The article presents a comprehensive analysis of modern approaches to scaling the business of equipment manufacturers and entering new markets in the context of the global digital transformation of the economy. The study is based on the systematization of scientific publications devoted to the internationalization of industrial companies, platform3based interaction models, digitalization of trade, and organizational mechanisms of international expansion. The paper examines changes in the logic of scaling associated with the transition from linear export growth to network3 based coordination forms built on partner ecosystems and reproducible digital processes. Particular attention is paid to the role of digital services, interaction standardization, and distributed sales channels that reduce transaction costs and enable scaling without proportional growth of resources. Barriers to companies’ transition to export activity are analyzed and interpreted as a filtration mechanism selecting firms according to their level of organizational maturity and ability to coordinate international operations. The study demonstrates that sustainable international scaling emerges through the synchronization of digital capabilities, managerial structures, and partnership networks ensuring business adaptability across different institutional environments. Scaling is considered an integrative process in which technological, organizational, and network factors form a unified architecture of international growth for equipment manufacturers. The article will be useful for researchers in international business and the digital economy, as well as specialists in industrial management, strategic development, and international marketing of technological products. 

This article examines the methodological aspects of transitioning service and asset management organizations to an autonomous decision–making mode based on artificial intelligence, with a focus on real estate operations. The practical relevance of the topic follows from the expanding use of digital client/tenant communications, the growing operational scope of property portfolios, and the transaction costs associated with manual coordination of requests, repairs, occupancies, and payments. The paper proposes an integrated project framework that combines a digital twin of an organization, event–log–based process reconstruction, human–in–the–loop/human–over–the–loop supervision, and AI risk management logic into a single scheme for autonomization. This paper describes the requirements for a digital footprint, the architectural link between a «twin», agent modules, and supervisory loops, and the criteria for the admissibility of autonomous execution in service and asset management. To achieve this goal, a comparative analysis and analytical synthesis of publications on digital twins, Human–in–the–Loop approaches, trusted real estate valuation, and generative artificial intelligence practices in property management were employed. The article is intended for digital transformation leaders, owners of management companies, developers of artificial intelligence agents, and risk management specialists. 

The article is devoted to the analysis of the use of artificial intelligence technologies to automate accounting processes and internal audit control in the context of digital transformation of the economic environment.

The relevance of the study is determined by the intensive introduction of intelligent data processing algorithms into the financial and accounting information systems of organizations, which leads to the transformation of the structure of accounting procedures and the adjustment of audit control methods. The scientific novelty of the work is expressed in the systematic consideration of modern areas of application of artificial intelligence in accounting practice, the identification of functional models of intellectual processing of financial information and the establishment of their impact on the effectiveness of accounting activities.

In the course of the study, the architectural principles of intelligent accounting systems were disclosed, the mechanisms of automated processing of financial transactions and algorithmic analysis of accounting data were analyzed, special attention was paid to considering the impact of machine learning technologies on the detection of financial deviations, optimization of audit procedures and the development of analytical financial statements.

The purpose of the study is to analyze modern scientific approaches to the application of artificial intelligence in accounting and internal audit. The study used methods of comparative analysis of scientific sources, systematization of research results and analytical generalization. The conclusion defines the main directions for the development of intelligent accounting systems. The article will be useful to specialists in the field of accounting, auditing and digital transformation of financial processes of organizations. 

In April 2026, the Government of the Russian Federation submitted to the State Duma a comprehensive draft law on digital currency and digital rights, fundamentally reshaping the architecture of the Russian digital financial assets (DFA) market. This paper examines the financial market implications of the new regulation, including changes in market structure and competitive environment, shifts in liquidity and pricing parameters, the investment potential of the emerging secondary market, and the role of digital assets in cross–border settlements under sanctions pressure.

The study demonstrates that the new regulatory framework is likely to lead to an oligopolistic market structure with high barriers to entry, while simultaneously creating conditions for qualitative growth in market depth through the legalization of organized trading and the introduction of a digital depository institution. Particular attention is given to the cross–border dimension, with an analysis of the «controlled gateway» model as a financial mechanism for settlements under sanctions–related constraints affecting traditional correspondent banking infrastructure. 

The article discusses the problems of assessing the financial stability of commercial banks in the context of financial market turbulence. A comparative analysis of the traditional approach implemented by the Central Bank (a system of supervisory requirements, capital adequacy standards and mandatory reserves) and an alternative method of data mining — Kohonen self–organizing maps (SOM) is carried out.

