Tetiana Vasylieva

This paper is devoted to providing affordable housing as a significant factor in public health management, inclusive growth, and SDG. The purpose is to empirically prove changes in the system of country’s population health care depending on the level of providing affordable housing. The empirical base includes time series and panel data for 27 EU countries during 2011–2019. Due to correlation analysis (Shapiro-Wilk testing, Spearman or Pearson correlation, lags in time), regression analysis, and building a dynamic panel estimation model with Sargan testing in STATA, the study empirically confirmed and formalized the impact of affordable housing funding on changes in the system of country’s population health care. In particular, the study found the dependence between overcrowding level and the share of homeowners with mortgages (a decrease of overcrowding level by an average of 0.61% with a time lag of 2 years due to an increase by 1%); the share of tenants on concessional terms/free (0.41% with a time lag of 3 years); and the share of public spending on housing development (0.25% with a time lag of 3 years). The direct relationship between the overcrowding and mortality from dangerous diseases (tuberculosis, AIDS, viral hepatitis, mental and behavioral disorders, diabetes, pneumonia) was also revealed. Public spending on housing under social protection programs (subsidies, etc.) proved to be the least effective. Preference should be given to the development of affordable mortgage lending (faster and greater effect). Generally, it impacts public management decisions in the health care system, social, and housing spheres.

Acknowledgments
The study was funded by the Ministry of Education and Science of Ukraine and performed the results of the project “Economic and mathematical modeling and forecasting, development of methodological and methodological foundations for creating a roadmap for reforming the health care system in Ukraine, taking into account behavioral, social, economic and legal determinants” (Agreement БФ / 24-2021).
This study received funding under the research subsidy of the Department of Applied Social Sciences of the Faculty of Organization and Management of the Silesian University of Technology for the year 2022 (13/020/BK_22/0072).

The stable functioning of the public finance system requires a rational regulatory apparatus. The central bank occupies a special place in this system. Science and practice prove that the central bank’s political and economic independence determines its effectiveness. Thus, it is crucial to determine the prerequisites for ensuring its independence. The study aims to assess the influence of governance quality on the central bank’s independence, considering the variance of the socio-political development of countries. The analysis was conducted based on 53 countries. Panel regression modeling with random effects was chosen as a research method. The analysis approach involves calculations for the groups of countries that differ in social and political development parameters according to the following criteria: the initial level of the central bank independence; level of human development; political rights freedom; level of civil liberties; and political regime.
Socio-political factors significantly affect the central bank’s independence in the following conditions: a high initial level of independence of the central bank, a high level of human development, and an average level of political and civil freedom. At the same time, the governance quality ensures the growth of the central bank’s independence regardless of the countries’ political regime. Three factors have the most significant influence on ensuring the independence of the central bank, namely “government efficiency,” “quality of regulation,” and “rule of law.”

Trust in public services is a driving force of socio-economic development. It ensures effective dialogue between citizens and government and becomes especially relevant in the digitalization. The lack of trust in the public sector can make reforms ineffective and the achievement of the goals of the Ministry of Digital Transformation within the framework of the State Strategy for Regional Development of Ukraine until 2027 in question. For this reason, marketing tools in public services should be directed toward achieving greater trust in those services and the government. This paper analyzes the current research on public sector marketing and its role in building trust as a foundation for the country’s digital development. Implementing multi-level bibliometric (Scopus tools), network (VOSviewer), and comparative (Google Trends) analysis, this study traces the development of marketing research on the process of public services delivery transformation from traditional to digital. 922 studies published between 1968 and 2022 were analyzed. The results show that public sector marketing is a multidisciplinary field of scientific research that is actively developing. Cluster analysis demonstrated that its modernization and the relationship between marketing in services and consumer behavior are the smallest and newest spheres of research. Researchers consider relationship marketing the principal mechanism for building trust in the public sector. This study found little research on the impact of marketing tools on consumers’ trust in public services. The comparative analysis confirmed the hypothesis of the need to change marketing tools due to the massive shift from offline to online services.

Acknowledgment
The authors acknowledge the funding in terms of the projects “Simulation modeling of the trajectory of the impact of behavioral attractors on macroeconomic stability: the role of transparency and public trust (0121U100469)” and “Modeling mechanisms for de-shadowing and de-corrupting the economy to ensure national security: the impact of the financial behavioral patterns transformation (№ 0122U000783)”.

