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This study aims to conduct a systematic literature review and bibliometric analysis on Transformational Leadership (TL), based on empirical research. Despite extensive studies on TL in recent decades, comprehensive research remains limited. The methodology used is a Systematic Literature Review (SLR) of articles containing “Transformational Leadership” in the title, abstract, or keywords, sourced from the Scopus database, which yielded 1,297 publications from 1977 to 2025. The data were analyzed using VOSviewer software. The findings suggest that TL is an innovative model in vocational education, bridging industrial systems with academic environments for authentic, practice-based learning. However, challenges include limited resources, insufficient instructor training, and inadequate institutional support. Recent innovations, such as advanced ICT, holographic technology for real-time interaction, and digital twins for process optimization, have enhanced the model's effectiveness. The study also discusses the conceptual framework of TL. This research uses the Scopus database, and future studies could broaden its scope by incorporating other databases like Web of Science. Practically, the study’s findings suggest integrating modern pedagogical strategies, including gamification, simulation, and project-based learning, to enhance student engagement and understanding of manufacturing processes. Socially, it encourages educational institutions to invest in infrastructure, strengthen industry partnerships, and provide continuous instructor training. This study highlights the growing global research on TL and calls for deeper exploration of the topic in existing literature.

This study aims to systematically review various studies that discuss the role of entrepreneurship education in developing students’ entrepreneurial spirit at the Senior High School (SMA) and Vocational High School (SMK) levels. The method used is the Systematic Literature Review (SLR), guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The reviewed articles cover publications from 2019 to 2025. Based on the selection of 20 scientific articles, the findings indicate that entrepreneurship education plays an important role in enhancing students’ creativity, innovation, self-confidence, and independence. The most effective learning strategies include project-based learning, business simulations, and collaboration with the industrial sector. In addition, teachers play a crucial role as facilitators in fostering an entrepreneurial mindset. The challenges identified include limited resources, insufficient teacher training, and suboptimal school policy support. Overall, entrepreneurship education has been proven to make a significant contribution to shaping entrepreneurial character and preparing students to face the challenges of the workforce.

This study aims to systematically examine the influence of digital literacy on the learning outcomes and 21st-century skills of high school students. The method used is a Systematic Literature Review (SLR) following the PRISMA guidelines. Data sources were obtained from various academic databases, including Google Scholar, ERIC, ScienceDirect, and SpringerLink, with publications ranging from 2019 to 2025. A total of 30 articles were selected based on predetermined inclusion and exclusion criteria. The analysis was conducted using a thematic approach to identify patterns, relationships, and the contribution of digital literacy to learning outcomes and the development of 21st-century skills, such as critical thinking, collaboration, communication, and creativity. The synthesis results show that digital literacy has a significant influence on improving learning outcomes and strengthening 21st-century competencies. This study emphasizes the importance of integrating digital literacy into secondary school curricula and teacher training to support effective 21st-century learning.

International Micro, Small and Medium Enterprises (MSMEs) face significant challenges in improving global competitiveness due to limited resources and access to effective market analysis, despite contributing 45% to the global economy (OECD, 2025). This research aims to develop an integrated machine learning (ML) model with a mixed-methods approach to optimise cross-border MSME market analysis. A combination of quantitative (transaction data analysis of 500 Indonesian export MSMEs 2020-2024 using XGBoost and SEM-AMOS) and qualitative (interviews with 15 MSME players) methods revealed that the XGBoost model achieved 89% accuracy in predicting market trends, with key variables including social media sentiment (28%) and exchange rate fluctuations (19%). Qualitative results show that 65% of MSMEs face cross-border regulatory barriers that ML models do not detect. The findings extend the Resource-Based View theory by validating AI-driven market intelligence as a strategic asset (β = 0.67, p 0.7. This research highlights the importance of technology integration and contextual adaptation in the digital transformation of MSMEs.