Oleksandr Vyshnevskyi

The article is devoted to the development of the General Economic Theory of Strategizing (GETS) as a metatheoretical framework for analyzing the normalitycrisis cycle. The research aims to substantiate a universal metalanguage for describing cyclical phenomena at the macro, micro, and individual levels by integrating the objective correlation between goals and means with the subjective perception of the actor. Within the GETS framework, two key matrices are proposed: the Goal-Means Commensurability Matrix, which systematizes nine distinct states (three types of equilibrium, three paradoxes, and three types of crises), and the Normality-Crisis Perception Matrix, which distinguishes between normality, a manifest crisis, a latent crisis, and a false crisis. The findings demonstrate the high explanatory power of this new toolkit. The matrices successfully offer a common metalanguage that allows reinterpretation of leading theories of the economic cycle: Neoclassical (as rational adaptation through equilibria and paradoxes), Keynesian (focusing on manifest demand crises and the liquidity trap), Austrian (the paradox of resource wastage and the latent crisis of unsupported ambitions), and Marxist (inherent internal contradictions of capitalism) from the perspective of aligning the specific goals and means of each school. The uniqueness of this approach is validated through empirical case studies: the entrepreneurial biography and illness of Steve Jobs (individual level), the history of Nokia's mobile business (micro level), and the dynamics of the United States' economic and geopolitical standing since 1991 (macro level). The study identifies a "blind spot" in traditional theories, which resides in the state of false crisis. The proposed matrices offer prospects for creating a holistic theory of strategic behavior under uncertainty and provide a synthesis of economics and strategic management.

The article explores digital sovereignty for small nations in the AI era. Using General Economic Theory of Strategizing (GETS), it justifies aligning interests between governments and global platforms. Key AI factors (energy, power, big data, and algo-rithms) are analyzed, identifying data scarcity as the primary challenge. A mechanism is proposed: trading market access for technology and investment. The study justifies regional digital alliances and local protectionism to pool resources. Scientific novelty lies in applying GETS to model state and platform-based TNCs interactions. This strategy shifts countries from pas-sive consumers to active competitors, enhancing sovereignty through proactive big data management.

In conditions of significant changes in economic relations and increasing uncertainty caused by the transformation of the current globalization model, the demand for adequate economic theory grows. Strategizing, as an approach to managing uncertainty, is regularly used by various actors – from individuals to states and international organizations. The general economic theory of strategizing (GETS) is intended to fill the gap in the mutual influence of economic theory and strategizing. On the one hand, by generalizing the developments of leading schools of economic theory, and on the other, by overcoming methodological individualism (L. Mises) with the dialectical method (G. Hegel), the basic axiom of activity (BAA) is formulated: "Individuals and organizations act in an institutional environment". From the BAA follows the corollary about the purposeful activity of actors. Based on the BAA, key economic concepts such as profit, loss, means, capital, demand, supply, production, exchange, market, cost, good, value are revealed, and economics is defined as the science studying the relationship between goals and means. From the positions of GETS, the article presents four schemes of economic dynamics describing simple and expanded reproduction, as well as crisis of the first type (identification of goals with capital) and crisis of the second type (system crisis of compression of goals and capital), as well as demarcation of goal-oriented and strategic activity, wherein the strategic goal is defined as a reflected desired result, integrated into a strategy. Strategizing, as a process of forming and actualizing strategy, represents reflected goal setting. In the context of GETS, the concepts of "subject" and "object" are rethought: the subject is an actor having a strategy and means for its realization, and the object is an actor realizing the subject's strategy, thereby being a means of achieving another's goal. This allows redefining economics as the science studying relationships between subjects and objects. In the concluding part of the article, definitions are given for feudalism, capitalism and communism as economic systems characterized by dominant objectness, and for strategiarchy as a system characterized by dominant subjectness.

This article investigates the impact of Artificial Intelligence (AI) on the industrial economy, analyzing it from the perspective of two competing theories: disruptive and closing innovation. The research is highly relevant due to the significant growth in investments (Nvidia's capitalization surpassed $5 trillion in October 2025) and AI's influence on global industrial production. This is particularly crucial for Ukraine, given the prospects for the transfer of military-oriented AI into the civilian economy. The literature review identifies two main groups of academics: proponents (AI as the core of Industry 4.0) and critics (AI primarily automates existing tasks, potentially leading to "over-automation" and a decrease in GDP). This contradiction forms the basis for two competing hypotheses: AI is a Disruptive Innovation, which changes markets and creates new players. AI is a Closing Innovation, which merely improves existing products and strengthens the position of current market leaders. A comparative analysis of AI was conducted based on criteria such as the impact on the product, the customer, market dominance, and the institutional space. The study demonstrates that AI represents a complex innovative phenomenon that simultaneously exhibits characteristics of both types of technologies: - Closing Role: AI improves existing platforms and products of market giants (Microsoft Copilot, Google AI Overviews, Siri), thereby strengthening their dominance. - Disruptive Role: AI creates fundamentally new products (ChatGPT, Grok), attracts new customers, and shapes new specialized legislation. The dual nature of AI presents several challenges, notably the lack of economic theory and tools for quantitative assessment of its effects at the micro-, meso-, and macro-levels. A list of key scientific challenges requiring resolution is formulated: Defining the theoretical foundations of AI's micro-, meso-, and macro-level impact as both disruptive and closing technologies. Substantiating the assessment methodology and testing the hypothesis regarding AI's statistically significant impact. Identifying economic constraints, minimizing risks, and systemizing directions for stimulating AI adoption. Substantiating recommendations for updating Ukraine's national industrial policy, institutional regulation (including taxation), and ensuring the economic efficiency of AI utilization. Understanding the dual nature of AI is crucial for economic forecasting and strategizing. Although AI possesses powerful disruptive potential, its implementation is currently dominated by incumbent large companies, which does not lead to the "disruption" of their positions. Addressing the outlined challenges is necessary for the urgent actualization of Ukraine's industrial policy.

