Aim. The work aimed to substantiate the conditions and factors necessary for the development of regional clusters as networked spatial-economic systems.
Objectives. The work seeks to review current definitions of the term “cluster”, determine the place and role of clusters in the socio-economic development strategies of regions in the Northwestern Federal District of Russia; and develop proposals for improving the effectiveness of cluster policy at the regional level.
Methods. The study employed a combination of scientific methods, based on a systems approach. Specifically, a substantive analysis of normative and regulatory documents was conducted, along with desk research, a logical approach, and a content analysis of recent-years research findings by Russian authors.
Results. Current definitions of the research category “cluster” were structured, and organizational and methodological approaches to cluster regulation at the level of constituent entities of the Russian Federation (RF) were identified. A survey of cluster participants identified systemic problems in the clustering process, and proposals were developed to improve the effectiveness of regional cluster policy.
Conclusions. The implementation of the potential of clusters as networked spatial-economic systems at the level of constituent entities of the Russian Federation requires the development and implementation of cluster policies as an independent component of the region’s overall socioeconomic policy. Successful implementation of the latter presumes the availability of infrastructural and institutional support, which application options are discussed in this article.

Aim. The work aimed to expand the Progressive Materialization of Anti-Idea (PMAi) model by integrating Hegel’s category of Aufhebung into its structure.
Objectives. The work seeks to formulate an expanded version of the PMAi as a dialectical sequence of phases; to operationalize the preserving-transforming effect by introducing the coefficients of destruction (Kd) and Aufhebung (Ka); to demonstrate the model analytical applicability through empirical illustrations and to outline the “damage zones” of innovation.
Methods. The study methodological basis was a conceptual and theoretical analysis with elements of historical and conceptual reconstruction, which was used to expand the PMAi model. Qualitative comparative case exemplifications were also used to test the heuristics and map the object of destruction (technological chains, competencies, regulations, infrastructure).
Results. Analysis of the PMAi model revealed its strength in its ability to formalize the destructive impulse of entrepreneurial innovation and define a clear criterion of novelty through the “anti-object” concept. The model represents successfully the key insights of Schumpeter’s concept of creative destruction, transforming it into a tool for assessing the scale and intensity of displacement of outdated solutions.
Conclusions. A methodological limitation has been identified, namely the innovation process reduction to “pure” destruction, which significantly limits the explanatory potential of the model. The Aufhebung category integration enables to address this shortcoming, transforming PMAi into a concept capable of describing innovation as a dialectical process where the destruction of form is combined with the preservation and transformation of essential elements of content. In its expanded form, the PMAi model becomes not only a theoretical description of the creative destruction phenomenon, but a fully-fledged tool for strategic analysis and innovation forecasting.

Aim. The work aimed to examine the key stages in the evolution of approaches to studying the impact of universities and regions on each other’s development.
Objectives. The work seeks to identify and systematize the key stages in the evolution of approaches to studying the impact of universities and regions on each other’s development; to analyze critically the existing approaches; to identify current trends; to justify the need to improve the methods and tools for analyzing and assessing the degree of mutual development between universities and regions, including for the purpose of adapting and improving the effectiveness of the competitive strategies of modern universities.
Methods. Using general methods of scientific knowledge, the factors and mechanisms of the influence of the university and the region on the development of each other are examined in various aspects. These factors are of particular research interest due to the implementation by institutions of the higher education sector of educational, scientific research, innovative and other functions that influence the socio-economic processes in the territory of presence and beyond.
Results. A systems analysis of Russian and international studies identified and characterized key stages in the transformation of approaches to studying the mutual impact of universities and regions on each other’s development. Shortcomings of theoretical and analytical-evaluative approaches are identified, and existing trends are traced. The need to expand the theoretical and methodological framework for analyzing and assessing the mutual development of universities and regions is argued, including for the purpose of adapting development strategies and competitive behavior in the changing higher education market, taking into account the region’s priority areas of socio-economic development.
Conclusions. The article substantiates the assertion that the relationship between universities and regions influences the adaptation of the latter’s development strategies, integrating competitive trends in the higher education market into the overall socio-economic development of the region in order to obtain additional benefits (resource availability, joint projects and programs, business involvement, commercialization and diffusion of innovations, etc.).

