Qubahan Academic Journal

A Comprehensive Framework for Improving the Assessment of Human Capital Quality: Evidence from Regional Analysis in Western Kazakhstan

2026-03-01T19:09:18+00:00

This study addresses the growing need for more robust and systematic approaches to assessing the quality of human capital in the context of ongoing socio-economic transformation. Human capital is recognized as a key driver of sustainable economic growth, regional competitiveness, and improved development outcomes. Its quality is shaped by institutional environments, state social and educational policies, and investment levels in education, healthcare, and professional skill development. The main objective of this study is to enhance existing approaches to evaluating human capital quality through an integrated analytical framework. The methodology combines a systematic literature review, comparative analysis, and conceptual modeling to capture the multidimensional nature of human capital as an economic, institutional, and social construct. This interdisciplinary approach enables a more comprehensive understanding of how human capital quality can be measured and interpreted across regions. The originality of the study lies in its synthesis and classification of existing measurement approaches, with particular attention to the context of Kazakhstan’s socially oriented economic model and sustainable development priorities. The research proposes a structured framework for ranking human capital quality into high, medium, and low levels based on key assessment criteria. This classification provides a practical tool for policymakers to evaluate regional disparities and improve the design of socio-economic development strategies. The findings contribute to both theoretical advancement and practical policymaking by offering an improved basis for monitoring, comparing, and enhancing human capital quality at the regional level.

Artificial Intelligence Enabled Green Human Resource Management and Environmental Sustainability: An Empirical Analysis of Pakistani Organizations

2026-02-04T14:42:09+00:00

The growing environmental challenges confronting organizations have increased the importance of integrating sustainable human resource practices with advanced digital technologies. This study examines the impact of Green Human Resource Management (GHRM) practices green recruitment, green training and development, green compensation and rewards, and employee empowerment on organizational environmental sustainability, while investigating the moderating role of Artificial Intelligence (AI). Data were collected from employees working in organizations across multiple sectors in Pakistan, and Structural Equation Modeling (SEM) using WarpPLS 8.0 was employed to test the proposed relationships. The findings reveal that green training and development is the strongest predictor of environmental sustainability, followed by green compensation and rewards, green recruitment, and employee empowerment. Furthermore, AI significantly strengthens the relationship between GHRM practices and sustainability outcomes by enhancing HR analytics, monitoring efficiency, predictive accuracy, and environmentally responsible decision-making. The study contributes to the emerging literature on AI-enabled sustainable HRM by providing empirical evidence on the integration of intelligent technologies with green HR practices in developing economies. The findings offer practical insights for policymakers, HR managers, and organizational leaders seeking to implement AI-driven sustainability strategies that improve environmental performance and long-term organizational sustainability.

Quality Gaps in Clinical Medical Education in Yemen: A Comparative Study of Student Satisfaction in Public and Private Universities

2025-08-26T15:42:38+00:00

The quality of clinical training is a decisive component of medical education, yet empirical evidence from conflict-affected settings such as Yemen remains scarce. This study investigates undergraduate medical students’ satisfaction with clinical education quality across public and private universities, with a focus on identifying structural and demographic determinants of variation. A cross-sectional survey was conducted among 670 clinical-phase medical students in two major Yemeni cities using an Arabic-adapted version of the National Student Survey (NSS), covering eight domains of educational quality. Data were analyzed using non-parametric statistical techniques at a significance level of α = 0.05. The findings reveal consistently higher levels of satisfaction among students enrolled in private universities, particularly in teaching quality, assessment and feedback, learning opportunities, and academic support. In contrast, public university students reported lower satisfaction across most domains, suggesting systemic constraints in resource availability and instructional delivery. Demographic factors also influenced perceptions, with male, married, and older students (24–26 years) reporting significantly higher satisfaction in selected areas. Importantly, institutional characteristics emerged as stronger predictors of satisfaction than individual-level factors. This study provides robust evidence of inequities in clinical education quality within Yemen’s higher education system. It contributes to the limited regional literature by offering a comparative and data-driven assessment of student experience in a fragile context. The findings underscore the need for targeted policy interventions, resource optimization, and pedagogical reforms to enhance the effectiveness, equity, and responsiveness of clinical medical education in Yemen.