The most significant problems in financing the public health system in Ukraine are the permanent deficit of public spending on medicine and the shallow development of the voluntary health insurance market. The aim of study is the search of optimal interactions between stakeholders in the system of relations “state – insurance companies – households” in the context of voluntary health insurance. The study hypothesizes that households can become more active participants in health insurance only if their average monthly income reaches a certain threshold level. It is calculated based on the results of simulation games using the Brown-Robinson iterative method. According to the simulation results, this threshold level is only 7% higher than the actual value of the average monthly income of Ukrainian households during the analysis. At the same time, under this condition, the state in Ukraine will be able to transfer part of the financial burden of compensating healthcare costs to insurance companies. According to the calculations made with the help of the game theory toolkit, with the maximization of insurance payments to the population under health insurance contracts, the burden on public health financing in Ukraine could be reduced by 67.7%. The paper was conducted on the data of the ten most potent insurance companies of Ukraine as of 2021 (it is they who accumulate the lion’s share of household insurance premiums), that is, before the start of a full-scale war between the Russian Federation and Ukraine. The obtained results can be used both by insurance companies during the management of insurance premiums and payments and at the level of state management of costs in the field of public health.

Acknowledgment
This study was undertaken as a part of the research projects granted by the Ministry of Education and Science of Ukraine: “Socio-economic recovery after COVID-19: modeling the implications for macroeconomic stability, national security and local community resilience” (registration number 0122U000778); “The impact of COVID-19 on the transformation of the system of medical and social security of population: economic, financial-budgetary, institutional-political determinants” (0122U000781).

The purpose of this study is to substantiate the theoretical provisions on the accounting support for sustainability reporting and develop practical recommendations for improving the mechanisms for generating fragments of non-financial reporting based on accounting data. The study is conducted on the example of Ukraine. The paper provides a bibliometric analysis of scientific publications on the reporting in the field of sustainable development. Generalizing the results of the content-context block of the bibliometric analysis allowed identifying seven clusters. In the context of the study, the most relevant is the fourth cluster, which reflects the relationship between sustainability reporting and accounting. To create an effective mechanism for building sustainability reporting, a five-step sequence of actions based on accounting data was proposed, and tables were created to simplify the search for the necessary information to fill out fragments of a sustainability report and assess social and environmental security based on accounting data.

The purpose of this study is to ground the causality, its character, and power between economic growth and housing spending within government social protection to strengthen poverty reduction. The study is conducted on a sample of 27 EU countries for 2012–2021 according to the following indicators: government expenditure on housing within social protection, government expenditure on housing development, and GDP per capita growth. Correlation analysis revealed the relationship between the variables. The paper employed time lags with the most significance based on Pearson and Spearman correlation coefficients depending on normal data (Shapiro-Wilk test). The causal analysis determined which of the studied indicators is the cause and consequence of established dependence based on the results of the Granger test. Calculations are made in STATA software. It is confirmed that government expenditure on housing within social protection influences GDP per capita growth in 14 countries (the highest impact is in Greece and Spain) and government expenditure on housing development – in 17 countries (the biggest influence is in Romania, the Slovak Republic, Ireland, and Lithuania). It is also emphasized that government expenditure on housing development influences economic growth more significantly and with higher strength than government expenditure on housing within social protection. The obtained results can be useful in further research and government decision-making in social and economic policy, particularly regarding the expediency of increasing government spending for affordable housing and its development according to social protection programs, poverty reduction, and inclusive economic growth.

Acknowledgments
The study is funded by the Ministry of Education and Science of Ukraine (No. 0122U000781) and the Vega Agency (No. 1/0638/23).

In the conditions of the war of russia against Ukraine, which began on February 24, 2022, Ukrainian universities are playing roles that were not characteristic of them in peacetime. To the greatest extent, this concerns the university’s third mission, serving society and responding to its urgent needs. The purpose of this study is to identify and characterize new meaningful directions for implementing the third mission of the university in the conditions of war and post-war reconstruction. The study uses quantitative and qualitative bibliometric analysis combining various methods, in particular, quantitative and dynamic analysis of publications and citations, keyword analysis, cluster analysis and content analysis of publications.
The study’s results proved the lack of conceptual studies devoted to the role of universities in the war and post-war reconstruction. The main clusters of implementing the third mission of universities and the existing and potential areas of activity of Ukraine’s universities during the war and post-war reconstruction that belong to them were determined. In conclusion, it is substantiated that a new dimension of the mission of universities is being formed, which is at the stage of its formation and needs time for the necessary transformations. Depending on the consequences of the war in Ukraine, it can be a separate cluster of the third mission of universities, and the selection of a new fourth mission of universities, dedicated to peacebuilding and the role of the university during the war and post-war recovery.

