A comprehensive economic and managerial analysis of the process of digital transformation of the Russian transport industry has been carried out using the example of implementing intelligent transport systems. The economic conditionality of transition from an extensive model of physical infrastructure development to an intensive one based on management processes intellectualization has been substantiated. The analysis of the intelligent transport system technological landscape has been carried out, in which technologies have been classified according to levels of readiness and economic purpose in the value chain: from data collection to control actions implementation. It has been established that the maximum socio-economic effect is achieved not through individual technologies implementation, but through integrated, synergetic systems creation. The methodology used in Russia for evaluating intelligent transport system projects based on extended net present value (ENPV), which allows key externalities monetization, has been considered. It has been revealed that the main barrier to increasing the level of intelligent transport system maturity lies not in the technological, but in the institutional and regulatory plane. The key constraints identified are institutional fragmentation, terminological and standard ambiguity, as well as a lack of specialized competencies. Practical recommendations aimed at overcoming the identified barriers have been formulated, including the need to develop a unified national intelligent transport system architecture, harmonize standards, and form competence centers.

With the rapid growth in the variety of business intelligence tools, the choice between visual Low-Code platforms and command line interface tools working in combination with large language models is increasingly subjective, which increases the risk of errors when implementing solutions. The study proposes the use of the Sheridan and Verplank Levels of Automation scale as an objective metric for comparing business analytics tools, adapting I.G. Korablev’s operation analysis methodology for assessing the level of automation for manufacturing enterprises to the tasks of dashboard development and the use of software pipelines interacting with large language models. The materials and methods of the study have been presented on the basis of an experiment that examined the processes of developing dashboards and process diagrams on the Apache Superset and Draw.io platforms, respectively, as well as using a software pipeline based on JupyterLab, Dash, Plotly, and PlantUML tools with the use of large language models. Based on the experiment results, the results of using quantitative assessment of automation levels on the Sheridan and Verplank scales have been described and the ergodicity in terms of the “stability” of business intelligence tools outside of ideal conditions. The findings demonstrate that the use of the Sheridan and Verplank scale of automation levels can help eliminate subjectivity when choosing business intelligence tools and can become the basis for management decisions in the IT sphere.

The relevance of the research topic is related to rapid development of the cryptocurrency market. Bitcoin, as the first and most capitalized cryptocurrency, has a tangible impact on the entire sector. Its high volatility and sensitivity to external shocks not only open up investment prospects, but also carry serious risks for market participants, especially for crypto funds, specialized structures that manage digital assets. Market shocks caused by macroeconomic changes, new laws, technological breakthroughs, or mass liquidations on exchanges can dramatically affect the bitcoin price. The author examines exactly how such shocks affected cryptocurrency funds from 2015 to 2025, what mechanisms transmit this impact, how fund portfolios changed, and what strategies helped reduce risks and adapt to the unstable market environment. The novelty of the study lies in a comprehensive analysis of the bitcoin market shocks impact on crypto funds in the long term (2015–2025), considering the evolution of asset management strategies, volatility transmission mechanisms, and fund resilience to macroeconomic and market shocks. Unlike most studies focused on the short-term volatility of cryptocurrencies, this study examines systemic changes in the funds structure, the dynamics of their assets under management, and investment approaches in the face of crisis events such as market crashes in 2018, 2020, and 2022. It has been proven that the use of statistical modeling and time series analysis methods makes it possible to identify patterns of adaptation of crypto funds to a volatile market environment and offer practical recommendations on risk management.

The active development of digital economy and specifically the IT sphere make it relevant to study the features of corporate communication of relevant companies. It has various forms, including a declaration of organizational values. The purpose of the study is to analyze the set of values declared by the leading Russian IT companies on their official Internet pages. The allocation of the relevant blocks of information made it possible to form a list of values of more than two dozen companies, which are among the largest. Tracing the semantic links among them has reduced it by about half, eliminating repetitions (expressed in different words of the same concepts). These systematized values (the most common of them are innovation, customers, teamwork, responsibility, and technology) have then been grouped into value imperatives (personal, universal, organizational, promising, and consumer), characterized by common ideas. An analysis of their distribution allowed for recording the interest of the IT companies under consideration in a wide range of values, including non-economic ones. When interpreting the results obtained, it was possible to trace the connection of many systematized values with the traditional values of Russian society (the most popular of them are creative work, collectivism, mutual assistance, and mutual respect). The originality of the conducted research lies in documenting the value field of leading Russian IT companies, as well as in finding a satisfactory balance between business interests and traditions in the considered sector of the economy. Despite its innovativeness, the latter contributes to traditional values strengthening in Russia, which is in line with the interests of the state and its society.

