Issue #3 (Volume 10 2026)

Type of the article: Research Article

This study examines how institutional policy support, academic work environment, access to professional development opportunities, and academic compensation and incentives are associated with individual academic performance among political science faculty in Vietnam, while also testing the mediating role of individual professional development. The analysis is based on 415 valid survey responses collected from political science faculty working in Vietnamese higher education institutions and analyzed using partial least squares structural equation modeling. The results show that academic compensation and incentives emerge as the strongest positive predictors of individual academic performance (β = 0.301), followed by academic work environment (β = 0.289), individual professional development (β = 0.189), institutional policy support (β = 0.165), and access to professional development opportunities (β = 0.081). Individual professional development also positively predicts academic performance and partially mediates the relationships between the four contextual factors and academic performance. The model explains 30.7% of the variance in individual professional development and 52.0% of the variance in individual academic performance. These findings suggest that incentive systems, supportive academic environments, and meaningful professional development are important factors associated with academic performance among political science faculty in Vietnam.

Acknowledgment(s)
This research is sponsored by the Vietnam Academy of Social Sciences under Grant No. KHXH/NV/2025-28.

Type of the article: Research Article

In the context of the knowledge economy and globalization, one key factor in regional economic development is universities’ intellectual capital. In this regard, the purpose of this article is to analyze the relationship between universities’ intellectual capital and socio-economic differences across Kazakhstan’s regions. The research used an integrated index of universities’ intellectual capital developed in the authors’ previous study, factor and cluster analysis, and regression modeling. The research database includes data from the National Bureau of Statistics for 20 regions of Kazakhstan for 2015, 2020–2023. The findings suggest that an increase in the universities’ intellectual capital index is associated with an increase in gross regional product per capita (β = 87.32). The results demonstrate that the population’s nominal incomes were statistically insignificant, indicating no clear short-term association with income redistribution. Instead, the Gini coefficient increases significantly, suggesting higher levels of observed inequality and a possible concentration of benefits among higher-income groups in regions with high levels of university intellectual capital. More specifically, a 1-unit increase in universities’ intellectual capital is associated with a 0.371-point increase in the Gini coefficient. Moreover, the results of the cluster analysis show a high level of socio-economic imbalance between regions with high and low levels of university intellectual capital. The quantile regression suggests that universities’ intellectual capital is positively associated with economic growth but is also related to higher levels of social inequality. The results suggest the need for a differentiated regional policy to support the development of regional universities and ensure inclusive development.

Acknowledgments
This research is supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (AP23488456 “Imbalances in the development of the economy and social sphere of problem regions of Kazakhstan and their risks: factors, assessment, possible scenarios, leveling mechanisms”, 2024–2026).

Type of the article: Research Article

Higher education plays an important role in advancing the sustainable development paradigm. The corresponding contribution of universities is measured, in particular, by the QS Sustainability Rankings, which summarizes nine comprehensive indicators for assessing various aspects of sustainability. The study aims to analyze the structure of the QS Sustainability Rankings for leading global universities and identify the indicators that most significantly distinguish the ranked profiles of these institutions. The study covered the top 30 universities in the QS World University Rankings: Sustainability 2026 (31 universities due to tied ranking scores). The Pearson coefficient showed a fairly strong pairwise relationship with the ranking score for indicators such as “Equality”, “Environmental Research”, “Impact of Education”, and “Employability & Opportunities”; however, the typology of university profiles is more complex. Therefore, based on the principal component analysis method, the indicators most strongly associated with the variation of universities in the Ranking were identified: “Health and Wellbeing”, “Knowledge Exchange”, and “Environmental Sustainability”. A cluster analysis showed that university profiles in the QS Sustainability Rankings vary across clusters: cluster I (17 institutions) is predominantly oriented toward strengthening social impact, cluster II (7 institutions) toward strengthening environmental impact, and cluster III (7 institutions) has a mixed orientation. Therefore, based on classification analysis, a combination of indicators (“Environmental Sustainability”, “Impact of Education”, “Health and Wellbeing”) was identified as most strongly distinguishing the obtained clusters, that is, differentiating the ranked profiles of leading universities. Other institutions can use this to substantiate the priorities of their sustainable transformation strategy.

