Galina P. Sorokina

This article provides a comprehensive analysis of the Russian Federation’s public financial and budgetary policy in the area of innovative development. It examines key areas of state participation in the formation of a national innovation system in the context of sanctions pressure and the pursuit of technological sovereignty. Particular attention is paid to a range of state financial support measures for the high-tech sector: national projects, preferential regimes for IT companies and small technology companies, infrastructure initiatives (technology parks, support funds), and human resource development programs. The paper compares Russian R&D funding indicators with those of a number of economically developed countries, identifying differences in the structure of funding sources and the intensity of investment in R&D. The article analyzes the dynamics and structure of innovation funding in Russia, highlights priority sectors, and identifies regional differences in scientific and technological development. Barriers hindering innovation are also considered, primarily insufficient private investment in R&D, a high administrative burden, and the risks of regulatory and supervisory activities, which are particularly significant for small and medium-sized businesses. The analysis yields conclusions regarding the potential of the current system of financial and economic support for innovation and the need for its further refinement. The importance of integrating scientific research into the real economy, expanding public-private partnership mechanisms, and adapting support instruments to the needs of individual industries and regions is emphasized. The authors believe this will improve the overall effectiveness of innovation policy and accelerate the achievement of technological development targets.

The article examines the relationship between innovative technological development and economic sovereignty of the Russian Federation in the context of external economic pressure and sanctions. The research methodology includes: generalization of theoretical approaches of foreign and domestic scientists on the relationship between innovation and economic growth; comparative analysis of indicators of scientific and technological development of the Russian Federation and leading countries of the world; assessment of regional differentiation of innovative activity in the Russian Federation; study of the regulatory framework of innovative technological development of the Russian Federation. The current state of the scientific and technological sphere of Russia is analyzed, including the dynamics of resource provision: the share of expenditure on science in GDP, the number of researchers, the volume of domestic expenditure on research and development. Particular attention is paid to the legal analysis of key documents defining strategic priorities in the field of innovative technological development, including the Strategy for Scientific and Technological Development of the Russian Federation and the Concept of Technological Development until 2030. The study identified the main problems hindering the achievement of technological sovereignty: low level of science funding, outflow of qualified scientific personnel, unevenness of innovative activity across the regions of the country. Continued dependence on imported critical technologies and equipment. Based on the analysis, areas for improving public policy are proposed, including: balanced support for the entire innovation cycle of technology development, development of small technology companies, digitalization of scientific and technological development management processes, strengthening the competitive selection and evaluation of research and innovation projects, and attracting extra-budgetary funding sources. It is substantiated that reaching a new level of innovative and technological development is a necessary condition for ensuring the economic sovereignty of the Russian Federation.

The aim of the study is to identify mechanisms for overcoming resistance to innovation, considering behavioral factors and assessing the impact of investments in science on economic growth. The research methodology includes economic and statistical methods, including the calculation of Pearson pair correlation coefficients to analyze the relationship between GDP, the production of innovative goods and services, expenditures on civil science and R&D costs (including for fundamental and applied research), a comparative analysis of international practices in stimulating innovation (China, USA, Germany, Japan, Israel, South Korea, USSR, Russia). Data sources: statistics from Rosstat and the United Nations, open sources on priorities of innovation policies, regulatory legal acts of the Russian Federation. Main results: a high correlation was found between R&D costs and GDP (r=0.99), as well as the production of innovative goods (r=0.99), investments in basic research have a stronger impact on GDP (r=0.94), applied research on the production of innovative products (r=0.92). Based on the analysis of the experience and priorities of countries with high innovation potential, the directions of transformation of state innovation policy were determined, considering the impact of behavioral distortions. Scope of application: government innovation policy, science support programs, behavioral design tools, technology transfer, educational programs. Conclusions. For GDP growth and technological sovereignty, it is necessary to combine the financing of science with consideration of behavioral mechanisms.

The purpose of the study is to assess the effectiveness of innovation activities of small enterprises in Russia in 2019–2024 based on an analysis of innovation activity dynamics, regional imbalances, cost effectiveness, and structural shifts. The analysis methodology is based on data from the Federal State Statistics Service (form No. 2-MP innovation) using methods of economic and statistical analysis such as calculation of absolute gains, variation indicators, cost effectiveness coefficient (ratio of the share of innovative products to the share of innovation costs), and Pearson correlation analysis. Over the period 2019–2024, the share of innovatively active small enterprises in Russia increased from 5.8 to 7.4 %, while chain growth slowed to 0.2 percentage points, which is two to five times lower than the level of developed countries (data from 2024). The coefficient of variation for the Federal Districts increased from 26.5 (2019) up to 44.0% (2024), which indicates the transition to significant interregional polarization. The cost effectiveness indicator decreased from 2.5 (2019) to 1.7 (2024), while research and development costs increased to 27.2% and software costs increased to 19.4% (from 0.8% in 2019). Correlation analysis (2024, 75 constituent entities) shows a weak link between innovation the cost of research and development activities (r = 0.22) and a negative relationship with the number of subsidies (r = – 0.19). Proposed measures to adjust government policy are regional innovation vouchers, technology commercialization centers, tax cashback, and interregional clusters.

