Based on the theoretical foundations of evolutionary economic geography and the concept of resilience, a methodological framework for identifying trajectories of economic reconstruction of territories is proposed. The framework is grounded on understanding historical heritage, capturing manifestations of resilience in the present, and shaping a vision of the future based on a combination of economic, social, and environmental values. This perspective allows the reconstruction of Ukrainian territories to be viewed not as a pre-designed process, but as a dynamic response to prolonged military threats and a high degree of uncertainty, in which adaptability and local innovative activity emerge as key drivers of structural transformation. It is shown that dependence on previously established industrial paths, institutional lock-ins, and regulatory barriers have constrained the emergence of new local innovation trajectories in Ukraine, thereby limiting the capacity of territories to respond to the polycrisis associated with large-scale military threats. At the same time, elements of historical legacy—such as sectoral structures, professional communities, educational institutions, production chains, and resilient social networks—can be considered a starting point for the formation of new trajectories of economic reconstruction. The importance of complementing formal institutional solutions with attention to emerging resilience is substantiated, understood as the capacity of communities for self-organization, creative response, and the development of new practices in the face of existential challenges. It is further argued that contemporary industrial culture shaped around the concept of DIY 4.0 opens new opportunities for broad citizen participation in local-level structural transformations on an innovation-driven basis. Production spaces such as FabLabs and RoboLabs combine elements of education, digital manufacturing, experimental entrepreneurship, and social cohesion—components that are critically important for reconstruction oriented toward wartime and post-war challenges. Such spaces not only contribute to strengthening human capital but also provide a foundation for transforming regional industrial ecosystems into systems capable of generating and sustaining new development trajectories under conditions of profound structural change.
This article provides a comprehensive study of the transformation of the industrial potential concept amidst global shifts and the accelerated transition toward the Industry 5.0 paradigm. The author argues that the modern era of turbulence necessitates a fundamental shift from the «fragile efficiency» model toward strategies rooted in resilience, scenario plan-ning, and foresight. The study clarifies the conceptual framework of «industrial development potential,» defining it as a dynamic synthesis of resources, conditions, and capabilities that determine the sector’s ability to meet the objectives of complex socio-economic systems while maintaining viability under volatile conditions. A central theme of the research is the structural analysis of educational and professional potential, which the author positions as the bedrock of the in-dustry’s innovative renewal. This potential is systematically categorized into four core pillars: the human dimension (economically active population with requisite motivation and cognitive skills), the material foundation (an integrated network of educational institutions and digital learning platforms), the institutional environment (state educational policies and rigorous quality standards), and the target partner ecosystem (direct involvement of industrial enterprises in vocational training).The research identifies strategic trajectories for industrial evolution in post-industrial society, emphasizing total digitalization, the deployment of cyber-physical systems, environmental stewardship through circular economic models, and a human-centric approach to labor. The author substantiates the necessity of deepening public-private partnerships in the educational sphere by establishing corporate universities, expanding dual education pro-grams, and fostering joint technological hubs. Furthermore, the paper proposes a diagnostic toolkit to evaluate the im-pact of each component on sectoral growth. These metrics serve as a rigorous basis for developing management deci-sions aimed at strengthening national economic security and restoring the strategic agency of Ukraine’s industrial sector in the post-war recovery period.
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.
The article examines the features of the development of electronic commerce (e-commerce), including online trade as its component, in the pharmaceutical industry in the context of economic digitalization. It identifies the main econom-ic risks associated with the functioning of digital sales channels, including financial, legal, logistical, and reputational risks, and analyzes their impact on the operational efficiency of enterprises in the sector. The study highlights the specif-ics of risk formation during the online distribution of pharmaceutical products, emphasizing that failures in logistics, regulatory compliance, or digital security can directly affect consumer safety and trust. The necessity of a comprehensive approach to risk management is substantiated, combining digital technologies, regulatory tools, and quality control mechanisms to ensure the stability and competitiveness of pharmaceutical e-commerce platforms. The article also pro-poses practical directions for risk mitigation, taking into account the industry’s characteristics, such as the critical im-portance of product safety, regulatory compliance, and the integrity of supply chains. Special attention is paid to the in-tegration of blockchain technologies, digital identification systems, and cybersecurity measures as key mechanisms to enhance transparency, prevent fraud, and protect consumer data. The findings demonstrate that an effective risk man-agement framework not only reduces the likelihood of negative events but also strengthens customer confidence, sup-ports sustainable business development, and promotes the long-term efficiency and competitiveness of pharmaceutical enterprises in the digital economy. This research contributes to the understanding of risk dynamics in the online phar-maceutical market and provides recommendations for industry practitioners, regulators, and digital platform managers.
