Employee Perspectives on the Implementation of Servant Leadership in a Local Automotive Company in Indonesia: A Qualitative Case Study

The dynamic transformation of the business environment has encouraged organizations to adopt leadership models that are flexible and human-centered. This study examines the implementation of servant leadership from the perspective of employees in a local automotive company operating in Bandar Lampung, Indonesia. Rooted in Greenleaf’s (1970) framework, servant leadership emphasizes leaders’ commitment to serving employees through ten core characteristics, including listening, empathy, healing, awareness, persuasion, conceptualization, foresight, stewardship, commitment to employee growth, and community building. This research employs a qualitative phenomenological approach with a case study design. Data were collected through in-depth interviews, non-participant observation, and document analysis, and were analyzed using the interactive model of Miles, Huberman, and Saldaña (2020). The findings reveal that servant leadership is only partially implemented within the organization, with four characteristics conceptualization, foresight, healing, and community building being consistently practiced. Key barriers to full implementation include the predominance of indirect communication patterns, a stronger emphasis on short-term business targets over human resource development, and the absence of systematic leadership training programs. The study concludes that the application of servant leadership in non-corporate local firms requires contextual adaptation, particularly in organizations characterized by family-oriented management structures and the socio-cultural dynamics of Indonesian business practices. These findings contribute to the servant leadership literature by highlighting the contextual limitations and practical challenges of implementing human-centered leadership models in small and medium-sized enterprises in emerging economies

Integrating AI-Assisted Speaking Platforms to Enhance English Speaking Skills among Polytechnic Students

English speaking skills are essential for polytechnic students to meet the communicative demands of an increasingly globalized workforce. However, many students face difficulties in developing oral proficiency due to limited speaking opportunities, low confidence, and anxiety in classroom settings. This study investigates the integration of an AI-assisted speaking platform to enhance English speaking skills among polytechnic students. Employing a descriptive qualitative research design, the study was conducted over four instructional meetings in an English for Technique course and involved 60 students from two classes. Data were collected through classroom observations, questionnaires, and analysis of students’ speaking practice supported by feedback provided through the AI-assisted speaking platform. The findings indicate that the platform supported the development of key speaking components, particularly pronunciation, fluency, and grammatical awareness, by enabling repeated and self-paced practice. In addition, the use of AI-assisted speaking contributed to increased speaking confidence and learner autonomy through immediate and intelligible feedback. Despite these positive outcomes, several challenges were identified, including technical constraints, limitations in interactional naturalness, and the need for pedagogical scaffolding. The study concludes that AI-assisted speaking platforms can serve as effective supplementary tools for enhancing English speaking instruction in polytechnic education when thoughtfully integrated into classroom practice

A Comparative Policy Analysis of Education Systems and TVET Teacher Competencies in Indonesia and Malaysia

Educational systems and the competence of Technical and Vocational Education and Training (TVET) teachers play a crucial role in shaping the quality of human resources and national competitiveness. This study aims to comparatively analyze the education systems and TVET teacher competencies in Indonesia and Malaysia, two neighboring countries with similar cultural backgrounds but different educational governance and policy orientations. The study adopts a qualitative descriptive approach based on document analysis of laws, regulations, policy reports, and relevant literature related to national education systems and TVET teacher development in both countries. The findings indicate that Indonesia and Malaysia differ significantly in terms of educational structure, governance, funding mechanisms, and curriculum implementation, particularly at the secondary and vocational education levels. Malaysia demonstrates a more centralized and systematically evaluated education policy framework, supported by higher public investment in education. In contrast, Indonesia faces challenges related to educational quality, equity, and consistency in policy implementation. At the TVET level, both countries encounter similar issues, especially regarding teacher quality, uneven distribution of vocational teachers, and limited industry experience among educators. In Indonesia, the Professional Teacher Education Program (PPG) is expected to address shortages and improve the quality of vocational teachers. Meanwhile, Malaysia emphasizes the Modern Apprenticeship or dual system to enhance teachers’ industry exposure and practical competence. Despite differences in terminology, both countries recognize four essential domains of TVET teacher competence: pedagogical, professional, personal, and social or communication competence. The study concludes that strengthening industry collaboration and continuous professional development is essential to improving TVET teacher competence and aligning vocational education outcomes with labor market needs

Leverage, Sales Growth, and ESG as Determinants of Financial Performance (Moderating Analysis of Board of Commissioners Size in Manufacturing Companies in Indonesia)

