In an era defined by the global transformation of the world order, characterized by a multitude of external and internal challenges, a new conceptual framework is advanced to steer the Russian economy toward a path of balanced growth aligned with the strategic imperatives of national security and sovereignty. The paper underscores the necessity of shifting away from the dominant paradigm, which prioritizes gross domestic product maximization and raw material exports, toward a novel, multi-vector model of economic development. In this emerging system, priority national objectives serve as the core reference points for strategic planning and the efficient allocation of resources.

A central proposition of the article is the reconceptualization of economic growth, not as an ultimate goal in itself, as historically assumed, but as an instrumental means to achieve broader, more complex objectives: technological sovereignty, enhanced quality of life, balanced regional development, and the sustainable renewal of human capital, recognized as the foundational asset of the post-industrial economy.

The analysis further identifies the institutional conditions required for this paradigm shift, wherein national projects evolve beyond mere programmatic initiatives to become the cornerstone of an integrated organizational and economic architecture. This architecture effectively unites state, civil society, and private-sector efforts into a cohesive and tightly interlinked development ecosystem. Special emphasis is placed on the imperative to adopt flexible and adaptive governance mechanisms, such as scenario-based forecasting and indicative planning, that allow for agile responses to internal and external shocks while preserving the strategic coherence of national economic policy. The paper also articulates a redefined role for the public sector: no longer as a monopolistic regulator, but as a strategic institutional investor, an innovation catalyst, and a guarantor of the social contract. In this capacity, the state ensures that principles of efficiency, environmental sustainability, and social equity are embedded within a unified national development strategy.

Finally, the success of the proposed model is argued to hinge less on the quantitative scale of available resources and more on the presence of sustained political will, high-caliber public administration, and informed societal choices oriented toward long-term collective welfare. This, in turn, necessitates the emergence of a new political economy grounded in trust, transparency, and shared responsibility for the nation’s future. The article is intended for scholars, policymakers, experts, and all stakeholders engaged in shaping Russia’s strategic trajectory.

The article provides a brief overview of the state of international political relations, states the transformation of the subjectivity of global processes and draws a conclusion about the crisis phenomena of modern globalization in the context of the crisis of its subjectivity. While it synthesizes these concepts at a high level, it often lacks specificity in operationalizing them. This conceptual breadth leads to a multiplicity — and frequently, ambiguity — of objectives, which in turn complicates the formulation of clear strategic priorities, particularly under conditions of limited resources. This article examines contemporary visions of a rational global order, aligned with the defining trends of our era that shape trajectories of accelerated socio-economic advancement. Building upon this analysis, it proposes the concept of an “economy of national goals” — a paradigm in which the primary measure of public policy efficacy and economic progress is no longer conventional GDP growth, but rather the tangible achievement of strategically vital objectives that ensure the nation’s long-term sustainability, resilience, and sovereignty. This new paradigm — accelerated development anchored in national goals — entails a fundamental shift: from reactive, market-driven policymaking to proactive, systemic design of the country’s future. Within the “economy of national goals”, economic strategy is explicitly aligned with a state-defined hierarchy of long-term priorities — those deemed essential for safeguarding sovereignty, ensuring national security, achieving technological self-reliance, and enhancing citizens’ quality of life. In contrast to classical economic models, where the market functions as the central coordinating mechanism, this paradigm positions the state as the strategic architect and enabler — orchestrating resources, institutions, and incentives to deliver socially transformative outcomes. For Russia, the articulation of national development goals forms the foundation of a novel civilizational and economic model. Anchored in principles of sovereignty, technological autonomy, and mission-oriented governance, this approach empowers the country not merely to adapt to global transformations, but to actively shape its own developmental trajectory. As a response to the existential and systemic challenges of the 21st century, this paradigm offers a blueprint for sustainable, secure, and equitable national development. Its successful implementation demands not only political will and institutional capacity, but also the emergence of a new economic science — one capable of strategic foresight, systemic thinking, and proactive policy design.