Acknowledgment
Yuriy Petrushenko gratefully acknowledges support from the Kirkland Research Program. The research
was supported by the Ministry of Education and Science of Ukraine (No. 0121U109553).

In order to set economic policy goals, it is important to understand the difference between adult education and lifelong learning, and how much research on SDG 4 combines lifelong learning and economic policy. The purpose of the article is to determine the main directions for justifying the lifelong learning system development, including for achieving sustainable development goal 4 (SDG 4). Based on scientific research data from the Scopus database using the VOSviewer software, this article analyzed the theoretical foundations for substantiating the temporal and geographical interrelationships of the categorical-conceptual system of such terms as “SDG 4”, “adult education”, “lifelong learning” and “economic”. This made it possible to identify the main trends in scientific research and cluster directions of international research on the relationship between adult education, lifelong learning and economic policy. The following trends were obtained: adult education as a driver of economic development; as a social phenomenon and as a source of innovation. The following clusters were identified: adult education as a part of life-long education; adult education under the influence of physical and age-related changes; adult education as part of professional education; the learning process, which is not related to professional activity. As a result of the analysis, an insufficient level of attention among scientific studies devoted to adult education within the framework of SDG 4 was revealed. The article confirmed the need for economic policy to support the lifelong learning system, as well as the difference between the concepts of adult education and lifelong learning.

Acknowledgment
The educational outcomes in this publication were created with the support of the EU Erasmus+ program within the framework of projects ERASMUS-JMO-2021-HEI-TCH-RSCH-101048055 – «AICE – With Academic integrity to EU values: step by step to common Europe» and ERASMUS-JMO-2022-HEI-TCH-RSCH-101085198«OSEE – Open Science and Education in Europe: success stories for Ukrainian academia». This study was funded by the grant from the Ministry of Education and Science of Ukraine “Modelling educational transformations in wartime to preserve the intellectual capital and innovative potential of Ukraine” (registration number 0123U100114). “Convergence of economic and educational transformations in the digital society: modeling of the impact on regional and national security” (state registration number 0121U109553).

This study aims to examine whether the labor productivity of the US population directly depends on public or private insurance coverage of people, employment level, life expectancies, spending on the public health system as a percentage of GDP, and spending on the public health system in natural terms.
Empirical testing was carried out on the USА statistical data for 1987–2021 using a regression model with the fitting procedure backward stepwise selection (in Statgraphics software), and a multivariate adaptive regression spline MARS (using Salford Predictive Modeler software). The research hypothesis was confirmed for only two indicators: life expectancies and spending on the public health system in natural terms. Their impact on labor productivity appeared to be directly proportional. As an indicator, spending on the public health system has a greater impact on the change in productivity (0.0058%), whereas life expectancy has a lesser effect (0.0047%). The study showed that the MARS model provides more objective and accurate results compared to the regression model with the fitting procedure – backward stepwise selection. This conclusion is based on a comparison of real data modeled by both methods. The study proved that labor productivity in the USA grew yearly from 1987 to 2021 (the constant term in the MARS model’s regression equation is +0.48428). To calculate the specific values of labor productivity for each year, a model was developed depending on the optimal basic functions (automatically generated by the MARS model depending on the current values of life expectancies and spending on the public health system in natural terms).

Acknowledgment
This study is funded by Department of Applied Social Sciences of the Faculty of Organization and Management of the Silesian University of Technology for the year 2023 (grant number 13/020/BK_23/0081).

This study examines the interconnections between transformations in the education sphere, migrations waves, and labor market in 2000–2021 based on a panel data set for 14 Central and Eastern European countries (7 – former members of the Council for Mutual Economic Assistance; 5 – former republics of the USSR, and 2 – former republics of Yugoslavia). Statistical data were collected from the World Bank, the Organisation for Economic Cooperation and Development, and the International Labour Organization databases. To describe this interconnection, a pool of parameters was formed. Those that cause the greatest variability were selected using exploratory factor analysis: for education – the number of teachers and students in higher education and public spending on education; for migration – the net migration flow, personal remittances sent and received; for labor market –unemployment rate and the share of highly educated people among the employed. Confirmatory factor analysis identified the most influential determinants: for education – the number of students in higher education; for migration – paid personal remittances; for labor market – unemployment rate. The covariance analysis demonstrated a robust direct correlation between education and migration (positive shifts in the education sector serve as a catalyst for pursuing superior employment opportunities or continuing education abroad). A relatively weak direct correlation was between education and the labor market (a more highly educated workforce has only a limited impact on the structure and dynamics of the labor market). Finally, a moderate inverse correlation was between migration and the labor market (deteriorating labor market conditions give rise to migration waves).

