Companies and countries have needed to adapt their activities to the consequences of the Russian war in Ukraine. The analysis in this article shows that both the Russian war in Ukraine and the subsequent trade restrictions have become a powerful trigger, significantly increasing the level of inflation and exacerbating the existing issues of economies. As a result, the confrontation between the West and Russia has greatly escalated, which will have a long-term, large-scale negative impact on most European companies and economies. There could also be a lasting restructuring of world trade. The article notes that not only the end date of the war in Ukraine may be important for business and economies, but also which of the trade and financial restrictions can be lifted from Russia, and when. The article also makes recommendations that may help company leaders plan, in a timelier and more accurate fashion, the changes necessary to maintain company sustainability.

This article examines a critical and timely issue in higher education: university students’ attitudes toward the ethical use of generative artificial intelligence (GenAI) in learning. Addressing a notable gap in quantitative research, the study investigates how students perceive the ethical dimensions of GenAI use through a survey of 760 students across three universities in two European countries. Analyses were conducted across national and institutional contexts, as well as by demographic and academic variables, including gender, age, mode of study, type of program, and field of study. The investigation aimed to assess how various student groups evaluate the ethical considerations of GenAI use in their academic work. To this end, it employed a combination of descriptive and inferential statistical methods. Findings were interpreted through the frameworks of virtue ethics and constructivist learning theory. Results indicate that students, on average, assign only moderate importance to the ethical aspects of GenAI use a concerning outcome given the increasing relevance of ethics in technology-enhanced learning. Furthermore, students’ ethical assessments were significantly lower than those of their instructors at the same institutions. The study concludes that students tend to undervalue ethical concerns related to GenAI, and that this tendency is shaped less by external or demographic factors than by internal institutional factors, including university culture and norms.

The article examines the issue of labour share convergence between Western Europe (EU15) and Central and Eastern Europe (EU11). The results of our research show that for the period of 2009–2018, the convergence of labour share between the EU11 and the EU15 at the aggregate level was almost 40%. At the sectoral level, convergence of labour share between the EU11 and the EU15 occurred in three of the four main sectors—manufacturing, services, and construction—while there was a divergence in the trade sector. At the sectoral level, the highest level of convergence occurred in manufacturing—over 89.7%. In the service sector, the convergence of labour share was almost 45%, but this was mainly due to the fact that in the information and communication industry, the convergence was almost 87.8%. We have determined that for a number of sectors and industries there is an inverse relationship between the level of labour share and its dynamics, which influences the convergence of labour share between the EU11 and the EU15. We also determined that during the period under review, the level of convergence of labour share between the EU11 and the EU15 was five times higher than the level of convergence of the economy and ascertained the main reasons for the labour share convergence being higher than the economy convergence.

In this paper, we consider the changes that occurred in the service exports of thirty-eight European countries in the period of 2005–2016. We have found that the existing world trend related to the growth of service exports is also present in Europe. However, the trend of the service exports’ share growth in the general volume of export is not common for all European countries. We found that higher growth rates are observed in European countries with lower levels of GDP per capita. We also discovered the presence of a strong positive correlation between growth in service exports and GDP growth, as well as between growth in service exports and GDP per capita. We also found that there is a linear correlation between the growth of service exports and the growth of GDP per capita, as well as between the growth in service exports and GDP growth. The data obtained allowed us to conclude that European countries, categorized as “Innovation Leaders” in accordance with the European Innovation Scoreboard, are not the leading countries in Europe with regard to the rates of service export growth. We also discovered that service exports in Europe are less sensitive to adverse macroeconomic effects than goods exports.

Re-exports are an important part of international trade, as they account for about a quarter of total exports, and the growth rate of re-exports exceeds the growth rate of exports. Researchers find that re-exports have a positive impact on economic growth. Despite this, in existing studies, little attention has been paid to the impact of re-exports on sectors of the economy and the direct and indirect effects of re-exports on the national economy. Based on this, the purpose of the article is to consider the impact of re-export activities on sectors of the economy and on the economy as a whole using the example of one company. The study examines the distribution of the effects of re-export companies’ activities between the national economy and foreign economies and among sectors of the economy. In addition, the value of the primary and secondary effects of the influence of the re-export company on the national economy was determined and the local multiplier value was calculated. This study identifies the main factors that influence the distribution of re-export effects between the national economy and foreign economies and among sectors and industries, as well as factors that affect the magnitude of direct and indirect re-export effects on the national economy. The local multiplier value of re-exports was also determined at 1.73.

Purpose.: This study aims to evaluate the effectiveness of using ChatGPT for a practically important but under-researched task in the scientific literature: the preliminary search and identification of potential business partners or counterparties. Design/Methodology/Approach.: An experiment was conducted where ChatGPT was tasked with suggesting ten digital marketing agencies for each of three countries - Germany, Latvia, and Poland, including links to these agencies’ homepages. The accuracy of the responses was verified. The study also compared the accuracy of responses between the latest version of ChatGPT (ChatGPT 4o) and the previous version (ChatGPT 4) connected to the Internet. Findings.: Both versions of ChatGPT were found to make a significant number of errors or inaccuracies when identifying potential business partners that met predefined criteria. Moreover, the frequency of these errors increased when searching in countries with smaller populations and economies. It was also found that the newer version, ChatGPT 4o, did not demonstrate improved accuracy compared to ChatGPT 4, which was connected to the Internet. Both versions of ChatGPT examined in the study provide a higher level of accuracy in identifying potential partners in countries with larger economies and populations. Originality / Value / Practical Implications.: This research contributes to a practical understanding of the limitations and capabilities of AI tools in identifying business partners, providing valuable information for both practitioners and researchers in the field. This study also provides a benchmark for determining the accuracy of ChatGPT in performing common and important business tasks such as preliminary search and identification of business partners. The results of the study provide a basis for future research to track the progress of language models in similar business applications. The proposed evaluation methodology can be applied to future research aimed at assessing the capabilities of language models in solving business problems.