This article examines the challenges of designing and implementing industrial policy in peripheral and semi-peripheral economies under conditions of external constraints, using Ukraine as an illustrative example. The Ukrainian economy operates under the influence of multiple and often contradictory factors whose combined effect significantly narrows the available industrial policy toolkit and increases the risk of further peripheralization within the international division of labour. The origins of this vulnerability can be traced to long-standing adherence to Washington Consensus prescrip-tions, and the neglect of key structural regularities of economic development, including increasing returns, diversifica-tion of economic activities, economic complexity, cumulative causation, economies of scale, and cluster and synergy effects. The study characterizes the structural weakness of the Ukrainian economy, manifested in processes of deindus-trialization, raw-material specialization, and the loss of economic complexity compared with the countries of Central and Eastern Europe. It also provides a theoretical interpretation of the nature of external constraints faced by peripheral and semi-peripheral countries in shaping industrial policy and systematizes their manifestations in Ukraine, including WTO trade commitments, the financial conditionality of IMF programmes, the requirements of the EU acquis com-munautaire and the “Ukraine Facility” programme, climate-related regulatory pressure from the European Union, as well as the asymmetry of bargaining power in interactions with transnational corporations. The paper shows that these constraints reflect deeper structural asymmetries of the global economy: countries that historically developed their in-dustries through protectionist policies and state support for domestic producers now shape international trade rules that effectively limit the ability of developing economies to replicate a similar development trajectory. For Ukraine, mitigat-ing the impact of these constraints requires both defending the right to expand the industrial policy toolkit in negotia-tions with international partners and strengthening domestic productive capabilities while increasing domestic value added. These conditions highlight the need for structural and technological transformation of industry along two inter-related dimensions: a techno-economic trajectory associated with the principles of Industry 4.0 and a value-oriented trajectory aligned with the concept of Industry 5.0. Using the economic complexity approach as an analytical basis for selective industrial policy, the study outlines related diversification paths for the Ukrainian economy that are relatively attainable given the country’s existing productive capabilities while also possessing the potential to increase technologi-cal sophistication and enable further diversification. This framework provides an analytical basis for the implementation of a selective industrial policy aimed at fostering more complex economic activities. On this basis, the article substanti-ates strategic principles for Ukraine’s industrial policy aimed at overcoming the peripheralization trap and facilitating the structural transformation of the economy through the development of productive capabilities under conditions of external constraints and the requirements of Industry 4.0 and Industry 5.0.
This article analyzes the impact of the Carbon Border Adjustment Mechanism (CBAM) on Ukraine’s iron and steel in-dustry. Beginning in 2026, CBAM significantly escalates regulatory pressure on Ukrainian iron and steel exports to the EU due to the high carbon intensity of traditional BF-BOF (blast furnace–basic oxygen furnace) technologies. The pur-pose of the study is to determine the adaptation pathways for the domestic steel sector, accounting for the time horizon and capital intensity of the proposed measures. Three key adaptation dimensions are identified: informational (improv-ing MRV reporting quality and transitioning away from default carbon intensity values), commercial (diversifying ex-port flows and optimizing carbon cost pass-through), and technological (transitioning to low-carbon technologies, spe-cifically DRI-EAF). The findings demonstrate that effective adaptation requires pairing short-term organizational mea-sures with long-term technological modernization. CBAM is examined not only as a threat risking the loss of export contracts, production cuts, and job losses, but also as a powerful institutional catalyst for industrial decarbonization and the integration of Ukrainian producers into European low-carbon value chains. The study reveals a significant diver-gence in the readiness levels of Ukrainian metallurgical enterprises. While certain companies (e.g., Interpipe) have al-ready deployed EAF technologies, others remain in the planning or early implementation stages of large-scale electric arc furnace projects. The success of this transition will heavily depend on timely access to investment capital, the devel-opment of a national MRV system fully aligned with EU standards, and effective state support. The author concludes that a comprehensive adaptation strategy—integrating data transparency, commercial flexibility, and deep technological transformation—will enable Ukrainian metallurgy to not only minimize current losses but also secure long-term com-petitiveness in the EU market during the post-war reconstruction period.
