The article examines the key factors of competitiveness of video game ecosystems based on the experience of four countries where video game clusters have been formed – the USA, Canada, the United Kingdom, and Japan – as well as Russia, where the industry is at an early stage of the growth. Video game clusters are cities or regions with a high concentration of companies and organizations associated with the development of the video game industry. The purpose of this study is to identify the conditions that contribute to the growth of the industry, as well as the socio-economic, technological, and institutional characteristics that shape the competitive advantages of video game clusters. It has been found that such clusters are characterized by a high level of digitalization, developed innovation and technological infrastructure, stable socioeconomic environment, and synergy with related industries that strengthen the ecosystem (for example, cinematography, information technology, animation). Additionally, one of the significant roles in the formation of competitive video game ecosystems is played by established and stable mechanisms of interaction be-tween the government, business, and industry associations, as they create conditions for effective implementation of industry policy and contribute to the formation of a favorable institutional environment. The research findings can be used to develop strategies, tools, and programs to stimulate the gaming industry in Russia to enhance its competitive position in the global market.

For implementing the high-level achievements of the neo-industrialization policy, significant investment resources are required, the external volumes of which have decreased due to the current geopolitical conditions. In this context the Russian economy has encountered significant contradictions and shock effects, which required significant public investment into the economy. The authors of the article emphasize under conditions of severe external restrictions, the needs for neo-industrialization are implemented by investing in the fixed capital of the industrial complex of Russia, in particular, its high-tech core, as well as investing in human potential, specifically, its intellectual core, being able of generating new development ideas, breakthrough technologies and organizational and managerial solutions, which are in demand by the sixth and subsequent technological structures. The paper states that implementing investment support for the goals of neo-industrialization policy requires coordinated work of specialized institutes of the technological core of the economic system, with the help of which the investment process will be established. The volumes of investment in fixed capital and human capital are analyzed, the structure of in-vestment is analyzed, the gender specifics of intellectual capital, its role in the processes of neo-industrialization of the Russian economy as a genera-tor of innovations and the main force of technological transformation of the economic system are analyzed. It is noted that without technology knowledge enhancement and proper organization of the educational process, it is impossible to ensure adequate development of the modern pro-duction process, filled with advanced technologies of the new order.

The platformization of the fashion industry is creating a new configuration of international trade in which intangible assets – data, algorithms and cultural narratives – outweigh the traditional factors of cost and labour. The aim of the study is to provide a theoretically and empirically sound explanation of how platformization generates trade asymmetries, and to evaluate models of digital sovereignty that could mitigate them. The study objectives are considering the theoretical foundations of analyzing the market structure in global fashion; studying the structures of the digital market in the fashion industry; identifying the features of fashion markets; developing a structural model for the transformed fashion market in the context of digitalization; conducting a structural comparison of traditional and digital models of fashion trade; developing a typology of digital trade asymmetries in the economy of fashion platforms. Using a systems‑oriented approach that combines platform economics, the theories for structuration and technological cycles, the study analyses the mechanisms for data monopolization, algorithmic bias and infrastructural lock‑in underlying digital trade asymmetries. It is shown how states and firms attempt to regain freedom of action by digital sovereignty strategies, regulatory frameworks and in-vestment in sovereign infrastructure. The findings suggest that platform‑mediated trade demands new policy instruments that integrate structural power, digital infrastructure and symbolic value creation. The models and typologies developed by the authors can be useful in decisionmaking both at the level of companies and government management of digital platforms.

Tightening international sanctions has highlighted the need for analytical tools capable of capturing adaptive strategies of economic agents under restrictions on cross-border capital flows. Agent-based modeling (ABM) has emerged as a promising methodology and has been actively used by central banks to study macro-financial processes. This article provides a conceptual review of two prominent ABM architectures – an Agent-Based Model of the Banking System (ABBA) and the Canadian Behavioral Agent-Based Model (CANVAS) – focusing on their potential to assess sanction circumventing via cryptocurrency channels. We systematize the main features of both models (agent typologies, adaptive mechanisms, reproducibility, documentation availability), identify their limitations in the context of on-chain transactions, and outline avenues for further research. Our findings suggest that despite their methodological sophistication, neither ABBA nor CANVAS adequately incorporate the specifics of cryptocurrency infrastructures (exchanges, P2P platforms, stablecoins), which limits their applicability for analyzing the resilience of financial systems under sanctions. The contribution of the paper lies in refining the suitability criteria for ABM in sanction-related research and setting a research agenda for the development of specialized models integrating behavioral and technical aspects of crypto-financial transactions.

