Purpose. The purpose of the article is to identify the features of spatial asymmetry in changes to the socio-economic potential and resilience of Ukraine’s regions under conditions of the full-scale war, as well as to substantiate the key factors that determine the differentiation of regional adaptive capacity, financial self-sufficiency, and structural resilience. Methodology. The methodological basis of the study is a comprehensive approach combining the provisions of regional economics, spatial development theory, resilience theory, and systems analysis. The research employs statistical and comparative analysis to assess interregional differences in demographic, infrastructural, financial, and economic transformations. The study uses indicators such as changes in the de facto population, the concentration of internally displaced persons, the scale of infrastructure losses, the share of official transfers in local budget revenues, and the level of economic diversification. Methods of generalization, synthesis, structural analysis, and graphical visualization are applied to identify spatially differentiated models of regional transformation under wartime shocks. Findings. The study demonstrates that the full-scale war has become a factor of profound transformation of Ukraine’s socio-economic space. It has intensified demographic losses, caused large-scale destruction of industrial, social, transport, logistics, and energy infrastructure, deepened financial disparities among regions, and increased migration vulnerability. The most severe losses of socio-economic potential are observed in frontline and partially occupied regions, where human capital has declined, production capacity has been destroyed, transport and social infrastructure have deteriorated, and local financial self-sufficiency has weakened. At the same time, relatively safe rear regions have become centres of population concentration, business relocation, financial resource accumulation, and economic activity. The research identifies spatially differentiated models of territorial social and financial return, including financially resilient regions, financially degraded regions, and transitional regions that combine high security risks with a relatively preserved capacity for economic functioning. It is substantiated that economic diversification is one of the key determinants of regional resilience, as it increases territories’ ability to adapt to shocks, maintain economic activity, and reduce dependence on individual sectors. Additional factors undermining resilience include migration losses, shrinking labour potential, youth and skilled labour outflow, population ageing, energy instability, and growing dependence of communities on external financial support. Originality. The scientific novelty of the study lies in substantiating the spatial asymmetry of changes in the socio-economic potential and resilience of Ukraine’s regions under conditions of full-scale war. The article develops an analytical approach to identifying spatially differentiated models of territorial transformation based on demographic, infrastructural, financial, and structural indicators. The study also highlights the relationship between territorial financial capacity, economic diversification, migration vulnerability, and regional resilience in the context of long-term military shocks. Practical value. The practical significance of the results lies in their applicability for improving state regional policy under wartime and post-war recovery conditions. The findings may be used to develop differentiated policy instruments aimed at supporting regions with critical losses of socio-economic potential, strengthening local financial capacity, reducing interregional disparities, stimulating economic diversification, and increasing the adaptability of regions and communities to long-term security, demographic, and socio-economic challenges.
Purpose. This study develops and substantiates a multilevel organisational and analytical model for regional planning and forecasting of skilled workforce training in Ukraine, taking into account the interests of key labour market stakeholders and the influence of political, legal, economic, social, and technological factors shaping demand for skilled workers and vocational education. Methodology. The study employs a combination of strategic and statistical methods. Strategic analysis tools, including PEST analysis and stakeholder-oriented approaches, are used to assess the external environment and institutional factors influencing workforce training. Quantitative methods, including correlation analysis and regression modelling with lagged variables, are applied to evaluate and forecast the impact of demographic trends and educational enrolment patterns on demand for vocational education and training. Findings. The results demonstrate that demand for skilled workforce training is shaped by a complex interaction of economic, demographic, social, technological, and political and legal factors. In particular, the study highlights the significant impact of Russia’s full-scale military aggression, which has intensified labour market imbalances through demographic losses, migration processes, and structural changes in regional economies. At the same time, recent updates to the legislative framework regulating vocational education and regional workforce planning have strengthened the institutional basis for forecasting and aligning training provision with labour market needs. Empirical analysis based on data from the Lviv region confirms a strong relationship between enrolment in vocational education institutions, demographic indicators, and higher education enrolment. The forecasting results indicate a potential decline in vocational education enrolment in the medium term, driven by demographic changes and persistent educational preferences. Based on the integration of strategic and statistical analysis, a three-level model for regional planning and forecasting of skilled workforce training -comprising basic (inertial), forecasting (analytical), and strategic (corrective) levels - is proposed. Originality. The originality of the study lies in the development of an integrated conceptual framework for regional workforce training planning and forecasting that combines strategic analysis tools with quantitative forecasting methods. The proposed approach contributes to the formation of a regional workforce forecasting system aligned with European practices of skills anticipation and labour market analysis. Practical Value. The proposed model can be used to improve the analytical basis for regional decision-making in workforce development, enhance coordination between vocational education systems and labour market needs, and increase the effectiveness of planning and forecasting of workforce training in the context of economic transformation and post-war recovery.