In the article the theoretical methodological and applied aspects of industrial sector’s technological transformation amid the 4th Industrial revolution are studied. The author grounds that modern digitalization is an unalternative process of ensuring the intensive development of industry. The scientific novelty of the work consists in renovating the conceptual model of changes’ management through the prism of synchronizing motivational imperatives and transformational potential at the basis of strengthening the capacity of industry for digital transformation. Special attention is paid to clarifying the motivation in the system of industry’s digital transformation management. It is proven that amid global competition traditional motivational factors are transforming into motivational imperatives – objective market requirements, ignoring which leads to technological marginalizaton. The following main groups of imperatives are systematized: reproduction and market positioning; strategic compensation of market shortages; technological intensification. With this digitalization is considered as “technological compensator”, enabling to level the shortage of production resources. In the article the digital capacity determinants of industry of Ukraine and the EU have been studied. Significant digital gaps have been revealed, in particular – in the resources’ supply, infrastructural support and organizational performance. It has been determined that the majority of enterprises in Ukraine now are in the state of reactive adaptation – forced spontaneous adjustment to exogenous requirements and challenges (in particular, ESG standards and CBAM framework), while the European model is oriented at proactive transformation of industrial sector (Industry 4.0/5.0). The renovation of a conceptual model of technological transformation of Ukrainian industry management has been grounded, based on synchronizing the motivational imperatives, transformational potential and industry’s capacity for digital transformation. The proposals are suggested concerning the transition from reactive adaptation policy to the strategy of proactive digital transformation of Ukrainian industry and overcoming digital gaps with the industry of the EU. The following priorities for the formation of a proactive transformational capacity of industry for digital changes are determined: strengthening resource capacity, expanding infrastructural support and increasing digital maturity. The realization of this approach requires: improvement of institutional and infrastructural landscape of digitalization; stimulation of entrepreneurial ecosystem to produce industrial innovations; strengthening regulatory stability; forming the compensatory mechanisms of covering investments’ shortage at the basis of donor and grand financing. Practical importance of the results consists in the possibility to use them in the design of industrial development strategies and business digital maturity programs.
The purpose of this article is to examine approaches to socially responsible supply chain management in the cement industry based on a content analysis of corporate documents issued by the world’s largest cement producers. It has been determined that cooperation with suppliers based on the principles of social responsibility has a direct positive impact on the financial performance of a cement company. This finding underscores the crucial role of institutional mechanisms of control, standardisation, and alignment of requirements within supply chains. A content analysis of supplier codes of conduct of Holcim, Heidelberg Materials and CRH was carried out using the text analytics tools of Voyant Tools. The results revealed substantial differences in semantic emphases, regulatory strictness and approaches to integrating corporate social responsibility into supply chain management. Holcim adheres to a socio-ethical model that combines managerial standards with a strong focus on workers’ rights and a corporate culture of integrity. Heidelberg Materials follows a normative-legal model built on strict compliance with international conventions, labour standards and technical environmental regulations. CRH demonstrates a process- and stakeholder-oriented model dominated by sustainability, risk management and due diligence. Despite a shared regulatory foundation, each document demonstrates its own emphases, which shape the company’s distinctive “social responsibility profile”. Taken together, these approaches reflect the spectrum of contemporary responsible sourcing practices in the cement industry and demonstrate how global companies are institutionalizing CSR in their interactions with their counterparties. The practical value of the study lies in deepening the understanding of mechanisms for shaping socially responsible supply chains in the cement industry, which can be used to improve corporate policies and enhance the resilience of supply chains.