Enhancing Business Performance through Competitive Capability: The Role of Strategic Resources in Vietnamese Cashew Firms

2026-03-26T17:30:34+00:00

This study investigates the influence of strategic enterprise resources on business performance through the mediating role of competitive capability in Vietnamese cashew firms. Drawing upon Resource-Based View (RBV) theory and Dynamic Capability Theory, the study examines how technological capability, supply chain orientation, business strategy, and market orientation contribute to organizational competitiveness and performance. Data were collected from 560 managers and executives working in Vietnamese cashew enterprises. The measurement model was validated using Cronbach’s Alpha and Exploratory Factor Analysis (EFA), while Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS was employed to test the hypothesized relationships. PLS-SEM was selected due to the predictive orientation of the study, the complexity of the structural model, and the inclusion of multiple mediating relationships. The findings reveal that strategic resources significantly influence business performance both directly and indirectly through competitive capability. Technological capability and market orientation emerged as key drivers of competitiveness, while supply chain orientation and business strategy demonstrated substantial effects on organizational performance. The results emphasize the critical role of internal resource deployment and dynamic capability development in achieving sustainable competitive advantage within the Vietnamese cashew industry. The study contributes to the literature by extending RBV and Dynamic Capability Theory in the context of agri-business competitiveness and offers practical implications for managers and policymakers seeking to strengthen firm resilience and long-term growth.

The Mediating Role of Ikigai at Work in the Relationship Between Transformational Leadership and Turnover Intention Among IT Employees

2026-02-16T13:07:53+00:00

High employee attrition and disengagement remain major challenges in the Indian information technology (IT) sector, creating an urgent need for effective leadership and retention strategies. This study investigates the mediating role of Ikigai at work in the relationship between transformational leadership and turnover intention among IT professionals. Rooted in the Japanese concept of purpose and meaning in life, Ikigai is examined as a psychological resource that may enhance employee engagement and reduce turnover intention. A quantitative research design was adopted using survey data collected from 362 IT professionals in India. Established and validated measurement scales were employed to assess transformational leadership, Ikigai at work, and turnover intention. The proposed relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that transformational leadership has a significant positive effect on employees’ sense of Ikigai at work, while Ikigai demonstrates a significant negative relationship with turnover intention. Furthermore, the direct relationship between transformational leadership and turnover intention was found to be statistically non-significant after introducing Ikigai, indicating a full mediating effect. These results suggest that transformational leaders contribute to employee retention primarily by fostering a sense of meaning, purpose, and fulfillment at work. The study contributes to leadership and organizational behavior literature by integrating Ikigai into employee retention models within the IT context. It extends existing knowledge on psychological resources and meaningful work by demonstrating the importance of purpose-driven leadership in reducing turnover intention. Practically, the findings provide valuable implications for organizations seeking to improve employee retention through leadership development initiatives, meaningful work practices, and psychologically supportive workplace environments.

Beyond Compliance in Tourism: Fostering Proactive Safety Culture in Multi-Crisis Hospitality

2026-02-06T21:11:40+00:00

The current study explores the effect of safety leadership on employees’ safety performance within a multianxious hospitality industry, with belief restoration as mediation and perceived susceptibility as moderation. The tourism and hospitality sector is especially vulnerable to climate-related disruption, including heavy rainfall, earthquakes, volcanic eruptions, and the collapse of infrastructure, resulting in increased occupational safety-related uncertainty for frontline workers. In such cases, successful safety performance depends on regulatory compliance and leadership, as well as psychological safety. A cross-sectional survey was conducted among 106 frontline employees across five hotels in Yogyakarta, Indonesia, a tourism destination exposed to recurring environmental hazards. Data were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Results indicate that safety leadership does not exhibit a significant direct association with employee safety behavior. Instead, leadership operates indirectly through belief restoration, supporting a full mediation pattern at the structural level. Perceived susceptibility strengthens the relationship between safety leadership and belief restoration and shows a marginal interaction effect on safety behavior. Theoretically, the study refines safety leadership research by modelling belief restoration as a domain-specific cognitive recovery pathway linking leadership cues to safety engagement under prolonged disruption. The findings suggest that in multi-crisis hospitality environments, leadership influence may depend less on direct compliance mechanisms and more on employees’ renewed confidence in the organization’s ability to manage safety threats.