regional workforce training plan, workforce forecasting, skills demand, vocational education and training (VET), higher education, regional labour market, multilevel model, human capital, skilled workers, strategic analysis, statistical analysis, regression analysis
Purpose. The purpose of the article is to assess the economic potential of Ukraine’s AI ecosystem through the analysis of its market structure, human capital, investment dynamics, and export capacity of the IT sector. Particular attention is paid to determining the role of the AI segment in increasing high-tech value added, labour productivity, export competitiveness, and the macroeconomic resilience of Ukraine. Methodology. The methodological basis of the study is a structural-dynamic and comparative analysis of statistical and analytical data characterizing the development of Ukraine’s IT sector and AI ecosystem. The empirical basis includes indicators of IT exports for 2019–2024, the number of IT and AI specialists, the share of AI specialists in IT employment, the structure of AI employment by type of employer, the dynamics of AI companies for 2013–2023, the geographical concentration of AI talent and business, and venture financing indicators. The study employs descriptive statistical analysis, growth rate comparisons, structural analysis, and the generalization of industry reports and international analytical sources. Findings. The study shows that Ukraine’s IT exports increased from USD 4.2 billion in 2019 to USD 6.4 billion in 2024, confirming the role of the IT sector as one of the key sources of foreign currency earnings and a stabilizer of the balance of payments. It is established that the AI segment remains relatively small in terms of employment, but demonstrates faster growth compared to the IT sector as a whole. The share of AI specialists in IT employment nearly doubled between 2019 and 2024, while the number of AI specialists increased from 0.97 thousand in 2013 to 6.1 thousand in 2025. The article identifies a structural shift from the outsourcing model toward product companies, indicating the strengthening of business models with higher value added. The analysis also reveals a high geographical concentration of AI business and talents in several regional centers, primarily Kyiv and Lviv. Regarding investment, a significant jurisdictional gap is identified: AI companies of Ukrainian origin incorporated abroad attract considerably more capital than those registered in Ukraine, which weakens the domestic economic multiplier. Originality. The scientific novelty of the article lies in the integrated consideration of Ukraine’s AI ecosystem through the combination of ecosystem indicators – human capital, company structure, employment models, geographical concentration, and investment flows – with macroeconomic indicators of IT exports and the role of the sector in maintaining the balance of payments. This approach makes it possible to assess the AI segment not only as a technological field, but also as a factor of structural transformation and long-term economic development. Practical value. The practical significance of the results lies in substantiating the need for state and business policies aimed at strengthening the economic effects of AI development in Ukraine. The findings may be used to support the development of Ukrainian jurisdiction for AI companies, stimulate regional innovation centers, attract investment, retain and develop human capital, and expand the use of AI beyond the IT sector in order to increase cross-sectoral productivity.
