The article considers the problem of classifying the directions of economic theory related to understanding the historical logic and prospects for the development of mainstream and unorthodox research. In line with the theory of T. Kun and the concept of I. Lakatos, the author shows that these studies are mainly developed within the framework of the general paradigm. Its nucleus acts in the form of “homo economicus”, and the periphery in the form of various institutional interpretations. In the mainstream program society is not considered by a real actor, therefore, an institutionalinstrumental approach is applied, within the framework of which economic descriptions are created on the basis of the liberal concept of a bunch of property rights, which ensures the priority of private interests. In unorthodox program society acts as a real actor and uses a valueinstitutional approach, according to which the economy is analyzed from the standpoint of the social concept of a bunch of property rights and understanding of society as a supreme owner. The author substantiates the statement that the classics of political economy proposed a cognitive paradigm, which, unlike the traditional paradigm, allows us to study the endogenous processes of economic development based on the dual nature of the economic interests of subjects and the classical concept of property. In the classical paradigm, taking into account the ideas of Aristotle and medieval thinkers, public property is understood as a complex-structure phenomenon, acting as a historical and logical basis for the analysis of various forms of property and economic systems of traditional and modern societies. The classical perspective focuses on creating the adequate realities of the sovereign model of the Russian economy based on a change in the outdated architecture of property relations and economic relations in accordance with the priority of the interests of society.

In recent years, the market has seen an increase in the number of integration transactions, and a structured approach to business combinations will help reduce the risk of this process. The purpose of this study is to propose a new mathematical toolkit of the category theory for describing the mechanism of enterprise unification, suitable for modeling integration processes of any type of systems according to the classification of systemic economic theory and allowing to identify risk factors of such processes. Using methods of category theory, systemic economic theory and operational risk management theory, three types of enterprise interfaces are described. Possible ways of modeling the mechanisms of enterprise integration, considered in this paper as socio-economic systems, are proposed for each of them. Risk factors for several levels of integration are identified when choosing a mechanism for combining through an internal interface with the allocation of subsystems of the enterprise: object, environmental, project and process. Anti-risk managerial actions are also proposed to mitigate the impact of identified risk factors on the activities of the combined enterprise. The appendices provide the basic terms and principles of the category theory, formalize the relationship between systemic economic theory and the category theory.

The article presents findings in a longitudinal study on the psychological adaptation of the population during the shock period triggered by the special military operation (2022). Using a sample of 313 respondents across six consecutive survey waves and employing probabilistic-statistical modeling methods, the dynamics of psychological well-being and coping strategies were analyzed. Two stable structural clusters of psychological indicators emerged: overall psychological well-being (comprising emotional, social, and personal components) and constructive coping (including positive reappraisal, acceptance, and humor). Composite indices were constructed for each cluster, revealing distinct dynamics: relative stability in “well-being” versus a significant decline in “coping” following the announcement of partial mobilization. Four distinct trajectory types were identified for each index, forming “mirror-image” pairs. Membership in a specific adaptation type was not determined by socio-demographic factors (gender, age, education, income) but was associated with initial socio-psychological attitudes. Using econometric models of nested dichotomies, statistical predictors of adaptation were identified: “trust in institutions,” “social optimism,” “identity-related attitudes,” and “cognitive strategies.” The study demonstrates that, under crisis conditions, individual adaptation trajectories are statistically predictable based on psychological attitudes measured during the initial survey period, highlighting the role of these initial attitudes as predictors of future adaptation.

The paper examines the impact of income sharing methods among collective members on Stackelberg strategy outcomes and the dynamic stability of cooperation within the framework of mathematical modeling of collective actions. It is assumed that the income function and the relative share of each participant in the income are known to everyone before the start of collective actions. Each agent seeks to maximize his own gain, which is represented by the difference between the part of the total income they receive and the monetary equivalent of the amount of effort they exert. When agents independently choose the size of their efforts, the collective falls into the «bad Nash equilibrium». Coordination of efforts based on interpersonal trust, which can develop in a small group of agents (coalition), allows its members to exert the effort required to maximize not individual, but coalition gains. The coalition effect resulting from the complementarity of efforts leads to a Pareto-­preferred outcome relative to the «bad equilibrium». In a sequential game with the coalition of the Stackelberg leader, the coalition effect is enhanced by the Stackelberg strategy. It is shown that if all participants have an equal ability to influence income through their individual efforts and if income is distributed in equal shares, the amount of effort exerted by coalition members is higher, while their gains are lower than those of non-cooperating agents. Accordingly, for the dynamic stability of cooperation, it is necessary to conclude an agreement that provides both conditions of individual rationality for all members of the collective and conditions compatible with incentives for coalition members. Such conditions suppose rejection of equality in income distribution in favor of coalition members. For a sequential Stackelberg game with the coalition as the leader, the interval of coalition share values that meet the necessary conditions was determined.