Type of the article: Research Article

Cybercrime is an increasingly visible digital safety concern for young adults in Vietnam, particularly for university students who rely heavily on social media for communication, learning, and risk-related information. This cross-sectional study examines the associations between social media use, legal awareness of cybercrime, media influence and misinformation exposure, family-school education, personal safety anxiety, and cybercrime risk perception and preventive awareness. Data were collected from 746 adult respondents in Vietnam, almost all of them were undergraduate students aged 18-24, and analyzed using EFA, CFA, CB-SEM, and bootstrap resampling. The results indicate that personal safety anxiety is the strongest correlate of cybercrime risk perception and preventive awareness. Family-school education, legal awareness, media influence and misinformation exposure, and social media use are also positively associated with both anxiety and the outcome construct. Indirect associations through personal safety anxiety were observed for all four antecedents, with the strongest indirect association involving family-school education. The findings should be interpreted as associational rather than causal because the data are cross-sectional and self-reported. The study contributes to socio-legal and communication research by showing how informational, legal, educational, and emotional factors jointly relate to cybercrime-related awareness among Vietnamese university students.

Type of the article: Research Article

The rapid development of digital transformation, artificial intelligence, and data-driven economic models has heightened concerns about personal data protection and social responsibility in Vietnam. In this context, this study aims to assess Vietnam’s legal framework for personal data protection and propose policy reforms to enhance social responsibility. Social responsibility is understood as responsible data governance achieved through the implementation of principles of transparency and accountability, thereby enhancing trust, and through risk-based governance that both respects traditional rights and ensures that data flows are not hindered in the digital context. The study employs theoretical legal analysis and comparative law methods to examine comprehensive legal frameworks for personal data protection, particularly Vietnam’s Personal Data Protection Law 2025 and Japan’s Personal Information Protection Law. The results show that Vietnam’s personal data protection regime remains hampered by fragmented regulations and an overly consent-based approach, and that the fundamental principles of the legal framework for protecting personal data are merely symbolic and formal on paper due to weak enforcement and monitoring mechanisms. In contrast, Japan’s experience demonstrates the effectiveness of a centralized supervisory body, a guidance-based management model, risk-based governance, and regular legal review cycles in promoting socially responsible data use. Based on these findings, the study proposes policy recommendations for Vietnam, focusing on improving the structure of a synchronized and unified legal framework for personal data protection; establishing a data governance mechanism based on risk management principles; and creating an independent agency to coordinate the development, monitoring, and implementation of the law nationwide.

Type of the article: Research Article

Generative artificial intelligence increasingly supports knowledge work in education and professional settings, yet its usefulness remains underexplored among people who combine study and employment. This study examines how working students perceive ChatGPT’s usefulness in selected professional applications. The study uses data from a quantitative online survey of 419 working students from five age groups conducted in Poland between April and June 2024. The questionnaire measured current and expected usefulness of ChatGPT in selected professional roles, motives for use, and the most frequently used version of the tool. The analysis used Kruskal-Wallis tests, post-hoc multiple comparisons, Cochran’s Q test, planned McNemar comparisons, Pearson’s chi-square tests, and effect-size measures. Most respondents used the Free version (n = 329), while smaller groups used Premium (n = 67) or Other variants (n = 23). Information retrieval was the most frequently reported motive for using ChatGPT (n = 298; 71.1%), followed by assistance in learning new skills (n = 249; 59.4%). Age-related differences appeared in the current assessment of ChatGPT as a customer relations specialist (p = 0.0018) and secretary (p = 0.0083), with respondents aged 40-50 assigning higher ratings in these roles. Younger respondents reported using ChatGPT for skill development more often than older respondents (p < 0.001). ChatGPT version also differentiated use: Premium users more often reported routine document preparation, code generation, and data analysis, while Other-version users more often reported code generation and data analysis. The findings show that working students perceive ChatGPT primarily as a knowledge-support tool rather than a substitute for professional roles.