economic potential, artificial intelligence, AI ecosystem, IT export, human capital, AI investments, productivity, Ukraine
Purpose. The purpose of the article is to analyze the impact of the shadow economy on the economic development of Ukraine and to substantiate the main directions of its minimization as an important factor in ensuring the sustainable development of the state. Methodology. An important aspect of the study is the assessment of the scale of the shadow economy. In scientific practice, various methodological approaches are used to measure it, in particular, direct methods, indicator-based methods and econometric models. The most common are indirect assessment methods based on the analysis of macroeconomic indicators, such as the volume of cash in circulation, the employment rate, the tax burden and other indicators of economic activity. Results. The paper summarizes the main approaches to understanding the essence of the shadow economy and identifies its main features. It is proven that it has a negative impact on the state economy, as it leads to budget losses, a decrease in the effectiveness of state policy, increasing inequality and worsening business conditions. At the same time, it is emphasized that the shadow sector partially performs an adaptive function in conditions of economic instability. The factors of formation of the shadow economy in Ukraine are analyzed. It is established that institutional, economic, regulatory and social factors have the greatest influence. These include imperfect legislation, complexity of tax administration, high level of tax burden, corruption, as well as low level of trust in state institutions. It is shown that the combination of these factors creates conditions for the spread of informal economic activity. The article analyzes the dynamics of the shadow economy of Ukraine in recent years. It is found that until 2021 there was a tendency to gradually decrease its level, however, modern crisis phenomena, in particular the pandemic and military events, led to an increase in the share of the shadow sector. This indicates a high sensitivity of the economy to external and internal challenges. Originality. Special attention is paid to international experience. It is noted that in the member states of the European Union the level of the shadow economy is much lower, which is explained by more effective state policy, high level of trust and developed institutions. This creates a basis for adapting best practices in Ukraine. Practical value. An author’s model for minimizing the shadow economy is proposed, which combines institutional, tax-economic, digital and social mechanisms. The model assumes coordinated interaction of the state, business and society and is aimed at increasing the transparency of economic processes, increasing tax revenues and improving the investment climate. The practical significance of the results lies in the possibility of their use when developing state economic policy. The implementation of the proposed approaches will contribute to strengthening economic security, increasing the efficiency of public administration and ensuring sustainable development of Ukraine.
shadow economy, minimizing the shadow economy, sustainable development, economic security, state regulation, tax administration, digitalization of the economy
Purpose. The study provides a comprehensive econometric analysis of the impact of import dependence on the sectoral structure of employment in a developed economy, using Germany as a case study. The relevance of the research is driven by the deepening integration of national economies into global value chains and the growing role of imports as a key determinant of labour market transformation. The purpose of the study is to deliver a quantitative assessment of the impact of import dependence on the industry-level structure of employment in the developed economy (Germany), accounting for threshold effects through the application of a dynamic threshold modelling approach. Methodology. The empirical basis of the study is constructed using panel data for the period 1995–2022, covering 42 economic activities. The methodological framework is based on a dynamic threshold regression model, enabling the identification of nonlinear relationships between variables and the estimation of critical values of import dependence at which both the magnitude and direction of its impact on employment change. A bootstrap procedure is employed to ensure the statistical robustness of the estimates, facilitating the refinement of threshold parameters and the validation of their accuracy. Findings. The findings confirm statistically significant threshold effects, indicating structural heterogeneity in the impact of import dependence on the labour market. The results show that crossing certain critical levels of import dependence is associated with changes in both the sign and magnitude of its effect on employment. Accordingly, three sectoral groups are identified: sectors with a predominantly negative impact (displacement effect), sectors with a positive impact (driven by participation in global production networks), and sectors with mixed or statistically insignificant effects. Originality. The scientific contribution of the study lies in applying a dynamic threshold framework to the analysis of the relationship between import dependence and employment, allowing for capturing the nonlinear, asymmetric, and sectoral heterogeneous effects. Practical value. The practical implications of the findings include providing an analytical basis for selective structural policies targeting sectors with high potential for integration into global value chains. The results are particularly relevant for transition and post-crisis economies, including Ukraine, where optimising import dependence and fostering employment are critical in the context of post-war economic recovery.