The author substantiates that the classical methods of the regulator based on strict regulatory values (instruction No. 199–I, etc.), despite the fact that they provide a unified assessment, have limited predictive ability and do not always allow timely detection of latent signs of bank destabilization in the early stages. In contrast, Kohonen’s self–organizing maps offer a tool for nonlinear clustering and visualization of multidimensional data, which makes it possible to identify hidden patterns, «weak signals» of crisis phenomena and assess the stability of a credit institution in dynamics based on neural network modeling. 

The contemporary system of higher education in the Russian Federation exhibits pronounced regional heterogeneity, driven by differences in the structure of specialist training. This article presents the results of a cluster analysis based on the 2024 Federal Statistical Observation VPO31, covering all 83 federal subjects and 56 fields of study.

Using Principal Component Analysis (PCA) and the k–means algorithm, a stable two–cluster structure was identified: the first cluster comprises scientific–technical and multidisciplinary centers, focused on STEM disciplines and creative industries; the second includes peripheral regions with a practice–oriented profile, dominated by socio–humanitarian and locally relevant fields.

The study demonstrates that Information Technology (IT) fields do not constitute a separate «digital» cluster but are inherently embedded within a broader scientific–technical ecosystem. These findings underscore the need for a differentiated approach to regional higher education policy. 

In modern economic reality, practical science is tightly integrated into the business environment. High3tech developments require government funding or private investment, and research results are aimed at application and profit. Advances in chemical industry have broad potential for implementation, from civilian to military sectors, biotechnological innovations are associated with medicine, food production, agriculture and projects in ecology. Without any differences of subject area, the final result of scientific activity is a product in material or unmaterial form, which must be developed through various channels, including B2B, B2C, and B2G sales. At the same time, entrepreneurs operating in scientific and regulated spheres of business, such as medicine, pharmaceuticals or chemical engineering always face a variety of crises and risk factors. In conditions of political and economic turbulence, companies develop strategies of adaptation to changes of external environment. One way to respond is to switch to creation of products which are in high demand. The author of article examines product portfolio management as a crisis management method in commercial organization. Using an experience of a company distributing analytical and medical laboratory equipment, author demonstrates indicators of product portfolio efficiency, points of risk, strategy of diversification and further development aimed at improving of sustainability and efficiency of business at all. The results of research can be used by professional managers, executives or business owners. 

The article examines the formation of entrepreneurial strategy on marketplaces under the conditions of digital transformation of trade. By the end of 2024, the volume of retail e–commerce in the Russian Federation exceeded 11 trillion rubles, indicating structural changes in the entrepreneurial environment and the increasing dependence of small and medium–sized businesses on platform infrastructure. The purpose of the study is to develop a theoretical and applied approach to shaping entrepreneurial strategy within the algorithm–driven marketplace environment. The object of the research is entrepreneurial projects selling goods via digital platforms. The subject of the research is the mechanisms of strategic behavior of entrepreneurs in the context of the platform economy. The study employs system analysis, comparative analysis, and structural–functional analysis of digital platforms. As a result, a typology of entrepreneurial strategies is proposed and an adaptive entrepreneurial strategy model is developed, aimed at managing digital performance indicators and ensuring project sustainability. The practical significance of the study lies in the applicability of the proposed model for small and medium–sized enterprises when designing strategic decisions on marketplaces.

Despite the steady numerical superiority of women in the demographic structure of the Russian Federation, their actual economic situation is characterized by persistent imbalances, which requires a systematic analysis of the causes of gender inequality.

The article gives a comprehensive assessment of the role and place of women in the Russian economy through the prism of key indicators: the gender wage gap, occupational segregation, entrepreneurial activity and the economic consequences of motherhood. On a systematic basis, demographic, labor and entrepreneurial parameters of the status of women in the Russian economy were compared, regional features of informal employment of women were identified, and wage losses associated with motherhood were quantified.

Based on the analysis of the causes of the gender wage gap, the author proposes directions for improving economic policy aimed at empowering women in Russia.

The study is based on the analysis of Rosstat data, empirical studies of Russian and foreign authors, as well as the results of panel studies and corporate reporting.

 The formulated conclusions can be used in the development of public policy measures aimed at reducing the gender pay gap, formalizing women’s employment in the informal sector, developing corporate programs to support employees with children and stimulating women’s entrepreneurship. 

The purpose of this article is to investigate the historical development and contemporary features of the tax system in the People’s Republic of China. The paper examines key stages of fiscal reforms in China since 1978 and analyzes the structure of current state budget revenues, which are primarily formed by VAT and corporate income tax. The author concludes that China’s current tax policy primarily pursues several equally prioritized objectives— stimulating the development of new economic sectors while maintaining a socialist orientation, balanced growth, and active state intervention in the redistribution of public goods; the existing system continues to adapt to address regional inequalities and stimulate the economy, demonstrating a specific level of tax rates compared to other world regions, while exhibiting its characteristic challenges.