Type of the article: Research Article

The growing demand for practice-oriented workforce development has increased the importance of dual education in vocational education and training systems. The purpose of this study is to examine the relationships between students’ satisfaction with learning outcomes and their intention to stay in their current job within dual education programs in the vocational education and training (VET) system in Kazakhstan. The methodological approach is based on a quantitative research design using survey data collected from 440 students enrolled in four VET institutions in Almaty. Structural equation modeling (SEM) with SmartPLS software was employed to test the proposed hypotheses and assess the relationships between the studied variables. The results demonstrate that enterprise internship satisfaction positively affects general learning satisfaction (β = 0.380), job involvement (β = 0.274), and intention to stay in the current job after graduation (β = 0.142). Job involvement has the strongest effect on intention to stay with the employer (β = 0.416) and significantly increases learning involvement (β = 0.636). However, general satisfaction with learning outcomes does not directly influence intention to stay in the current job. The findings indicate that practical workplace experience and active integration into the work environment are more important determinants of students’ intention to stay with their current employer than general perceptions of educational quality. The study contributes to understanding the role of dual education in strengthening workforce retention intention and early career commitment in vocational education contexts.

Type of the article: Research Article

Lebanese technical schools have a vital responsibility to develop young talents and improve their practical abilities. These institutions are assessed on the competencies demonstrated by students, not just on knowledge transfer. Yet graduates face employment challenges due to a focus on theory rather than practical capabilities. This skill gap stems from the mistaken belief that theoretically taught total quality management (TQM) practices alone improve competencies. The objective is to examine the relationship between three total quality management practices and students’ practical competence based on instructors’ perceptions by analyzing the mediating role of instructors’ self-efficacy. A quantitative research design was used, and data were collected via a questionnaire from a random sample of 380 instructors across 12 technical institutions in north Lebanon. Instructor self-efficacy was positively associated with students’ practical competency as perceived by instructors (β = 0.570; p < 0.001). Among TQM factors, process standardization was most influential (β = 0.540), followed by TQM training adequacy (β = 0.511) and Kaizen commitment (β = 0.482). TQM factors predicted instructor self-efficacy, with process standardization (β = 0.823) and Kaizen (β = 0.703) showing the highest associations. All indirect effects were significant, with process standardization (β = 0.560) and TQM training adequacy (β = 0.409) confirming self-efficacy’s mediating role. This study supports instructors’ self-efficacy as a mediator of technical education competency building, offering a differentiated, human-centered perspective. This study can serve as a guide for technical schools by proposing actionable strategies to support practical competencies and promote graduates’ readiness in a resource-constrained context like Lebanon.

Type of the article: Research Article

Lecturer performance in geographically dispersed higher education institutions depends on more than individual expertise; it also requires the coordinated use of academic knowledge. This study aims to examine how transformational leadership and perceived organizational support explain self-reported lecturer performance and whether interpersonal collaboration skills mediate these relationships in higher education institutions in the Nias Archipelago. Survey data from 217 permanent lecturers were analyzed using partial least squares structural equation modeling. Transformational leadership was positively associated with interpersonal collaboration skills (β = .340, p = .003) and self-reported lecturer performance (β = .226, p = .010). Perceived organizational support was positively associated with collaboration skills (β = .387, p < .001) and performance (β = .267, p = .003). Interpersonal collaboration skills had the strongest direct association with performance (β = .401, p < .001). The indirect effects of transformational leadership (β = .136, 95% CI [.039, .263]) and perceived organizational support (β = .156, 95% CI [.077, .244]) were significant, indicating complementary partial mediation. The model explained 46.6% of the variance in collaboration skills and 62.8% in self-reported lecturer performance. The findings show that leadership and organizational support contribute to perceived academic accomplishment partly by enabling lecturers to communicate, coordinate responsibilities, build trust, manage disagreement constructively, make joint decisions, and collaborate across units.

Acknowledgment
The authors thank the participating lecturers and the institutional contacts who supported the survey distribution. The authors also appreciate the editor and reviewers whose comments improved the methodological transparency and focus of the manuscript.

