Issue #1 (Volume 10 2026)

Type of the article: Research Article

Editorial boards are vital components of scholarly journals, ensuring the integrity, quality, and academic rigor of published research. They play a key role in guiding a journal’s vision, selecting content, and upholding ethical standards. Journal reputations are reinforced by the endorsement of recognized scholars. Although many scientists worldwide have chosen to distance themselves from Russian institutions following the full-scale invasion of Ukraine in February 2022, we noticed that members of the global scientific community were still included on the editorial boards of journals published by an international publisher and edited by academic institutions in the Russian Federation. Given their importance, during 2024, we performed an email survey of members of non-Russian institutions serving on the editorial boards of 140 such journals and sent the letters to 709 international members of these boards. Based on 165 responses received, the findings reveal that 70.9% of international members of these editorial boards were either unaware of their membership, or did not fulfill their editorial duties, or were retired, or were deceased (17 cases). Inclusion of these individuals without their knowledge or consent clearly constitutes an unauthorized misrepresentation as to editorial board memberships, which might be harmful to the reputation of specific scientists. After the inquiries, 60.1% of respondents reported their decision to withdraw their names from these editorial boards as an ethical conflict resolution. The results of the analysis help to understand how journals and researchers respond to ethical and geopolitical challenges, ensuring that their practices comply with international standards and values.

Acknowledgment
Alex Plastun gratefully acknowledges financial support provided by Volkswagen Foundation, Ref.: 9C853, Project “Sustaining Ukrainian Scholarship”, hosted by New Europe College.

Type of the article: Research Article

Modern defense environments demand sustainable, knowledge-driven training systems that adapt to technological, organizational, and strategic challenges. This study explores the sustainability of military distance learning in Lithuanian military education and its role in enhancing adaptability and resilience. It assesses how digital, knowledge-based systems support long-term effectiveness and flexibility. Sustainability refers to maintaining scalable, resilient education under changing conditions. Adaptability is the ability to adjust learning processes and technologies, while resilience ensures institutional stability and performance during disruptions. The study employs fuzzy logic integrated with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to analyze interdependencies among eight critical factors of sustainable distance learning. A structured expert survey was conducted in 2024 with 17 Lithuanian military education specialists, all holding Ph.D. degrees and possessing extensive academic and practical experience in e-learning, instructional design, and technology management. The analysis revealed that technological infrastructure, instructional design, and scalability function as primary causal drivers shaping learner engagement and institutional support. Quantitative results show that technological infrastructure exerted the highest influence weight (0.187), followed by instructional design (0.162), while psychological support acted primarily as an effect factor. These findings confirm that sustainable distance learning enhances adaptability by ensuring uninterrupted access to training, flexible pacing, and integration of emerging digital tools. In conclusion, the study demonstrates that sustainable military distance learning serves as a strategic enabler of knowledge transfer, leadership development, and organizational effectiveness, thereby strengthening both the adaptability and institutional resilience of military education systems.

Acknowledgment
We acknowledge the General Jonas Žemaitis Military Academy of Lithuania for financial support in publishing this article.

Type of the article: Research Article

In a rapidly evolving digital landscape, higher education institutions face increasing challenges in faculty retention. The study analyzes the impact of Student Initiatives, Mentorship, Advocacy, and Collaboration on faculty intention to stay through the mediation of faculty satisfaction. The research process began with an exhaustive review of existing literature and the development of a structured questionnaire using a quantitative approach. A further survey was undertaken by collecting 390 responses from faculty members working in higher education institutions in Karnataka, India. The mediation was analyzed utilizing confirmatory factor analysis (CFA) to check the model fit and Structural Equation Modelling (SEM) to test hypothetical relationships. Results revealed significant direct effects of Student-Led Peer Mentorship, Advocacy Groups, Student Initiatives, and Collaborative Learning on faculty satisfaction. These constructs also significantly predicted faculty retention, both directly and through the mediating effect of faculty satisfaction. Faculty satisfaction mediated these relationships, with the strongest total effect for advocacy groups (β = .537). While collaborative learning had a strong direct effect (β = .347), its mediated impact was comparatively weaker (β = .082). This study highlights that institutions that recognize and value the connection between student engagement and faculty engagement are poised to develop a strong academic community. The practical significance of the current study is considerable for institutional decision-makers and academic leaders. Institutions should not rely on just extrinsic rewards, such as salary or tenure, to be able to develop their faculties, but rather should intentionally develop a participative academic culture.

Acknowledgment
The authors acknowledge financial support for the Article Processing Charges (APC) from Yenepoya (Deemed to be University).