This study examines the effects of leverage, sales growth, and Environmental, Social, and Governance (ESG) disclosure on the financial performance of manufacturing companies in Indonesia, with board size as a moderating variable. The research is motivated by the need to understand how internal financial and non-financial factors influence firm performance in a dynamic economic environment. A quantitative associative approach is employed using secondary data obtained from annual reports and sustainability reports of consumer goods manufacturing companies listed on the Indonesia Stock Exchange during the 2020–2024 period. The data are analyzed using panel regression and moderated regression analysis. The results indicate that leverage has a negative and significant effect on financial performance, suggesting that higher debt levels reduce profitability. Sales growth, however, does not have a significant effect, implying that increased revenue does not necessarily translate into improved financial outcomes. In contrast, ESG disclosure shows a positive and significant effect, highlighting the importance of sustainability practices in enhancing firm performance. Furthermore, board size is not found to moderate the relationships between leverage, sales growth, ESG, and financial performance, indicating that the effectiveness of corporate governance depends more on the quality of oversight rather than the number of board members. Overall, this study emphasizes the importance of optimal capital structure and ESG implementation in improving financial performance, while also providing insights into the limited moderating role of board size in the manufacturing sector

GARCH-M Approach for Energy Stock Volatility Estimation in the LQ45 Index

Stock price movements in the energy sector in Indonesia often exhibit high volatility, especially for stocks listed in the LQ45 Index. This high volatility is caused by vulnerability to fluctuations in global commodity prices, energy transition issues, and regulatory changes, which in turn pose challenges in investment decision-making and risk management. This study aims to estimate the volatility of energy stocks in the LQ45 Index using the Generalized Autoregressive Conditional Heteroskedasticity in Mean (GARCH-M) approach. This model was chosen because of its ability to dynamically model return variance (volatility) while linking it to expected returns, thus enabling a direct analysis of the risk-return trade-off. The data analyzed are daily returns from January 17, 2020, to December 27, 2024, for eight energy stocks in the LQ45 Index: ADRO, BRPT, ITMG, MEDC, PGAS, PGEO, PTBA, and UNTR. The analysis was conducted by building the most optimal GARCH-M model and evaluating the estimation results through statistical criteria.  The research results are expected to demonstrate significant volatility persistence in energy stocks, while providing strong evidence of the link between increased risk and expected returns. Therefore, the application of the GARCH-M model is expected to make a significant contribution to understanding the risk-return dynamics in the domestic energy sector and provide a basis for investors and portfolio managers in formulating more adaptive strategies

The Effect of Financial Literacy, System Security, and Accounting Information System Quality on Transaction Effectiveness in Mobile Banking Usage

The development of Mobile Banking services requires reliable information systems to support the effectiveness of digital financial transactions. This study aims to analyze the effects of financial literacy, system security, and accounting information system quality on the effectiveness of Mobile Banking transactions. This research employs a quantitative approach using a survey method, with data collected through questionnaires distributed to Mobile Banking users. Data analysis was conducted using Structural Equation Modeling–Partial Least Squares (SEM-PLS). The results indicate that, partially, financial literacy and system security do not have a significant effect on the effectiveness of Mobile Banking transactions. In contrast, the quality of the accounting information system has a positive and significant effect on transaction effectiveness and emerges as the most dominant variable. Simultaneously, financial literacy, system security, and accounting information system quality have a significant effect on the effectiveness of Mobile Banking transactions, with a coefficient of determination of 67.1%. These findings emphasize that the quality of accounting information systems plays a crucial role in enhancing the effectiveness of Mobile Banking transactions; therefore, banks need to prioritize the development of system quality to improve digital service performance

The London Exodus: A Spatial Analysis of Public Health Shocks and Economic Drivers of Internal Migration During the COVID-19 Pandemic

The COVID-19 pandemic in 2020 triggered a significant urban exodus in major global cities, shifting internal migration patterns in unprecedented ways. This study investigates the determinants of internal net migration across 33 London boroughs to understand the drivers behind this population displacement. Utilizing a spatial econometric framework, the research integrates public health indicators (COVID-19 cases), economic variables (housing prices and GDP), and geographic characteristics (population density and distance to the city center) into an enriched Ordinary Least Squares (OLS) model. The methodology is validated through rigorous diagnostic testing, including Heteroskedasticity-Consistent (HC1) standard errors and spatial autocorrelation checks (Moran\u27s I), confirming that spatial feature engineering sufficiently captures geographic dependencies. The results reveal that the public health shock was the primary driver of the exodus; total COVID-19 cases exhibited a highly significant negative correlation with net migration, indicating that boroughs with higher infection burdens experienced larger population outflows. Population density acted as a secondary push factor, while traditional economic drivers such as housing prices and regional GDP were statistically insignificant. These findings suggest a temporary paradigm shift where immediate health security outweighed economic maximization in residential location decisions during the crisis