Acknowledgment
This study is funded in terms of the projects “Business-Education-Science” Coopetition: Institutional and Economic Models of Innovation Transfer for National Security and Sustainable Development (№ 0122U000772) and “Modelling educational transformations in wartime to preserve the intellectual capital and innovative potential of Ukraine” (№0123U100114).

The structure of the higher education market in 2012–2021 in 38 European countries was analyzed using concentration levels and Herfindahl-Hirschman indices based on the number of higher education institutions and their share in the QS World University Rankings, and the number of students. This market in 2021 has a low concentration: the 3 countries with the largest number of higher education institutions (Germany, Ukraine, France) covered about 36% of the market in total; the 3 countries with the largest number of universities in the QS (United Kingdom, Germany, Italy) – 5%; the 3 countries with the largest number of students (Germany, France, United Kingdom) – 37%; and the 3 countries with the largest number of foreign students (United Kingdom, Germany, France) – 5%. Using parametric and non-parametric comparison tests, it was found that although the number of higher education institutions and students does not generally depend on the population’s income level, the number of universities ranked in the QS and foreign students does. The correlation analysis revealed that GDP and GNI, population, and separately the employment and unemployment rates (for ranked universities and foreign students) are important factors that determine the uneven structure of the higher education market. The identified factors formed the basis for clustering countries using Ward’s hierarchical method, which revealed the clear existence of 3 clusters: the smallest of them accumulates the 4 largest European economies with the most ranked universities; the largest (24 countries) is quite diverse, which indicates relatively equal opportunities in the market and its unification.

Acknowledgment
Tetiana Vasylieva and Artem Artyukhov thank project 0122U000772, and Nadiia Artyukhova thanks project 0124U000545 for carrying out their part of this research.

During the pandemic and russia’s war against Ukraine, higher education shifted to hybrid and distance learning, with some universities forced to adapt or relocate from occupied territories. This article analyzes the institutional, spatial, and financial aspects of Ukraine’s higher education market (1990–2023), focusing on financial data from 2020–2023 across 24 regions and Kyiv, excluding occupied territories. The calculated results based on concentration levels and the Herfindahl-Hirschman index for the number of educational institutions, students, and postgraduate students showed that the higher education market is highly competitive, with an uneven geographical distribution between regions. The analysis of the level of concentration of financial resources among higher education institutions, calculated based on state funding, showed that the distribution of financial resources among universities is relatively even (in 2023, the 20 largest higher education institutions accumulated more than 43.5% of total state funding). The share of state resources aimed at developing the scientific potential of higher education institutions decreased for the 20 largest higher education institutions from 58% in 2020 to 55% in 2022. Non-parametric correlation analysis revealed a low correlation between the amount of general funding for higher education institutions and the amount of revenues to the special fund for research, which indicates insufficient support and prioritization of the scientific sector in the country. These conclusions can be used in implementing the reform (balancing and optimization) of the existing educational network in Ukraine, which has been actively pursued in recent years.

As cities increasingly adopt smart technologies and seek to foster innovation-driven economies, it is vital to understand how smart city development relates to the strength of local startup ecosystems. This study investigates whether a statistically significant relationship exists between a city’s performance in the smart city ranking and the strength of its startup ecosystem. The study employed available data from the Global Startup Ecosystem Report (by Startup Genome) and the Smart City Index (SCI by the IMD World Competitiveness Center). A balanced panel regression analysis was conducted on a dataset comprising 77 cities across the years 2020, 2021, and 2023 (2022 is excluded as the SCI was not published). The findings reveal that the Random Effects model yielded statistically significant results, indicating a weak (R² = 25.63%) but significant inverse relationship between SCI and startup ecosystem development, which means cities that rank higher on smart city metrics tend to show lower levels of startup ecosystem performance. This counterintuitive result challenges the assumption that technologically advanced cities automatically provide fertile ground for entrepreneurial activity. One possible explanation is that smart cities, dominated by large tech players and rigid governance structures, may present entry barriers for emerging startups. High operational costs, regulatory constraints, and a focus on large-scale infrastructure projects may disincentivize startups from localizing their innovations within these environments. Although the R² suggests that other variables beyond the smart city ranking influence startup development. This study highlights the need for urban policies that actively integrate startup-supportive mechanisms into smart city strategies.