Bridging the Intention–Practice Gap in Green Accounting Adoption: The Moderating Role of Environmental Ethics in Saudi Firms

2026-04-04T22:29:35+00:00

This study investigates the determinants of intention to adopt Green Accounting (GA) in Saudi firms to understand how intentions translate into actual GA practices as per the Theory of Planned Behavior (TPB). Moreover, the moderating role of Environmental Ethics (EE) is also tested in this relationship. Structural equation modeling is applied to data collected from 209 respondents by purposive sampling from accounting professionals, auditors, and finance managers. We find that attitude toward GA positively affects intention and actual practices of GA. Subjective norms, perceived behavioral control, perceived usefulness, and EE do not directly affect intention. However, intention positively predicts the practices of GA. In addition, EE has a positive direct effect on GA practices and also positively moderates the nexus between intention and actual GA practices. Thus, EE is found helpful in bridging the intention-practice gap. The model explains 61.8% of the variance in GA practices, which also demonstrates strong predictive relevance as per the results of Q². Based on findings, we suggest that Saudi firms foster positive managerial attitudes and strong environmental ethics, which could enhance GA practices, consequently, and could help in converting intentions into sustainability practices in the accounting system. Moreover, policymakers should embed ethical and environmental standards in corporate governance, which can help in bridging the intention-practice gap and support the Sustainable Development Goals.

Cultivating Innovation Readiness in Biology Education: The Mediating Roles of Plant Attitudes and Scientific Argumentation in Deep Learning and Cognitive Flexibility

2026-02-23T14:50:01+00:00

Innovation readiness has become an essential competency in biology education, enabling students to engage in evidence-based reasoning, problem-solving, and responsible scientific innovation. This study examined the relationships among cognitive flexibility, deep learning, plant attitudes, scientific argumentation, and innovation readiness among undergraduate Biology and Biology Education students. A cross-sectional survey was conducted with 538 students at Universitas Negeri Makassar, Indonesia, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Two structural models were compared to evaluate the contribution of plant attitudes to the predictive performance of the framework. The findings demonstrated that the inclusion of plant attitudes substantially improved the explanatory power of the model. Cognitive flexibility significantly predicted both plant attitudes and scientific argumentation, influencing innovation readiness primarily through indirect pathways. Deep learning emerged as the strongest predictor of innovation readiness through both direct and mediated effects. Plant attitudes significantly enhanced scientific argumentation and directly contributed to innovation readiness, while scientific argumentation further strengthened students’ readiness for innovation-oriented activities. Multi-group analysis revealed generally stable structural relationships across academic programs, although the effect of plant attitudes on innovation readiness differed significantly between Biology and Biology Education students. The study highlights the importance of integrating affective engagement with plants, deep learning strategies, and scientific argumentation practices to foster innovation readiness in biology education.

Integrating Artificial Intelligence in Higher Education Language Teaching: Insights from Academic Discourse

2026-05-11T20:13:54+00:00

This study aims to examine the integration of artificial intelligence (AI) in foreign language education within the broader context of digital transformation in higher education. Adopting a qualitative research design, the study employs inductive thematic analysis to explore insights obtained from academic round table presentations and panel discussions involving educators and experts from higher education institutions. The data consist of contributions from four round table presenters and six panel participants, through which prevailing pedagogical trends, opportunities, and challenges related to the implementation of AI in language teaching were identified. The findings indicate that artificial intelligence is widely perceived as a transformative pedagogical tool in foreign language education, supporting personalized learning, enhancing student engagement, and facilitating the development of language skills through adaptive and interactive technologies. Participants highlighted the evolving role of teachers, who increasingly act as facilitators and designers of learning experiences. In this context, AI integration was considered effective when it promotes higher-order thinking, learner autonomy, and collaboration. At the same time, concerns were raised regarding potential overreliance on AI, issues of academic integrity, and the growing need to develop students’ critical digital literacy. Furthermore, the study emphasizes the importance of aligning AI use with established pedagogical frameworks that prioritize knowledge construction and authentic learning. Importantly, it proposes an integrated perspective that connects AI-supported pedagogy with constructivist learning theory and ICT-based frameworks such as 21st Century Learning Design (21CLD), highlighting how AI can support knowledge construction in language education. Overall, the study offers discourse-based, context-specific insights and provides practical implications for educators and policymakers seeking to implement responsible and human-centered approaches to language teaching in higher education.

