2782-6015 19 1 2026

RAR RUS 7-35 V-1094-2019 56968223000 0000-0002-0941-6358 Peter the Great St.Petersburg Polytechnic University Babkin Alexander babkin@spbstu.ru

Russia, 195251, St.Petersburg, Polytechnicheskaya, 29

Q-4229-2017 57195759467 0000-0003-3644-4239 Voronezh State Technical University Shkarupeta Elena 9056591561@mail.ru

20 letiya Oktyabrya st., 84, Voronezh, Russia

Liberman Irina iliberman@kantiana.ru Klachek Pavel PKlachek@mail.ru Industry 6.0: Development of neurodigital tools for strategic goal setting and planning Advancing the foundations of the strategizing concept, this paper proposes a framework for meta-strategizing of cyber-social meta-ecosystems within Industry 6.0. The strategist within this framework is not a specific human professional or a group of specialists, but a symbiotic superintelligence, allowing for symbiotic interaction (immersive human–machine convergence) for a wide range of intelligences: neurodigital, emotional, hybrid computational, etc., integrating the central technologies of Industry 4.0–6.0. Applying the core principles of the symbiotic intellectual equilibrium economy, the conceptual framework of Industry 6.0, the methodology and technology of DNA engineering for cyber-social meta-ecosystems, we developed a universal model for meta-strategizing these cyber-social meta-ecosystems. Building on the concept of the systemic triad of neurodigital tools for strategic goal-setting and planning for Industry 5.0, within G.B. Kleiner’s systemic paradigm and V.L. Kvint’s strategizing concept, we constructed a promising version of a symbiotic neurodigital toolkit for Industry 6.0. A system for meta-strategizing cybersocial meta-ecosystems is proposed, where the Strategist is a complex of human–machine cognitive clusters. Extensive validation of this applied neurodigital toolkit was conducted to address the challenges of creating and developing highly profitable agricultural enterprises in the Kaliningrad region. Successful validation paves the way for standardizing this approach and its associated toolkit for various sectors of the Russian economy and industry. The developed architecture of the symbiotic neurodigital toolkit enables a wide range of applied projects and experiments in the future. This includes both a methodological perspective, i.e., developing the principles, methods and procedures comprising the toolkit’s systemic tetrad, and creating the standardized (universal) applied solutions intended to drive the modernization of Russia’s technological landscape and propel its strategic economic and industrial sectors forward. 10.18721/JE.19101 658.5 digital economy innovation cybersocial meta-ecosystems artificial intelligence Industry 5.0/6.0 https://economy.spbstu.ru/article/2026.117.1/ 01_babkin_shkarupeta_liberman_klachek.pdf

RAR RUS 36-61 Тashkinov Alexey alekss.perm@gmail.com Conceptual model of a digital adaptive ecosystem for an industrial enterprise in Industry 4.0 Digitalization, robotics, the Internet of Things, artificial intelligence and cyber-physical systems are fundamentally changing production processes, value chains and business models. Today, the concept of digital transformation is widely proclaimed, guiding businesses not simply to implement technologies but to rethink their future development. However, the theoretical and methodological foundations lag behind practical demands: a conceptual model of a digital adaptive ecosystem for an industrial enterprise that would integrate new methods of organizing production, logistics and intercompany interactions into a unified, holistic and adaptive management system has yet to be developed. The relevance of this research lies in the search for new organizational and management forms capable of not simply implementing individual technologies but also ensuring holistic adaptation to technological change. This work is based on a comprehensive literature review and critical analysis of existing adaptive management paradigms. The author synthesizes various theoretical and methodological approaches, including systems-cybernetic, evolutionary-synergetic, organizational-managerial and complex adaptive systems theory. The objective of this study is to develop a conceptual model of a digital adaptive ecosystem for an industrial enterprise capable of ensuring its long-term competitiveness in the face of Industry 4.0 challenges. The following scientific results were obtained. The absence of a single, generally accepted definition of a “digital adaptive ecosystem for an enterprise” was established in scientific discourse. The author's definition of the concept of “digital adaptive ecosystem for an enterprise” in the context of digital transformation was introduced into scientific circulation. The structure and key elements of a digital adaptive ecosystem for an enterprise were described. A conceptual model of a digital adaptive ecosystem for an enterprise has been developed, and the main stages of its formation are described. The parameterization of management concepts based on the Cobb-Douglas production function has made it possible to develop a system of metrics for assessing the economic efficiency of the digital adaptive ecosystem for an enterprise. The implementation of a digital adaptive ecosystem based on management concepts makes it possible to formulate a unified digital transformation strategy to achieve a synergistic effect and ensure the competitiveness of industrial enterprises in the context of Industry 4.0. 10.18721/JE.19102 338.2 adaptive management Industry 4.0 industry systems Cobb-Douglas production fun-ction region synergistic effect digital adaptive enterprise ecosystem https://economy.spbstu.ru/article/2026.117.2/ 02_tashkinov.pdf