Type of the article: Research Article

This study examines whether knowledge management practices in commercial banks influence employees’ knowledge of environmental law, providing empirical evidence from Vietnam’s banking sector as an emerging Asian economy. Data were collected from 568 employees across 35 Vietnamese commercial banks in the first quarter of 2025, and the hypotheses were tested using partial least squares structural equation modeling (PLS-SEM). The results indicate that all three knowledge management components (information-sharing systems, a learning-oriented organizational culture, and training and skill development) have positive effects on both work motivation and perceived organizational support. Information-sharing systems exert a strong influence on organizational support (β = 0.188) and work motivation (β = 0.207), while a learning-oriented culture significantly enhances organizational support (β = 0.204) and work motivation (β = 0.165). Training and skill development show the strongest effects on work motivation (β = 0.240) and organizational support (β = 0.185). In turn, work motivation and organizational support directly and positively affect employees’ environmental law knowledge (β = 0.343 and β = 0.363, respectively). Moreover, both variables significantly mediate the relationships between KM components and environmental law knowledge. These findings underscore the relevance of social exchange theory in explaining how effective knowledge management practices enhance employees’ legal knowledge, thereby contributing to more sustainable organizational development. Accordingly, practical implications are proposed for bank managers to strengthen knowledge management implementation.

Acknowledgment
The authors would like to thank the Editor-in Chief and a reviewer for their helpful comments that in our view have helped to improve the quality of the manuscript significantly. Beside, this study is the result of collaboration between researchers from the University of Law, Hue University, and School of Business and Economics, Duy Tan University. The authors would like to thank both institutions for their support and facilitation in the publication of this research.

Type of the article: Research Article

Equal 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.

Acknowledgments

The 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

AI is widely regarded by the IMF and the World Bank as a catalyst for growth. AI should be understood as a multidimensional socio-technical system embedded across institutions, industries, and society. Its economic contribution depends on which pillars of the national AI system expand (e.g., R&D capacity, infrastructure, governance, or social acceptance). For this reason, the seven pillars of AI development are measured by the AI Vibrancy subindices, which help avoid reliance on a single composite indicator that may conceal offsetting effects. This study examines how different pillars of the national AI ecosystem shape the architecture of the knowledge economy and its economic outcomes by estimating heterogeneous within-country associations between GDP per capita and seven AI ecosystem pillars, operationalized through AI Vibrancy subindices, using a balanced panel of 36 countries with complete data over the period 2020–2023. Fixed- and random-effects models are estimated using heteroskedasticity-robust and Driscoll-Kraay standard errors. The results indicate that, within countries over time, the R&D (β = –5.676, p < 0.001) and Infrastructure (β = –16.306, p < 0.001) subindices have strong and statistically significant negative associations with GDP per capita, while Public Opinion shows an adverse effect that is significant at the 5% level under heteroskedasticity-robust inference (β = –9.126, p = 0.040) and marginally significant under Driscoll-Kraay inference (p = 0.054). Responsible AI exhibits a marginally positive association (β = 5.773, p = 0.065) in the Driscoll-Kraay specification, whereas Economy, Education, and Policy & Government show no significant within-country effects.

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.

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

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

A balanced gender distribution is observed in agricultural sciences in Kazakhstan. This study aims to define and analyze the factors influencing women’s participation in the agricultural research sector in Kazakhstan using the 5Ms analytical framework (macro/meso environment, money, motherhood, management). The study applies quantitative statistical analysis of science development indicators from bulletins of the Bureau of National Statistics, extracts from the minutes of the National Scientific Council, and qualitative content analysis of regulatory legal acts from the “Adilet” system. The empirical analysis covers the period 2018–2025. In Kazakhstan, 1,185 women scientists are engaged in agricultural research, accounting for 9.2% of female scientists and 51.3% of researchers in agricultural science. Women’s participation is shaped by factors across all dimensions of the 5M framework. Key drivers include the public policies promoting equal opportunities, access to postgraduate education in agriculture (master’s programs: 11.1-66.7%; Ph.D. programs: 20-90.9% of students), and employment opportunities in the agricultural system (18,212 people, 30%). The barriers include stereotypes about the masculinity of the scientific profession and activities in the agricultural sector, as well as limited access to large research grants. One of the most significant barriers is the “glass ceiling”, reflected in the underrepresentation of women in leadership positions (3.2% female executives, 8.8-21% female rectors, etc.) and the presence of a gender pay gap (21.2% in salaries, 60.8% in grants), as well as the “motherhood penalty”. Strengthening women’s participation in agricultural sciences requires not only increasing their representation but also promoting their presence in leadership and decision-making positions.

Acknowledgments
This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (IRN AP19579256 “Mechanisms for empowering women in scientific activity in the interests of the development of the innovative economy of Kazakhstan”).

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.