A Methodological Framework for Developing Polite Speech Culture and Reflective Competence in Education and Social Media Contexts

2026-02-02T20:09:50+00:00

With an upsurge in both online communication and societal turbulence, universities and educational systems face pressing challenges, including respect for diverse opinions and fostering civil discourse among students. To address this, a novel language-focused approach has been developed that uniquely integrates the concepts of polite speech culture with reflexive competence, providing both theoretical and practical insights into improving digital and educational communication. These objectives, thought to be especially pertinent in contemporary contexts, are now approached through a new methodological lens that promotes wider consideration. The broader conceptual framework encompasses a unified structure and cultural perspective. This study contributes by offering a theoretically grounded model that explicates the interaction between polite speech culture and reflexive competence, highlighting mechanisms that enhance communication effectiveness in educational and social media environments. The interactions of multiple factors at different levels impose further modifications to established concepts, extending their relevance to a wider variety of contexts. Such a wide-ranging framework supports endeavors across education and social media to impart an awareness of people’s rights to communicate freely and respectfully, as expressed through organized respect knowledge and speech skills.

Optimizing Dependability in Classroom Action Research Skill Assessment: A Multivariate Generalizability Theory Analysis of Alternative Measurement Designs

2026-03-19T11:08:14+00:00

Reliable assessment of classroom action research skill is essential for supporting valid absolute decisions in teacher education, particularly when performance assessments involve multidimensional constructs and rater-mediated judgment. This study investigated how alternative measurement designs influence the index of dependability and variance structure of classroom action research skill assessment scores within a multivariate generalizability theory (MGT) framework. Specifically, the study compared fully crossed and nested measurement designs and examined the number of raters required to achieve acceptable dependability for absolute decision-making. The participants consisted of 58 fourth-year student teachers majoring in primary education whose classroom action research reports were evaluated by four raters using a multidimensional assessment form aligned with the Plan–Act–Observe–Reflect (PAOR) framework and supported by double-layer scoring rubrics. Data analysis was conducted sequentially using the many-facet Rasch model (MFRM) to examine rater effects, followed by MGT-based generalization and decision studies. The findings showed that the fully crossed design produced a higher composite index of dependability than the nested design (Φ = .8468 vs .7823) and generated different composite universe score variance structures. Under the fully crossed design, three raters were sufficient to achieve acceptable dependability for individual-level absolute decisions, whereas the nested design required four raters to reach a comparable level. The study contributes to educational measurement literature by demonstrating that measurement design influences not only the magnitude of dependability but also the variance structure underlying multidimensional performance assessment scores. The findings further highlight the importance of aligning measurement design with the intended interpretation and use of assessment scores in teacher education contexts.

Generative Artificial Intelligence and the Development of Creative Thinking among University Students in Creative Disciplines

2026-02-17T05:54:04+00:00

The rapid advancement of artificial intelligence (AI) technologies has transformed higher education by expanding opportunities for personalized learning, creative exploration, and digital innovation. Despite growing interest in AI in education, limited research has examined its role as a pedagogical tool for developing students’ creative thinking, particularly within creative disciplines and in emerging educational contexts. This study investigates the impact of generative artificial intelligence tools on the development of creative thinking among students of creative specialties in higher education institutions in Kazakhstan. Drawing on theories of divergent thinking and creativity, the research adopts a mixed-methods design integrating quantitative and qualitative approaches to examine how AI-supported learning influences students’ fluency, flexibility, originality, and elaboration of ideas. The study involved the use of generative AI tools, including ChatGPT, Midjourney, DALL-E, and AIVA within the educational process of students in creative disciplines. The findings demonstrate positive changes in key dimensions of creative thinking, particularly in idea fluency, cognitive flexibility, and originality, when AI tools are integrated with structured pedagogical guidance and reflective learning activities. At the same time, the results indicate that the effectiveness of AI depends on meaningful pedagogical mediation, as unstructured use may encourage superficial creative engagement. The study contributes to the literature by positioning artificial intelligence not merely as a technological innovation but as a cognitive and pedagogical partner that can support the development of higher-order creative competencies. Furthermore, the research expands empirical understanding of AI integration in the context of Kazakhstan’s higher education system and provides practical implications for the design of AI-supported creative learning environments in developing educational systems.

