Issue #2 (Volume 10 2026)

Type of the article: Research Article

The study aims to analyze institutional policies governing the use of generative artificial intelligence (GenAI) in Ukrainian universities and assess their regulatory maturity. Drawing on the authors’ Taxonomy of Institutional AI Policy Maturity (AI-PMT), which comprises twelve analytical dimensions, the study examines a sample of 23 publicly available institutional policy documents adopted between 2023 and 2025. The analysis combines qualitative and quantitative approaches. A directed content analysis was used to assign ordinal scores (0-2) across twelve dimensions, enabling the construction of a cumulative maturity index (0-24) for each institution. The results reveal an uneven distribution of regulatory development, with more elaborated provisions related to teaching and learning, and comparatively less developed components addressing research practices, data governance, and infrastructural support. To synthesize these patterns, an analytical typology of institutions was developed based on cumulative maturity scores, identifying three broad groups that differ in the degree of regulatory completeness and procedural specification. In parallel, thematic analysis of policy content identified recurring patterns, including the normalization of AI use in education, the emphasis on transparency and disclosure, the prevalence of precautionary approaches to data and confidentiality, and several contested provisions. Comparison with international policy frameworks suggests that Ukrainian universities broadly align with global normative trends in principles, but exhibit limited operationalization of governance mechanisms and research-related provisions. The findings highlight structural imbalances in institutional AI governance and underscore the need to further develop research-oriented regulation, institutional support mechanisms, and coordinated policy approaches.

Acknowledgment
We thank the Armed Forces of Ukraine for providing security for this work, which was made possible only thanks to the resilience and bravery of the Ukrainian Army.

Type of the article: Research Article

Lecturers’ financial well-being is an important factor influencing work motivation, teaching quality, and professional commitment in implementing the Tri Dharma of Higher Education. This study is motivated by the financial challenges faced by lecturers at private higher education institutions in underdeveloped, frontier, and outermost regions, particularly in Southwest Papua, Indonesia, which are characterized by limited income and high financial vulnerability. The study aims to examine the effects of financial stress, money attitude, financial risk tolerance, and financial socialization on financial well-being, with financial literacy as a mediating variable. Using a quantitative explanatory design, data were collected from 230 certified lecturers across eight private higher education institutions in Southwest Papua through a census approach within a defined sub-population. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). The findings show that money attitude has a positive and significant direct effect on financial well-being and financial literacy. Financial stress and financial risk tolerance significantly influence financial literacy but have no direct effect on financial well-being, while financial socialization shows no significant effect. Financial literacy significantly mediates the relationships between financial stress, money attitude, and financial risk tolerance toward financial well-being. The model explains 39.7% of financial well-being and 34.8% of financial literacy variance. These results highlight the importance of structured financial literacy programs for lecturers in underdeveloped, frontier, and outermost regions.

Type of the article: Research Article

Despite the rapid digital transformation in higher education, empirical evidence explaining how digital entrepreneurship learning contributes to human capital formation, entrepreneurial universities, and economic growth remains limited. This study investigates the role of Digital Canvas Learning (DCL), a digital-based entrepreneurship learning approach that enables students to design and test business models using an interactive Business Model Canvas. The study employs a structured survey conducted in 2024 involving 206 undergraduate and graduate students enrolled in entrepreneurship programs at universities within Higher Education Service Institutions Regions III and IX, Indonesia. The respondents were selected because they were actively engaged in entrepreneurship education, making the sample relevant for examining the outcomes of digital entrepreneurship learning. The data were analyzed using Partial Least Squares – Structural Equation Modeling (PLS-SEM). The results show that DCL has a strong and significant effect on Human Resource Development (β = 0.752; p < 0.001) and Economic Growth (β = 0.690; p < 0.001), and a significant influence on University Entrepreneurship (β = 0.337; p < 0.001). Furthermore, Human Resource Development significantly affects University Entrepreneurship (β = 0.527; p < 0.001) and Economic Growth (β = 0.273; p < 0.001), while University Entrepreneurship strongly contributes to Economic Growth (β = 0.662; p < 0.001). The structural model explains 79.4% of the variance in Economic Growth, indicating substantial explanatory power. These findings demonstrate that Digital Canvas Learning not only enhances students’ entrepreneurial competencies but also strengthens human capital development, supports entrepreneurial universities, and contributes to sustainable economic growth.