Aim. The work aimed to develop a scientifically based, differentiated approach to regulating technological development processes in Russia’s agro-industrial complex (AIC), taking into account the classification of regions based on their role in the development and use of advanced production technologies (APT) to ensure national food security.
Objectives. The work seeks to verify the hypothesis of the structural heterogeneity of Russian regions, manifested in the division between technology-developing regions and technology-using regions; to conduct a cluster analysis and identify typological groups of regions based on a set of indicators, such as the activity of APT use, level of development, investment attractiveness, and agricultural efficiency; to formulate recommendations for stimulating the development and implementation of technologies, as well as for constructing regional cooperation to achieve the goals of AIC technological independence.
Methods. The methodology is based on a cluster analysis conducted to classify the Russian regions into groups based on their role in technological support of food security. A set of indicators, based on Rosstat data, was applied. This set of indicators was classified into three groups, namely technological activity (the number of advanced technologies developed and used for the AIC), the level of agricultural development (the share of agriculture in the region’s Gross Regional Product and the share of people employed in agriculture), and the investment attractiveness and efficiency of agriculture (the share of investments in fixed capital of the field, the proportion of highly productive jobs in agriculture, and the profitability of the products sold in the industry).
Results. A tool was developed for classifying regions based on their role in creating the technological foundation for food security. Four clusters were identified, each characterized by a specific combination of technological potential and level of agricultural development. This typology was the basis for developing differentiated recommendations for each group of regions.
Conclusions. Russian regions are classified into “developers” (research centers of the country) and “users” (agricultural regions) of agro-industrial technologies. A differentiated approach to developing incentives for regions to achieve technological independence in the food sector involves classifying entities based on their technology use activity and the level of development of agriculture as a key sector for achieving national food security goals. Regions leading in technology development and implementation function as drivers of technological transformation and hubs for cooperation. Regions with high agricultural potential require intensified technology development and implementation processes through local research centers. Regions with low technology adoption require incentives and targeted support for their implementation. Agricultural regions with uneven levels of technology adoption activity are encouraged to adopt the experience of successful regions and replicate best practices. The primary recommendation is to establish cooperation between developer and user regions through technology platforms and specialized technology implementation centers. The resulting tools for developing targeted regional policies allow for the most effective unlocking of the specific potential of each region type to achieve the national goal of technological ensuring of food security.

Aim. The work aimed to develop a methodological approach to assessing the formation of an innovative code for regional economic development, based on the technological modernization of Russian society.
Objectives. The work seeks to identify the stages of formation of an innovative code for economic development in industrial regions within their economic genotype; to develop tools and evaluate the formation of an innovative code for regional economic development.
Methods. For assessment of the formation of an innovative code, the author proposes using comprehensive indicators reflecting the effectiveness of the triple helix in the context of institutional interaction trajectories, namely an innovation policy quality index, an innovation activity index, and an innovation competencies index. The study period was 2008–2023. The coherence and discontinuities of the triple helix that form the innovative code are demonstrated using a correlation analysis, which identifies the extent to which changes in the variable indicating the performance of one economic transformation trajectory are consistent with changes in the performance variable of another trajectory.
Results. The innovative code of regional economic development is still in its nascent stage within the economic genotype of industrialized regions. This is evidenced by the weak development of innovation activity in industrialized regions; gaps in the triple helix of institutional interactions that drive variability in the economic legacy of regions; and the lack of a positive impact of innovative transformations on the dynamics of the gross regional product (GRP) of the constituent entities of the Russian Federation.
Conclusions. Industrially developed regions generate impulses for technological development that have not yet been transformed into an innovative code capable of driving variability in the economic legacy of regions and ensuring the evolution of regional economic development as a whole. The transformation process can be accelerated by strengthening the coordination of administrative, industrial, technological, and scientific research trajectories, ensuring the integrity of the helix of institutional interactions among the basic carriers of the regions’ economic genotype. The results obtained can be used by state and local governments to develop new and improve existing scientific and technological policy implementation strategies in industrial regions aimed at enhancing the innovative development of manufacturing industries, as well as spatial development strategies for Russia as a whole.

