Global Academy of Multidisciplinary Studies

The impact of fiscal loss compensation and corporate governance on tax avoidance: The moderating role of foreign share ownership

Muhammad Daniel NA — 2025-08-28

Purpose: This study examines the influence of fiscal loss compensation and corporate governance, proxied by independent commissioners and the audit committee, on tax avoidance, with foreign ownership as a moderating variable in Indonesian manufacturing companie.

Research/methodology: A quantitative design was applied using purposive sampling of 65 manufacturing companies listed on the Indonesia Stock Exchange during 2020–2024, producing 280 valid observations. Data were collected from financial statements accessed via the IDX and company websites. The analysis employed descriptive statistics, classical assumption tests, multiple regression, and moderated regression analysis (MRA).

Results: The findings reveal that fiscal loss compensation significantly increases tax avoidance, while independent commissioners and the audit committee reduce it. Foreign ownership does not directly affect tax avoidance but moderates the relationships. Specifically, foreign ownership weakens the negative effects of independent commissioners and the audit committee on tax avoidance, whereas it does not moderate the relationship between fiscal loss compensation and tax avoidance.

Conclusions: Corporate governance mechanisms remain crucial in mitigating tax avoidance, but the presence of foreign shareholders creates complex dynamics that may undermine governance effectiveness.

Limitations: The study focuses only on manufacturing firms within a five-year period and relies on secondary data, limiting generalization across industries and contexts.

Contribution: This research contributes to the literature by integrating fiscal loss compensation, corporate governance, and foreign ownership into tax avoidance studies in emerging markets. Practically, the findings offer guidance for policymakers and investors to enhance governance mechanisms and reduce tax avoidance risks.

Digital module development of islamic education to improve student independence in learning at middle school program

Ahmad Bukhori — 2025-10-14

Purpose: This study aimed to identify the need, design, validity, practicality, and effectiveness of developing digital modules for Islamic Religious Education to enhance students’ learning independence.

Research methodology: This study examines a type of research and development (R&D) and develops a digital module for Islamic Education using the ADDIE model (analysis, design, development, implementation, evaluation). A learning independence questionnaire was administered to 70 students at Insan Cendekia Madani Middle School, Serpong, to assess the effectiveness of the module delivered via an online platform.

Results: The results indicate the need for a digital Islamic Religious Education module to enhance students' learning independence. The design produced a module, supporting tools, and research instruments. Validation tests confirmed the validity of the module based on expert evaluations.

Conclusion: The developed digital Islamic Religious Education module is a valid and potentially effective tool for promoting student learning independence. The structured design and integration with online platforms support interactive, flexible, and self-paced learning, which aligns with current educational demands.
Limitation: This research was limited to a single school context with a relatively small sample size of 70 students, which may affect the generalizability of the findings to other regions or educational settings. Furthermore, this study primarily measured short-term learning independence without assessing its long-term impact.
Contribution: This study contributes to the growing body of literature on digital learning in Islamic Religious Education by offering a validated and practical module design based on the ADDIE model. It provides a replicable framework for educators and policymakers seeking to enhance independent learning through technology-assisted instruction in similar educational contexts in the future.

Autonomy & accountability in 4IR: Ethical implications of AI driven automation in Sustainable Business

Moutusi Tanha — 2025-10-15

Purpose: The purpose of this study is to explore how AI in Industry 4.0 is impacting work and business, posing ethical concerns. It addresses labor market disruptions, organizational transformation, sustainability, algorithmic bias, data privacy, and job displacement ethics. The report examines how AI adoption might help inclusive economic development and SDGs.

Research Methodology: The research uses mixed methodologies, incorporating qualitative and quantitative data. Secondary sources include 2019–2025 academic journal articles, government papers, industrial publications, and international databases. The research uses a systematic literature review, thematic analysis, statistical evidence from robotics adoption databases, and case studies in manufacturing, logistics, and service industries to discover patterns. The integration of theory and practice employs descriptive-exploratory approaches.

Results: Results indicate rising global use of industrial robots and AI, with South Korea, Singapore, and Germany exhibiting the highest robot density. AI automates monotonous activities and creates hybrid professions that demand digital and analytical talents. AI-adopting companies are becoming more flexible and data-driven. However, ethical issues such algorithmic bias in recruiting and decision-making, surveillance technology privacy threats, and low-skilled worker job displacement persist.

Conclusions: AI has promise to improve productivity, efficiency, and sustainability, but requires strong governance, ethical frameworks, and ongoing reskilling. Without controls, inequities and ethical problems may grow

Limitations: The study depends on secondary data and literature evaluation, with minimal original field research for context-specific insights.

Contribution: This study advances ethics, management, sustainability, and offers practical AI recommendations for stakeholders.