RAR RUS 62-79 Petruchenya Irina Identification and practical interpretation of new features for classifying compliance risks in an artificial intelligence environment In the context of the digital transformation of the compliance environment, not only are new relevant compliance tools emerging and developing, but a new category of “technogenic” risks is also being formed, for which traditional, static methods of systematization and grouping are of little use. The goal of this study is to identify new types of compliance risks from the use of artificial intelligence (AI) and to develop an improved classification, as well as to verify the practical significance of the research results by assessing their impact on minimizing potential losses for organizations. The work is based on a theoretical and methodological approach, incorporating a range of theoretical and analytical methods, such as systems and comparative legal analysis, content analysis of regulatory documents and scientific publications and formal logic modeling, which allowed for the structuring of the research. A comparative analysis of existing scientific studies on this topic in domestic and foreign literature revealed their limited applicability to the risks posed by AI and Big Data. The scientific novelty of the research lies in the development of a theoretical and methodological approach to improving the classification of compliance risks, based on the identification and systematization of new specific types of threats generated by the fundamental properties of AI systems (autonomy, variability, scalability), including latent discrimination and algorithmic distortion of factual data; as well as on the ontological substantiation of the classification criteria for specific types of compliance risks, which has expanded the scope of digital compliance and increased the risk coverage ratio from 42% (in basic models) to 90% (in the author's model). To confirm the practical validity of the theoretical and methodological principles of the proposed classification, the author developed an instrumental and computational block aimed at verifying the predictive effectiveness of the proposed measures. This novelty aspect lies in the development of a methodology for quantitatively assessing the effectiveness of the proposed solutions, including the substantiation of a comparative effectiveness coefficient, allowing for mathematical verification of the superiority of the author's approach over traditional static models; and the derivation of a proprietary formula for determining prevented potential damage, ensuring the conversion of qualitative risk indicators into measurable quantitative indicators of the organization's economic benefit. The classification of compliance risks proposed in this article can serve as a theoretical foundation for the creation of predictive compliance monitoring models, proactive adaptation of the regulatory framework, development of predictive, preventive control systems, digital compliance risk profiles and the automation of entity liability assessment. 10.18721/JE.19103 005.334:004.8 risk classification compliance risks digital compliance set of criteria risks artificial intelligence big data regulatory environment companies https://economy.spbstu.ru/article/2026.117.3/ 03_petruchenya.pdf

RAR RUS 80-105 Tarasovа Olga Aletdiova Anna aletdinova@corp.nstu.ru Digital platforms as a source of weak signals for regional development The study focuses on the analysis of digital platforms as a source of weak signals that reflect emerging public interests and the possible direction of future regional development. The relevance of the work is determined by the need to identify early signs of social, economic and cultural changes that are not yet captured by statistical data or reflected in strategic documents. Digital crowdfunding platform projects represent a form of open digital participation, where alternative ideas, new practices and shifts in public value manifest, making them a significant tool for predictive research. The aim of the study is to explore the potential of using data from crowdfunding platforms to identify weak signals of future regional development and to demonstrate how such data can serve as indicators of emerging public interests, values and practices. To achieve this aim, the following tasks were addressed: analyzing the theoretical foundations of the weak signals concept, investigating the properties of digital platforms, examining the structure and dynamics of projects on the Planeta.ru platform from 2021 to 2024 and identifying categories that can serve as indicators of future transformations. The research employs methods of content analysis, comparative data analysis, clustering of project categories and interpretation of their success rates. Original empirical data from the crowdfunding platform were used, containing information on project themes, regional affiliation, goals and outcomes. The results reveal a multi-level structure of signals: established directions, intensifying new trends with high predictive potential and areas of high uncertainty. It is substantiated that crowdfunding initiatives enable the identification of directions in their early stages of development. The novelty of the research lies in the integration of the weak signals approach and crowdfunding data analysis for regional development tasks, as well as in the development of a cluster-based structure of signals that allows for the interpretation of digital initiatives as early indicators of future changes. The practical value of the study is in the potential application of its findings by regional authorities, analysts, social entrepreneurs and researchers for monitoring public demands and formulating more precise development strategies. In conclusion, directions for further research are outlined, related to expanding data sources, comparing platforms and modeling the dynamics of weak signals. 10.18721/JE.19104 332.1:332.055 weak signals regional development digital platforms crowdfunding social trends https://economy.spbstu.ru/article/2026.117.4/ 04_tarasova_aletdinova.pdf