Aim. The work aimed to develop a process-project methodology for managing and assessing digital transformation, adapted for small and medium-sized enterprises (SMEs) and aimed at increasing their competitiveness and sustainable development in the digital economy.
Objectives. The work seeks to analyze conceptual approaches to business digitalization and identify their limitations when applied to SMEs; define strategic and tactical goals of digital transformation and align them with key business processes; develop a process-project management model for digitalization, including a system for assessing the maturity of processes and the effectiveness of individual digital initiatives; formulate practical recommendations for creating an organizational and methodological framework (Digital Competency Center) to support the transformation; as well as to substantiate the integration of the author’s method with digital maturity models (ADKAR, McKinsey DQ, Capgemini DMM) to develop a comprehensive digitalization management tool.
Methods. We applied systems and process-project approaches, providing a holistic consideration of digital transformation as a multi-level and continuous process encompassing strategic, tactical, and operational management levels. A combination of methods was employed, including a comparative analysis of conceptual approaches to digitalization, a structural-functional method for identifying the relationships between processes and projects, and modeling to construct a process-project architecture for digital transformation. In order to assess performance, a twotier metrics system is proposed, focused on measuring the maturity of end-to-end business processes and the effectiveness of a number of digital initiatives. This enables not only to identify bottlenecks but also to formulate recommendations for improving the digital maturity and competitiveness of SMEs.
Results. The process-project approach represents a balanced and effective methodological foundation for the digital transformation of SMEs, as it aligns strategic goals with tactical initiatives and avoids fragmentation of digitalization. The analysis revealed that the use of a process-based or project-based approach leads to limited effectiveness, since the former results in the risk of mechanical automation of inefficient processes, while the latter results in a silo effect and project inconsistency. The developed proprietary methodology, based on a two-tier assessment system (the maturity of end-to-end business processes and the effectiveness of digital initiatives), enables the identification of key growth points and ensures the integrity of digital transformation. The practical significance of the study consists in the proposal of an organizational mechanism in the form of a Digital Competence Center, which serves as an integrator and coordinator of digital projects, thereby contributing to the increased digital maturity, sustainability, and competitiveness of SMEs in the digital economy.
Conclusions. The digital transformation of SMEs should not be viewed as a combination of isolated projects, but as a comprehensive and continuous process based on strategic goals and end-to-end business processes. A comparative analysis revealed that a process-project approach serves as the optimal methodological basis for digitalization, as it ensures a balance between improving operational efficiency and achieving long-term strategic development. The proposed methodology for assessing digital transformation, based on a two-tiered metrics system, enables objective measurement of process maturity and the effectiveness of digital initiatives, thereby facilitating the development of a holistic digital ecosystem of an enterprise. The practical value of this article consists in the development of recommendations for creating a Digital Competence Center that ensures the integration of projects and processes, as well as in the rationale for a combined approach using digital maturity models (ADKAR, McKinsey DQ, Capgemini DMM). The results confirm the need for a systemic, proactive, and data-centric approach, which contributes to the growth of digital maturity, competitiveness, and sustainable development of SMEs in the digital economy.