The article examines innovative approaches to evaluating the effectiveness of economic development projects in the context of intensive digital transformation of economic systems. The relevance of the study stems from the growing need to modernise traditional assessment methods, which mainly rely on financial indicators and fail to account for digital maturity, innovativeness, social inclusion, and environmental impacts. The aim of the research is to develop a comprehensive integrated model capable of assessing the performance of digital, innovative, infrastructure, and hybrid development projects. The methodology combines data standardisation, multi-criteria decision-making methods (AHP, TOPSIS), composite indexing, clustering, and regression modelling. Applying the model to a sample of 50 projects enabled the identification of three categories of successful initiatives: digitally oriented platforms, innovative R&D projects, and integrated smart-city/green-digital solutions. A comparison of traditional and innovative approaches demonstrated that the integrated effectiveness index provides a significantly more accurate representation of project outcomes, especially for those generating substantial intangible benefits. Regression analysis confirmed the leading role of digital maturity and innovativeness as key determinants of project performance, alongside the important contribution of social inclusion and environmental sustainability. The practical value of the study lies in the applicability of the proposed model for government bodies, investors, and donors to make evidence-based decisions regarding project prioritisation and funding. The model is scalable, adaptable, and suitable for integration into territorial and sectoral development planning systems, making it highly relevant for countries with transforming economies, including Ukraine.
The paper systematizes determinants of irrational consumer decisions in commodity markets and proposes an operational coefficient of propensity to irrational behavior that integrates personality traits (emotional instability, introversion, conformity) with situational drivers (limited time and low awareness). We outline a hybrid measurement procedure combining surveys, digital analytics and neuromarketing signals, and show how the coefficient can be embedded into demand and marketing-response models for e-commerce.
The article substantiates the applied principles of assessing and implementing the investment potential of enterprises under martial law, with a focus on the coal mining industry. Investment potential is interpreted not only as a set of avail-able financial, production, and labor resources, but also as the ability of enterprises to transform these resources into financial stability, operational continuity, modernization of the production base, and restoration of investment activity under conditions of heightened security, energy, logistical, and personnel-related risks. The study analyzes the largest enterprises in the coal mining industry for the period 2021—2025. The assessment is based on indicators that character-ize the scale of operations, financial performance, and efficiency of resource use, including net revenue, net profit/loss, net profit margin, and return on assets. The results show that a high level of net revenue does not automatically ensure the ability of enterprises to implement their investment potential. The key constraints are loss of profitability, deteriora-tion in the efficiency of asset use, growing uncertainty of future cash flows, and the impact of war-related risks on pro-duction continuity. Particular attention is paid to structural changes in the industry caused by the deterioration of the security situation and the suspension or restriction of operations at certain production assets. The analysis confirms that enterprises with significant market shares may rapidly lose their capacity for self-financing investment if profitability declines or assets cease to generate a positive financial result. This highlights the need to assess investment potential not only through the availability of resources, but also through the real ability of enterprises to convert these resources into investment decisions. The article proposes a conceptual approach to implementing the investment potential of coal min-ing enterprises under martial law. The approach is based on the principles of resilience, adaptability, transparency, opti-mality, liquidity, and systemic coordination. It provides for the differentiation of investment decisions into basic, opera-tional, and strategic levels, depending on the financial condition of the enterprise, profitability, liquidity, efficiency of asset use, and level of war-related risks. The practical value of the proposed approach lies in its ability to support the prioritization of investment decisions, the formation of liquidity reserves, the reduction of capital loss risks, and the gradual restoration of production and investment activity in the post-war period.
This paper explores the role of digital-based high-tech agriculture as a central driver of innovation and sustainability in the agro-industrial complex. Emphasis is placed on the strategic importance of technology transfer, foresight-based planning and data-driven solutions to improve productivity and enhance resilience. The findings reinforce the notion that high-tech agriculture is not an isolated phenomenon but an integral part of a broader digitalized industrial economy. This paper presents a systems-based digitally supported approach for the transfer and commercialization of agricultural technologies.