The article examines the transformation of theoretical and applied approaches to the study of economic growth in the context of digitalization and sustainable development. The relevance of the study is determined by the need for the Russian economy to transition to a new growth model focused on quality, innovation, and human capital. The current challenges of global competition, technological restructuring, and institutional uncertainty require a rethinking of traditional sources of economic growth and the development of a comprehensive methodological framework.

To develop a theoretical and methodological foundation for a new model of economic growth that corresponds to the contemporary challenges of digital transformation and sustainable development.

The research employs methods of analysis and synthesis, systemic and structural-functional approaches, as well as comparative and statistical analysis. The empirical part is based on official statistical data. The application of a systemic approach made it possible to construct a conceptual framework — the “core — shell — quality filters” model — reflecting the interrelation between endogenous, institutional, and digital, and environmental factors of growth.

The study systematizes modern models of economic growth and identifies the key directions of their evolution — from exogenous to endogenous and institutional concepts. It is established that the core of modern models consists of knowledge, innovation, and human capital; the institutional shell determines the conditions for realizing their potential; and the quality filters represent ecological sustainability, social inclusiveness, and digital transformation. The empirical analysis of the Russian economy confirms the relevance of shifting from an extensive to an innovation-driven and digital type of growth focused on productivity enhancement, technological renewal, and human potential development.

The formation of a new model of economic growth in Russia requires the integration of digital, institutional, and human factors into a unified development strategy. Priority should be given to improving human capital quality, stimulating innovation, strengthening institutions, and creating conditions for sustainable technological advancement. The transition to such a model will ensure the long-term competitiveness and stability of the Russian economy and promote the concept of qualitative growth based on productivity, social well-being, and ecological balance.

The formation of a sustainable and dynamic economy is one of Russia’s national development goals, the achievement of which requires the coordination of strategic priorities at both the federal and regional levels of public administration. This article addresses the task of translating national goals into a system of measurable indicators that capture the dynamics of socio-economic processes in the regions of the Russian Federation, along with regionally governed factors associated with these indicators.

The aim of the study is to develop and empirically validate a model for assessing business efficiency as an integral indicator that quantifies the contribution of regional processes to the attainment of national development goals and reflects key parameters of regional socioeconomic performance. The research methodology is based on econometric modelling using aggregated official statistics of the Federal State Statistics Service, processed through the applied analytical platform “Regional Economic Strategies”.

The model was tested using data from eight regions of the Russian Federation, selected to represent all federal districts and characterized by median values of gross regional product per capita. The analysis identified and statistically confirmed relationships between the governing indicators and the governed factors, revealing stable universal and region-specific socio-economic processes across Russian regions.

The findings confirm the analytical robustness of the proposed model and demonstrate its practical applicability for monitoring regional socio-economic development, as well as for designing regional roadmaps aimed at enhancing entrepreneurial activity, supporting trade development, and stimulating small business as drivers of sustainable economic growth.

The relevance of the study is determined by the key role of digital transformation as a driver of global economic growth and Russia's national priority in digitalizing the economy and social sphere, which requires a deep understanding of the factors influencing this process in the regions.

The purpose of this research is to develop and test a multifactor model that explains the differentiation in the levels of digitalization across Russian regions under the influence of a complex set of drivers and to determine the contribution of each to the development of digital infrastructure and human capital.

The research methods included regression and variance analysis to identify and quantify the strength of the factors' influence on the resulting digitalization indicators (penetration of fixed and mobile broadband internet, share of ICT employment). The analysis was based on Rosstat data from 2010–2023 for Russian regions. The results showed that digitalization is a deterministic process most strongly influenced by three groups of factors: demand-side (concentration of high-productivity jobs), geographical (level of urbanization), and institutional-investment (volume of targeted ICT funding). Significant interregional differences were identified, with the development of digital infrastructure and human capital responding to the factors with varying intensity.