Enhancing Student Engagement in Nanotechnology through STEM-Based Instruction: Evidence from a Quasi-Experimental Study in Higher Education

2026-01-18T15:34:07+00:00

The integration of STEM-based instructional approaches into advanced scientific fields such as nanotechnology is increasingly recognized as essential for improving student engagement and conceptual understanding in higher education. However, empirical evidence on its effectiveness in physics education remains limited. This study examines the impact of STEM-oriented, project-based instruction on undergraduate students’ interest in nanotechnology. A quasi-experimental design was implemented involving 108 second- and third-year physics students from three universities in Kazakhstan. Participants were divided into an experimental group (n = 53), which received STEM-based project and laboratory instruction, and a control group (n = 55), which was taught using traditional lecture-based methods over a 15-week semester. Student interest in nanotechnology was measured using a validated 20-item Likert-scale questionnaire with high reliability (Cronbach’s α ≥ 0.80), administered before and after the intervention. Pre-test results confirmed no statistically significant differences between groups (p > 0.05), ensuring baseline equivalence. Post-test findings demonstrated a marked improvement in the experimental group (+28 points) compared to the control group (+7 points). Statistical analysis using the Mann–Whitney U test confirmed a significant difference between groups (p < 0.001), with a large effect size (r ≈ 0.78). These results provide strong evidence that STEM-based, inquiry-driven instruction significantly enhances student engagement and interest in nanotechnology. The study contributes to STEM education literature by highlighting the effectiveness of experiential and interdisciplinary teaching strategies in fostering motivation toward emerging scientific fields. The findings also offer practical implications for curriculum developers and educators seeking to modernize science education through active learning methodologies.

AI-Driven Islamic Classroom Management in the Digital Era: The Roles of Neuro-Pedagogy, Spiritual Intelligence, and Innovative Teaching Performance

2025-10-13T18:35:41+00:00

The rapid advancement of digital technologies and artificial intelligence (AI) is reshaping educational systems worldwide, including Islamic education institutions that seek to preserve spiritual and ethical values while embracing pedagogical innovation. This study investigates the influence of digital technology integration, Islamic neuro-pedagogy, classroom environment, and teachers’ spiritual intelligence on Islamic classroom management and innovative teaching performance in madrasahs in Medan City, Indonesia. A quantitative research design was employed using structured questionnaires distributed to 120 teachers, and the collected data were analyzed through path analysis to examine direct and mediating relationships among variables. The findings reveal that Islamic neuro-pedagogy exerts the strongest positive effect on innovative teaching performance (β = 0.268), followed by digital technology integration (β = 0.253). Although classroom environment and spiritual intelligence demonstrate comparatively smaller direct effects, both significantly contribute to effective pedagogical practices and classroom interaction. Furthermore, Islamic classroom management plays a significant mediating role, strengthening the relationship between technological, cognitive, and spiritual dimensions and teachers’ innovative performance. The study proposes a holistic framework for AI-supported Islamic education that integrates neuroscience-informed pedagogy, digital learning technologies, and spiritual intelligence within value-based classroom management practices. These findings contribute theoretically to contemporary Islamic educational research and provide practical implications for educators, curriculum designers, and policymakers seeking to foster innovative, ethical, and spiritually grounded learning environments in the digital era.

Intergenerational Shifts in Equity Investment Behavior: From Traditional Media to Social Media Among Family Business Investors

2026-02-12T15:17:34+00:00

This study examines the changing patterns of behavioural decision-making in equity investments among family business investors, with a particular focus on the intergenerational shift from traditional media sources such as newspapers and television to digital and social media platforms. The study aims to understand how generational influence, digital literacy, and technological expectations affect behavioural intention and the quality of investment decision-making within family-owned businesses. Using a purposive sampling technique, data were collected from 227 respondents from family-owned enterprises through a structured questionnaire. The main variables considered in the study include performance expectancy, effort expectancy, social influence, sentiment, credibility, family generational influence, behavioural intention, and investment decision-making. The collected data were analysed using SPSS and AMOS. The analyses included reliability testing, correlation analysis, regression analysis, mediation analysis, and structural equation modelling (SEM). The findings reveal that second- and third-generation family investors show a stronger preference for social media platforms due to their higher level of digital fluency and familiarity with technology. Furthermore, behavioural intention was found to mediate the relationship between digital transformation factors and the quality of investment decision-making. The study highlights the growing influence of digital platforms and social media on investment behaviour among different generations in family businesses. The study provides practical implications for financial institutions, fintech firms, and policymakers in developing intergenerational digital literacy initiatives and creating user-friendly investment platform ecosystems within family businesses. The study also contributes to the existing literature by integrating technology adoption models with intergenerational behavioural finance perspectives and by positioning family generational influence as an important independent construct in understanding investment decision-making in family firms.

