This study investigates the influence of Environmental, Social, and Governance Disclosures (ESGD) on the profitability of firms, using a sample of 385 publicly listed companies on the Thai Stock Exchange. Data from 2018 to 2022 is sourced from the Bloomberg database, focusing on ESGD scores as indicators of companies’ ESG commitments. The study utilizes a structural equation model to examine the relationships between independent variables; ESGD, Earnings Per Share (EPS), Debt to Assets ratio (DA), Return on Investment Capital (ROIC), Total Assets (TA), and dependent variables Tobin’s Q (TBQ) and Return on Assets (ROA). The analysis reveals a positive relationship between ESGD and TBQ, but not with ROA. Further exploration is conducted to determine if different ESGD levels (high, medium, low) yield consistent effects on TBQ. The findings indicate discrepancies: high and medium ESGD levels are associated with a negative impact on TBQ when EPS increased, whereas low ESGD levels correlate with an increase in TBQ with rising EPS. This nuanced approach challenges the conventional uniform treatment of ESGD in previous research and provides a deeper understanding of how varying commitments to ESG practices affect a firm’s market valuation and profitability. These insights are crucial for firm management, highlighting the importance of ESGD in relation to other financial variables and their effects on market value. This study offers a new perspective on ESGD’s impact, emphasizing the need for differentiated strategies based on ESG commitment levels.

In this study, we are interested in WCM (working capital management) strategies and profitability in the UK furniture manufacturing sector. Observing the period from 2007 to 2023 of public companies panel data has found that extreme (aggressive and conservative) and moderate (moderate) WCM approaches are associated with firm performance. The results indicate that a conservative WCM investment policy augments liquidity and profitability and thereby confirms that maintaining liquidity is conducive to operational efficiency. Novel to the literature and considering economic externalities and technological progress, the analysis carries important implications for academics and working capitalists concerning profitability enhancement via better WCM.

Our study investigates the relationship between firm profitability, board characteristics, and the quality of sustainability disclosures, while examining the moderating effects of financial leverage and external audit assurance. A key focus is the distinction between Big 4 and non-Big 4 audit firms. Using data from Malaysia’s top 100 publicly listed organizations from 2018 to 2020, we analyze sustainability reports based on the Global Reporting Initiative (GRI) standards. Unexpectedly, our results indicate a negative association between firm profitability and board characteristics, challenging traditional assumptions. We find that non-Big 4 audit firms significantly enhance sustainability disclosure quality, contradicting the widely held belief in the superiority of Big 4 firms. Our finding introduces the “Big 4 dilemma” in the Malaysian context and calls for a reassessment of audit firm selection practices. Our study offers new perspectives on the strategic role of board composition and audit firm selection in advancing sustainability disclosures, urging Malaysian organizations to evaluate audit firms on criteria beyond the global prestige of Big 4 firms to improve sustainability reporting.

This paper examines the influence of green accounting and environmental performance on stock prices, focusing on Indonesia’s mining sector. It aims to understand whether these factors, along with profitability, impact the growth of stock prices. The study is grounded in stakeholder, legitimacy, and signal theories, emphasizing the role of stakeholder support and environmental responsibility in company survival. The research explores the conflicting results of previous studies on the impact of green accounting on stock prices. It uses various indicators, such as environmental costs for green accounting and the PROPER rating system, to measure environmental performance. The study also considers profitability as a moderating variable. The population in this research is all mining companies listed on the Indonesia Stock Exchange in 2017–2021. The sample was selected based on purposive sampling with several criteria. Multiple regression analysis and hypothesis testing were used to analyze the data. Key findings suggest that green accounting positively influences stock prices, while environmental performance has a negative effect. Profitability positively affects stock prices but does not significantly moderate the impact of green accounting on stock prices. However, it does enhance the relationship between environmental performance and stock prices. The study concludes that companies should increase disclosures related to green accounting and environmental performance, which are crucial for long-term investment considerations.

This study investigates the impact of toll road construction on 59 micro, small, and medium enterprises in Kampar, Pekanbaru, and Dumai cities. The research aims to analyze the economic and environmental effects of infrastructure expansion on businesses’ profitability and sustainability, providing insights for policymakers and stakeholders to develop mitigation strategies to support MSMEs amidst ongoing infrastructure development. Structural equation modeling, spatial environmental impact analysis, and qualitative data analysis using five-level qualitative data analysis (FL-QDA) were all used together in a mixed-methods approach. Data collection involved observations, interviews, questionnaires, and geospatial analysis, including the use of a Geo-Information System (GIS) supported by drone reconnaissance to map affected areas. The study revealed that the toll roads significantly enhanced connectivity and economic growth but also negatively impacted local economies (β = 0.32, R² = 0.60, P-value ≤ 0.05). and the environment (β = 0.34, P-value ≤ 0.05), as 49% of respondents experienced a 50% decrease in profitability. To mitigate the risk of impact, policymakers should prioritize the principle of prudence to evaluate the significance of mitigation policy implementation (β = 0.144, P-value ≥ 0.05). In a nutshell, toll road construction significantly impacts MSMEs’ business continuity, necessitating an innovative strategy involving monitoring and participatory approaches to mitigate risk.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.