The conclusions confirm that the digital transformation of Russia's regions is a multifactorial and region-specific process. Its successful stimulation requires a differentiated approach that considers local economic and institutional conditions, as well as a balance between the development of infrastructure, human capital, and innovation demand from the real sector of the economy.

Amid the convergence of technological, macroevolutionary, and demographic singularities, conventional approaches to analyzing and forecasting economic growth are increasingly losing relevance and predictive power. The surge in information overload underscores the urgent need to shift from reactive to proactive (preventive) governance — a transition that presents economic science with a fundamentally novel challenge: the timely and accurate identification of emerging trends and sustainable competitive advantages within massive, dynamic data streams.

The core objective of this study is to formalize a practical framework for updating economic growth models in complex socio-economic systems. To achieve this, the research employs an interdisciplinary synthesis drawing on classical growth theory, institutional economics, strategic management (strategizing), complex systems theory, mathematical modeling, and cutting-edge advances in human — machine collaboration.

The outcome is a universal strategic analysis methodology, structured around nine logically integrated stages: (1) Multi-level environmental scanning and trend forecasting; (2) OTSW analysis (Opportunities, Threats, Strengths, Weaknesses) as a strategic sense-making tool; (3) Systemic goal formulation; (4) Lifecycle-oriented process management of value chains; (5) Identification and prioritization of core strategic components; (6) Development of a digital analytical infrastructure leveraging big data; (7) Mathematical modeling of causal relationships and detection of critical inflection points; (8) Multi-agent AI-assisted interpretation and decision support; (9) Generation of a transformation roadmap via digital twin — based behavioral simulation.

This methodology enables a decisive shift, from descriptive analysis to actionable strategy, from correlation to causation, and from rigid, static planning to dynamic, adaptive governance. Crucially, the proposed framework is not a mere technical supplement but a paradigm shift in strategic thinking: a collaborative partnership between humans and intelligent systems in co-designing the future. Its value lies in bridging critical divides: theory and practice, datadriven insights and contextual judgment, global-scale challenges and implementable solutions.

Potential applications span national, regional, and corporate governance, with particular emphasis on enhancing institutional capacities in education and research.

This paper analyzes methodological approaches for creating an info-technological platform for “digital portraits” of complex socioeconomic systems using the example of regional systems in Russia, as a necessary element of strategic management of the national development goals achievement.

To address the challenges associated with creating digital portraits, practical applications of Data mining technologies, artificial intelligence algorithms, mathematical statistics, linear algebra, and cluster and economic factor analysis are identified. Based on these approaches, models are proposed for the digital transformation of regional socioeconomic management systems.

The development of a system of indicators and methodologies for monitoring and assessing progress toward achieving the goals of the Decree of the President of the Russian Federation N 312 of May 7, 2024, «On the National Development Goals of the Russian Federation for the Period up to 2030 and for the Perspective Up to 2036» is currently an important applied task.

The purpose of this article is to assess the factors influencing demographic processes in Russia's regions within the framework of achieving the national goal of «preserving the popula tion, improving health and well-being, and supporting families».

Based on the analysis of foreign and Russian literature on the subject matter, the author substantiated the factors influencing the birth rate (poverty level, unemployment rate, primary real estate value, residential area per capita, personal loan debt, number of women aged 18 to 45) and the death rate (poverty level, number of hospital beds per 10,000 people, retail sales of alcoholic beverages per capita, share of employed population with higher education, number of registered crimes per 100,000 people, air pollutant emissions from stationary sources).

The study period was 2013–2023, the object was 85 regions of the Russian Federation, and the source of primary statistical information was collections and databases of the Federal State Statistics Service. Empirically, a negative impact of poverty and loan debt on the birth rate in the regions of the Russian Federation was revealed. A 1% decrease in the price per square meter of residential real estate increases the birth rate in a region by 0.22 %. A significant direct impact on mortality in Russian regions was found for the factors “crime rate” and “retail sales of alcoholic beverages”. A 1 % increase in the share of the employed population with higher education reduces mortality by 0.7 %. Contradictory results were obtained for factors such as “unemployment rate”, “residential area per capita”, “number of hospital beds”, and “air pollutant emissions from stationary sources”, requiring further analysis and evaluation.

