Every plant is significantly important in tackling climate change, including Makila (Litsea angulata BI) an endemic wood species found in the forest of Moluccas Provinces. Therefore, this research aimed to examine the role of the Makila plant in tackling climate change by measuring biomass content using constructing an allometric equation. The method used was a destructive sampling, where 40 units of Makila plant at the sampling level were felled, and sorted according to root, stem, branch, rating, and leaf segments. Each segment was weighed both at wet and after drying, followed by a classical assumption test in data processing, and the formulation of an allometric equation. The regression model was examined for normality and suitability in predicting independent variables, ensuring there were no issues with multicollinearity, heteroscedasticity, and autocorrelation. The results yielded a multiple linear regression, namely: Y = −1131.146 + 684.799X₁ + 4.276X₂, where Y is biomass, X₁ is the diameter, and X₂ is the tree height. Based on the results of the t-test: variable X₁ partially affected Y while variable X₂ partially had no effect on Y. The F-test indicated that variables X₁ and X₂ jointly affected Y with R Square: 0.919 or 91.9% and the rest was influenced by other unexplored factors. To simplify biomass prediction and field measurement, a regression equation that used only 1 independent variable, namely tree diameter, was used for the experiment. Allometric equation only used 1 variable, Y = −1,084,626 + 675,090X₁, where X₁ = tree diameter, Y = Total biomass with R = 0.957, and R² = 0.915. Considering the potential for time, cost, and energy savings, as well as ease of measurement in the field, the biomass of young Makila trees was simply predicted by measuring the tree diameter and avoiding the height. This method used the strong relationship between biomass, plant diameter, and height to facilitate the estimation of biomass content accurately by entering the results of field measurements.

The Trans Sumatra Toll Road (TSTR) is a mega toll road project with an assignment State-Owned Enterprise (SOE) scheme in Indonesia. In its development, TSTR has several limitations, including funding, low investment feasibility and the un-optimum implementation of land value capture (LVC). This has the impact of delaying the completion of project development, decreasing the performance of toll road developer companies and even causing bankruptcy. LVC is an alternative funding scheme proven successful in other countries such as Hongkong, England and Vietnam. Several transportation projects based on transit-oriented development have successfully achieved profits using the LVC method. With a low project feasibility, the implementation of the Road Plus Property Developer (RPPD) business model is expected to be a solution to improve investment performance in the TSTR project. RPPD is defined as an assignment scheme toll road business model based on LVC implementation. This research aims to develop policies for implementing the RPPD business model on toll road SOE-assigned schemes. The data was collected by in-depth interviews with experts in two stages. The data analysis method used is Soft System Methodology (SSM). This research produces two recommended actions: ratification of the Presidential Regulation regarding the implementation of LVC and institutional transformation of regionally owned business entities in the property sector. It is hoped that implementing the RPPD policy will become a priority in completing the TSTR project.

The study looks at Ghana’s mining industry’s audit culture and green mining practices about their social responsibility to the communities where their mines are located. Results: According to this study, the economic motivations of mines and green mining are inversely related. Even large mining companies incur significant costs associated with their green mining initiatives because they require a different budget each year, which has an impact on their ability to maximize wealth. Conversely, mines with strong green mining initiatives enjoy positive public perception, and vice versa. Ghanaian mines do not have pre- or during-mining strategies; instead, they only have post-social and post-environmental methods. The best method for evaluating mines’ environmental performance in the community in which they operate is, according to this study, social auditing. This is primarily influenced by the mine’s audit culture, but it is also influenced by the auditor’s compliance with audit processes, audit guidelines, and, ultimately, the audit firm’s experience. The analysis confirms that Ghana’s mine environmental performance is appallingly low since local audit firms are not used in favor of foreign auditors who lack experience or empathy for the problems encountered by these mining communities. Last but not least, corporate social responsibility (CSR) is connected to Ghana’s development of green mining, either directly or indirectly. Whether the mine adopts a technocrat, absolutist, or relativist perspective on mining will determine this. The study discovered that, in contrast to the later approach, the first two views generate work in a mechanistic manner with little to no consideration for CSR.

India’s economic growth is of significant interest due to its expanding Gross Domestic Product (GDP) and global market influence. This study investigates the interplay between production, trade, carbon dioxide (CO₂) emissions, and economic growth in India using Granger causality analysis. Also, the data from 1994 to 2023 were analyzed to explore the relationships among these variables. The results reveal strong positive correlations among production, trade, CO₂ emissions, and GDP, with production showing significant associations with export, import, and GDP. Co-integration tests confirm the presence of a long-term relationship among the variables, suggesting their interconnectedness in shaping India’s economic landscape. Regression analysis indicates that production, export, import, United States (US)-India trade, manufacturing cost of energy, and CO₂ emissions significantly impact GDP. Moreover, the Vector Error Correction Model (VECM) estimation reveals both short-term and long-term dynamics, highlighting the importance of understanding equilibrium and deviations in economic variables. Overall, this study contributes to a better understanding of the complex interactions driving India’s economic growth and sustainability.

This article emphasizes the importance of Small and Medium-Sized Enterprises (SMEs) and large companies in driving economic growth. SMEs are labour-intensive and agile, creating more jobs, while large companies are capital-intensive and rely on technology, having more resources for research and development. In the Gulf Cooperation Council (GCC) region, SMEs contribute significantly to Gross Domestic Product (GDP) and job opportunities, while large companies dominate specific sectors. The research employs a multidisciplinary approach using an extensive literature review to summarize the current literature, highlight the economic impact of SMEs and large companies in GCC, and highlight the importance of large companies in developing local citizens. Policy-makers must consider these differences to integrate these dynamic changes for effective support policies. This study examines the economic impact of SMEs and large companies in the GCC region, providing recommendations to support large businesses. It addresses challenges and opportunities related to employment, household earnings, economic output, and value addition. Promoting the economic impact of SMEs and large companies can lead to sustainable economic growth and development in the GCC region. Also, this article pointed out the importance of large companies and their economic impact in the GCC region; policy recommendations will help the governing bodies in decision-making towards promoting sustainable economic growth.