The purpose of the article is to develop methodological principles for assessing the competitiveness of a cement production enterprise based on the calculation of the Operational Competitiveness Index. A number of partial indicators were used to calculate the Index, in particular, sales profitability, EBITDA profitability, production cost level, profitability of net assets and EBITDA growth, since they comprehensively reflect the operational efficiency of the enterprise in conditions of capital-intensive production. In the cement industry, which is characterized by a high level of energy consumption, significant material intensity and sensitivity to cost fluctuations, these indicators allow an objective assessment of the enterprise’s ability to maintain sustainable profitability. The proposed indicators provide a comprehensive assessment of the operational competitiveness of a cement industry enterprise, taking into account both current operational efficiency and the potential for growth and adaptation to changes. The construction of the Operational Competitiveness Index is based on the aggregation of individual partial indicators. For their correct aggregation, the author applied the normalization procedure using the “minimax” method. In order to confirm the practical applicability and analytical potential of the developed Operational Competitiveness Index of a cement manufacturing enterprise, the author tested it on the example of one of the leading players in the global cement market - the international corporation CRH plc. Based on the calculations of the Operational Competitiveness Index of CRH for the period 2014—2024, a gradual and mostly stable growth of the integral indicator was revealed. Such dynamics reflects positive changes in internal management processes, cost rationalization, and increased efficiency of operations. The developed Operational Competitiveness Index can be effectively used as an analytical tool for assessing and monitoring the activities of a cement industry enterprise. The index makes it possible to objectively track changes in the operational efficiency of the enterprise against the background of fluctuations in the market environment, in particular energy prices, logistics costs and raw materials, which are critical for the cement industry. The analytical structure of the index allows identifying weak links in the cost or profitability management system, which will contribute to the formation of sound management decisions.
Economic development is inextricably linked to the introduction of new technologies that improve production processes, resource management, and economic activity organization. However, the scale and nature of this impact vary significantly depending on the industry, region, and level of technological integration in production, leading to ambiguous consequences for the economy. Given this, the study of mechanisms through which new technologies affect production processes and the identification of patterns of economic system transformation under technological progress conditions is becoming increasingly relevant. In the modern context, it is essential to determine the economic consequences of the widespread adoption of Industry 4.0 technologies, such as artificial intelligence, the Internet of Things, blockchain, and 3D printing. Will these technologies lead to structural shifts in the economic system, or will their impact be limited to improving the efficiency of specific production processes? The answers to these questions will help assess the feasibility and prioritization of stimulating the development of Industry 4.0 technologies. Considering the importance of this issue, the article examines the impact of Industry 4.0 technologies on economic system transformation. The role of key technological innovations, including artificial intelligence, the Internet of Things, blockchain, and 3D printing, is analyzed concerning their influence on production process changes, resource optimization, and the formation of new economic relationships. The historical context of previous technological revolutions is reviewed, comparing their impact with modern changes driven by digitalization and automation. Theoretical approaches to understanding the diffusion of technology and its influence on economic growth are substantiated, drawing on the concepts of Joseph Schumpeter, Carlota Perez, and Klaus Schwab. Particular attention is paid to the socio-economic consequences of integrating intelligent technologies into production, particularly automation’s impact on the labor market, changes in institutional regulatory mechanisms, challenges of “surveillance capitalism,” and potential solutions. The paper also explores the prospects for the application of Industry 4.0 technologies across various economic sectors, including industry, energy, transportation, healthcare, and finance. Based on an analysis of current technological innovation trends, conclusions are drawn regarding potential scenarios for the transformation of the economic system in the near future. Key challenges and opportunities for government policy, business, and society in the context of technological development and structural economic changes are identified. The aim of the article is to identify patterns of technological impact on economic processes and to forecast their influence on the structural elements of the economic system in the context of the widespread adoption of Industry 4.0 production models. The study results indicate that at the current stage of the Fourth Industrial Revolution, particularly the transition to the Industry 4.0 production model, artificial intelligence should be considered a breakthrough technology. It radically reduces production costs while enhancing the effectiveness of complementary technologies such as the Internet of Things, 3D printing, and blockchain. Each of these technologies, both individually and collectively, contributes to changes in the established structural elements of the economic system. 3D printing, combined with the infrastructure of the Internet of Things and the computational capabilities of artificial intelligence, simplifies the production of customized goods, altering the structural element of the economic system related to product assortment decisions-essentially answering the question of “what to produce.” Additionally, 3D printing shortens the value chain of product creation, which in turn affects production methods, addressing “how to produce.” This structural element is also influenced by blockchain technology, which provides opportunities to reduce the transaction costs of regulatory institutions governing economic relations. Finally, the structural element of “for whom to produce” is transformed by the Internet of Things, enabling manufacturers to collect and analyze consumer data, ensuring production adapts to individual needs.
