The interconnected global trading system has proved to be both vulnerable and resistant to crises, despite its asymmetries. The global trading system is constantly changing under the influence of such factors as the digitalization of economic processes and the growing number of nontariff measures to regulate trade volumes, including trade protection measures introduced by countries in order to ensure national economic interests etc. This article analyzes the impact of the tariff and nontariff instruments of export and import regulation on the asymmetries of the global trading system across countries and separate customs territories, depending on their presence in geographical regions or groups of countries associated with different levels of economic development. In order to quantify the possible asymmetries in the global trading system, analysis of variance and regression analysis are applied to explain the variance in the volume of global trade. The regression models for the dependence of export volumes on a number of trade indicators are fitted for developed, developing, and least-developed countries alongside the global trading system as a whole. The research showed that asymmetries of the global trading system exist on the global, regional and bilateral levels. In this research, two types of asymmetries are discussed: asymmetry directly and indirectly linked to international trade processes. To ensure economic development, the global trading system must be modernized so as to reduce the asymmetry. Accordingly, in order to increase effectiveness of the World Trade Organization, suggestions are proposed in regards to reconsidering trade-dispute settling, improving the monitoring of members’ obligations, increasing negotiation process efficiency and defining criteria for categorizing members according to their economic development.

Purpose. The article studies the convergence between the regions of Ukraine in terms of the basic foodstuff consumption per capita during 2000–2019, taking into account the effects of spatial interaction across regions. Methodology / approach. The convergence analysis between regions of Ukraine is based on the concept of β-convergence which can be tested using spatial econometric models namely spatial autoregressive models and spatial error models. The need for considering spatial interaction can be explained by the fact that regions are characterized by constant interaction with each other. Therefore, region should not be considered as isolated objects in space in empirical research with usage of panel data. Ignoring the spatial interaction between regions and using standard evaluation procedures can reduce the reliability and validity of the obtained results to some extent. Results. The results of our calculation confirm the process of β-convergence of average per capita consumption of all food groups, which means that food consumption in regions with an initial low level of consumption is growing faster than in regions with high initial levels of consumption. Also, as part of the use of spatial econometric models the convergence process was determined to be influenced by spatial interaction between regions while the influence of neighbouring regions has a positive effect on food consumption in particular region. Originality / scientific novelty. The article further develops the main ideas of modeling interregional differentiation based on convergence theory and for the first time, spatial econometric models were used to estimate β-convergence of Ukrainian regions by the levels of consumption of basic foodstuffs. Practical value / implications. The approach proposed by the authors and the obtained results can be used both by state authorities on agrarian policy and food issues, and by enterprises of the agricultural sector in the analysis and forecasting of trends in the consumption of basic foodstuffs at the regional level; when planning the production, processing and delivery of agricultural products, when planning state or regional trade policy in the field of food. At the same time, the inclusion of spatial effects in the model of evaluating convergence will allow policymakers to take into account the geographical features of the convergence process and, accordingly, make more informed decisions to reduce the differentiation of regions of Ukraine by the levels of consumption of basic foodstuffs.

The optimization value of maintenance facilities in order to ensure the effective development of the company is grounded. Conceptual bases of the effective management of the maintenance and replacement of fixed assets are considered in the article. The importance to ensure the competitiveness of products with the aim to prevent lowering of product quality is determined. The necessity of a high level of discipline of statistical observations to ensure forecasting objectivity of technical condition of fixed assets is grounded. To solve the task of increasing the efficiency of maintenance and replacement of equipment the usage of statistical and simulation approaches is offered. In order to find the optimal time between maintenance (replacement parts), that will minimize costs, the model of expected failures is applied. The model is based on the time interval and the average cost of replacement parts. The use of simulation approach has allowed building of a model of replacement equipment or parts on the basis of continuous probability distribution of breakdowns occurrence. The proposals for the optimal length of time to review and eliminate breakdowns of equipment have become the results of developed models testing.

Digital leadership in higher education requires evidence about whether investments in digital systems are accompanied by stronger institutional decision-making and measurable collaboration beyond the university. Existing smart university studies examine infrastructure, educational technologies, and sustainability extensively but provide less quantitative evidence on the conditional relationships between internal digital capacity, management analytics, and distinct forms of external engagement. This study measures the divergence between internal digital transformation and ecosystem integration and estimates how their component dimensions are associated with partnership activity, thereby identifying empirically relevant priorities for university digital leadership. The analysis draws on a June 2026 institutional survey covering 110 Ukrainian higher education institutions across five macroregions, including state, communal, and private institutions differentiated by enrollment size, with responses assessing administration, research information, business collaboration, public-sector engagement, and project activity. Five-point composite indices were assessed using Cronbach’s alpha, compared with paired Wilcoxon signed-rank tests and percentile bootstrap confidence intervals, and analyzed using Spearman rank correlations with Benjamini–Hochberg false-discovery-rate adjustment and multivariable ordinary least squares with heteroskedasticity-consistent type-three standard errors in Python 3.13.5 using NumPy, SciPy, and statsmodels. Internal digital transformation averaged 3.958 against 2.900 for external integration, yielding a paired mean difference of 1.058 points (95% bootstrap confidence interval 0.899–1.224), with the internal index exceeding the external index in 100 of 110 institutions. The composite-index Spearman correlation was 0.366, whereas the component-level regression associated research-information capacity positively with external integration (coefficient 0.341; probability value 0.005) and administrative digitalization negatively conditional on the other regressors (coefficient −0.230; probability value 0.006), demonstrating why digital leadership cannot be inferred from an undifferentiated technology score. Educational partnership ratings exceeded research-commercial partnership ratings by 1.136 points on average (95% bootstrap confidence interval 0.939–1.338), revealing a measurable gap between relatively established teaching relationships and more demanding research-oriented collaboration despite universities’ digital provision. These findings provide university governing bodies and higher education policymakers with statistically grounded indicators for prioritizing digital leadership, management analytics, and research partnerships, while supporting future longitudinal and independently verified assessments of organizational change and collaborative performance.