John Soss

Russia’s open aggression against Ukraine has resulted in significant changes across all sectors of the Ukrainian economy and its financial sphere, including financial security. The paper aims to identify the impact of the primary macroeconomic determinants, i.e., military defense spending, non-performing bank loans, exchange rate, foreign debt, and state (total) reserves, on the financial security of Ukraine under martial law. The canonical correlation analysis is employed to assess the strength of the relationship between the above macroeconomic indicators and the level of the state’s financial security. It was found that the reduction of the state’s financial security level in 2022 was 63.9%, explained exactly by the changes in the above macroeconomic determinants after the start of a full-scale invasion. The study determined the degree of influence of each indicator on Ukraine’s financial security level. An increase in the level of military defense spending, non-performing bank loans, hryvnia’s devaluation, and external debt growth had a direct negative impact on Ukraine’s financial security. At the same time, an upsurge in total reserves had an indirect negative impact (through the external debt growth). The research findings confirm the necessity for effective monitoring and management of the macroeconomic indicators to maintain both Ukraine’s financial security and macro-financial stability in order to ensure its’ sustainable economic development during the postwar recovery period.

Acknowledgment
This research is financially supported by the NATO SPS Program “Security of territorial communities: evidence from the Eastern European countries”.

One of the main challenges in higher education management is the complexity of resource optimization and increasing volumes of data, which limits the efficiency and accuracy of decision-making. The application of artificial intelligence can address these issues.
The present study aims to identify the key trends, knowledge gaps, and opportunities for further research into the economic effects of using artificial intelligence and ChatGPT tools in higher education. For this purpose, a systematic literature review was conducted to identify and screen the scientific articles related to the topic of this study indexed in Web of Science and Scopus from 1986 to 2024. A total of 234 articles were selected, all demonstrating positive growth both in scholarly output and citation count. The study identified the key contributors to scientific research on this topic by region (the United States, China, and India). It concluded that the relevant research centers are still at an early stage of their development. Based on bibliometric clusters formed by co-occurrence relations, three main areas of research were defined: 1) artificial intelligence in education for decision-making; 2) process automation and digital transformation in educational institutions; 3) artificial intelligence technologies and their application in education.
The study highlights the main areas of economic effects of artificial intelligence and ChatGPT tools in higher education, including reducing administrative costs, saving time for teachers and students, and improving the quality and accessibility of educational process.

Acknowledgments
The publication is part of the research topic “Economic Basics of Technology Diffusion into the National Economy of Ukraine Considering Best International Practices” (№0124U003482).

In the context of digital transformation, the education sector needs innovative solutions to ensure continuity and quality of the learning process amidst contemporary challenges. One solution is using cloud technologies, which allow for the virtualization and replication of key institutional processes, from academic programs to campus operations. In this regard, this article aims to identify the challenges associated with the concept of cloud universities and their impact on the resilience of higher education. A science mapping analysis is conducted based on the most relevant scientific papers indexed in the international Scopus database from 2000 to 2024 using Scopus and SciVal built-in tools and the Science Mapping Analysis Tool. The results show a significant increase in the number of studies, especially within the fields of Computer Science and Social Sciences, dedicated to the use of cloud services and technology in education, with a growing focus on “digital twins”. The application of science mapping tools revealed key trends in research development, which evolved from the development and optimization of cloud infrastructure and difficulties of technological usage and the adoption of new technologies by users to the deep integration of various technologies into the educational process, exploring their reception by students and teachers, as well as the effectiveness of these initiatives. The analysis identified key challenges cloud universities face, such as the need for reliable technical infrastructure, adherence to cybersecurity standards, preparing educators and students for working with new technologies, financial costs of implementing cloud technologies, and ensuring academic integrity.

Acknowledgments
The publication was part of the Erasmus+ project “Disaster Resilience in Higher Education Systems via a Cloud University Model” (project number 2O24-1-AT01-KA220-HED-000249632).