The paper investigates the relationships between economic, social, and environmental dimensions of sustainable development. GDP growth represents the main economic dimension, greenhouse gas (GHG) emissions and renewable energy consumption the environmental dimension, and corruption the social dimension of sustainable development. The investigation of these relationships is based on the concept of the Environmental Kuznets Curve hypothesis about the non-linear relationship between economic growth and environmental pollution. The authors used the panel data of EU countries and Ukraine for 2000–2016 years from the Eurostat database. The obtained results confirmed the Environmental Kuznets curve hypothesis for the EU and Ukraine. All the indicators were statistically significant at 1% and 5% levels. The findings proved that increasing renewable energy (RE) by 1% led to a decline of GHG in the interval (0.166103, 0.220551), and аn increase of the Control of Corruption Index by 1% provoked a decline of GHG by 0.88%. The conducted study enabled the authors to conclude that Ukraine needs to increase the GDP level per capita given the economy diversification and via the introduction of more effective and “clean” production technologies.

This paper investigates the impact of renewable energy sources (RESs), CO₂ emissions, macroeconomics, and the political stability in a country on the Gross Domestic Product (GDP). The authors analyse the dynamics of RESs use, CO₂ emissions, and GDP development and also test the following hypotheses: (1) The country’s economic growth is related to the energy consumption, in terms of both human resources and capital; (2) the share of the renewable energy consumption of the total energy consumption has a positive impact on the economic growth; and (3) the share of the renewable energy consumption of the total energy consumption is unrelated to the economic growth. To test the above hypotheses, the authors use the modified Cobb-Douglas production function, which also considers RES production volumes, CO₂ emissions, and economic growth. The study employs data between 1995 to 2015 from the candidate and potential candidate countries for the EU membership. The data are drawn from the World Bank and Eurostat. The analyses entail panel unit root tests, Pedroni panel cointegration tests, fully modified OLS (FMOLS), dynamic OLS (DOLS) panel cointegration techniques, and the Vector Error Correction model (VECM). The findings confirm the relationship between RESs, CO₂ emissions, and the GDP. For the EU countries, RESs as human resources and capital have an impact on the GDP. Moreover, the results reveal a correction retraction when the economic growth leads to an increase in renewable energy consumption. The investigation also finds that candidate and potential candidate countries for the EU membership should foster renewable energy development. The authors conclude that developing affordable and effective instruments and mechanisms to boost the RES implementation is necessary to decrease the anthropogenic impact on the environment (in particular, decreasing CO₂ emissions) without any attendant reduction in the economic growth.

The article substantiates the existence of convergence processes in the field of digitization of countries, taking into account the number of Internet users; people with advanced skills; and indicators of infrastructure (network coverage, population covered by at least a 3G mobile network, population covered by at least a 4G mobile network), access (access to ICT at home, active mobile broadband subscriptions, fixed broadband subscriptions), enablers (fixed broadband over 10 Mbps, mobile data and voice basket, high consumption) and barriers (improved broadband access from 256 kbps to 2 Mbps and from 2 Mbps to 10 Mbps mobile data and voice basket, low consumption) of digital development. The methodological basis for determining the sigma convergence of digitization processes is the coefficient of variation. The values of the coefficient of variation confirmed the high level of convergence between the studied countries in terms of the degree of use of the Internet for conducting digital transactions. The developed econometric model, which describes the influence of statistically significant integral indicators of the national cybersecurity level, ease of doing business, and the anti-money laundering index on the country’s digital development level, made it possible to determine the average trend of dependence on the level of digital development. One hundred four countries were considered for the analysis. The conducted study of the impact of digitalization on economic transformations based on developed quantile regressions made it possible to analyze exactly how the level of digital development for countries with a high level of digitalization and for countries with a low level of digitalization development depends on the value of the national cybersecurity indicator and the ease of doing business, and which countries have the least resistance to the risk factors of their involvement in fraudulent schemes for the purpose of legalizing criminal income.

The article aims to identify the latest trends in research on renewable energy, sustainability and the environment. A total of 92,873 publications from 123 Scopus sources for 2020–2021 are compared using the scoping review method. The results show that the most cited works in this sample are those by authors from the Asian region. The research of these authors focuses on the security, efficiency and reliability of separate elements in energy systems. Besides, the paper considers the problems regarding COVID disease along with the renewable energy sources, perovskite and organic solar panels, nanostructured materials and high energy density. Finally, the paper analyses applications of computer science methods in research on renewable energy, sustainability and the environment. The findings evidently show that recent advancements in computer science methods were not extensively used in the discussed research domain and give a great room for novel strategies of prognosing, simulation and processes optimisation.

This article investigates the relationship between Sustainable Development Goal 4 (SDG 4), academic integrity as its part, and artificial intelligence (AI) through a bibliometric analysis, assessing whether this intersection represents a clash or win-win cooperation. SDG 4 aims to ensure equitable access to quality education, while AI technologies have the potential to enhance educational practices but demote academic integrity. By analyzing a comprehensive body of the literature, this study identifies key trends and thematic areas where AI is applied in educational settings, particularly concerning maintaining academic integrity. The findings reveal a growing body of research highlighting AI’s role in personalizing learning experiences, improving educational accessibility, and supporting educators’ teaching methodologies. However, challenges such as ethical considerations, data privacy, and the digital divide are also addressed, indicating potential conflicts that need to be navigated. Ultimately, this analysis suggests that while there are significant opportunities for synergy between AI and SDG 4, the management of careful implementation and policy frameworks is essential to ensure that AI serves as a tool for promoting inclusive and sustainable education rather than exacerbating existing inequalities. AI transforms science management by enhancing data analysis, streamlining research processes, and improving decision-making, ultimately leading to more efficient and effective scientific research and innovation. The findings reveal that while AI can facilitate personalized learning and enhance educational accessibility, it also poses challenges related to academic misconduct, such as plagiarism and the misuse of AI-generated content. This duality highlights the need for educational institutions to develop robust frameworks that leverage AI’s capabilities while safeguarding academic integrity. The article concludes that a collaborative approach, integrating AI into educational practices with a strong emphasis on ethical considerations and integrity, can lead to a synergistic relationship that supports the goals of SDG 4. Recommendations for future research and practical implications for managers, educators, scientists, and policymakers are also discussed, emphasizing the importance of fostering an educational environment that embraces innovation while upholding ethical standards.

Even now, in the times of advanced digitization, the planning and implementation of many organizational measures remain human-driven. Corresponding to a global trend of application of artificial intelligence in all areas of life, it has received more attention in the last few years and garnered emerging clusters of research in usage of this technology for organizational issues. Some companies already offer tools that support different management tasks in the area of organizational development, but they are not holistic. According to the google trend analysis of the search for artificial intelligence, the inquiry to this topic continues increasing. The purpose of the described investigation was to identify the academic trends in research interaction between such scientific fields, as Artificial Intelligence, Organizational Management, Organizational Development, Organizational Change, and Organizational Culture using bibliometric and network publication analysis. In order to achieve this purpose, we systematically analysed 191 publications between 1983 and 2020 as well as cited and citing publications. The findings of this study provide important conclusions of the current research state. The insightful results are presented in the form of critical review and frame the body of knowledge.