A Conceptual Framework for Developing Appropriate Technology Based on Local Needs to Promote Sustainable Community Independence and Welfare

Appropriate technology has emerged as a strategic approach to address community development challenges, particularly in resource-constrained environments. However, many technology-based initiatives fail due to a mismatch between proposed solutions and actual community needs, as well as limited integration of local potential and participation. This study aims to develop a conceptual framework for appropriate technology that is grounded in community needs, local resources, and participatory principles. The study adopts a qualitative and conceptual approach by synthesizing findings from previous literature related to community-based development and appropriate technology. The framework is structured through three main stages: identifying community needs, analyzing local potential and resources, and designing appropriate technology based on user-centered and context-based principles. In addition, the framework incorporates participatory processes and multi-stakeholder collaboration to enhance implementation effectiveness. The results indicate that appropriate technology designed with simplicity, affordability, and adaptability can improve relevance, usability, and sustainability. The integration of local materials, skills, and cultural values strengthens community self-reliance, while participatory approaches foster ownership and increase adoption. Furthermore, the proposed framework demonstrates potential impacts on both economic and social dimensions, including increased productivity, expanded economic opportunities, improved skills, and stronger community engagement. In conclusion, this study highlights that appropriate technology should be viewed not only as a technical solution but also as a strategic tool for empowering communities and supporting sustainable development. A holistic approach that integrates local context, resources, and participation is essential to ensure long-term success and scalability

Enhancing Community Economic Independence through Capacity-Building Training Services: The Mediating Role of MSME Development Strategies

The role of Micro, Small, and Medium Enterprises (MSMEs) in strengthening community economic independence has become increasingly important, particularly in developing countries. However, many MSMEs still face challenges related to limited managerial capacity, low financial literacy, and ineffective business strategies. This study aims to analyze the effect of capacity-building training services on community economic independence, with MSME development strategies acting as a mediating variable. A quantitative approach was employed using Structural Equation Modeling–Partial Least Squares (SEM-PLS) to test the relationships among variables. The results indicate that capacity-building training services have a significant positive effect on MSME development strategies and community economic independence. Furthermore, MSME development strategies significantly influence economic independence, demonstrating their role in improving business performance and sustainability. The mediation analysis reveals that MSME development strategies partially mediate the relationship between training services and economic independence, indicating that training becomes more effective when translated into practical business strategies. This study highlights the importance of integrating training programs with strategic implementation to achieve sustainable economic outcomes. The findings provide both theoretical and practical contributions by emphasizing the role of strategy as a key mechanism in transforming capacity building into economic independence. Therefore, policymakers and practitioners are encouraged to design training programs that focus not only on knowledge transfer but also on the development of actionable business strategies

From Concept Image to Computational Thinking: A Design-Based Research on Python-Integrated Mathematics Learning

The increasing demand for computational thinking (CT) in mathematics education requires instructional designs that meaningfully connect abstract mathematical concepts with algorithmic reasoning. Grounded in the theory of concept image, this study investigates how Python-integrated learning activities can foster students’ mathematical understanding while simultaneously supporting the development of computational thinking. Using a Design-Based Research (DBR) methodology, this study was conducted across three iterative cycles involving undergraduate mathematics students and how Python-integrated learning activities can enrich students\u27 mathematical understanding while simultaneously developing CT skills. The study was conducted across three iterative cycles in a Calculus II, Integration course involving twenty-six mathematics education students PGRI University of Yogyakarta. Data were collected through concept image mapping, CT performance assessments, classroom observations, and the analysis of Python code artifacts. The finding indicate that Python-assisted dynamic visualization facilitated a transition from static, procedural understanding toward deep, relational mental representations. Programming activities were proven to strengthen abstraction and algorithmic reasoning capabilities, where code serves as an externalization of students\u27 concept images. This study yields three key instructional design principles: Concept-First Coding, Representational Fluidity, and Reflective Alignment. In conclusion, Python integration designed as a "cognitive bridge" effectively transforms mathematical intuition into formal-computational understanding that is transferable to complex problem-solving contexts. By leveraging programming as a representational medium, educators can create rich, interactive learning ecosystems where students actively construct knowledge, refine mental models, and develop transferable cognitive competencies. Future directions may include expanding these practices across disciplines, refining assessment models for CT in text-based programming, and investigating long-term retention and applicability of learned skills beyond academic settings