Aim. The work aimed to develop a system of indicators to identify those that must be considered when achieving synergistic effects for the successful implementation of projects, as well as to identify the significance and weighting of these indicators, using an entropy model.
Objectives. The work seeks to reveal the essence of synergistic effects and the industry-specific nature of their manifestation in the oil and gas industry; identify a set of indicators based on expert assessment; and assess the significance of these indicators in the context of risk and uncertainty in the industry.
Methods. The study applied general scientific methods, including the analytic hierarchy process, the Delphi method, and expert assessments.
Results. The authors propose a unique approach to assessing the effectiveness of large projects implementation under conditions of risk and uncertainty. They examined the feasibility of using indicators exerting the greatest impact in relevant fields to assess synergies during project implementation and the effectiveness of large-scale project management, using the oil and gas industry as an example. The work identified a system of performance indicators that impact the project effectiveness across six aspects (social, environmental, economic, technological, geopolitical, and security). The entropy weights of the indicators were also calculated. Cronbach’s theory was applied, contributing to more objective and valid analytical results.
Conclusions. This article addresses the problem of calculating weighting coefficients for various project performance indicators and proposes a solution based on expert assessment and entropy weight calculation. The methodology proposed by the authors is universal and adapted to Russian realities. Since this methodology takes into account the specifics of the oil and gas industry, it became obvious that its use in other industries requires adjustments to the indicators based on assessments of experts in the appropriate field.

Aim. The work aimed to identify the factors that are most significant for small and mediumsized enterprises in their innovation activities.
Objectives. The work seeks to conduct a systematic review and identify factors influencing the innovative development of small and medium-sized enterprises (SMEs) based on an analysis of published works by Russian and international scholars, as well as to identify the determinants of increasing the innovative potential of SMEs.
Methods. The authors used a content analysis of publications by various researchers on the topic under consideration, as well as the analytic hierarchy process as a tool for identifying the most significant factors and criteria for enhancing the SME innovative development.
Results. The most significant factors were found to be management competencies, technological potential, and financial aspects. The study demonstrates that these factors, as well as the criteria that shape each of them, are key in determining the innovative activity of SMEs. The results of the hierarchy analysis indicate the need for an integrated approach to developing SME innovation, including improving management practices, modernizing the technological base, and ensuring financial stability.
Conclusions. The work presents a list of factors determining SME innovation development based on content analysis. The application of the hierarchy analysis method enabled to develop a hierarchical model and rank the identified factors according to their influence on the SME innovation activities. A formalized approach to verifying the consistency of expert judgments was used to verify the reliability and coherency of the data. Interpretation of the final priority vector calculations helped identify and reveal the dominant role of three determinants, namely the company’s technological potential, the level of development of management competencies, and the financial and economic conditions that determine the SME innovation activities.

Aim. The work aimed to study the implementation of the digital ruble as a means of increasing the transparency of financial flows in the Russian Federation (RF).
Objectives. The work seeks to analyze research by contemporary economists on various aspects of the digital ruble implementation; to examine the stages of development of the Central Bank digital currency (CBDC) from a global perspective; to explore the potential for introducing the digital ruble as a means of increasing the transparency of financial flows and ensuring the targeted use of loans; and to identify the advantages and challenges of implementing the digital ruble.
Methods. The study employed a comprehensive approach, general scientific methods, and comparative economic analysis.
Results. The experience of developing, implementing, and disseminating CBDCs in several foreign countries was examined, and the specific features of this process were identified. The dynamics of non-cash payments in Russian trade turnover from January 2017 to May 2025 was analyzed. Challenges associated with introducing the digital ruble into the Russian financial system as a mechanism for strengthening control over cash flow were identified. The study demonstrated the influence of technological, legislative, financial, and institutional factors on the adoption and development of the digital ruble.
Conclusions. The digital ruble integration into the Russian financial system could lead to a significant reduction in the shadow economy and increased transparency of financial transactions, as well as become an effective mechanism for reducing corruption and the shadow economy. An analysis of changes in the share of non-cash payments in Russia’s trade turnover from January 2017 to May 2025 revealed increased public interest in digital payment instruments and a growing demand for faster and more convenient financial transactions. The digital ruble will enable the state to monitor effectively the fund transfers and conduct ongoing audits of the budget and personal funds of individuals and legal entities. This will significantly reduce the time required to process financial transaction data and improve the efficiency of tax administration. However, to ensure financial security, it is necessary to develop methodological units and regulatory framework for the digital ruble circulation.