Acknowledgment
We would like to express our deepest gratitude to the Education Fund Management Institute (LPDP) of the Ministry of Finance of the Republic of Indonesia and Universitas Terbuka for the administrative and funding support and the opportunities given to the author.

Type of the article: Research Article

The purpose of this article is to evaluate the current state of collaboration between universities and businesses, identify obstacles, and propose solutions based on international experience, regional characteristics, and the challenges of Ukraine’s post-war economic reconstruction. The article examines the role of universities in smart development, using international experience and the results of an original sociological study conducted in Ukraine in 2025 as a reference point. The empirical basis includes two surveys: one of local authorities with 111 respondents and one of businesses with 300 respondents. The research methodology uses descriptive statistics and binary logistic regression to determine the factors that influence cooperation between higher education institutions (HEIs), local authorities, and businesses regarding smart and sustainable development. The results demonstrate the structurally weak integration of universities into local smart development ecosystems. The study’s originality lies in identifying the main obstacles to developing cooperation between universities, businesses, and local authorities: bureaucratic barriers, inflexibility, and outdated management systems in local authorities and higher education institutions; and a lack of initiative and incentives for cooperation among all stakeholders. The article confirms the insufficient awareness of Ukrainian universities’ role as drivers of socioeconomic development and their potential to become powerful agents of change if their innovation and entrepreneurial capacity is strengthened. The practical significance of the results is to identify areas for improving interaction and overcoming obstacles. The key to doing so is strengthening through digitalization, which will transform the participants and their internal structure, as well as all communication and interaction between them.

Type of the article: Research Article

This study examines the intricate mechanisms by which entrepreneurial purpose affects the success of small and medium enterprises (SMEs) in East Java, Indonesia, focusing on the essential roles of entrepreneurial competence, education and training. Although the psychological factors influencing entrepreneurship have been extensively studied, empirical data linking these factors to concrete business outcomes in resource-limited emerging nations remain incomplete. This study uses PLS-SEM to analyze cross-sectional survey data of 280 small and medium-sized enterprise owners and administrators. The results suggest that entrepreneurial competence and entrepreneurial intention are both strongly predicted (β = 0.714, p < 0.001) by participation in education and training. However, it does not have a significant direct effect on an SME’s efficacy (β = 0.086, p = 0.297; p < 0.001). Furthermore, entrepreneurial competence alone was insufficient to drive business success in this context. Conversely, entrepreneurial education and training emerged as a vital transformative mechanism, significantly enhancing firm performance and serving as a key bridge that converts motivational drive into measurable economic outcomes. These findings challenge the traditional assumption that intention and competence automatically lead to success, highlighting instead the necessity of structured, practice-oriented training to navigate structural market barriers. This study provides critical information for policymakers and practitioners, highlighting that the sustainable expansion of SMEs in emerging economies necessitates focused external capacity-building measures instead of only depending on individual psychological characteristics.

Type of the article: Research Article

Whether national artificial intelligence (AI) ecosystem development shapes tourism’s contribution to GDP is an open empirical question, particularly given the multidimensional nature of modern AI ecosystems and the heterogeneous reliance of countries on tourism. This study identifies which dimensions of national AI ecosystem development drive within-country changes in tourism’s direct GDP share, using panel data from 33 countries over 2017–2023. Fixed-effects estimation with clustered standard errors is applied to both the composite Stanford HAI AI Vibrancy Score and its seven constituent pillars, complemented by lagged, dynamic, and interaction specifications. The aggregate AI Vibrancy Score shows no significant within-country effect on tourism’s GDP share after controlling for macroeconomic factors (β = 0.061, p = 0.622), indicating that overall AI vibrancy alone does not measurably move tourism’s economic contribution. The pillar decomposition reveals, however, that this null result masks two significant positive drivers of tourism’s GDP share – AI-related R&D (β = 1.811, p = 0.005) and Policy and Governance (β = 0.353, p = 0.037) – both robust to alternative standard errors and two-way fixed effects. The Talent pillar exerts a significant positive effect on tourism’s GDP share with a one-year lag (β = 0.183, p = 0.025), indicating that the human-capital channel requires time to materialize. The COVID-19 pandemic reduced tourism’s GDP share by approximately 37% (β = –0.455, p < 0.001), and AI development did not moderate this decline. The findings imply that targeted AI policies – particularly in R&D and governance – can strengthen tourism’s economic contribution, while aggregate AI metrics obscure heterogeneous pillar-level effects.