Interpersonal Relationships in Migrant Worker Families: An Integrated Psychological, Legal, and Pedagogical Model

2026-03-26T19:53:11+00:00

Parental labor migration affects the socio-psychological development of children in a holistic sense emphasizing emotional, social adjustment and stability of the family unit. The precise effects of parental absence on psychological outcomes have received little attention in Uzbekistan despite the existence of community mechanisms like the mahalla system. This study explores the socio-psychological effects of parental labor migration on school-age children and seeks to shed light on the effectiveness of institutionalized support programs. A cross-sectional mixed-methods design was used, involving 150 children (95 from high-migration regional areas and 55 from Tashkent). Quantitative data were collected using René–Gilles test on emotional and social adaptation, while qualitative data were collected through semi-structured interviews with children and families and expert questionnaires for professionals. There is a heightened emotional-social inadaptation among children of migrants, with 60% classified as moderate-to-high emotional risk. Institutional support was varying between regions, and it did not include rural areas in most cases. Qualitative data suggested inadequacies with family reintegration efforts and erratic professional intervention efforts. Findings underscore the need for structured socio-psychological support programs tailored to children affected by parental migration. There is proposed a scalable model that combines diagnostic assessment, targeted family interventions, and institutional reintegration programs to monitor the well-being of children on a systemic level, as well as to enhance family support systems in urban and regional settings.

Integrating Intellectual Capital and University Social Responsibility: Pathways to Institutional Empowerment in Higher Education

2025-12-29T12:25:40+00:00

Contemporary universities face increasing demands for transparency, social commitment, and academic excellence in increasingly complex and competitive environments. In this context, intellectual capital, university social responsibility, and institutional empowerment emerge as fundamental pillars for the strategic development of higher education institutions. This study aimed to analyze the importance of intellectual capital and social responsibility in universities as a strategic factor for empowerment in higher education. The bibliometric phase, based on publications indexed in Scopus, revealed sustained growth in global scientific production on these topics, as well as geographical and thematic gaps. The systematic review included 35 rigorously selected articles. It confirmed that intellectual capital strengthens organizational learning and innovation, that social responsibility improves institutional legitimacy and social relevance, and that empowerment fosters participatory governance and adaptability. The findings show that the interaction between these elements generates synergistic effects that improve institutional performance and support the development of more resilient and socially engaged universities. This study contributes to the theoretical consolidation of these constructs and offers empirical evidence that can guide university management policies and strategies. Future research should focus on regional comparative studies and longitudinal analyses to evaluate the long-term impact of integrated management approaches in diverse institutional contexts.

From Compliance to Reflection: Constructing Sustainability Reporting in the Public Sector through a Constructivist Grounded Theory Approach

2026-04-01T20:26:49+00:00

Sustainability reporting in the public sector is often positioned as a technical and compliance-based governance tool; however, its practical implementation remains fragmented, inconsistent, and highly context-dependent. This study reconceptualizes public sector sustainability reporting as a socially constructed governance practice shaped by institutional pressures, ethical considerations, and interorganizational interactions. Employing a constructivist grounded theory methodology supported by an exploratory sequential mixed-methods design, the study investigates how sustainability reporting is interpreted, enacted, and continuously reshaped within public organizations. The findings indicate that formal governance structures alone are insufficient to explain reporting practices. Instead, sustainability reporting emerges through iterative and interpretive processes involving moral accountability, negotiated transparency, legitimacy construction, and collaborative meaning-making among stakeholders. These processes collectively form what this study defines as reflective governance, a dynamic organizational capability characterized by reflexivity, dialogue, and continuous learning in interpreting sustainability information. Reflective governance operates as a mediating mechanism between institutional conditions and actual reporting practices, extending traditional institutional and accountability theories that often neglect interpretive and processual dimensions of governance. This study contributes to public sector accounting and sustainability literature by demonstrating that reporting quality is not solely determined by compliance with standards, but by the organization’s capacity for reflection and learning. Methodologically, it highlights the value of constructivist grounded theory in capturing the complexity of governance practices in real-world institutional settings. The study concludes that enhancing sustainability reporting requires strengthening organizational reflexivity, participatory interpretation, and learning-oriented governance rather than relying exclusively on formal disclosure frameworks.