RAR RUS 106-117 Lyu Lingli Guzikova Ludmila guzikova@mail.ru Structural changes in Sino-Russian energy cooperation  Intensification of geopolitical instability has fundamentally reconfigured the structural foundations of Sino-Russian energy cooperation. Confronted with unprecedented Western financial sanctions and supply chain disruptions, bilateral cooperation has undergone a fundamental transition from simple quantitative expansion toward building institutional resilience. Through a comprehensive analysis of empirical data, including trade dynamics and joint project structures, this study reveals a system of three complementary and synergistic mechanisms underpinning this structural transformation: 1) strategic reconfiguration of infrastructure; 2) innovative instrumentalization of settlement mechanisms; 3) institutionalized integration based on equity participation. The development of pipeline networks, such as the Power of Siberia, and Arctic liquefied natural gas (LNG) projects has not only diversified supply sources but also driven a strategic redistribution of global energy flows, effectively mitigating geopolitical risks associated with traditional transit routes. The Renminbi payment system has evolved from a crisis-response tool into a complete, institutionalized financial infrastructure; its share in energy settlements has grown, effectively hedging sanction risks and systematically reducing reliance on the US dollar system. In strategic projects like Yamal LNG and Arctic LNG 2, the Chinese side, through tiered equity participation models, has secured shared governance and internalized risks, elevating the level of cooperation from transactional relationships to strategic co-management. The research demonstrates that these interlocking mechanisms successfully convert external pressure into internal structural resilience, collectively establishing an independent Arctic–Northeast Asia energy corridor. This study provides a replicable analytical model and practical paradigm for emerging economies confronting geopolitical fragmentation, illustrating how infrastructure sovereignty, currency instrumentalization and co-governance architectures offer a viable alternative pathway for constructing a more resilient energy security system independent of US dollar hegemony. The findings are of interest to corporate executives involved in China–Russia energy cooperation and to academic researchers studying international energy cooperation within a shifting geopolitical landscape. 10.18721/JE.19105 658 geopolitical instability Sino-Russian energy cooperation infrastructure development settlement mechanisms equity cooperation https://economy.spbstu.ru/article/2026.117.5/ 05_lyuy_linli_guzikova.pdf

RAR RUS 118-134 Peryshkin Mikhail Methodological approach to developing of interregional network structures based on resource complementarity (the case of Northwestern and Central federal district regions) The relevance of the study is determined by the need to improve the efficiency of using the industrial and scientific-technological potential of Russian regions in the context of limited resources and the need to ensure technological leadership. The high level of differentiation between regions in terms of socioeconomic development creates barriers to the development of innovative projects and the formation of sustainable economic growth. This requires the new regional development tools that enable regions to leverage their strengths. One such tool could be the formation of interregional network structures that activate resources within cooperation and facilitate the development of long-term value chains. The goal of the study is to develop methodological approaches to the formation of network structures between regions based on their resource complementarity. To achieve this goal, the efficiency of industrial portfolios of the Northwestern and Central federal districts was assessed using spatial shift-share analysis; cluster analysis to group regions by their functional specialization; network analysis to identify potential areas of interaction between regions based on data on the transfer of the results of intellectual activity (RIA) and the proximity of their industrial profiles. The study revealed that more than half of the regions in the Northwestern and Central federal districts are underutilizing their industrial potential. Even when specializing in growing industries, their performance lags behind regions with similar industrial portfolio structures. Most regions in the Northwestern and Central federal districts are characterized by a specialization in low-innovation activities, a low share of innovation expenditures in the total volume of shipped goods, works and services, and declining investment in fixed capital. A methodological approach has been developed to identify promising areas of cooperation between regions in the Northwestern and Central federal districts based on their functional specialization, structural and technological proximity and an analysis of existing RIA transfer flows. This approach allows for an assessment of both the current and potential levels of cooperation and provides a comprehensive assessment of the likelihood of developing effective network structures. Implementation of the proposed measures will bridge the gap between industrial potential and the actual level of interaction between regions, thereby contributing to the achievement of technological leadership. Future studies may include the service sector in the analysis, as well as develop new methods for the formation and development of network structures at the interregional level. 10.18721/JE.19106 332.1 network structures regional economy regions of Russia technological leadership “shift-share” method interregional cooperation https://economy.spbstu.ru/article/2026.117.6/ 06_perishkin.pdf