Innovation activity of the manufacturing industry organizations in Russia in 20202024 is analyzed. The purpose of the study is to identify the discrepancy between the growth in the number of innovatively active enterprises and the dynamics of innovative production release, as well as to assess the effectiveness of innovative costs. The study is based on official statistical data from the Federal State Statistics Service for 2020–2024. The following methods are used: statistical analysis of the dynamics (calculation of chain and basic increments), comparative analysis of the manufacturability degree and economic activity types, calculation of innovation efficiency (ratio of the share of innovative products to the share of innovation costs), Spearman’s rank correlation coefficient, and graphical methods of presenting the results. A key contradiction is revealed: as the share of innovatively active enterprises increased from 21.3% to 23.7%, the share of innovative products decreased from 8.5% to 8.3%. Innovation efficiency peaked at 3.8 in 2023 and dropped to 3.3 by 2024. The research paper proves that the relationship between the level of innovation activity and the share of innovative products is weak, while costs correlate with the result significantly more strongly, which indicates the predominance of extensive factors with a decrease in the quality of innovation. The authors develop recommendations to shift the focus from increasing the number of innovatively active enterprises to stimulating the launch of fundamentally new products, as well as process innovations in high-tech industries and the development of sectoral import substitution programs for medium-tech and low-tech sectors.

In the context of digitalisation, the transformation of the educational process is inevitable and is a priority issue for any country that wants to maintain or improve its position on the world stage. The article presents a comparative analysis of digital competencies and the possibility of their implementation in the higher education system in Russia. The comparison of the formulated competencies in the methodology approved by the Order of the Ministry of Economic Development of the Russian Federation No. 41 dated January 24, 2020, as well as the International Telecommunication Union and other European organisations is considered. The descriptors (knowledge, skills and abilities) of graduates in various fields who, in the era of digitalisation, must have the necessary digital competencies are identified. Today, professional standards, even in the humanities, define the requirements for technical and computer skills. The article proposes formulations of universal competencies in the higher education system based on the analysis.

In the conditions of digitalisation, it is necessary to have the appropriate skills. Therefore, many applicants choose occupations in which information technology (IT) and programming knowledge is predominant. Comprehensive measures for preparing graduates in the context of digitalisation cover the formation of appropriate educational programmes. The aim of the study is to provide recommendations for improving the educational process in the field of artificial intelligence (AI) and machine learning based on comparing various programmes affecting the training of professionals in this field. The research uses the following methods. First, it is a sample survey, due to which 4 Russian universities that provide training in programmes in IT, are selected. Second, this is grouping and typology of basic educational curricula, professional standards and disciplines, due to which appropriate typological groupings, are constructed. That allows specifying requirements for knowledge, skills, and abilities necessary for specialists in the field of AI. A comparative analysis of professional standards taking into account the work of a modern specialist with digital skills has been carried out. The competence approach in the educational process has been defined, and the need for a professional standard for IT specialists has been identified. Based on the results obtained, recommendations have been prepared on the basic disciplines that need to be included in the educational programmes of universities to prepare competitive graduates.

The article summarises the system of indicators characterising the development of the information society. A generalising characteristic of the subjects of the Russian Federation was given for each of the 23 indicators, which made it possible to identify regions with different fluctuations of the trait. All indicators have been formed into four factors: human capital, innovation potential, information and communication infrastructure and access, and the economic environment. According to the indicators included in each group, the corresponding subindexes have been calculated. Ratings of regions according to the value of sub-indices have been compiled. Based on the values of the sub-indices, the integral indicator characterising the development of the information society has been calculated. The leading and lagging subjects of the Russian Federation in terms of its significance have been identified. In order to identify regions that are homogeneous in terms of the level of development of the information society, their grouping has been carried out.

This article is devoted to the transformation of Russian education system in accordance with the requests of the new technological scheme of the economy. The global economy has changed dramatically during an extremely short period of time due to the COVID-19 pandemic. All levels of the economy and people’s behavior have been modified, and according to experts, these changes are almost irreversible. In this situation, there is a need not only to change the management system of all levels of economic systems, but also to transform education, especially Russian higher education system, due to the fact that now Russian education has two simultaneous tasks: to adapt to the changes that have occurred under the influence of the pandemic and to increase the prestige of Russian universities in the international educational space. Universal scientific methods were used in this research process, including comparative and factor analysis methods, synthesis, and generalization. Achievements: 1. In the article the current trends in the development of the Russian economy in the context of the pandemic and the entry of innovative technologies in all areas of economic relations were analyzed, which have an impact on the formation of new labor market demands. 2. The specific features and problematic aspects of the current system of Russian education, which are slowing down the processes of its transformation, are identified. 3. It is justified, that the higher education system itself should correspond to the smart development model, focused on the adoption of a new paradigm of economic decision-making, on the application of progressive organizational and managerial, informational, environmental, social and other technologies to achieve this goal. 4. The positive practices, which demonstrate advanced domestic higher education institutions, are described. They fit into emerging new markets and correspond to consumer’s sentiment and expectations, taking into account the emerging professions of the future and the increasing complexity of professional tasks. 5. The main trajectories of restructuring Russian education to meet the needs in the innovative economy are made, in general, and to ensure the current basic training of graduates, in particular, to achieve their competitiveness in the labor market.