The spread of the coronavirus disease in 2019 (COVID-19) in Thailand has led to a lack of liquidity and income for entrepreneurs, increasing the variety of distribution channels compared to store sales. This will be a solution for businesses struggling and creating value to raise the income levels of community enterprises in Thailand. This was an integrated and participatory action research using qualitative techniques through observation, interviews, recordings, analysis, and interpretation of the operational characteristics of community enterprises from field visits for consultation. This study aimed to examine the problems and obstacles of online selling by community enterprise entrepreneurs and to find guidelines for advising lead entrepreneurs in the Digital Market. These 25 community enterprise entrepreneurs produced community herbal products in Thailand. The research findings were analyzed using grounded theory according to the research objectives. From the research results, it is possible to summarize the problems and obstacles faced by entrepreneurs in selling products online among community enterprise entrepreneurs owing to the lack of knowledgeable administrators and the decline in demand for products affected by the COVID-19 pandemic. Furthermore, barriers to laws, regulations requirements related to cannabis products included legal controls only for cultivation and the production process until the product was sold, and production capacity could not be produced to meet the demand when there was a large volume of orders. Solutions were as follows: increasing skills and knowledge for entrepreneurs, especially in the potential; finding a way to pass on the business to the new generation to continue the business; using strategies to create cooperation with other enterprise networks and government agencies; creating online selling channels through various platforms; increasing funding to develop production processes; and using technology to create competitive advantages and marketing planning and delivery to make online sales an essential channel.

The study aims to investigate the relationship between ESG (Environment, Social, Governance) performance on bank value when moderated by loan loss reserves. Using all 11 Thai listed banks for the period 2017–2021, data were collected from Bloomberg database, the official website of the Stock Exchange of Thailand (SETSMART), and Bank of Thailand, totalling 55 observations. The selected CAMEL indicators served as the control variables. Multiple linear regression and conditional effect analyses were executed using Tobin’s Q as a bank value. This study carefully tested the validity of the dataset, including fixed and random effects. The research outcomes demonstrate the interaction between ESG performance and loan loss reserves has a notably negative effect on the association between ESG performance and bank value. Subsequent analysis reveals that the negative influence of ESG performance on bank value is more pronounced with higher levels of loan loss reserves. These findings have important implications for bankers, investors, and policymakers, offering insights into the dynamics of ESG and loan loss reserves considerations.

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.

The government’s land registration program aims to protect communities from future land disputes. However, lack of community support presents challenges to its process and implementation. Utilizing a qualitative case study approach, this article examines these challenges from the community’s perspective, focusing on land registration, community participation, and implementation dynamics. It suggests that learning from these dynamics can enhance the program’s effectiveness, highlighting the need for a systematic approach to community involvement.

This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.

Proper understanding of LULC changes is considered an indispensable element for modeling. It is also central for planning and management activities as well as understanding the earth as a system. This study examined LULC changes in the region of the proposed Pwalugu hydropower project using remote sensing (RS) and geographic information systems (GIS) techniques. Data from the United States Geological Survey's Landsat satellite, specifically the Landsat Thematic Mapper (TM), the Enhanced Thematic Mapper (ETM), and the Operational Land Imager (OLI), were used. The Landsat 5 thematic mapper (TM) sensor data was processed for the year 1990; the Landsat 7 SLC data was processed for the year 2000; and the 2020 data was collected from Operation Land Image (OLI). Landsat images were extracted based on the years 1990, 2000, and 2020, which were used to develop three land cover maps. The region of the proposed Pwalugu hydropower project was divided into the following five primary LULC classes: settlements and barren lands; croplands; water bodies; grassland; and other areas. Within the three periods (1990–2000, 2000–2020, and 1990–2020), grassland has increased from 9%, 20%, and 40%, respectively. On the other hand, the change in the remaining four (4) classes varied. The findings suggest that population growth, changes in climate, and deforestation during this thirty-year period have been responsible for the variations in the LULC classes. The variations in the LULC changes could have a significant influence on the hydrological processes in the form of evapotranspiration, interception, and infiltration. This study will therefore assist in establishing patterns and will enable Ghana's resource managers to forecast realistic change scenarios that would be helpful for the management of the proposed Pwalugu hydropower project.