Lim Chee Ann

Background of study: Increased global attention to sustainability has compelled companies to adopt Environmental, Social, and Governance (ESG) principles in their operations. However, the rise of greenwashing—misleading sustainability claims—has undermined investor trust and market transparency. Strong corporate governance and regulatory frameworks are expected to prevent such practices, yet challenges persist. Aims and scope of paper: This paper explores how corporate governance disclosure and environmental regulations shape investor perceptions of greenwashing. It also evaluates the effectiveness of existing regulations in preventing companies from engaging in deceptive ESG reporting. Methods: This study employs a qualitative approach through a comprehensive literature review, analyzing academic journals, regulatory reports, sustainability disclosures, and relevant case studies. The data were examined using content analysis to identify patterns and critical themes related to transparency, investor trust, and regulatory enforcement. Result: The findings indicate that although formal ESG regulations exist, gaps in enforcement, lack of independent audits, and inconsistency with international standards (e.g., GRI, SASB) still allow greenwashing to occur. Investor perception is significantly influenced by the clarity and credibility of ESG reports. Institutional investors and media play vital roles in pressuring companies toward transparency. Conclusion: Effective ESG regulation requires more than formal compliance; it demands robust enforcement, third-party audits, and alignment with global reporting standards. Investor engagement and stakeholder oversight are crucial in mitigating greenwashing risks. Strengthening transparency mechanisms will foster greater trust and support sustainable investment decisions.

Artificial Intelligence (AI) is revolutionizing economies and societies, offering profound implications for emerging economies. This chapter explores AI’s role in enhancing economic and social sustainability, focusing on productivity, employment, sector-specific impacts and ethical considerations. The transformative potential of AI is evident in its ability to automate tasks, thereby increasing productivity and economic growth. For instance, AI’s application in the finance sector streamlines fraud detection and risk management, while in manufacturing, AI-powered robots optimize production and enhance quality control. Despite these benefits, AI also poses significant challenges, such as the displacement of human labour and job market upheavals. Addressing these challenges requires strategic public policies and reskilling initiatives to prepare the workforce for new, AI-driven job roles. Additionally, the chapter delves into the ethical and social changes brought about by AI, including issues related to algorithmic transparency, bias and data protection. A comparative study of AI’s impact in developed countries, such as Japan, the United States and Germany, provides insights that can inform the implementation of AI in emerging economies. The study emphasizes the importance of ethical and legal frameworks in mitigating negative consequences and ensuring responsible AI use. By leveraging AI responsibly, emerging economies can achieve sustainable development that balances technological advancement with human-centric values. This chapter outlines a framework for harnessing AI’s potential while addressing its associated challenges, aiming to promote equitable and beneficial outcomes for all stakeholders.

HRMARS is well established journal publisher based in Pakistan. It is publishing prominent journals in social sciences since 2011.

The aim of the paper is to propose a comprehensive conceptual framework of open and distance learning (ODL) for economics courses to enhance the effectiveness and accessibility of economics education. The rise of ODL, fueled by advances in digital technology, has significantly transformed higher education, providing flexible learning opportunities that transcend geographical limitations. However, teaching economics in an ODL environment presents unique challenges, particularly in maintaining student engagement and delivering complex theoretical content. This research draws from literature review and key concepts to conceptualise a model for ODL in economics undergraduate teaching and learning. The proposed framework emphasizes the integration of synchronous and asynchronous learning methods, the use of Learning Management Systems (LMS) and the incorporation of interactive technologies such as virtual and augmented reality to facilitate an engaging and effective learning experience. Additionally, the framework addresses curriculum design, student engagement and assessment strategies, proposing a balanced approach that combines traditional teaching methods with innovative digital tools. By focusing on the goal of teaching students to "think like an economist," this framework provides a structured approach to ODL that enhances both the delivery and the reception of economic education. The paper’s recommendations are to modernize the curriculum, strengthen institutional support and optimize the use of digital tools in the teaching of macroeconomics. This research contributes to the broader discourse on the potential of ODL to transform economics education in Malaysia and beyond.

Mitigating global warming has been a challenge, and policymakers are responding to this issue by strengthening the commitment to enhance the renewable energy target from 20 to 31 percent in 2025 for Malaysia. However, adopting renewable energy in stages based solely on microeconomic factors, such as the price of energy, is insufficient. Thus, it is essential to investigate the macroeconomic variables that influence the share of renewable energy in Malaysia. In detail, this study introduces selected macroeconomic indicators, including gross domestic investment, domestic investment, foreign direct investment, trade openness, urbanization, financial development, and carbon emissions level, and their impact on renewable energy in Malaysia. The study utilized ARDL (Auto-Regressive-Distributed Lag) estimation based on annual time series data spanning 50 years of observations, beginning in 1971 and ending in 2020. Long-run elasticities show that greater economic development and urbanization increase the proportion of renewable energy. In contrast, increased foreign investment, trade liberalization, and carbon emissions could reduce the use of these clean energies. This paper concludes with a policy recommendation that could assist the country in achieving its goal of implementing a low-carbon, renewable energy-focused state policy.