Bridging Digital Awareness and Entrepreneurial Readiness: ICT-Enabled Entrepreneurship Among Omani Undergraduates

2026-04-20T21:14:43+00:00

Digital entrepreneurship (DE) has emerged as a key driver of innovation, economic diversification, and employment generation in the digital economy, with information and communication technology (ICT) serving as a critical enabler of entrepreneurial activity. This study examines Omani undergraduate students’ awareness of ICT-enabled digital entrepreneurship, their motivational orientation toward engaging in digital entrepreneurial activities, and the perceived challenges that hinder practical entrepreneurial participation. Using a quantitative diagnostic approach, data were collected from 380 students across four universities in Oman through a structured 30-item questionnaire. Descriptive and inferential statistical analyses were conducted using IBM SPSS Statistics to assess relationships among awareness, motivation, and perceived barriers. The findings reveal that students demonstrate relatively high conceptual awareness of ICT’s role in entrepreneurship and moderate-to-high motivational orientation toward digital entrepreneurial engagement. However, students report lower confidence in practical entrepreneurial competencies, particularly regarding risk-taking and implementation-related skills. Gender differences significantly influence both awareness and motivation, with female students demonstrating higher motivational orientation than male students, while both groups experience similar structural and practical barriers to ICT-enabled entrepreneurship. The study identifies a substantial gap between conceptual understanding and practical entrepreneurial readiness among undergraduate students. These findings contribute to the growing literature on digital entrepreneurship in higher education by highlighting the need for stronger integration of experiential learning, industry collaboration, mentorship, and practice-oriented entrepreneurial training within university curricula. The study also provides practical implications for policymakers and educational institutions seeking to strengthen digital entrepreneurial capacity in support of Oman Vision 2040 and the country’s broader goals of economic diversification and digital transformation.

Discriminant Analysis of Infant Feeding Patterns Among Infants Aged 6–24 Months in Al-Aflaj Governorate, Saudi Arabia

2026-03-14T18:54:43+00:00

Breastfeeding (BF) is the safest option for feeding infants in the first six months of a baby's life. But their rates are still low globally. This necessitates developing evidence-based interventions to support BF, which requires an understanding of the factors that affect infant feeding patterns. The current study was based on a conceptual framework that classifies determinants of infant feeding patterns into structural, cultural, psychological and physical, and institutional domains, consistent with contemporary maternal and child health theories. This is the first national study in the Al-Aflaj region of Saudi Arabia, where a cross-sectional study was conducted at Al-Aflaj General Hospital and healthcare centers. 653 infants, aged 6 to 24 months, were included in the final analysis. 653 infants, aged 6 to 24 months, were included in the final analysis. Results of discriminant analysis were presented as standardized coefficients to identify the factors significantly associated with infant feeding. Although patterns. It was categorized as three outcomes (3) practicing exclusive breastfeeding (EBF), (2) mixed BF, and (1) formula feeding. Results of the current study revealed that the rate of mixed feeding was 37.5%, followed by EBF at 35.5% and formula feeding at 27%. The discriminant analysis (DA) demonstrated a good fit and strong classification accuracy (91.4%). Strong positive predictors are colostrum feeding (0.985), accurate knowledge of the definition of EBF (0.670), antenatal care visits (0.620), rooming-in (24 hours) (0.568), BF initiation within three days (0.549), antenatal BF education (0.530), mode of delivery (0.524), Knowledge of EBF benefits (0.518), husband’s support and family (0.465. Conversely, the variables least likely to practice EBF include work and study pressures (-1.024), insufficient milk supply (-0.663), traditions and beliefs related to BF, (-0.537), and prelacteal feeding (-.340). Institutional determinants also demonstrated a positive effect on exclusive breastfeeding, and structural, cultural, and psychological determinants indicated a dual role of facilitating or hindering EBF. Considering the results of this study, a systematic program to advance EBF is recommended. Enhance prenatal and postnatal education by highlighting the advantages of colostrum, the need of starting breastfeeding early, and knowledge of BFHI. Create policies at work that allow working mothers to breastfeed, such as flexible scheduling, lactation breaks, and support for a six-month maternity leave requirement. Addressing misconceptions and cultural barriers through community assistance and counseling.