The semiconductor industry is a cornerstone of the European Union’s economic resilience and technological sovereignty, forming a critical pillar of modern industrial policy. In response to growing geo-economic tensions, supply chain vulnerabilities, and technological dependence on third countries, the EU has intensified its efforts to regain strategic autonomy. These efforts are embodied in the adoption of the EU Chips Act, which provides a comprehensive regulatory and financial framework to expand semiconductor production capacities within the EU. Complementary initiatives include the creation of regional innovation clusters (Silicon Saxony, Grenoble Valley, Eindhoven), the development of next-generation materials such as gallium arsenide (GaAs), silicon-germanium (SiGe), and indium phosphide (InP), and the reduction of critical material dependencies through diversification of imports and strategic partnerships with like-minded nations, including Japan, South Korea, and Taiwan. In this context, the article provides a systematic analysis of the EU’s semiconductor policy and identifies tools that can be adapted to Ukraine’s post-war recovery and long-term economic development. Given Ukraine’s legacy in microelectronics, scientific potential, and role as a key supplier of rare gases such as neon and palladium, the country possesses the foundations to rebuild a resilient semiconductor ecosystem. The study highlights Ukraine’s opportunity to develop specialized production capacities in SiGe-based radiofrequency chips and GaN-based power electronics, which are in high demand for defense, space, and next-generation communication systems. Special attention is paid to institutional constraints, such as underfunded R&D, workforce shortages, and weak IP protection, which hinder Ukraine’s technological revival. The paper proposes practical policy recommendations, including the implementation of forward-looking industrial policy, integration into EU value chains, and alignment with European research initiatives (Horizon Europe, Digital Europe). It also emphasizes the importance of building domestic production hubs, developing export-oriented competencies, and leveraging public-private partnerships to attract investments in the semiconductor sector. Overall, the paper underscores the strategic potential of adapting the EU’s industrial model to Ukraine’s context, advocating for the formation of a high-tech national semiconductor strategy. Such an approach would not only strengthen Ukraine’s defense capabilities and economic sovereignty but also position the country as a valuable partner in the broader European technology landscape.
The study is devoted to identifying the impact of automation and artificial intelligence technologies on the labor structure and the phenomenon of economic polarization in the context of the digital transformation of the labor market. Its objective is to test the hypothesis that the human — AI collaboration model represents the most effective and safe trajectory for societal development. A comprehensive approach was applied to analyze contemporary theoretical concepts, global research, and empirical data, complemented by an original online survey conducted among Ukrainian youth (92 respondents). The first part of the research defines the conceptual framework and examines the phenomenon of labor market polarization, whereby technological progress leads to a decline in medium-skilled positions, while demand concentrates in high- and low-skilled segments. Risks to social structure and economic stability are outlined, supported by historical examples (the USA and Europe after the 1980s) and modern forecasts. The empirical stage included designing a questionnaire and conducting a survey that covered access to technology, digital skills, attitudes toward artificial intelligence, motivational barriers, and migration intentions. The results indicate a high level of technical access among young people but also a formal attitude toward learning. Nearly half already use AI services (ChatGPT, Copilot); however, their understanding of the technology remains moderate. It was determined that, to ensure Ukraine’s sustainable economic development, the education system and labor market must reorient toward training specialists capable of creating and maintaining modern technologies (engineers, analysts, data specialists), as well as developing sectors where the human component remains critical — education, healthcare, and creative industries. The findings confirm that Ukraine’s economy can harness the potential of artificial intelligence for accelerated growth only if investments are made in human capital and in developing a workforce capable of effective collaboration with technology; otherwise, there is a risk of increased outmigration of skilled workers. The Human + AI model offers Ukraine the opportunity to leapfrog intermediate stages of industrial development and build a “smart” economy from the outset — a particularly vital advantage during post-war recovery, where deploying robotics for infrastructure reconstruction, implementing AI systems in urban governance, and creating new high-skilled jobs can generate rapid economic gains and sustainable growth.