The tax system is one of the most important ways to mobilize financial re-sources to solve economic, political, and social problems of the state. Its objectives change in light of changing political and economic realities. The article examines tax revenues of the budgets of the country's budget system, which have developed under the existing taxation system. In order to ensure objectivity of the conclusions, the study was conducted not only on the basis of budget data for Russia, but also in the context of federal districts. The article examines the provisions of the tax reform – 2025 for the main types of taxes: personal income tax, VAT, corporate income tax, simplified taxation system, and analyzes their impact on budget revenues. This determines the relevance of the research topic. The objective of the study is to examine the structure of tax revenues and revenues in general of budgets at various levels. The objectives of the study are to establish the impact of the declared tax reform – 2025 on the revenues of budgets at various levels. The research methods were the following: analysis and syn-thesis, grouping, comparison, generalization, tabular and others. The study is based on the tax legislation, Rosstat data, reports of the Federal Tax Service of Russia, publications on the topic of the study. The study found that the tax system is characterized by a high degree of centralization of tax revenues in the federal budget, an insignificant role of regional and local taxes in the formation of consolidated budgets of the constituent entities of the Russian Federation, which increases their dependence on the federal center, is reflected at the level of socio-economic development of the regions; imbalance in favor of the function of filling the budget to the detriment, first of all, of the function of stimulating sustainable economic development of the territories; budget system deficit, dynamism.

The article examines the historical stages of financial technology development in a global context, from the late 19th century to the present day. It traces the evolution of financial instruments and infrastructures under the influence of key technological breakthroughs, including telegraph communication, payment automation, data digitization, and the spread of the Internet. Particular attention is paid to the transformation of banking operations under the influence of internet banking, mobile applications, electronic payment systems, and cryptocurrencies. The role of fintech as one of the key drivers of innovative changes in management of high-tech companies and financial organizations is considered. The authors analyze the impact of the introduction of biometric technologies, artificial intelligence, block-chain, cloud computing, and the Internet of Things on the processes of digital transformation and business model optimization. It is shown that modern fintech provides integration of financial services into non-financial digital ecosystems, which transforms the principles of customer interaction and intensifies competition between traditional banks and IT companies. The paper also analyzes promising trends for further development, including the growth of e-commerce, expansion of platform ecosystems, and in-creased sustainability of financial structures. It concludes that the global evolution of fintech is shaping new mechanisms for managing innovation and opening up broad opportunities for monetizing technologies, while taking into account technological, economic, and regulatory factors.

In the light of significant acceleration of scientific and technological progress affecting changes in economic, social and cultural interactions, innovation and technology introduction play a key role in all the aspects of social and human existence. The paper examines the current state and cur-rent directions of government participation in improving digitalization of the national economy, as well as the consequences of this phenomenon impact on the processes taking place in the labor market. The positive effects of digitalization are being actualized, such as the impact of the process un-der consideration on the national economy, improving provision of public services to population, and transforming the employment structure. The study examines the issues of territorial differentiation of digitalization processes at the federal district level, as well as their impact on the standard and population’s quality of life. Through the prism of introduction of the latest innovative achievements, completely new aspects of ensuring economic stability and security of the national economy are analyzed, and the need for systematization of improving state regulation in this area is substantiated. The findings of the study allow assessing the scale of digitalization impact on the national economy and understanding the impact of this process on changing the nature of social interactions and the quality of life of the Russian population.

The article examines the theoretical and practical aspects of implementing the regional component of the national project to support small and medium-sized enterprises at the municipal level. Special attention is paid to the methodological issues of monitoring fulfillment of the decomposed values of the national project indicators established for the municipalities of the region. The study of the implementation of the regional component of the national project using the Samara urban district as a case study is carried out based on the analysis for the decomposed values of the indicators established for the municipality, and a comparative assessment of achievement of the national project indicators by municipalities and the region as a whole. The structural and dynamic analysis for the current state and development of small and medium-sized enterprises in the Samara urban district during the implementation of the national project complements the objective assessment of effectiveness of the implemented project-program activities at the municipal level. The issues of interaction between federal, regional and local authorities within the framework of implementation of national projects and programs for development of small and mediumsized businesses are considered. The regional and municipal measures of state support for entrepreneurship in the Samara region are analyzed. Based on the findings of the study, practical recommendations are pro-posed for public authorities to improve implementation effectiveness of the regional component of the federal project "Effective and Competitive Economy", aimed at developing small and medium-sized businesses in the region.