Purpose. The aim of the study is to determine the impact of social and labour relations on the formulation of cost management strategies for enterprises in the agro-industrial complex and to substantiate approaches to improving the efficiency of labour resource utilisation within the strategic cost management system. Methodology. The study utilises a range of general scientific and specialised methods, including analysis and synthesis, the systems approach, comparative analysis, and the synthesis of academic sources and practical experience regarding the operations of agribusiness enterprises. To substantiate the proposed approaches to cost management, methods of strategic analysis of social and labour relations and assessment of the effectiveness of motivational mechanisms were applied. Findings. It has been established that social and labour relations are an important factor in the formation of an effective cost management strategy for agribusiness enterprises. The main factors influencing personnel costs have been identified, in particular the level of remuneration, employee productivity, vocational training and social security. The feasibility of integrating the system for managing social and labour relations into the process of strategic cost management has been substantiated. Directions for improving the effectiveness of cost management through the improvement of labour relations, the development of corporate culture and the enhancement of staff qualifications have been proposed. Originality. The scientific novelty of the study lies in the development of an approach to integrating social and labour relations into the cost management system of agribusiness enterprises through the introduction of a hybrid staff motivation system, which combines key performance indicators (KPIs), piecework pay and cost indicators. The study proposes the use of ‘cost-reduction’ KPIs, digital monitoring of staff performance and the seasonal adaptation of incentive mechanisms to ensure increased labour productivity and a reduction in production costs. Practical value. The practical significance of the research findings lies in their potential use by managers of agribusiness enterprises to improve cost management systems, enhance the efficiency of labour resource utilisation, develop modern incentive mechanisms and strengthen the competitiveness of enterprises. The proposed approaches can be utilised when developing sustainable development strategies for agribusiness enterprises in the context of the digital transformation of the economy.
social and labour relations, cost management, agribusiness enterprises, enterprise strategy, labour resources, key performance indicators, labour motivation
Purpose. The purpose of the study is to determine and comprehensively assess the main indicators of the efficiency of resource potential use of livestock enterprises in the Carpathian region of Ukraine and justify the corresponding reserves for their increase to ensure the growth of production of competitive products and export opportunities. Methodology. The study was based on general scientific research methods, namely: the monographic method was used during a comprehensive study of the theoretical and practical foundations of the formation and effective use of resource potential of livestock enterprises; methods of analysis and synthesis were applied in the study of the dynamics of livestock development indicators in enterprises; the calculation-constructive method was used when determining the influence of the main factors on the indicators of the efficiency of resource potential use of enterprises, the system method was taken into account to build cause-and-effect relationships between factors and values of indicators of the effective use of resource potential of enterprises in the industry. Results. The article examines the dynamics of the main components that form resource potential in livestock enterprises. The main factors that determined the change in the quantitative and cost indicators of the resource potential of the enterprises of the industry for the studied period were established and substantiated. A system of indicators for assessing the resource potential of the enterprises of the industry was proposed, which include: the volume and cost of products produced per average annual head of productive animals of different species, as well as per average annual conditional head for a more objective comparison; per hectare of forage land area taking into account different levels of potential yield; per ton of feed used, taking into account the conversion level for each direction of animal husbandry; per unit of capital cost. Originality. The main reserves for increasing the efficiency of resource use in the enterprises of the animal husbandry industry of the Carpathian region were substantiated, which include the implementation of a system of organizational and economic, information and advisory and financial and investment levers to promote technological modernization of production. According to the results of the study, it was found that the efficiency of resource potential use is highest in enterprises that produce eggs, milk and raise pigs for meat with significant justified opportunities for further growth in the cost of produced products per unit of cost or the number of resources involved. Practical value. The study consists in determining the values of the main types of indicators of the efficiency of resource potential use in enterprises of the livestock industry, as well as identifying important growth reserves for adjusting and improving the system of supporting the development of a balanced agricultural sector of the Carpathian region with an increasingly large share of livestock production in the inter-sectoral balance in order to optimally use the resources involved and increase the export opportunities of products with higher added value.
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UDC 332.1:338.124.4:355.01(477); JEL R11, R12, R58, H77, O18