This article examines the factors of firm competitiveness in the context of two key contemporary trends: economic digitalization and multipolarity. The authors analyzed firm evolution in relation to the development of a market economy and technological advances. They found that as firm’s competitive environment evolved, so did its competitiveness factors, as well as the scientific approaches to studying them. The contributions of Russian and international scholars to the study of external and internal factors of firm competitiveness were identified. A comparative analysis of firm competitiveness factors and their evolution revealed that technology has always been a decisive factor. The authors clarified the concept of “multipolarity,” established the relationship between the development of digital technologies and multipolarity, and identified the specific factors of firm competitiveness in a multipolar environment. Based on an analysis of modern economic and statistical data, international reporting, and expert assessments, the authors identified the key tools of the digital economy that are shaping technological trends of the near future: artificial intelligence, blockchain, cloud computing, and new user interfaces, and determined their impact on firm operations. The authors structured the external and internal factors of a company’s competitiveness in a digital economy in a multipolar world by type (economic, technological, institutional, and social), the type and nature of their impact on the company’s operations (direct and indirect), identified and analyzed the interrelations between these factors. A study of the application of digital economic tools revealed the high potential of artificial intelligence for comprehensively modeling a company’s external and internal environment. It was found that artificial intelligence significantly increases the efficiency of blockchain, cloud computing, and new user interfaces, and can therefore significantly enhance a company’s competitiveness in a digital economy in a multipolar world by reducing transformation and transaction costs and increasing not only the company’s material, technological, and financial potential, but its human potential as well.

The article analyzes the impact of global economic fragmentation and sanctions pressure on foreign direct investment (FDI) flows in the countries of Eurasian Economic Union (EAEU). The purpose of the study is to identify the key determinants of FDI inflows and outflows and to assess their dynamics under economic fragmentation and external restrictions. The relevance is determined by the insufficient inflow of FDI and the predominance of capital outflows, which limited sustainable development in the EAEU. The novelty of the research consists in the simultaneous econometric assessment of both inflows and outflows of FDI in the region over the period of 2010–2022, taking into account institutional, macroeconomic, and financial factors. The study is based on a panel dataset for five EAEU countries, with econometric analysis using Pooled OLS, Fixed Effects, and Random Effects models. The findings indicate that economic growth stimulates FDI inflows, while high wages reduce investment attractiveness. An inverse relationship of outflows and labor productivity was revealed. The Random effects model best explains inflows, while Fixed effects model more accurately capture the outflows. The dynamics of FDI in the EAEU are determined by market size, macroeconomic stability, and labor costs. To increase resilience to external shocks and enhance investment attractiveness the study recommends strengthening financial integration within the EAEU, expanding cooperation with Asian partners, and introducing digital currencies.

This study identifies patterns of protectionist policies implemented by countries around the world that made them part of the world leading economies. Based on this analysis, it highlights the need for a selective industrial policy in the Russian regions to restructure their economy towards a focus on high-tech and knowledge-intensive industries that can both meet domestic demand under external technological sanctions and replace traditional Russian exports goods (hydrocarbons and other natural resources) which are the subject to sanctions imposed by their former long-standing consumers. Two criteria for searching regions for industrial policy realization were formulated and described: diversification of their economies based on the Herfindahl index and potential for high-tech exports. Based on official statistical data from the Federal State Statistics Service, a quantitative analysis was carried out, and a group of regions with the greatest potential for successful implementation of industrial policy was identified. As a result, 16 constituent entities of the Russian Federation were selected based on their high production and scientific and technological potential, which were found suitable for implementing selective industrial policies aimed at developing high-tech and knowledge-intensive export-oriented industries in the context of limited government resources.

The article presents a discussion on the issue of industrial enterprise growth in the Russian economy within the imperative of accelerated technological development and the implementation of import substitution programs in various industries. Theory and practice of economic development indicate that the intensity of technological changes in the industrial sector directly depends on the critical mass of medium and large enterprises and the dynamics of their transformation. In this regard, the purpose of this article is to examine the dynamics of changes in the size of industrial enterprises, as well as to identify the nature of the relationship between the transformation parameters of industrial enterprises and their involvement in cluster associations. To achieve this goal, the authors use a proprietary database for assessing cluster cooperation in the industrial sector. Several hypotheses are formulated: first, it is assumed that there is a correlation between the dynamics of industrial changes and the distribution parameters of industrial enterprises by size. Second — ​the authors suggest a positive relationship between the growth rates of industrial enterprises and the presence of cluster associations in the structure of the respective industry. To test these hypotheses, the article examines international practices of implementing industrial changes, focusing on managing the distribution parameters of small, medium, and large enterprises across various industrial sectors. The methodology for studying the relationship between the growth dynamics of industrial enterprises and their participation in cluster structures includes the analysis and systematization of theoretical foundations of cluster development, as well as an empirical assessment of statistical data on the growth dynamics of industrial enterprises participating in cluster initiatives compared to those not involved in such associations. The use of the proprietary database, which assesses the parameters of enterprises participating in cluster associations over time, empirically proved that the development of existing clusters and the formation of new cluster initiatives under current structural constraints will contribute to the growth of medium- and high-tech industries. The findings contribute to the advancement of cooperation and clustering theory and can be used to formulate industrial sector development strategies for the Russian economy.