Toward a Risk-Calibrated Civil Liability Framework for Personal Data Breaches: A Comparative Study of Saudi, Jordanian, and EU Law

2026-05-02T17:23:25+00:00

This study provides a theory-driven comparative analysis of civil liability for personal data breaches across three comparative legal frameworks: Saudi law, Jordanian law, and the European Union’s data protection regime, with particular emphasis on the interaction between civil liability rules and personal data protection regulation, and the European Union General Data Protection Regulation (GDPR). It examines how these frameworks address key liability challenges arising from digital harms, including burden of proof, attribution of responsibility, non-material damages, and multi-party processing environments. Methodologically, the study adopts a functional comparative approach, complemented by a post-functional critical perspective that assesses the transferability of legal doctrines across jurisdictions. It develops a five-indicator analytical matrix to operationalize adequacy and effectiveness in civil liability systems, focusing on burden distribution, damage recognition, attribution mechanisms, preventive capacity, and judicial accessibility. Drawing on recent jurisprudence of the Court of Justice of the European Union (notably C-300/21 and C-340/21), the study identifies structural limitations in both Saudi and Jordanian regimes, particularly their continued reliance on traditional fault-based liability and limited doctrinal clarity regarding intangible harm and causation in complex digital environments. Building on these findings, the paper proposes a Risk-Calibrated Accountability Model (RCAM), which integrates a calibrated fault standard based on objective security benchmarks, a conditional presumption of liability, a structured approach to non-material damages, and layered joint attribution for distributed data processing. The model is theoretically grounded in accountability theory and moderate strict-liability principles, while remaining aligned with the institutional and doctrinal structures of Saudi and Jordanian law. The study concludes with targeted legislative and regulatory recommendations to enhance the effectiveness and coherence of civil liability for data breaches in both jurisdictions.

An Integrating AI-Driven Hyper-Personalization, Customer Experience, and E-Trust to Explain E-Loyalty in Indonesian E-Commerce: A PLS-SEM Study

2026-03-28T19:10:32+00:00

This study extends TAM and Relationship Marketing Theory by positioning hyper-personalization as a central explanatory mechanism linking AI capability to e-loyalty. The sample in this study consisted of 400 respondents, aged 18 years and over, who had shopped online for at least the past month. The data analysis technique used SEM analysis with the Smart PLS application. The results showed that of the twelve proposed hypotheses, ten were accepted and two were rejected. Artificial intelligence plays a crucial role in creating hyper-personalization, significantly enhancing the customer experience. Customer experience and hyper-personalization also directly strengthen customer loyalty by providing relevant and personalized experiences. E-trust serves as a crucial foundation for creating a sense of security and trust in customers, thus increasing loyalty. However, its role as a moderator of the relationship between hyper-personalization and e-loyalty is insignificant.

Strategic Stakeholder Integration in the AI Era: A Bibliometric Mapping of the Shift from Intelligent Tutoring to Generative Educational Systems

2026-05-14T15:21:52+00:00

Higher education faces social and technological challenges driven by the democratization of the generative artificial intelligence (GenAI). The generative shockwave has marked a major shift in traditional learning from centralized and controlled Intelligent Tutoring Systems (ITS) to decentralized and unmanaged Shadow IT. To rigorously map higher education institution transition during the generative shockwave, the current study used a pre-defined protocol for an exploratory PRISMA-based bibliometric analysis of 459 academic documents retrieved from the Web of Science Core Collection. Its main findings highlight the magnitude of this shift, as 82% of the considered articles were published in 2024 and 2025, confirming the generative AI shockwave. Thematic mapping shows that while the key problems with artificial intelligence in education are universally recognized, higher education institutions lack adequately adapted policies to manage them. Furthermore, important psychological factors that influence technology acceptance, such as students' self-efficacy and mental strain, require special academic interest. By considering the dual theoretical lenses, using a scalar analysis approach, of the micro-level Technology Acceptance Model (TAM) and the macro-level Institutional Theory, the current study highlights the relationship between AI-based learning evolution and the inefficient management of AI risks through top-down IT systems. Instead, a collaborative approach that integrates stakeholders must be built. By working with localized institutional entrepreneurs and providing appropriate socio-technical support, universities can bridge gaps, meet the expectations of modern students, sustain their legitimacy, and adapt to the inevitable challenges posed by artificial intelligence, especially in an adaptive personalized learning ecosystem.