Tetiana Kolodizieva

The influence of information is the main productive force and the subject of production for the economic systems development. Information services contribute to the competitive economy, to the provision of optimal conditions for human development, and the implementation of effective democratic procedures. The results of the socio-economic development of Ukraine testify to the growing lag of the parameters of its competitiveness from many countries of the world and to the strengthening of differentiation in the regional development. Since the regional environment today largely determines the competitiveness of the entire national economy, it becomes important to discuss the appropriate methodological tools for assessing the development level of information and communication infrastructure (ICI) in the regions of Ukraine.
Given the necessity of solving a specific problem, a methodological approach to assessing the development level of ICI is proposed, which is based on the calculations of integral indicators by the entropy method and aimed at the implementation of a group of economic regions in accordance with its defined parameters. The improved methodical toolkit takes into account consistent stages of the system for estimating indicators, which allows to analyze and evaluate the levels of ICI regions development and to obtain the value of specific digital divisions between individual regions.
The implementation of the proposed scientific and methodological approach allowed to obtain the results of the assessment of the ICI development level, to allocate regional clusters depending on the ICI development levels, to identify factors that restrain the ICI development in the regions and to propose recommendations for their elimination.

The article proposes an approach to analyzing reliability factors of commercial banks during the 2014–2017 systemic crisis in the Ukrainian banking system, using the Kohonen self-organizing neural networks and maps. As a result of an experimental study, data were obtained on financial factors affecting the stability of a commercial bank in a crisis period.

It has been concluded that during the banking crisis in Ukraine in 2014–2017, the resource base of a bank was the main factor of this bank stability. The most preferred sources of resources were funds from other banks (bankruptcy rate of 5.7%) and legal entities (bankruptcy rate of 8%), and the least stable were funds from individuals (bankruptcy rate of 28.5%).

The relationship between financial stability and the amount of capital and the structure of bank loans is less pronounced. However, one can say that banks that focused on lending to individuals experienced a worse crisis than banks whose main borrowers were legal entities.

The tools considered in the article (the Kohonen self-organizing neural networks and maps) allow for efficiently segmenting data samples according to various criteria, including bank solvency. The “hazardous” zones with a high bankruptcy rate (up to 49.2%) and the “safe” zone with a low rate of bankruptcy (6.3%) were highlighted on the map constructed. These results are of practical value and can be used in analyzing and selecting counterparties in the banking system during a downturn.

The article explores theoretical and methodical aspects of managing dual relationships that arise between participants in logistic cooperation in the process of formation and functioning of supply chains. The use of a behavioral approach to defining supply chains has allowed identifying and justifying the priority role of behavioral factors that influence modern logistics entities and determine the effectiveness and long-term satisfaction with logistics cooperation. Given the literature summary, the study has classified types of cooperation in logistic activity and proved that among the behavioral factors influencing the of logistical cooperation efficiency, the trust is of particular importance, which remains a limitation, a bottleneck in the process of formation and development of dual relationships in logistics chains. It is proposed to introduce a generic indicator, namely the level of confidence in the supply chain to assess the social, economic and strategic aspects of logistics interaction. A methodological approach to assessing the level of trust in logistic cooperation was adjusted based on determining the composition of criteria that directly affect this indicator and using the expert survey of supply chain participants. The study proposes to use the confidence indicator to form and improve networks and supply chains, taking into account its value when constructing a generalized outsourcing model.

Improving the logistics service quality (LSQ) requires its assessment to identify appropriate reserves, which actualizes the scientific task of improving the appropriate methodological support for LSQ assessment. The purpose of this paper is to develop a model for assessing the quality of logistics services based on a specified list of criteria, their grouping, and the application of the mathematical apparatus of the fuzzy sets theory.
The study substantiates the expediency of using the fuzzy set method to assess the quality of logistics service and builds an LSQ assessment model that includes 12 criteria grouped into four groups: company reputation, product availability/quality, reliability/flexibility, and consumer service.
As a result of assessing the quality of logistics service, an integral indicator was obtained, which made it possible to determine the evaluations of its components: product availability/quality is rated high; reliability/flexibility – average; consumer service – good; and company reputation – poor. The obtained results indicate that such an aspect of logistics service quality assessment as company reputation needs particular attention, which confirms the modern trend of prioritizing the perception of the quality of logistics service, personal service/contact, and empathy by customers. Therefore, customers’ perception of the quality of logistics service becomes a decisive factor in the competitive struggle in the logistics services market. Moreover, it is a bottleneck in the process of increasing LSQ, which requires further research to develop appropriate management mechanisms.

The study aims to examine the impact of international trade on the sustainability of regional ecosystems in Ukraine, particularly amid the ongoing Russia-Ukraine war. The paper applies econometric modeling, factor analysis, cluster analysis, and geographic information systems (GIS) for spatial analysis. Sustainability indicators include environmental resilience indicators (carbon emissions, water quality), economic stability metrics (GDP per capita, investment in green technologies), and social sustainability factors (employment rate, access to education and healthcare). Results indicate that a 1% increase in exports enhances sustainability indicators by 0.9%, while a 1% rise in imports or demographic density reduces these indices by 0.94% and 0.75%, respectively. Cluster analysis identifies five groups of regions with varying ecological resilience, revealing critical vulnerabilities in southern and eastern Ukraine where resilience indices are below 0.5. War actions exacerbate these issues, causing infrastructure destruction, soil and water degradation, and pollutant emissions ranging from 152.5 to 16,311.4 thousand tons. Recommendations include scaling up environmental protection investments by 20% (from the current 5,965–165,228 thousand UAH) and integrating sustainability standards into international trade policies to harmonize economic activities with environmental management in crisis and post-war recovery contexts.