Type of the article: Research Article

Education financing through the School Operational Fund (SOF) program significantly helps overcome challenges in achieving educational goals, both in terms of quantity and quality. In this context, governance mechanisms play a crucial role in evaluating the effectiveness of SOF management. This study examines how governance mechanisms – accountability, transparency, and internal control – influence the effectiveness of SOF management in public primary and secondary schools in Indonesia. Drawing on agency theory, this study addresses the limited empirical evidence on the governance of public education funds in a decentralized education system. Using survey data collected from 216 school principals across 459 public schools in Padang Pariaman Regency, Indonesia, this study applies multiple linear regression to test the proposed relationship. The sample size of 216 was calculated at 95% confidence with a 5% margin of error. The results of this study show that accountability (β = 0.187, p < 0.05), transparency (β = 0.128, p < 0.05), and internal control (β = 0.446, p < 0.05) positively affect the effectiveness of educational operational fund management (SOF). These results support the three proposed research hypotheses. The results of this study highlight the importance of governance mechanisms in mitigating agency problems in publicly funded education programs. This study expands the literature on public sector financial management by providing empirical evidence from a developing country context. It provides policymakers with practical insights to strengthen oversight mechanisms and improve the implementation of educational operational funding programs.

Type of the article: Research Article

The conversion of knowledge into organizational and market performance is a central challenge for innovation-driven economies. This study examines how innovation activity and its commercialization shape the entrepreneurial performance of knowledge ecosystems, using green and digital energy start-ups as an empirical context. The aim is to investigate the non-linear relationships among knowledge creation, knowledge commercialization, and start-up development, with particular attention to whether mismatches between innovation activity and market uptake generate diminishing returns or imitation-driven entrepreneurial dynamics. The analysis is based on a balanced panel of 37 countries over the period 2018–2023, comprising 222 country-year observations. The methodology applies TWFE with DK standard errors, complemented by quadratic specifications, turning-point analysis, and lagged models. The findings reveal an inverted U-shaped relationship between innovation commercialization and start-up activity, confirmed by negative, significant squared terms for sales of new-to-market and new-to-firm innovations in green start-ups (β₂ = −0.1588) and digital start-ups (β₂ = −0.1462), with turning points at 0.1428 and 0.0021, respectively. Funding dynamics demonstrate threshold effects: product innovation has a U-shaped relationship with early-stage digital funding (β₂ = 2.0630), while process innovation strengthens later-stage funding for green (β₂ = 1.8100) and digital start-ups (β₂ = 1.8434). The knowledge commercialization gap positively affects digital start-ups (β = 0.1111), suggesting that uncommercialized knowledge may stimulate market entry. Lagged results confirm temporal effects, with past innovation commercialization reducing digital start-up activity (β = −0.2483). Knowledge creation alone does not ensure performance growth; sustainable start-up development requires effective knowledge-to-market conversion.