This study empirically examines the cross-border environmental and health impacts of mineral fertilizer use in European countries by applying spatial panel models. Specifically, it evaluates how nitrogen and phosphate fertilizers affect public health expenditures and water quality within national borders and adjacent countries. To accurately capture transboundary influences, the analysis uses a spatial weights matrix based on shared land borders constructed from geospatial data (Natural Earth shapefiles), enabling the assessment of spillover effects between neighboring countries. The models cover the timespan 2006–2021 for 29 European nations, except those that do not have common land borders (island countries), with available and comparable data. The results confirm significant spatial effects. The spatial lag model revealed strong direct and spillover effects for health expenditure, particularly for nitrogen and pesticide use, indicating that increased agricultural intensity in one country can raise health costs in neighboring states. Phosphate and potash use were associated with reductions in health expenditure, though the interpretation may reflect regional differences in environmental management. In contrast, the spatial error model best explained unsafe drinking water outcomes, highlighting the role of unobserved, spatially correlated environmental pressures. Nitrogen and pesticide use were linked to increased water contamination, while phosphate showed a strong but context-dependent negative association.

As health systems worldwide increasingly focus on mitigating the burden of non-communicable diseases, the strategic role of insurance schemes in facilitating early detection and preventive care, thereby reducing the substantial costs associated with advanced-stage treatment, has become a critical area of policy and research attention. This study aims to evaluate the impact of various health financing models, specifically voluntary, compulsory, and social insurance, on the burden of cardiovascular diseases and neoplasms, measured by Disability-Adjusted Life Years (DALYs), across working-age and older populations. The analysis is based on unbalanced panel data from 51 countries covering the period 2000–2021, drawing from the Global Burden of Disease database for DALY rates and the OECD and WHO Global Health Expenditure Database for health financing indicators. Fixed and random effects panel regression models with clustered robust standard errors were employed to estimate the associations. Results show that voluntary private insurance significantly reduces DALY rates from cardiovascular diseases, by approximately 19-28%, among working-age (15-49) and older adults (50-69). Compulsory and social insurance models also exhibit protective effects, but of smaller magnitude. Government health financing schemes similarly correlate with improved outcomes. In contrast, enterprise-based financing is positively associated with higher DALY rates, especially in older age groups. Insurance schemes demonstrate weaker and more inconsistent associations for neoplasms, with compulsory insurance and government schemes showing the most stable links to reduced burden among older adults.

The effectiveness of anti-money laundering systems is vital for national economic resilience, especially in transitional economies facing wartime challenges, such as Ukraine. This study aims to identify key managerial determinants of the effectiveness of Ukraine’s anti-money laundering and counter-terrorist financing (AML/CFT) system and to develop evidence-based recommendations for improving its performance. Based on data from Ukrainian national institutions for the period 2011–2023, the study employs principal component analysis and multiple linear regression to evaluate 44 statistical indicators related to institutional workload, procedural efficiency, and inter-agency coordination. The findings reveal that a small set of indicators, including the volume of suspicious transaction reports from non-banking institutions, the number of dossiers compiled, and the backlog of unresolved judicial cases, explain over 70% of the system’s output variance. The final model exhibits high explanatory power (R² = 0.963), underscoring the importance of prioritizing high-impact operational metrics. The study concludes that targeted procedural reforms and enhanced coordination between institutions can significantly strengthen AML/CFT outcomes in fragile and reforming contexts.

Acknowledgment
This study was supported by the Ministry of Education and Science of Ukraine (project No. 0123U101945 – National security of Ukraine through prevention of financial fraud and money laundering: war and post-war challenges).