This study complements the existing body of work assessing the conditions and factors of demographic processes.

Ensuring a decent and high-quality standard of living for the population constitutes a central objective of national socioeconomic development — one that cannot be achieved without a coherent, systemic strategy for building human capital, whose cornerstone lies in education and healthcare. This article explores contemporary frameworks for conceptualizing education and healthcare as strategic pillars of national policy and empirically tests the hypothesis that macroeconomic performance at the regional level in the Russian Federation is significantly associated with indicators in these two domains.

To address this objective, the study employs an interdisciplinary methodology that inte grates econometric modeling with approaches from educational and health policy analysis. The empirical foundation draws on a comprehensive dataset sourced from official statistics, encompassing both macroeconomic variables and metrics of social well-being. The paper proposes the adoption of two composite indicators: “Health Capital” and “Education Level”, as key tools for tracking progress toward national goals related to improving population health, unlocking human potential, and fostering talent development.

Within the human capital paradigm, health and education are not viewed as separate social sectors but as interdependent and mutually reinforcing dimensions that jointly shape long-term economic resilience and quality of life. Econometric findings reveal a strong elasticity between healthcare accessibility and health outcomes: a 1 % increase in the capacity of outpatient care is associated with a 6.87 % rise in the Health Capital index, underscoring the high eco nomic return on investments in primary healthcare infrastructure. Similarly, a 1% expansion in broadband internet access and the diversity of digital educational services correlates with a 0.26 % increase in the Education Level indicator, highlighting the role of digital inclusion in advancing educational attainment. The study concludes that effective strategies for sustain ing and enhancing regional human capital must be grounded in a cross-sectoral governance model, aligning the efforts of public authorities, private enterprises, educational and medical institutions, and civil society actors.

The insights generated can inform evidence-based policymaking aimed at fostering syner gistic development between human capital and the broader economy.

National projects are a modern way of implementing strategic objectives of social and state development. This approach may be considered new, but the objectives of developing (restor ing) the national economy should be considered traditional.

At the initiative of the President of the Russian Federation, 19 new national projects were launched in 2025. They cover virtually all areas, including strategic transportation. Implementation of these plans should improve the quality of life for Russians and elevate many industries to new heights. (Presidential Decree No. 309 of May 7, 2024).

A distinctive feature of national projects is that they are not confined to a single industry, but rather represent complex projects that intersect not only with internal but also with external challenges. All three areas of the national projects — “Human Capital”, “Comfortable Living Environment”, and “Economic Growth” — have a clear transport dimension.

Railways and their restoration and construction are a prerequisite for any progressive de velopment. In turn, the development of the state and society presupposes clear goal-setting.

Railways are a relatively expensive element of a state's economic infrastructure, capable of outliving the state in which they are built. On the other hand, investments in infrastructure help stabilize development for decades to come.

The construction industry holds a pivotal role in the economic and social framework of the Russian Federation, functioning not merely as a production sector but as a system-forming component essential for achieving priority national objectives. Given that the volume of construction work is projected to reach 16.8 trillion rubles in 2024 and the sector provides employment for more than 6 million people, including those in related industries, the study of its macroeconomic impact and potential for digital transformation is of heightened relevance.

This article aims to quantitatively assess the construction industry’s contribution to regional socioeconomic development and to delineate the core directions of its digital modernization as a necessary condition for sustainable growth and the fulfillment of national development goals.