This study analyzed the temporal dynamics of the relative frequency of the term “reconstruction” in English-language printed literature from 1860 to 2022. The analysis revealed that its usage was primarily associated with negative events of regional or global scale — such as wars, military conflicts, natural disasters, and economic crises — and efforts to address their consequences. Additionally, the term was linked to positive societal transformations related to decolonization, urbanization, and sustainable development. Understanding of the reconstruction concept has been enhanced through synthesizing its definitions found in scholarly, regulatory, and informational sources. This involved identifying of its core and composite types of change and the term’s contextual polysemy. The proposed typology of changes that reflect the essence of reconstruction may serve as a framework for analysis and decision-making, particularly in the selection of priority recovery projects for regions and communities. Building on the postulates and principles of O. Vyshnevskyi’s General Theory of Strategizing, this typology is integrated with the main branches of contemporary philosophy (ontology, epistemology, and axiology), which enables the identification of the most appropriate type of change aligned with the mission, vision, and values of a specific territory. Such an integrated approach ensures a scientifically grounded choice of reconstruction strategy (ranging from adaptive recovery for stable territories to comprehensive recovery for the most severely affected regions) and contributes to improving the quality of strategic planning in the field of regional development. A comparative analysis of reconstruction and related concepts was conducted, identifying their common feature and conceptual distinctions across five criteria: depth of change, scale of change, object of change, time horizon, and initiator of change. Despite their formal semantic similarity, most English-language terms commonly used as synonyms for “reconstruction” (such as “recovery”, “rebuilding”, “renovation”, “restoration”, “regeneration”, and “rehabilitation”) operate according to different change logics and have more limited applications. The analysis also found that the term “recovery” dominates in frequency of use in English-language printed literature. However, this stems not from its conceptual precision in describing recovery processes, but from its political appeal and linguistic simplicity. Of all related concepts, reconstruction encompasses the broadest range of changes, including both physical-spatial and functional transformations — at the levels of improvement and/or transformation — designed to mitigate the destructive impacts of shocks and crises or to facilitate societal transformations. These conceptual differences carry practical implications: terminological inaccuracy directly affects the quality of strategic planning, while term substitution may result in a narrowing of strategic vision and distortion of development priorities for territories.
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.
The article is devoted to the consideration of the features and global trends of the development of the instrumentation engineering industry and the main ideas for industrial policy for its development in the context of the transition to Industry 4.0 and 5.0. The basic global models of the development and projects in instrumentation engineering industry are determined. Recommendations for industrial policy in the field of instrumentation engineering industry in Ukraine are formulated.
The article examines the challenges of ensuring an adequate supply of skilled labour for Ukraine’s industrial sector during wartime and substantiates approaches to modernizing the state system for forecasting labour demand. It is established that the shortage of qualified personnel in industry is systemic and shaped by a combination of demographic, migration, and structural factors that constrain industrial modernization and limit the potential for sustainable economic recovery. A comparative analysis of international practices of labour market forecasting is conducted, focusing on approaches based on multi-level modelling, scenario analysis, the integration of statistical and administrative data, and the use of big data derived from online vacancies. The study evaluates the current Ukrainian Methodology for Forecasting Labour Demand and identifies its major shortcomings, including methodological inertia, the absence of scenario-based forecasting tools, the failure to account for technological and structural changes in skill composition, and the insufficient integration of data from diverse sources. The article substantiates the need to develop a renewed forecasting system that combines macroeconomic, sectoral, occupational, and skills-based levels of analysis, allowing for the modelling of multiple labour market development scenarios. An institutional model is proposed that envisages the establishment of a specialized state analytical centre responsible for coordinating methodological frameworks, consolidating data sources, and producing scenario-based forecasts of labour market needs. Such a system would enable the regular updating and harmonization of forecasts across sectors, regions, and education levels, improving the responsiveness of workforce planning to real industrial demand. The research findings provide a conceptual foundation for enhancing the evidence base of employment, education, and industrial policies in Ukraine and for building an integrated national system of analytical and forecasting support in the context of post-war economic recovery.