Impact projects are ushering in a new era of responsible entrepreneurship, but they face various challenges during implementation. This article analyzes current methodological approaches to assessing the social (environ-mental) influence of impact projects, which are characterized by the lack of standardized tools for measuring their contribution to the achievement of sustainable development goals. Accordingly, the main purpose of this study is to develop and substantiate a methodological approach to assessing the impact of impact projects using formalized mathematical and statistical methods. The methodological basis of the study was the «Five Dimensions of Impact» theory and the Sustainable Development Concept itself, which integrate analytical and managerial approaches to assessing an organization impact on society and the environment. In this regard, the system re-search methods and comparative analysis were integrated, as well as tools of set and discrete function theory to construct a quantitative impact assessment model. The information base included the results of international and domestic studies, materials from domestic research schools and charitable foundations, and analytical reports from Impact Management Project (IPM) and Global Impact Investing Management (GIIN). Collectively, this led to the following findings: a formalized scale for assessing social (environ-mental) impact was developed, which allows for the classification of impact projects by impact assessment levels, minimizing subjectivity. Thus, the following conclusion was reached: the proposed methodology ensures objectivity and reproducibility of impact assessment and can serve as the basis for developing a national system for measuring the contribution of impact projects to the achievement of the Sustainable Development Goals.

The article analyzes modern digital solutions used in the marketing of fit-ness clubs and their impact on the development of the industry. The relevance of this study is due to the rapid digitalization of the service sector and changes in consumer behavior, especially after the pandemic restrictions that have led to transition to online classes. The purpose of this work is to identify new marketing opportunities in the fitness industry by using mobile apps, VR/AR technologies, CRM systems, hybrid classes, omni-channel communication, and artificial intelligence tools. The study used the industry statistics, reports from the National Fitness Community, and relevant scientific publications, including the Russian and foreign sources. The findings demonstrate that the integration of digital technologies – from mobile platforms for customers to virtual training and big data analytics – increases marketing efficiency of fitness clubs, expands the audience reach and enhances customer engagement. The practical examples of successful use of digital tools (e.g. mobile apps for recording and online training, VR programs, CRM for personalized communications) are dis-cussed, and emerging challenges are identified – the need for an omni-channel strategy, ensuring loyalty and adapting staff to new technologies. It is concluded that digital solutions are becoming a key factor in competitiveness in the fitness market, allowing for a unique consumer experience and sustainable customer relationships.

The relevance of the work lies in the fact that the modern mining and processing industry is undergoing a profound transformation due to the processes of digitalization and the need for increasing global competitiveness. This article presents a theoretical analysis for the fundamental principles of innovation management in the context of the specifics of mining and processing plants (GOK). The relevance of this study is due to the need for overcoming the methodological gap between general theories of innovation and the practical management needs of modern mining and processing enterprises. The purpose of the paper is to systematize the conceptual framework and develop a theoretical and methodological foundation for understanding the essence of innovation management in the context of the digital transformation of the industry. The research methods included a system analysis, comparative analysis, historical and logical method, method, classifications, secondary analysis of industry and consulting research data, as well as the case studies of leading enterprises (Rio Tinto and Aktogayskoye field). Based on the critical analysis for existing approaches to the definition of the terms "innovation" and "innovation activity", their limitations are identified, related to ignoring the managerial component and industry specifics. The author's definition of innovation management at a mining and processing enterprise is proposed as an integrated, dynamic and adaptive system that integrates methods of generation, selection, implementation and commercialization of innovations to achieve sustainable competitive advantages. To operationalize this definition, a system of seven key features of innovation management has been developed: digitalization, flexibility and adaptability, data-driven approach, open innovation, consistency and integration, focus on sustainable development, knowledge management. Each feature is illustrated with the examples from the practice of leading companies in the industry, such as Norilsk Nickel and Rio Tinto. The article highlights the specifics of mining and processing plants, including high capital intensity, long production cycles and increased environmental risks, which must be taken into account when building an innovation management system. It is concluded that overcoming the gap be-tween potential of digital technologies and the practice of their implementation requires development of integrated methodological approaches synthesizing classical theories of innovation and modern concepts of the digital economy. The proposed conceptual framework and the system of features form the basis for further empirical research and the creation of tools for diagnosing maturity of the innovation management system in specific enterprises.