The empirical foundation of the study draws on official statistical data. A linear econometric model incorporating regression and variance analysis is employed to evaluate the relation ship between the indicator “Housing commissioned per 1,000 residents” and two dependent variables: gross regional product (GRP) per capita and turnover of small enterprises. The f indings reveal a statistically significant positive correlation: an increase in housing construc tion directly boosts GRP per capita and stimulates small business activity, thereby initiating a cascade of multiplier effects — ranging from enhanced value added in allied sectors to greater consumer spending and upgraded urban infrastructure. Special emphasis is placed on digital transformation as a critical enabler of efficiency gains in construction. The analysis examines contemporary technologies, including domestic Information Modeling Systems, digital twins, and platform-based solutions, all of which contribute to cost reduction, error minimization, and acceleration of design and construction workflows.

The study underscores that the construction sector is indispensable for realizing national priorities such as fostering a comfortable urban environment, enhancing quality of life, and advancing human capital development. Nevertheless, unlocking its full potential hinges on comprehensive digital modernization, underpinned by supportive government policies, reformed educational curricula, and the establishment of a conducive innovation ecosystem.

At the current stage of globalization, agglomerations act as the driving forces of the Russian Federation's economy and social development. They are home to over 60% of the Russian Federation's population, approximately 70% of its GDP, as well as finance, innovation, scientific and human resources.

The objective of this study is to examine the role of agglomeration processes in achieving the national goal of “a comfortable and safe living environment”. The research methods used include theoretical generalization and comparison, logical analysis, comparative characteristics, analysis, and synthesis.

The research is based on data from the Federal State Statistics Service. This paper ex amines indicators of a comfortable and safe living environment: housing availability, regional crime rates, and the quality of the urban environment. The author presents the impact of ag glomeration processes on these indicators.

Agglomeration processes are a driver that can either create a severe housing crisis or be come the driving force behind mass affordable housing construction. Agglomeration processes are not a direct cause of increases or decreases in crime, but they create an environment and conditions that can be exploited for both criminal and legal purposes. Effective management will help create a comfortable living environment in the agglomeration.

This study complements the existing body of work examining the effects of agglomeration processes and quality of life.

The article analyses the process of forming the intelligent and digital maturity of Russia's regional economy in the context of the transition to the technological paradigm of Industry 5.0. 

It examines the key features of the development of the innovation environment in the country's major macro-regions and identifies differences in the pace of integration of cognitive, digital and intelligent technologies into production and management processes. Based on dynamic data for the Central, North-Western and Volga Federal Districts, the degree of readiness of regional economies for the spread of human-machine technologies and intelligent systems is investigated.

The application of standardised indicators and the construction of integral sub-indices allows us to identify stable structural differences between districts, as well as to determine local drivers and constraints on development. The results demonstrate a marked growth in the intelligent contour and a simultaneous slowdown in digital dynamics, reflecting the transi tion of regional systems from automation to the introduction of more complex technologies. Particular attention is paid to the cognitive component, where a sharp increase is recorded in 2024, due to the strengthening of research infrastructure and organisational mechanisms. The final integrated maturity index shows that regional economies are in the process of form ing the intelligent foundation necessary for the transition to a technologically saturated and innovation-sustainable development model.

Based on the results of the study, recommendations are proposed aimed at improving the regulatory, infrastructure and educational environment, as well as strengthening mechanisms to support innovation activity. The conclusions presented emphasise the importance of the coordinated development of all elements of the regional innovation system, ensuring the ad aptation of the economy to new technological requirements.

The project-based approach to strategic management of the socioeconomic development of the Russian Federation has proven itself effective. As a result, second-generation eco nomic crisis projects for 2025 have been adopted and are being implemented to replace the national projects completed in 2024. An analysis of the progress and results of the national projects revealed that, in a number of cases, there is inefficiency in both the achievement of project objectives and the expenditure of budgetary resources. The following factors have been identified as the causes of this situation: lagging methodologies for statistical sup port of national projects, insufficient methods for developing the implementation of projects, and weak methodological support for assessing the effectiveness of national projects. The purpose of this article is to develop methodological and methodological support for national project implementation indicators designed to improve their effectiveness. The article pro poses and tests a proprietary methodology for assessing national project implementation indicators, which can be used in practice to ensure the quality and comprehensiveness of their implementation.