Type of the article: Research Article

Artificial intelligence has become a driver of knowledge transformation, skills renewal, and institutional change, making lifelong learning increasingly important for adapting to AI-driven labor markets and societies. This study aims to examine whether national AI development indicators are associated with realized participation in education and training across different adult age groups in European countries, and to discuss what these associations may imply for lifelong learning and knowledge transfer policies. The analysis is based on a panel of 18 European countries for 2017–2024 and applies two-way fixed-effects models with country and year effects, contemporaneous, one-year, and two-year lag specifications, and Driscoll–Kraay robustness checks. The results show that the total AI Vibrancy Score is not a statistically significant predictor of participation in education and training: the contemporaneous coefficients are 0.4822 for adults aged 18-74, 0.1054 for those aged 45-54, and 0.5006 for those aged 50-74. Descriptive statistics indicate that average lifelong-learning participation declines with age, from 20.09% among adults aged 18-74 to 14.82% among those aged 45-54, and 9.34% among those aged 50-74. The lagged structural models show that AI-related R&D is negatively associated with subsequent participation, with one-year lag coefficients of −1.2310, −0.9392, and −0.8911 for the three age groups, respectively. In contrast, AI-related Policy and Government activity has a positive two-year lagged association for adults aged 18-74 and 45-54, with coefficients of 0.6064 and 0.7346. This suggests that policy-related AI development, rather than national AI development alone, may be more relevant for observed adult participation in education and training.

Acknowledgments
This research was funded by an EU grant “Immersive Marketing in Education: Model Testing and Consumers’ Behavior” under project No. 09I03-03-V04-00522/2024/VA and by the Ministry of Education and Science of Ukraine “Modeling and forecasting of socioeconomic consequences of higher education and science reforms in wartime” (No. 0124U000545).

Type of the article: Research Article

This study is relevant given the growing reliance of post-Soviet higher education systems on bibliometric indicators to evaluate academic performance and allocate research funding. The purpose of the study is to examine whether generational cohorts of productive scientists in Kazakhstan differ in their publication patterns under the transition to bibliometric-based research evaluation. The study is based on a bibliometric analysis of 220 highly productive authors across 22 subject areas using Scopus and SciVal data for 2018–2023, with correlation analysis applied across three age cohorts (under 40, 41-55, and 56+). The results reveal significant generational differences in publication strategies. Among researchers under 40, a very strong correlation is observed between total publications and Q1 journal output (r = 0.95), and between publication activity and international collaboration (r = 0.98). This cohort also demonstrates higher publication activity in internationally co-authored papers and stronger alignment with formal bibliometric indicators. In contrast, the 41-55 cohort shows the weakest relationship between publication output and Q1 publications (r = 0.40), lower levels of leading authorship, and less pronounced integration into international publication networks. Researchers aged 56+ occupy an intermediate position but demonstrate the highest share of publications in journals later excluded from Scopus, indicating greater exposure to potentially problematic publication practices during earlier stages of Kazakhstan’s research system transformation. The findings suggest that highly productive scientists from different generational cohorts respond differently to formal bibliometric evaluation requirements. The presence of publications in journals later excluded from Scopus across all cohorts suggests that bibliometric-based evaluation systems may encourage strategic responses to performance criteria.

Acknowledgment
This research was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. BR21882373).

Type of the article: Research Article

Higher education institutions face a dual imperative: accelerating digital transformation while advancing sustainability commitments. For academic staff, these agendas converge in a single psychological space, yet leadership research has largely treated digital leadership and sustainable leadership as parallel paradigms. This study examines how both styles concurrently shape lecturers’ job involvement, and whether person-organization (P-O) fit acts as a common mechanism linking them to role investment. Grounded in Social Exchange Theory, Job Demands-Resources Theory, and Person-Environment Fit Theory, an integrated structural model was tested on survey data from a non-probability sample of 312 full-time lecturers in selected Vietnamese public and private universities using partial least squares structural equation modeling (PLS-SEM). Results show that digital leadership exerts both a direct positive effect on job involvement (β = 0.333) and an indirect effect via P-O fit, while sustainable leadership strongly enhances P-O fit (β = 0.663) but has a non-significant direct path to job involvement, revealing a fully mediated, value-lagged structure. P-O fit emerges as the central gateway (β = 0.488) through which both leadership styles activate job involvement, with the model explaining 70.4% of its variance. The study contributes by integrating two leadership paradigms within a unified framework, conceptualizing P-O fit as a dynamic mediating process shaped by leadership behaviors, and foregrounding job involvement as a strategically important outcome driven by these dual leadership orientations. Practical implications point to the design of integrated leadership development and fit-focused HR practices in higher education institutions, navigating concurrent digital and sustainability transitions.