This article identifies existing financial management issues and analyzes current financial management models in commercial organizations and their relationship to labor market economic factors. It examines and systematizes a number of contemporary challenges facing corporate financial management, such as profitability, competition, digitalization, automation, diversification, optimization, and others. It explains their essence and offers possible solutions. The author's classification of current financial management models in businesses is presented, detailing and examining such financial management models as the traditional model, cash flow management, financial risk management, strategic financial management, zero-based budgeting, and others, revealing their advantages and disadvantages. Special attention is paid to their practical application, and the factors of great importance for commercial organizations, such as accessibility, cost, and effectiveness, are assessed. The paper emphasizes the role of digitalization, artificial intelligence-based technologies, and the pro-grams on corporate financial management systems. This study hypothesizes that financial management and labor market conditions are closely interrelated; financial management issues influence labor market conditions; and labor market conditions influence the choice of a financial management model for a commercial organization. These hypotheses are con-firmed by the study. The article applies theoretical and empirical research methods such as analysis, synthesis, comparison, observation, contrast, modeling, and data processing and interpretation. The relevance of this study lies in the growing interest of financial managers in scientific developments and research into financial management issues to address their own challenges arising in their business financial management systems. The scientific novelty of this study lies in its identification of the relationship between changes in the labor market conditions and a business financial management system. The findings are drawn based on the study.

In the context of global digitalization of socio-economic processes, the development of effective approaches to organizational risk management is becoming particularly urgent. This is driven by the need for flexible and ac-curate analytical tools capable of accounting for multiple risk factors and large data volumes, as well as for assessing risks in real time before they impact the socio-economic system. This paper provides a comparative analysis of three key statistical methods for risk assessment: Markov chains, Bayesian analysis, and the Monte Carlo method. Using a case study on borrower credit risk assessment, the capabilities and limitations of each technique are demonstrated. The study substantiates the expediency of applying Markov chains to model credit portfolio dynamics and borrower migration between rating categories. The Bayesian analysis is used for the sequential risk assessment of individual borrowers based on incoming discrete data. The Monte Carlo method is used to obtain a complete probability distribution of financial outcomes, accounting for the uncertainty of key economic variables. The study concludes that these methods are not interchangeable and that their integrated application enhances the robustness of risk assessment results.

In conditions of increased inflationary uncertainty, indexed bonds, such as Indexed Federal Loan Bonds (OFZ-IN), are becoming a key tool for protecting purchasing power of savings. The purpose of this study is to conduct a comprehensive analysis of the investment attractiveness of Indexed Federal Loan Bonds (OFZ-IN) and develop practical recommendations for private and institutional investors. The paper uses methods of analyzing secondary data, discounting cash flows in real and nominal terms, as well as scenario analysis of profitability for a five-year horizon at various levels of inflation (from 4% to 7% per annum). The information base was compiled by the data from the Moscow Stock Exchange, the Bank of Russia and the Ministry of Finance of the Russian Federation. The results show that Indexed Federal Loan Bonds (OFZ-IN) provide stable real returns of about 2,5% per annum, regardless of the inflationary scenario, effectively hedging inflationary risks. At the same time, their nominal profitability directly de-pends on actual inflation, which makes them especially attractive during the periods of macroeconomic instability. It is recommended to include Indexed Federal Loan Bonds (OFZ-IN) in a diversified portfolio with a share of 20–30%. The findings of the study can be used by investors in the formation of long-term strategies, as well as regulators to improve debt policy. A promising area of further research is the analysis for the impact of liquidity and transaction costs on the final profitability of the instrument.

The formation of securities optimal portfolio is an urgent task of modern financial analysis. Investors face the need for choosing assets that can provide maximum profit with minimal risks. To achieve this, various stock selection strategies are used, based both on investors' subjective preferences and on objective market statistics. The paper provides a detailed re-view of the methods for making investment decisions in conditions of un-certainty associated with fluctuations in stock prices on the Russian stock market. The authors use company profitability statistics to assess investment prospects and offer analytical tools that help minimize risks and in-crease the expected return on a portfolio. Among the approaches considered, the Laplace, Waide, Savage, and Hurwitz criteria, as well as the maximum criterion, stand out. These methods allow for evaluation of attractiveness of stocks based on the market conditions and the risk level. A numerical experiment is conducted using specialized spreadsheet software to compare effectiveness of each method in real market situations. The study resulted in the proposed algorithm for selecting stocks based on mathematical expectations, taking into account the market conditions and the expected risk level. This approach significantly increases the likelihood of achieving high returns on investment portfolios in a highly volatile and uncertain financial market environment.