Technology development in the agricultural sector is important in the development of Thailand’s economy. The purpose of this research was to study the approach of guidelines for future agricultural technology development to increase productivity in the Agricultural sector in order to develop a structural equation model. The research applied mixed-methodology. Qualitative research by in depth interview from 9 experts and focus group with 11 successful businesspersons for approve this model. The quantitative data gather from firm, in the 500 of agricultural sector by using questionnaire, using statistical tests of descriptive analysis, inferential analysis, and multivariate analysis. The research found guidelines for future agricultural technology development to increase productivity in the Agricultural sector composed of 4 latent. The most important item of each latent were as following: 1) Agrobiology Technology (= 4.41), in important item as choose seeds that for disease resistance and tolerate the environment to suit the cultivation area, 2) Environmental Assessment (= 4.37),, in important item as survey of cultivated areas according to topography with geographic information system, 3) Agricultural Innovation (= 4.30), in important item as technology reduces operational procedures, reduce the workforce and can reduce operating costs, and 4) Modern Management Systems (= 4.13), in important item as grouping and manage as a cooperative to mega farms. In addition, the hypothesis test found that the difference in manufacturing firm sizes. Medium and Small size and large size revealed overall aspects that were significantly different at the level of 0.05. The analysis of the developed structural equation model found that there was in accordance and fit with the empirical data and passed the evaluation criteria. Its Chi-square probability level, relative Chi-square, the goodness of fit index, and root mean square error of approximation were 0.062, 1.165, 0.961, and 0.018, respectively.
The aim of this study is to examine the relationship between Environmental, Social and Governance (ESG) activities and the performance of Thai listed firms. The moderating roles of board size and CEO duality on this relationship are also assessed. The ESG score provided by LSEG (formerly Refinitiv) is chosen to measure ESG activities, both as an overall ESG combined scores and as Environment, Social, and Governance pillar scores. Multiple regression analysis is used to test the impact of ESG on firm performance while the PROCESS macro is used to test the moderating effects. Results reveal that the overall ESG combined score demonstrates no statistically significant effect on firm market-based performance. However, it shows the significant effects on firm performance for both the ESG combined score and the Environmental and Social pillar scores when moderated by board size and CEO duality; Governance pillar score exhibits no significant effect. Additionally, it is found that when the CEO operates only as the managing director and small board size and average board size are evident, higher ESG disclosure scores enhance firm performance. However, when the CEO serves as both managing director and chairman of the board of directors, and where there is a large board size, higher ESG disclosure scores diminish firm performance. This study contributes to the ESG literature and encourages companies to enhance their performance by implementing ESG combined activities with good governance policies.
The global economic recession has caused pessimism in terms of prospects of sales recovering in the future. The present study is an attempt to investigate the cost stickiness behavior by focusing on specific characteristics of companies. The research was done through documentary analysis and access to quantitative data, with the use of statistical methods for analysis as panel data. The statistical population of the actual study included all companies listed on the India stock exchange from 2017 to 2021. They were selected after screening 128 listed companies. The regression method was used to examine the relationship between variables and to present a forecast model. The results of testing the first hypothesis showed that companies’ costs are sticky and according to the results of this hypothesis, an increase in costs when the level of activity increases is greater than the level of reduction in costs when the volumes of the activities are decreased. The results of the second hypothesis showed a remarkable relationship between the cost stickiness and specific characteristics of companies (size, number of employees, long-term assets, financial leverage, and accuracy of profits forecast). Based on the third hypothesis, there is a notable difference between cost stickiness at different levels of specific characteristics of companies. Therefore, the results show that environmental uncertainty such as COVID-19, increases cost stickiness.
The quality of indoor classroom conditions influences the well-being of its occupants, students and teachers. Especially the temperature, outside acceptable limits, can increase the risk of discomfort, illness, stress behaviors and cognitive processes. Assuming the importance of this, in this quantitative observational study, we investigated the relationship between two environmental variables, temperature and humidity, and students’ basic emotions. Data were collected over four weeks in a secondary school in Spain, with environmental variables recorded every 10 minutes using a monitoring kit installed in the classroom, and students’ emotions categorized using Emotion Recognition Technology (ERT). The results suggest that high recorded temperatures and humidity levels are associated with emotional responses among students. While linear regression models indicate that temperature and humidity may influence students’ emotional experiences in the classroom, the explanatory power of these models may be limited, suggesting that other factors could contribute to the observed variability in emotions. The implications and limitations of these findings for classroom conditions and student emotional well-being are discussed. Recognizing the influence of environmental conditions and monitoring them is a step toward establishing smart classrooms.
Previous studies support the direct relationship between outdoor physical activity and natural spaces in cities. The Active City and Nature concept explores the relationship between urban, green and active environments; it aims to demonstrate the scientific evidence for the need for action to be taken to increase participation in active living and sport, leading to healthier cities and communities. Our research seeks to analyse the city’s natural spaces as scenarios to encourage physical activity and sport, through a combined study of qualitative research techniques: the use of a digital webGIS platform, collaborative maps made by citizens, and surveys conducted with citizens and the local government. This methodology has been tested in the city of Malaga, the European City of Sport 2020. The study of the city’s main sport areas, the waterfront and natural green spaces provided data on the types of physical activity taking place in each of these areas and the physical activity needs of citizens. This research argues that it is important to know the criteria of local communities for physical activity and/or sport in natural environments, as well as the main demands expressed. This will provide valuable information to design and manage natural public spaces as a means of promoting physical activity and healthy habits.
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