Type of the article: Research Article

Digital transformation has changed the way human resource management is organized in higher education. In private universities with strong accreditation demands, digitally supported human resource practices are increasingly relevant for helping academic staff manage teaching, research, publication, and institutional service responsibilities. The study analyzes the relationship between Digital Human Resource Management practices, human resource agility, and self-reported academic staff performance among full-time Associate Professors in Indonesian private universities with “Excellent” accreditation status. A quantitative explanatory approach was used, based on cross-sectional survey data collected from June to December 2025. Of 537 responses collected, 500 valid responses were analyzed using Partial Least Squares Structural Equation Modeling. The results show that Digital Human Resource Management practices are positively associated with self-reported academic staff performance (β = 0.297, t = 7.367, p < 0.001) and human resource agility (β = 0.495, t = 12.713, p < 0.001). Human resource agility is also positively associated with self-reported academic staff performance (β = 0.422, t = 10.463, p < 0.001). Mediation analysis indicates a positive indirect effect of Digital Human Resource Management practices on self-reported academic staff performance through human resource agility (β = 0.209, 95% Boot CI [0.160, 0.264]), with a total effect of β = 0.506. The model explains 29.9% of human resource agility and 48.7% of self-reported academic staff performance. The findings suggest that digital human resource practices are positively associated with perceived academic performance when accompanied by agile academic work behavior. Practically, universities should align digital human resource systems with agility-oriented staff development.

Type of the article: Research Article

This study examines the relationships among generative AI tool usage for Workplace Learning, Learning Agility, and Workplace Creativity among electronic retail employees in Indonesia. Learning Agility was modeled as a second-order construct comprising developing leadership or growth, seeking feedback, and developing systematically. Data were collected through a cross-sectional survey of 286 employees who actively used generative AI platforms for learning and work-related support. The hypotheses were tested using covariance-based structural equation modeling and bias-corrected bootstrap analysis. The results show that generative AI tool usage was positively associated with Learning Agility (β = 0.738, p < 0.001), while Learning Agility was positively associated with Workplace Creativity (β = 0.484, p < 0.001). Generative AI tool usage also maintained a positive direct relationship with Workplace Creativity (β = 0.408, p < 0.001). The indirect relationship through Learning Agility was statistically significant, with a bias-corrected 95% confidence interval ranging from 0.179 to 0.509. These findings indicate complementary partial mediation, suggesting that Generative AI Use is related to Workplace Creativity both directly and through employees’ adaptive learning capacity. The study applies Social Cognitive Theory to generative AI-supported workplace learning by distinguishing AI-enabled learning resources from employees’ behavioral engagement with those resources. The findings suggest that Generative AI Use is associated with Workplace Creativity both directly and indirectly through Learning Agility. Practically, electronic retail managers should combine AI adoption with employee development practices that encourage feedback seeking, reflection, experimentation, and systematic learning.

Type of the article: Research Article

The growing integration of social networking sites (SNSs) into higher education has fueled debate about their contribution to academic performance. This study examines how three forms of academic SNS use, interaction with friends, interaction with lecturers, and cooperative learning, affect self reported performance among 510 undergraduate students from public, private, and international universities in Hanoi, Vietnam, and tests the moderating roles of academic motivation and self regulated learning. Multiple regression and moderation analyses (Hayes’ PROCESS macro) were used.

Cooperative learning was the strongest predictor of performance (β = .479, p < .001), followed by interaction with lecturers (β = .253, p < .001) and interaction with friends (β = .184, p < .001), with the model explaining 63.8% of variance. Academic motivation and self regulated learning significantly strengthened the effect of friend interaction on performance but did not moderate the effects of lecturer interaction or cooperative learning. This indicates that structured, instructionally guided SNS activities produce stable academic benefits regardless of motivation or self regulation, while the value of informal peer interaction depends on these individual capacities. Performance and self regulated learning also differed significantly by gender, year of study, and university type, but not by discipline. Overall, results suggest that the academic effectiveness of SNSs depends on the structuredness of interaction and students’ motivational and self regulatory capacities, not merely on usage intensity. Academic performance was measured via self report rather than objective academic records.