Aim. The work aimed to identify the economic and organizational features of constructing digital corporate educational platforms (DCEPs) as a tool for strategic human capital management in a company’s digital transformation environment.
Objectives. The work seeks to study the economic nature of DCEPs; to develop a functional and structural model of the platforms, taking into account expenses; to describe the DCEP operating cycle; to develop a core DCEP framework and construct a cost matrix for the implementation and maintenance of the DCEPs.
Methods. We applied structural and functional analysis, modeling, content analysis of empirical sources, and a synthesis of digital learning implementation practices in Russian and international companies.
Results. The work proposes a functional and structural model of the DCEP, comprising seven main levels (strategic, operational, technological, methodological, functional, user, and infrastructural). It also characterizes the full platform operating cycle, consisting of five interrelated stages. These include the development of strategic training objectives, employee competency analysis, the creation of individual development trajectories, training, and the assessment of learning outcomes. A core DCEP diagram has been developed, reflecting the relationships between platform modules, and a cost matrix has been presented to assess investment burden and effectiveness.
Conclusions. The DCEP represents an investment-intensive yet highly effective intangible asset integrated into the human capital management transformation system. Their successful operation requires a systematic approach to the company’s architecture, digital infrastructure, resourcing, and organizational maturity.

Aim. The work aimed to examine modern approaches to investing in cryptoassets, as well as the prospects, benefits and implications of corporate investments in these digital currencies. Objectives. The work seeks to analyze the standpoints of academic researchers regarding the use of cryptoassets for adaptation in the corporate sector; to identify key risks; and to determine the least risky investment strategies for the portfolio formation.
Methods. The study employed the results of research by scientists and experts in the field of risk management and financial asset management, along with general scientific research and cognitive methods.
Results. It was established that the optimal share of cryptoassets in a corporate portfolio varies depending on courage to risk, industry specifics, and investment horizon. Empirical data confirms that even a small allocation (1 to 5%) to highly liquid cryptoassets such as Bitcoin (BTC) and Ethereum (ETH) can improve overall portfolio returns over the long term due to their low correlation with traditional asset classes in certain periods. Companies in the technology and financial sectors, which have the expertise to manage the associated operational and cyber risks, are showing the greatest interest in cryptoassets.
Conclusions. Regulatory uncertainty is the main obstacle. Unclear legal status and taxation deter institutional investors, despite the recognition of cryptoassets as property. High operational risks require significant investments in secure infrastructure (cold storage, smart contract auditing), which increases costs. The dual nature of cryptoassets determines two strategies for their use, namely speculative (for capital growth) and as “digital gold” (for hedging against inflation). The optimal strategy is a hybrid one combining portfolio diversification through a combination of traditional assets (including gold and stocks) and crypto assets to mitigate risks. A key integration tool is institutional products (ETFs, stock mutual funds), which provide market exposure while minimizing direct ownership risks.

Aim. The work aimed to assess the contribution of various cargo types to the gross regional product (GRP) and regional budget revenues.
Objectives. The work seeks to create a panel database for all maritime regions of Russia for 2015–2023; cluster the regions by level of port activity; as well as develop and test models based on gradient boosting and Shapley methods to identify nonlinear relationships between logistics and economic indicators.
Methods. The analysis includes several stages. These include creating a database, including port cargo transportation volumes by cargo type for all maritime regions of Russia for 2015–2023; clustering the regions by level of port activity based on their share of cargo turnover in the Russian total cargo turnover; and constructing models to assess the impact of freight traffic flows on GRP indicators and budget revenues.
Results. The economic impact of port activities has been established to depend not only on the total volume of cargo turnover but also on its structure. The most significant cargo types in regions with high port activity are liquid bulk and raw materials, while these coal and containers are in regions with medium port activity, and dry bulk carriers for supply purposes in regions with low port activity.
Conclusions. The Shapley method was used to clarify the role of each cargo type in the formation of GRP and budget revenues, providing a more accurate basis for management decisions. A transition from aggregated approaches to a structural analysis of freight traffic flows was concluded to be necessary when formulating regional socio-economic policy.