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 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 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 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 ArticleArtificial 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 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 ArticleEqual participation in scientific activity is an important indicator of the fair distribution of opportunities in a democratic society. This article examines the issue of women’s representation as leaders in Kazakhstani science, with a particular focus on the gender aspect of participation in scientific projects. For this purpose, the study analyzed the distribution of grants for scientific projects funded by the government between 2018 and 2024 in Kazakhstan. The findings show a positive trend in women’s participation in project leadership over the period analyzed, with the share of projects led by women increasing from 38.2% in 2018 to 48.4% in 2022, noting that most projects are funded for three years. At the same time, the analysis reveals pronounced disciplinary disparities. Women are most strongly represented in the social sciences and humanities, while their participation remains considerably lower in technical and natural science fields. The results also indicate a persistent gender gap in access to large-scale funding, as projects with higher budget allocations are predominantly led by male researchers. Overall, the results highlight both quantitative progress and structural limitations, underscoring the need for targeted policy measures aimed not only at increasing women’s participation but also at reducing gender imbalances across scientific fields and funding levels in Kazakhstani science.AcknowledgmentsThe research presented in this paper was funded by the Science Committee of the Republic of Kazakhstan under grant No. AP22784063 “Strategic Directions of Women’s Empowerment and Access to Quality Employment in Kazakhstan”.
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 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.
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 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 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 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 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 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 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 In emerging digital economies, knowledge hiding can disrupt organizational knowledge flows that support innovation, yet empirical evidence on how artificial intelligence adoption shapes these effects remains limited. This study examines how knowledge hiding influences knowledge integration capability and innovation climate in digital firms and tests the moderating role of artificial intelligence adoption. Data were collected in May 2025 through a questionnaire survey of 145 firms operating in Thailand’s New S-Curve digital sectors. Respondents included senior executives, middle managers, and knowledge management specialists involved in artificial intelligence implementation, knowledge management, and innovation activities. A total of 426 responses were obtained and aggregated to the firm level. The data were analyzed using partial least squares structural equation modeling. Results show that knowledge hiding significantly reduces knowledge integration capability (β = −0.503, p < 0.001) and innovation climate (β = −0.339, p < 0.001), while knowledge integration capability positively affects innovation climate (β = 0.337, p < 0.001). Artificial intelligence adoption weakens the negative effects of knowledge hiding on knowledge integration capability (interaction β = 0. 359, p < 0.001) and innovation climate (interaction β = 0. 500, p < 0.001), indicating a buffering mechanism through improved access to organizational knowledge. These findings suggest that digital firms should address knowledge hiding while strengthening knowledge integration practices and implementing artificial intelligence in ways that complement collaborative knowledge processes.
Type of the article: Research article The increasing development of digital business environments has contributed to the diversification of knowledge sources globally, making smart knowledge management crucial for enhancing the accuracy of decision-making processes. This study aims to investigate the impact of AI-driven capabilities, including adaptive learning, intelligent analytics, automation capability, integration capability on knowledge systems, and the role of smart knowledge management as a mediating factor within the context of the Federal Civil Service Council in Baghdad, Iraq. The study employed a quantitative method to collect data between April 2025 and August 2025 from 161 employees with at least three years of experience in knowledge management, organizational content and records, data, and machine learning. This sample included knowledge management managers, knowledge management specialists, data analysts, knowledge support technicians, and operations managers at the Federal Civil Service Council. The findings indicate that enhancing AI-driven capabilities across the four dimensions of adaptive learning, intelligent analytics, automation capability, and integration capability contributes to organizational success. This is evident from the correlation between adaptive learning (p = 0.012, < 0.279), analytical intelligence (p = 0.018, < 0.213), automation capabilities (p = 0.02, < 0.05), and knowledge systems. The study found that intelligent knowledge management plays a crucial mediating role in the relationship between AI capabilities and knowledge systems, contributing to the success of digital organizations and the accuracy of decision-making. This is further demonstrated by the positive correlation between the dimensions of AI capabilities and knowledge systems.
Type of the article: Research Article In the era of digital transformation, organizations are increasingly integrating digitalization and artificial intelligence to enhance employee behavior and organizational outcomes. This study examines the associations among digital leadership, AI-based performance assessment, employee empowerment, work engagement, and organizational performance in a Chennai-based IT company in India. Specifically, the study investigates the direct and indirect effects of digital leadership and AI performance assessment on organizational performance through employee empowerment and work engagement. Data were collected from 373 IT employees using an online survey conducted between June and August 2025 and analyzed using partial least squares structural equation modelling (PLS-SEM). A stratified random sampling technique based on organizational job levels (entry, mid, and senior) was adopted to ensure adequate representation of hierarchical positions within the organization. Hypothesis testing revealed that digital leadership and AI performance assessment significantly enhance employee empowerment and work engagement (β = 0.490, 0.415, 0.527; p < 0.001), which in turn positively influence organizational performance (β = 0.383, 0.477, 0.195, 0.287; p < 0.001, 0.033). Furthermore, employee empowerment and work engagement significantly mediate the relationships between digital leadership, AI performance assessment, and organizational performance (β = 0.135, 0.199, 0.265, 0.244; p < 0.001). In addition, a multi-group analysis was conducted to examine differences across employee hierarchical levels. The findings highlight that transformations in modern workplaces and digitalized HR practices contribute to organizational performance across the workforce, while ensuring that employees from different hierarchical levels are adequately represented in the sample.
Type of the article: Research Article Educational reform in Morocco continues to face persistent challenges related to learning outcomes, territorial disparities, and the limited effectiveness of centralized policy instruments. In this context, participatory governance at the school level has emerged as a potential lever for improving school effectiveness. This study examines how the internal participatory mechanisms embedded in the Integrated School Project influence teachers’ perceptions of effectiveness in pilot schools. The analysis is based on data collected through a self-administered questionnaire distributed to teachers involved in the project in the Marrakech-Safi region between early June and late July 2025. Out of 420 questionnaires administered, 357 were retained after quality control. Measurement constructs were validated using confirmatory factor analysis, and the empirical relationships were estimated using median quantile regression with robust standard errors to address non-normality and heterogeneous perceptions. The results show that perceived effectiveness increases significantly when school action is structured around collective prioritization of objectives, inclusive working groups, clear assignment of responsibilities, and strong methodological rigor. Institutionalized decision-making spaces and teachers’ involvement in concrete pedagogical choices also exert a positive effect. In contrast, collaborative project co-design and the formal documentation of collective decisions do not significantly influence effectiveness, while shared diagnosis has a more moderate impact. Overall, the findings indicate that participatory governance improves school effectiveness only when it is operationalized through structured and stable mechanisms rather than symbolic participation, with important implications for strengthening guided school autonomy in Morocco.