The issues of poverty and socio-economic inequality remain highly relevant in the context of global challenges, including technological transformations and geopolitical changes, hindering sustainable development of national and global economies. Of particular importance is the role of state financial regulation as a tool for smoothing market failures and ensuring social justice, which is especially relevant in the context of the national goals of Russia, which envisage reducing poverty to 7% by 2030 and the Gini coefficient to 0.37. The purpose of the study is to develop theoretical foundations of state financial regulation based on the financial and investment model of social security. To achieve this goal, the tasks of determining the types of state financial regulation, analyzing the role of the financial and investment model of social security as an operational mechanism for implementing social policy, comparative analysis of poverty and socio-economic inequality, as well as building a theoretical model of the impact of state financial regulation on these phenomena, economic growth, and technological progress have been solved. The research methodology is based on a theoretical analysis, systematization, and a comparative approach to the study of the economic schools concepts. The study results include clarifying the role of the financial and investment model of social security as a key operational tool of state financial regulation in the social sphere, identifying the relationship between overcoming poverty and reducing socio-economic inequality, as well as developing a theoretical model demonstrating the possibility of achieving national goals through a balanced combination of budget expenditures and progressive taxation.

A comprehensive statistical, economic, geographical, and cultural analysis of international tourism in the Middle East for the period 2000–2024 has been carried out. The study is based on systematization of data from the UNWTO (renamed in UN Tourism as of January 2024), the World Bank, the IMF, the Arab Tourism Organization, and national statistical agencies. The purpose of the study is to identify key trends in inbound tourism development and factors of territorial concentration of tourist flows and to determine the impact of tourism on regional macroeconomic stability. Special attention has been paid to the spatial and temporal dynamics of tourist arrivals, changes in the tourist income structure, and the role of tourism in the post-oil economy of the Persian Gulf countries. The analysis showed that in 2000–2024, the volume of international arrivals more than tripled, and the contribution of tourism to the region’s GDP reached 9.7%. The UAE, Saudi Arabia, and Egypt are showing the highest growth rates, where tourism is becoming an element of the soft power strategy and a tool for promoting national cultural identity. A cross-country comparative analysis has been conducted on indicators of employment, investment activity, and tourist products diversification. It has been shown that digitalization and cultural positioning of countries have a decisive impact on their competitiveness in the global tourism hierarchy. The scientific novelty of the research lies in an integrated approach to assessing the tourism potential of the Middle East as an integrative indicator of economic diversification and cultural development. The obtained results can serve as an analytical basis for forming national and interstate programs of sustainable tourism in the region. 

Tourism industry development plays a key role in the structural transformation of regional economies, especially in the context of declining efficiency of traditional sectors. The Vologda Region has significant but under-realized potential for tourism growth due to its unique combination of cultural heritage and natural resources. The priorities of the Vologda Region tourism industry development as a direction of structural and technological transformation of the region’s economy have been considered. Currently, the region’s tourism potential remains poorly utilized. The purpose of the study is to determine the priorities of tourism in the region in the long term. Achieving this goal required an analysis of tourist demand in the region, a strategic analysis of the industry’s development, as well as promising areas development based on its results. Based on the analysis of statistical data, key trends in tourist demand in the Vologda Region have been identified. Conducting a SWOT analysis allowed to identify potential strategies for implementation. As a promising project, it has been proposed to create a high-tech amusement and recreation park that ensures the growth of tourist traffic based on the synthesis of modern digital technologies and traditions of Russian culture. The scientific novelty of the research lies in strategic directions for developing the region’s industry, which can reduce dependence on external factors and increase tourist flow. The study results can be applied by the authorities to form a regional tourism policy and serve as the basis for further scientific research in the tourism development sphere.

The modern ecosystem for startups in Russia is dynamically developing under the influence of a wide range of government support measures. An additional incentive is provided by regional programs and strategic initiatives that generate demand for domestic innovations in priority sectors of the economy. Due to the sanctions and the withdrawal of Western brands, a product vacuum has formed in the industry in a number of areas. The purpose of the study is to develop a methodology for managing key success factors of innovative startup projects in the context of digital transformation aimed at the sustainability and competitiveness of small and medium-sized businesses. The study is based on the concept of an integrated approach to creating a plastic environment. The research methodology contains the big data analysis through the prism formed by the planes of innovation, monitoring, and levels of the economic system. The theoretical part of the study provides an overview of domestic and foreign sources on the innovative projects success and analyzes a number of management models for key success factors of companies. The empirical part of the study presents the results of a survey of the founders and managers of 78 Russian startups at various stages of development. The author’s methodology for managing the success factors of a startup in the process of its sustainable development has been proposed. The results of testing have been presented on the basis of the information technology company TOFEKT LLC, which is developing a mobile application in the fashion sphere. The proposed methodology can be widely used in high-tech industries due to its innovativeness and adaptability to digital transformation and dynamic changes in the business environment from the macrolevel to the microlevel, ensuring effective management of innovative projects.