Increasing the level of production intellectualization is a current trend and a strategic priority of modern industrial development. Managing the development of intellectual production requires appropriate tools, one of which is a maturity assessment model. Research for defining intellectual maturity was conducted for several decades within various scientific disciplines. Therefore, the aim of this article is to develop a methodological approach for assessing the intellectual maturity of industrial systems in the data economy, based on the analysis and integration of various assessment concepts and tools. The evolution and specific features of various approaches and models for assessing intellectual maturity are presented: concepts of intellectual capital and knowledge management, maturity assessment models for Industry X.0, smart manufacturing, artificial intelligence, prospects for the development of industrial metaverses and ecosystems. The most common assessment areas within each approach are identified. The feasibility of building a model of an industrial system’s intellectual maturity in the form of a dynamic complex of sub-models is substantiated, allowing for its structure to be customized depending on the context of a specific enterprise. The strategic goals of the enterprise are highlighted as a key contextual factor determining the priority areas and depth of assessment for each of them. Specific principles for assessing intellectual maturity are formulated: strategic alignment, hierarchy, continuity, integration, redundancy, faceted choice, contextual intellectualization of design, quantification, convergence, and proactivity. A conceptual model for assessing the intellectual maturity of industrial systems is proposed.

This study addresses how modern companies can align their key objectives of production development, revenue generation, and strengthening competitive advantages with demands of society and the state for solving social issues, as well as the integration of environmental and ethical principles into their business activities. The objective of the study is to identify priority areas and assess the contribution of Russian businesses to the development of their local communities through interactions. Based on analysis of the current state of affairs and study of public opinion of local industrial enterprises, expectations regarding business contribution to the development of urban and rural areas are identified. Key areas for improving the comfort of the urban environment are identified. The role of business in creating and maintaining comfortable living conditions in cities is underestimated. Indicators for assessing the contribution of enterprises to the development of their local communities, including the environmental well-being of the population, are proposed. The study focuses on the development of regions where Russian businesses operate through their interaction with local communities. It examines the priority areas and contribution of businesses to the development of their regions through interaction with local communities. It was established that the key points of convergence between the interests of businesses and local residents are addressing the issue of personnel shortages and the existing contradiction between the public’s expectations of business participation in socially significant activities and the existing potential of companies in this area. It is proposed to supplement the national “Sustainable Development Goals” system, data on which is published on the Rosstat website, with specific indicators for assessing business contribution to regional development, to implement the developed coefficients for the environmental responsibility (the key, most widely represented of the 17 “Sustainable Development Goals”) of municipal enterprises and the level of environmental reliability of regional enterprise projects, and to rank the priority areas of socially responsible business activity based on the number of settlements and public opinion.

The article offers an approach to the interpretation of the concepts of “digitalization” and “digital transformation”. It examines the current processes that largely define these concepts — ​management in an environment of rapidly changing business conditions typical of ongoing digital transformation. The evolution of enterprise management concepts is described from the resource–based J. Barney and M. Porter (RBV, Resource Based View) to the concept of capabilities/abilities (CBV, Capability Based View) by D. Teece. An approach based on dynamic abilities is discussed. There is a growing need for modern enterprise management models and insufficient supply for practical use. The possible development of the concept is considered, an approach of dynamic management based on research on the dynamic abilities of the enterprise is proposed and micro-foundations of employees and managers — ​properties, the presence of which contributes to successful operation in turbulent conditions. The characteristic features of this approach necessary for the successful implementation of the digital transformation of the enterprise are described.

Intellectualization of the management system of an industrial enterprise in the current stage of economic development can be considered as a factor for increasing the speed and efficiency of technological and management processes. This article presents the author’s interpretation of the concept of intellectualization of the management system, alongside key aspects of the concept of the intellectualization using graphical and mathematical tools. A schematic representation is provided to illustrate the essence of enterprise intellectualization based on hybrid intellectual development of management and technological processes, and their impact on the final product. The article includes a conceptual scheme for raising the level of enterprise intellectualization, with a description of the inputs and outputs of the intellectualization process through the interactions between human (natural) and artificial intelligence as management actors, considering strategic, tactical, and operational enterprise management levels. As a research tool for analyzing the intellectual transformation of enterprises, a modernized production function is proposed, which accounts for the maturity levels of human and artificial intelligence within the organization. A formula for calculating the bifurcation point of intellectualization is introduced. The bifurcation point enables the identification of the critical moment in the development of the management system, when small changes in the management parameters of artificial intelligence implementation and function redistribution lead to a qualitative leap in the level of intellectualization.