This article substantiates the development of smart manufacturing as a key determinant of Ukraine’s industrial policy in the context of global transformations. Trends in global deindustrialization are analyzed using the Lawrence model, which reveals a unidirectional dynamic: rising GDP per capita leads to a declining share of manufacturing in GDP. Ukraine is currently undergoing accelerated deindustrialization marked by pendulum-like fluctuations, which necessitates the implementation of reindustrialization policies that align with contemporary needs. The study identifies both external and internal factors shaping demand and supply for manufacturing output and evaluates the effectiveness of current «Made in Ukraine» policy initiatives. To operationalize the logic of local protectionism, the research proposes creating registries of goods, services, and activities aligned with Industry 4.0 technologies, as well as the establishment of special regulatory regimes based on industrial parks.

The purpose of the article is to define prospects and limitations of artificial intelligence as a core of in the new industrial revolution. The definition of the concept of AI in the scientific community remains the subject of heated debate. At the same time, in the regulatory and legal plane, a trend is being formed towards unification of the concept of AI. Based on the analysis conducted and literary sources, the following prospects for AI can be identified on theoretical and practical levels. On theoretical level: (1) alienation of tacit knowledge from the individual (employee and entrepreneur); (2) optimization of the planning system; (3) revision of the socialist-calculation debate; (4) decreasing information asymmetry. On practical level: (1) formation of new products and markets; (2) increasing labor and capital productivity; (3) massive creation of new jobs; (4) optimization of business processes; (5) opportunity for rapid growth for small businesses and startups. Limitations: (1) long-term structural unemployment; (2) inflated expectations from AI and, as a consequence, the possible formation of a speculative bubble in the global stock market; (3) energy consumption of AI; (4) outdated pre-AI corporate culture and regulatory environment. Further improvement of AI (including the transition from AI to AGI) and the expansion of its use can make a significant contribution to solving problems related to economic calculation and minimizing information asymmetry, and therefore optimizing transaction costs in the economy. AI, certainly acting as a locally useful tool at the level of individual enterprises and organizations, causes the acceleration of attracting funds to the stock market, which can lead to the formation of a bubble on global level. If this bubble bursts, expectations about the economic efficiency of AI will be revised, and some AI-related companies will experience significant margin reductions (perhaps losses and bankruptcies). But this, in turn, will initiate the next stage of AI development, will accelerate its transition from the current narrow specialization to the creation of full-fledged general artificial intelligence (artificial general intelligence), which has a greater potential to change the economy at all levels. As a result, AI will become established as the core of the new industrial revolution.

The monograph presents theoretical and scientific and practical principles for determining and forming strategic directions for the development of countries and regions of Europe through smart specialization and the prospects for using it to enter the trajectory of sustainable development of industrial regions of Ukraine in the process of European integration; The genesis of the theoretical and methodological principles of strategizing smart specialization of countries and regions of Europe is studied, smart specialization is considered from the positions of different schools of economic theory. The features of the restoration of old industrial territories of Europe in the context of the Global Goals and the implementation of smart specialization strategies are identified. The priorities of the EU regional policy and the prospects for their reproduction in Ukraine in the context of European integration and overcoming the consequences of the war are determined.

This paper aims to describe role of AI, deployed on a platform of strategizing, functions as a third party to mitigate information asymmetry within the framework of signaling theory. The entire history of human development can be viewed from the standpoint of the desire to overcome information asymmetry. This takes the significance of the category "information asymmetry" to a new level, demonstrating its universal nature. Thus, information asymmetry is a universal category that is an integral characteristic of the development of nature and society, as well as all possible types of communications between key actors: individuals, organizations, nature and AI. The four primary categories of actors (persons, organizations, nature, AI) give rise to 10 different types of interaction, which are divided into two groups (peer-level and hierarchical). Actors have different amounts of information, which describes information asymmetry. In turn, information asymmetry generates economic inequality. The negative effects of information asymmetry can be reduced in two strategic approaches: either by providing additional information to the less informed party, or by redistributing the economic benefits received by the more informed party in favor of the less informed party. Both of these strategic approaches can be implemented within the framework of the logic of platform strategiarchy using artificial intelligence. This assumes that all actors have formalized public strategies that are taken into account when concluding and implementing smart contracts. This approach can be considered as a further development of the provisions of the signaling theory (by M Spence), where public strategies play role of reliable signals.

