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.

Improving the competitiveness of tourism destinations is crucial for driving local economies and achieving income growth. In light of this evidence, numerous government departments strive to assess specific factors that impact the competitiveness of tourism destinations, enabling them to issue appropriate new tourism policies that promote more effective forms of tourism business. Therefore, the primary objective of this paper is to investigate how various elements such as tourism resources, tourism support, tourism management, location conditions, and tourism demand influence regional competitiveness in the Northern Bay region of Guangxi Province in China. To accomplish this goal, an online survey was conducted to collect data from 420 visitors who had experienced North Gulf Tourism; yielding an impressive response rate of 95 percent. The findings reveal that all aforementioned factors—namely: Tourism resources, tourism support, tourism management, location conditions and tourist demand—significantly impact destination competitiveness. Notably though, it was found that among these factors influencing destination competitiveness; it is primarily determined by effective local-level management (β = 0.345). Following closely behind are tourist demand (β = 0.133) as the second most influential factor affecting destination competitiveness; followed by location conditions (β = 0.116) ranking third; then comes tourist support (β = 0.03) as fourth in line impacting destination competitiveness; finally with least impact being exerted by available tourist resources (β = 0.016). Consequently, highlighting that regional competitiveness within Guangxi’s Northern Bay area predominantly hinges on efficient local-level management practices thus strongly recommending relevant authorities formulate novel work policies aimed at enhancing levels of local-level competitive advantage within the realm of regional touristic offerings.

There are a number of issues that can influence elderly life satisfaction, which can mirror their welfare. This study aims to explore the differences in elderly parents’ life satisfaction across socioeconomic characteristics and investigates how the traits of both children and parents associate with elderly parents’ life satisfaction in Thailand. This study uses individual data obtained from Thailand’s National Statistical Organization covering 2008–2015, 2018 and 2020, with a total sample size of 28,494. To investigate the association between children’s and parents’ characteristics, particularly formal education and parental life satisfaction, this study uses ordered logistic regression for the analysis. Our results show that male parents are more likely to have higher life satisfaction than their female counterparts. Parents who are employed, holding a bachelor’s degree, and living with female children are more satisfied with their life. Statistically, children’s formal education demonstrates its importance for their elderly parents’ life satisfaction. This documents the vital role of schooling in improving parental life satisfaction. Moreover, facing the challenge of entering an aging society, government agencies must take a proactive stance on creating jobs suitable for the elderly or retirees to maintain their sense of independence. The evidence of intergenerational mobility reaffirms the importance of children’s education along with their caring ability, which should be strengthened.

This study aims to explore the implications of imported electrical equipment in Indonesia, analysing both short-term and long-term impacts using a quantitative approach. The research focuses on understanding how various economic factors, such as domestic production, international pricing, national income, and exchange rates, influence the country’s import dynamics in the electrical equipment sector. Employing an Error Correction Model (ECM) for regression analysis, the study utilises time-series data from 2007 to 2021 to delve into the complex interplay of these variables. The methodology involves a comprehensive analysis using the Augmented Dickey-Fuller and Phillips-Perron tests to assess the stationarity of the data. This approach ensures the robustness of the ECM, which is employed to analyse the short-term and long-term effects of the identified variables on electrical equipment imports in Indonesia. The results reveal significant relationships between these economic factors and import levels. In the short term, imports are shown to be sensitive to changes in domestic economic conditions and international market prices, while in the long term, the country’s economic growth, reflected through GDP, emerges as a significant determinant. The findings suggest that Indonesia’s electrical equipment import policies must adapt highly to domestic and international economic changes. In the short term, a responsive approach is required to manage the immediate impacts of market fluctuations. The study highlights the importance of aligning import strategies with broader economic growth and environmental sustainability goals for long-term sustainability. Policymakers are advised to focus on enhancing domestic production capabilities, reducing import dependency, and ensuring that environmental considerations are integral to import policies. This study contributes to understanding import dynamics in a developing country context, offering valuable insights for policymakers and industry stakeholders in shaping strategies for economic growth and sustainability in the electrical equipment sector. The findings underscore the need for a balanced, data-driven approach to managing imports, aligning short-term responses with long-term strategic objectives for Indonesia’s ongoing development and industrial advancement.