Type of the article: Research Article

Abstract
This study investigates the structural relationships between educational and scientific regulatory interventions and socio-economic development in countries affected by armed conflict and political instability, using the framework of Sustainable Development Goals (SDGs), specifically SDG 4 (Quality Education), SDG 8 (Decent Work and Economic Growth), and SDG 9 (Industry, Innovation and Infrastructure). Rather than focusing on regulatory interventions in a narrow administrative sense, SDG 4 is conceptualized as a reflection of national efforts to improve access to and quality of education, including institutional reforms, policy initiatives, and capacity-building measures in post-conflict settings. The analysis covers 16 countries affected by conflict and instability across Eastern Europe, including Ukraine; the Balkans (Albania, Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia, Serbia, Slovenia); the Middle East (Israel, Jordan, Lebanon, Syrian Arab Republic, Turkey); and the South Caucasus (Armenia, Azerbaijan, Georgia), using data from 2011 to 2020. Employing multivariate confirmatory factor analysis (CFA), the study reveals statistically significant and conceptually meaningful covariances between the selected SDGs. The strongest relationship is observed between SDG 8 and SDG 9, underscoring the interdependence of economic growth, industrial development, and innovation. Moderate but significant correlations between SDG 4 and both SDG 8 and SDG 9 highlight the foundational role of education in enabling socio-economic recovery and technological advancement. Key indicators such as primary school completion, secondary and tertiary enrollment, employment in industry and services, and high-tech value-added production serve as measurable proxies for these dynamics. The findings emphasize the importance of aligning education policy with broader development strategies to support resilience and sustainable growth in fragile contexts.

Acknowledgments and research funding
This research was funded by the European Union grants “NextGenerationEU through the Recovery and Resilience Plan for Slovakia” (No. 09I03-03-V01-00130) and “Immersive Marketing in Education: Model Testing and Consumers’ Behavior” (No. 09I03-03-V04-00522/2024/VA). This research was also prepared as part of project 0124U000545.

Type of the article: Research Article

Abstract
The banking and financial system of the countries of the world is constantly developing, but at different rates and ways, given their differences in the levels of economic, financial, and innovation development. The purpose of this article is to identify factors that link upper-middle- and high-income countries in terms of banking ecosystem digitalization, based on cluster analysis. The research sample includes 40 countries – 20 top-performing upper-middle-income and 20 high-income economies – based on the 2023 ICT Development Index. The analysis is based on 15 standardized indicators characterizing digitalization in the banking ecosystem, sourced from the International Monetary Fund, the World Bank, and the International Telecommunication Union. These indicators cover ICT development, AI readiness, cybersecurity, GovTech maturity, financial development, banking access, and digital transaction activity. Data standardization was performed in Stata (v19.5) using the built-in function to create new variables with a mean of 0 and a standard deviation of 1. Cluster analysis was conducted using the k-means method in Statgraphics (v19), with silhouette scores computed in Python to determine the optimal number of clusters. Cluster analysis revealed four distinct country groups, demonstrating that similarities in banking ecosystem digitalization transcend income levels. Key convergence factors include ICT development, GovTech maturity, mobile banking adoption, and AI readiness. Some upper-middle-income countries exhibit digitalization patterns comparable to high-income economies, highlighting the role of strategic investment and policy, rather than income, as primary drivers of digital financial advancement.

Type of the article: Research Article

Amid growing global challenges such as technological change and socio-economic uncertainty, fostering youth creativity has become vital for sustainable development. In Ukraine, open science provides a promising pathway to develop key competences like creativity, critical thinking, and collaboration, essential for navigating ongoing social and educational transformation. This study aims to investigate the relationship between Ukrainian young people's engagement with open science practices and their creative development across academic disciplines and educational levels. Drawing on data from a nationwide survey of 2,250 Ukrainian university students (Bachelor, Master, and Ph.D.), this study applies non-parametric methods to analyze how young people engage with open science. The results show that engagement with open science practices among Ukrainian students varies significantly by both level of education and field of study. Ph.D. students report the highest frequency of participation (median = 4.0 on a 5-point scale), significantly more than Bachelor's and Master's students (Kruskal-Wallis χ² = 44.92, p < 0.001). They also rate mentorship and collaborative research as more effective for creativity (e.g., mentorship: p = 0.00008 between Bachelor and Master levels). Disciplinary differences are most evident in the perceived effectiveness of webinars (χ² = 31.69, p = 0.0002) and collaborative research (χ² = 23.34, p = 0.0055), with students from engineering and life sciences showing the highest appreciation. These differentiated patterns confirm that the creative development potential of open science is powerfully shaped by students’ academic stage and disciplinary background.

Acknowledgment
This research was funded by the grant VEGA 1/0271/23 “Sustainable renewal of spa tourism in the Slovak Republic in the context of the impacts of civilisation crises”. This research was also prepared as part of projects 0124U000545 and ERASMUS-JMO-2022-HEI-TCH-RSCH-101085198.