RAR RUS 135-152 Kochetkov Sergey Smirnova Olga cam@spbstu.ru Kochetkova Olesya Vavilina Alla Innovative capacity of the Russia’s economy: The formation, level and intensity of usage The article assesses the impact of leveraging innovative capacity on the growth of the Russia’s economy. For this purpose, an economic construct of innovative capacity has been developed and its optimal level of usage has been determined. By defining the components of the innovative capacity of the economy based on the identified factors, its economic and mathematical model was built. Calculation of the effectiveness of using the innovative capacity of the Russia’s economy showed alignment between existing possibilities to newly emerging needs. Based on the contribution of the factors under study to GDP growth rate, the structure of the Russia’s economy was revealed. Taken together, this constitutes an approach in which innovative potential is comprised of such elements as innovative capabilities and innovative reserve. Achieving the targeted (planned) GDP growth rates is ensured by the optimal usage of the innovative capacity of the Russia’s economy, revealing the state of economic equilibrium. The developed criterion for the optimal usage of the innovative capacity shows a ratio between innovative capabilities and innovative reserve, which ensures the required growth rate of the final economic indicator. Determining the rate of using the innovative capacity, calculated as the ratio of innovative capabilities to innovative reserve, designates the point of ideal state of the economy. Exceeding this point indicates the intensity of its further usage. All of this substantiates the quality of the structure of the Russia’s economy. Taken together, this forms a methodology for assessing the impact of innovative capacity on the economic growth, which enables the identification of relevant research topics and, on this basis, determine promising directions for the implementation of their results. It also serves as a missing component in Russia’s modern economic strategy. 10.18721/JE.19107 330.341; 330.352.3 innovative capacity innovative capabilities innovative reserve GDP growth rate quality of the economic structure optimum of innovative capacity Russia’s economy https://economy.spbstu.ru/article/2026.117.7/ 07_kochetkov_smirnova_kochetkova_vavilina.pdf

RAR RUS 153-185 Tumilevich Elena Review of strategic and operational mechanisms for integrating corporate social responsibility into management systems to achieve organizational sustainability This article addresses the problem of fragmented approaches to integrating corporate social responsibility (CSR) into strategic management systems to achieve organizational sustainability goals. The relevance of the study stems from the persistent gap between companies' articulated commitment to adopting the increasingly prevalent ESG policies and their actual managerial practices. The study aims to conduct a comprehensive scientific review to identify, classify, and synthesize specific models and mechanisms for embedding CSR principles into sustainable management processes. Following the PRISMA methodology, a corpus of scholarly publications from 2001 to 2025 was analyzed, with a focus on recent works (2022–2025). As a result, three interrelated clusters of determinants for effective integration were identified and systematized: a portfolio of specific CSR practices requiring matrix alignment with the UN Sustainable Development Goals (SDGs); a set of internal organizational transformations, including structural changes, corporate culture shift, and innovation management; and external engagement mechanisms, such as shaping the institutional environment and developing strategic reporting systems. The primary scientific novelty of the work lies in the multilevel classification developed for strategic and operational CSR integration mechanisms, structured along two axes, the management level and the mechanism type. Secondly, the nonlinear and mediated nature of CSR's impact on sustainability was substantiated, with the reputational capital and employer branding playing a key transmission role. Thirdly, an integral analytical model was proposed, visualizing the dynamic relationship between external drivers, internal transformations, mediating factors, and ultimate outcomes across the three dimensions of sustainability. The practical significance of the research lies in providing executives and boards of directors with a structured roadmap for building a holistic sustainability management system, as well as in offering regulators evidence-based justification for developing not only normative requirements but also support infrastructure to enhance companies' managerial capacity. 10.18721/JE.19108 338.24:316.422:658.3 corporate social responsibility (CSR) sustainable development management system PRISMA systematic review Sustainable Development Goals (SDGs) ESG https://economy.spbstu.ru/article/2026.117.8/ 08_tumilovich.pdf

