and applying innovative instruments of state policy for sustainable development in the field under consideration.
Methods. The study employed comparative analysis, economic and mathematical modeling, as well as principles of implementing a joint auction platform. Comparative analysis was used to identify differences in the set of mechanisms used to implement state policy for sustainable development in Russia and China. Using economic and mathematical modeling, a pricing model for renewable energy was created. Cross-border management of renewable energy can be implemented by generating a cross-border traceability system for green energy based on blockchain, the Vickrey – Clarke – Groves (VCG) joint auction platform, and a system of mutual recognition of technical standards.
Results. Innovative government regulation instruments contribute to the growth of the efficiency of cross-border transactions in the field of green energy, shorten the product certification cycle, and increase the effectiveness of the integration of digital technologies.
Conclusions. The innovative instruments and programs of state regulation proposed in the study are aimed at strengthening cross-border energy cooperation and global carbon neutrality management.