The accelerated development of smart manufacturing is taking place all over the world, but the definition of the theoretical foundations of its stimulation, as well as the unequivocal understanding of "smart manufacturing" concept still has an untapped research potential. Therefore, the purpose of the article is to determine the theoretical foundations of stimulating the development of smart manufacturing in Ukraine based on local protectionism. The systematization and arrangement of concepts related to the Fourth Industrial Revolution (Industry 4.0) allows not only to clarify the concept of "smart manufacturing", but also to distinguish the concepts of "smart production", "smart maintenance", "smart manufacturing” and define the place of the latter in the system of interconnected concepts. Smart manufacturing is a part of smart production that concerns the production of tangible goods through the use of Industry 4.0 technologies embodied in smart services. Based on the definition and role of smart manufacturing, it becomes clear that smart manufacturing cannot exist without “ordinary” manufacturing, as well as conceptual directions for stimulating the development of smart manufacturing are distinguished, relating to: (1) sphere of smart services, generated by Industry 4.0 technologies; (2) sphere of smart production; (3) sphere of smart distribution; (4) sphere of smart exchange; (5) sphere of smart consumption; (6) sphere of production of smart products by smart manufacturing; (7) sphere of production of smart products by "ordinary" manufacturing; (8) sphere of production of "ordinary" products by smart manufacturing; (9) sphere of production of "ordinary" products by "ordinary" manufacturing. Given the reduction of national manufacturing in Ukraine, the development of services to ensure the smartization of manufacturing actually insures the smartization of foreign manufacturing that produces goods that are then imported into Ukraine. Therefore, it is advisable to stimulate the development of smart manufacturing in several directions at the same time: (1) stimulation of the manufacturing as a whole; (2) stimulating the development of smart services and tools for smartization of manufacturing; (3) stimulating the introduction of smart services in manufacturing; (4) stimulation of demand for products produced by the domestic smart manufacturing. There are two centers of smartization of manufacturing in Ukraine: (1) traditional manufacturing, as it invests in its own smartization; (2) a small business that creates smart services. The state, which in recent years has turned into an important player in the field of IT services, currently is not working purposefully on the smartization of manufacturing. In Ukraine there is also a contradiction between the need to harmonize the domestic economy with the EU market and the arrangement of favorable conditions for the development of smart manufacturing. This contradiction has the potential to be resolved on the basis of local protectionism theory through the expansion and improvement of the practice of applying special economic regimes (for instance, technology parks), and as well as the implementation of institutional and organizational solutions that simultaneously correspond to the provisions of both liberal and protectionist schools of economic theory.

Smart specialization is one of the key modern economic policies implemented in the European Union. Its essence is to ensure innovative development depending on a specific region's existing conditions and features. Smart specialization is aimed at ensuring the regional development of the countries that are part of the European Union and those countries that have a cooperation agreement with it. This tool involves taking into account the peculiarities and capabilities of each region and identifying competitive advantages, which helps to unlock economic potential and more effectively develop innovations at the regional level. Smart specialization aims to: (1) identify the most promising investment areas through a thorough analysis of existing opportunities, assets, competencies, and competitive advantages of the region; (2) more efficient spending of state resources by concentrating on the main industries of a certain region; (3) elimination of duplication of measures that may lead to waste of public resources; (4) implementation of mechanisms that ensure strategic development based on multilateral interaction. The purpose of the study is to determine directions for improving the strategizing of smart specialization in the regions of Ukraine from the standpoint of Schumpeterianism, institutionalism, and developmentalism. The theoretical provisions of ensuring the smart specialization of Ukraine's regional development process in practice face several problems that can be systematized and solved from the positions of different schools of economic theory at the regional and national levels. From the standpoint of the Schumpeterian school of economic theory, the priority direction for improving the smart specialization strategy of the regions of Ukraine is to combine innovation policy with regional smart specialization strategies, as well as the creation of innovative infrastructure to support smart specialization. From the standpoint of the institutional school of economic theory, the priority direction for improving the strategizing of smart specialization in the regions of Ukraine is the systematic alignment of institutions with the goals of smart specialization, the harmonization of the regulatory and legal framework for ensuring innovative activity and strategizing regional development, as well as the elimination of institutional deficiencies in the formulation of strategic documents at the state and at the regional level, which prevent the application of the principles of smart specialization. From the standpoint of the developmental school of economic theory, the priority direction for improving the strategy of smart specialization in Ukraine’s regions is improving economic policy at the national level in the area of stimulating high-tech exports.