RAR RUS 186-202 Nghikofa Fiel U. Social entrepreneurship in Namibia and transformation of personality and society in a new socio-technological order This research provides a comprehensive analysis of the sociocultural foundations of social entrepreneurship development in Namibia and examines its role in transforming individuals and society in the context of a new socio-technological order. The relevance of this study is driven by acute socio-economic challenges in developing African countries, including high unemployment rates, dominance of informal economies, gender inequality and lack of inclusive mechanisms for social development. The research methodology is based on a systems approach and incorporates methods of participant observation, statistical analysis, comparative case study analysis and critical literature review, enabling the integration of theoretical and practical dimensions of the problem. The primary research findings include: 1) a first systematic analysis of the relationship between African Ubuntu philosophy and contemporary social entrepreneurship practices in the Namibian context, demonstrating that traditional sociocultural values of collectivism and community solidarity create a favorable foundation for socially-oriented business; 2) development of an original conceptual 3C Partnership model (Coordination – Capacity building – Cultural adaptation) that describes mechanisms for overcoming institutional barriers in developing countries through the integration of technological innovations, local capacity development, and cultural adaptation; 3) identification and systematization of mechanisms through which social entrepreneurship influences individual and societal development at three levels: individual (development of entrepreneurial competencies and self-efficacy), organizational (creation of hybrid models and formalization of the economy), and societal (strengthening of social capital and transformation of social practices). The scientific novelty of this research lies in establishing the critical role of sociocultural factors as a system-forming element in the development of entrepreneurial ecosystems in the context of a new socio-technological order, thereby expanding existing theoretical understanding of the interaction between culture, innovation, and economic development in developing countries. The practical significance consists in developing an operationalized conceptual model directly applicable to designing and implementing social entrepreneurship support programs in developing African countries, as well as providing empirically-grounded recommendations for policymakers, international organizations and social development practitioners. 10.18721/JE.19109 005.591:334.012.64(688) social entrepreneurship digital technologies digitalization Namibia new socio-technological order developing countries https://economy.spbstu.ru/article/2026.117.9/ 09_ngikofa.pdf

RAR RUS 203-216 Gumerov Marat System modeling in economics: evolution of approaches and development prospects The goal of this paper is to analyze currently existing approaches to modeling economic systems from the perspective of how they incorporate various aspects of their functioning into the modeled domain and what practical recommendations in the field of economic systems management are developed on this basis. This analysis is conducted in order to further create from the existing approaches a new integrated approach, within which it will be possible to construct models of economic systems that are more comprehensive in covering aspects of their operation for the development of more comprehensive strategies for managing these systems. The study summarizes the features of four existing approaches to system modeling of economic phenomena, within which the objects of study and practical management influence can be: the processes of restoring equilibrium in an economic system in response to disturbances (D. Forrester's system dynamics), the organization of interactions between its subsystems (G.B. Kleiner's economic tetrads), the combination of management functions in a system during a change in the phases of its life cycle (I. Adizes's PAEI model) and the dissemination of the results of an economic system's work in the external environment (Bass–Rogers diffusion model). An approach to describing economic systems has been developed that integrates the principles of the four previously analyzed approaches. Within this framework, economic system management is proposed to be structured taking into account the fact that the system's product gradually encompasses new consumer groups, while the economic system itself simultaneously moves through the phases of its life cycle, each characterized by its own mechanism for restoring systemic equilibrium, a distinct distribution of roles between subsystems and the need for distinct combinations of management functions. Thus, the contours of a general strategy for managing economic systems are formed based on a more multifaceted model representation. The developed approach to modeling economic systems and formulating management strategies for them is also integrated with the system-wide law of the spiral development of S-shaped life cycles. The main principle of this approach is the need to ensure the continuity of individual life cycles of the economic system, each of which is managed according to the model described in the previous section. The obtained results provide the basis for detailing the developed approach as applied to economic systems with different specificities. 10.18721/JE.19110 338.242.2 systems theory economics systems approach modeling system life cycle management decision making https://economy.spbstu.ru/article/2026.117.10/ 10_gumerov.pdf