Type of the article: Research Article

The rapid digital transformation of universities and the expansion of the digital economy require new approaches to organizing knowledge creation and transfer within innovation infrastructure. This study aims to develop and substantiate an institutional model of innovation infrastructure in the digital economy that conceptualizes digital universities as key actors in knowledge creation and transfer. The research is conceptual and methodological and is based on systematic analysis, structural-functional modeling, elements of graph theory, and quantitative modeling. The proposed model interprets the innovation potential of an actor through the proportional interaction of three complementary components: access to knowledge content, technological provision, and competencies. A weakness in any component may constrain overall innovation potential even when the others are well developed. Illustrative model-based calculations demonstrate this relationship rather than provide empirically verified results. The graph-based representation conceptualizes digital universities as integration hubs coordinating resource flows among innovation actors. The model identifies four interrelated structural blocks of innovation infrastructure: resource and potential, regulatory and technological, methodological, and institutional-managerial. These blocks support the identification of bottlenecks in knowledge creation and transfer and indicate directions for more balanced resource interaction. The study concludes that the effectiveness of innovation infrastructure depends on the proportional development of knowledge content, technologies, and competencies, with digital universities performing a central coordinating function. The proposed approach provides a conceptual and methodological basis for further empirical research on digital universities in innovation ecosystems.

Acknowledgment
The study did not receive any special funding from the government, commercial, or non-profit organizations. The author would like to thank colleagues for their professional comments and academic support during the study. The statements expressed in the article are solely the responsibility of the author.

Type of the article: Research Article

Research on quality management in higher education remains conceptually fragmented, with recurrent organizational issues examined across partially disconnected strands of literature. This study analyzes Scopus-indexed higher education research using quality management terminology and organizes its recurrent concerns into an integrated conceptual account. A two-level design combined bibliometric mapping of 1,829 records published between 2004 and 2025 with full-text thematic conceptual synthesis of 159 retained studies. Publication activity increased from 25 records in 2004 to a peak of 157 in 2019, while total quality management terminology remained prominent alongside quality assurance and quality improvement vocabularies. The conceptual synthesis organized recurrent concerns into four higher-order dimensions: strategic leadership and governance, implementation of QM frameworks and digital transformation, quality culture and organizational dynamics, and performance evaluation and external accountability. Studies situated in emerging and developing country contexts additionally highlighted external quality requirements, adaptation of established frameworks, institutional capacity for implementation, and supporting information systems. The four dimensions were integrated into a conceptual model spanning strategic, operational, organizational, and evaluation levels. Overall, the results place framework adoption within a broader organizational context by highlighting the conditions under which quality arrangements are implemented and sustained. For institutional leaders and quality managers, this suggests assessing whether formal arrangements become embedded in organizational practice and inform subsequent decisions.

Acknowledgment
This research was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. BR28712521).

Type of the article: Research Article

Digital skills anchor human-capital policy in the European knowledge economy, yet which dimension of digitalization moves lifelong learning remains unsettled, as connectivity, specialist, and training targets are pursued in parallel. The paper aims to quantify the association between the workforce’s digital-skills composition and adult participation in learning across 31 European economies, using an unbalanced annual 2015–2023 panel supplemented by DigComp 2.0 waves for 2021–2025, and to draw implications for human-capital policy. Both are estimated with two-way fixed-effects models, lagged regressors, country-clustered standard errors, and an audit of survey redesigns. The lagged employment share of ICT specialists is positively associated with adult learning: a one-percentage-point increase corresponds to a 1.38-point gain (β = 1.379, p = 0.034; wild-cluster bootstrap p = 0.077). Diffusion-type measures – daily internet use and online health-information seeking – show no such link (β = 0.021 and 0.025), although the specialist coefficient is not statistically distinguishable from theirs. The coefficient stays positive across estimators and samples (0.44–1.76) and significant in the pre-break 2015–2020 window (β = 1.536, p = 0.024); a formal test does not reject constancy across the 2021 EU-LFS redesign. Direct skills measures point the same way but stay insignificant (β = 0.042–0.121); unemployment is counter-cyclical (β = 0.583–0.694). The evidence is consistent with rebalancing policy from connectivity targets towards workforce skills composition – a margin unmeasured in Ukraine, Kazakhstan, and Armenia – with specialist pipelines as the instrument most directly supported and enterprise ICT training as a possible, not yet established, channel.

Acknowledgment
Vladyslav Smiianov contributed to this article within the framework of the research project “Modelling the impact of economic digitalization on public health in Ukraine in the context of preserving human capital”, funded by the Ministry of Education and Science of Ukraine (State Registration No. 0126U001085).