This study aims to identify the causes of delays in public construction projects in Thailand, a developing country. Increasing construction durations lead to higher costs, making it essential to pinpoint the causes of these delays. The research analyzed 30 public construction projects that encountered delays. Delay causes were categorized into four groups: contractor-related, client-related, supervisor-related, and external factors. A questionnaire was used to survey these causes, and the Relative Importance Index (RII) method was employed to prioritize them. The findings revealed that the primary cause of delays was contractor-related financial issues, such as cash flow problems, with an RII of 0.777 and a weighted value of 84.44%. The second most significant cause was labor issues, such as a shortage of workers during the harvest season or festivals, with an RII of 0.773. Additionally, various algorithms were used to compare the Relative Importance Index (RII) and four machine learning methods: Decision Tree (DT), Deep Learning, Neural Network, and Naïve Bayes. The Deep Learning model proved to be the most effective baseline model, achieving a 90.79% accuracy rate in identifying contractor-related financial issues as a cause of construction delays. This was followed by the Neural Network model, which had an accuracy rate of 90.26%. The Decision Tree model had an accuracy rate of 85.26%. The RII values ranged from 68.68% for the Naïve Bayes model to 77.70% for the highest RII model. The research results indicate that contractor financial liquidity and costs significantly impact construction operations, which public agencies must consider. Additionally, the availability of contractor labor is crucial for the continuity of projects. The accuracy and reliability of the data obtained using advanced data mining techniques demonstrate the effectiveness of these results. This can be efficiently utilized by stakeholders involved in construction projects in Thailand to enhance construction project management.

The service quality of a logistics operation is a key research factor. According to Parasuraman in 1988, there are 5 dimensions about the service quality. In this paper will detective the affecting factors by collecting data from 1560 customers who experienced the service of Beibu Gulf Port Group, Guangxi, China. We used structural equation modeling (SEM) to test whether the service quality factors would affect the logistics operation or not from tangible, responsiveness, reliable and empathy to assurance. Moreover, with the Regional Comprehensive Economic Partnership (RCEP) has been signed, whether this free trade agreement’s effect would affect this Group’s service quality or not would be a consideration of this research. And the traditional service quality factors will affect the RCEP implementation or not will be tested, too. The results in the paper show the significance positive in co-relationship and supporting evidences for the Group’s future development.

This paper examines the relationship between renewable energy (RE) generation, economic factors, infrastructure, and governance quality in ASEAN countries. Based on the Fixed Effects regression model on panel data spanning the years 2002–2021, results demonstrate that domestic capital investment, foreign direct investment, governance effectiveness, and crude oil price exhibit an inverse yet significant relationship with RE generation. An increase in those factors will lead to a decline in RE generation. Meanwhile, economic growth and infrastructure have a positive relationship, which implies that these factors act as stimulants for RE generation in the region. Hence, it is advisable to prioritise policies that foster economic growth, including offering tax breaks specifically for RE projects. Additionally, it’s crucial to streamline governance processes to facilitate infrastructure conducive to RE generation, along with investing in RE infrastructure. This could be achieved by establishing one-stop centres for consolidating permitting processes, which would streamline the often-bureaucratic process. However, given the extensive time period covered, future research should examine the short-term relationship between the variables to address any potential temporal trends between the factors and RE generation.

China’s graduate quality management system is designed to ensure that students possess the necessary skills, knowledge, and competencies for future success. This system is rooted in China’s ambitious educational reforms aimed at cultivating a highly skilled workforce to drive economic growth and innovation. Effective graduate quality management significantly impacts employment levels, training models, and national policy formulation. This study investigates the quality management approaches of 56 vocational institutions in Yunnan Province using a 5-level questionnaire and a quantitative research methodology. A sample of 556 individuals was selected through stratified random sampling. Exploratory factor analysis identified five primary components of the quality management model: College graduate quality (mean = 4.56, SD = 0.49), teaching quality (mean = 4.39, SD = 0.42), hardware environment (mean = 4.38, SD = 0.44), social support (mean = 4.37, SD = 0.42), and job satisfaction (mean = 4.38, SD = 0.42). College graduate quality and teaching quality were the most influential factors, while hardware environment, social support, and job satisfaction had lesser impacts.

Sustainability is a top priority for municipal administrations, particularly in large urban centers where citizens rely on transportation for work, study, and daily errands. Public transportation faces a significant challenge beyond availability, performance, safety, and comfort: balancing the cost for the city with fare attractiveness for passengers. Meanwhile, bicycles, supported by public incentives due to their clean and healthy appeal, compete with public transit. In Curitiba, the integrated transport system has been consistently losing passengers, exacerbated by the pandemic and the rise in private vehicle usage. To address this, the city is expanding bicycle infrastructure and electric bike rental services, impacting public transit revenue, and prompting the need for financial compensation to maintain affordable fares for those reliant on public transport. Therefore, this study’s objective is to analyze the bicycle’s impact on public transportation, considering the impact of public policies on economic and social efficiency, not just ecological and environmental factors. Data from six main bus lines were collected and analyzed in two separate linear regression models to verify the effects of new bicycles in circulation, bus tariffs, and weather conditions on public transportation demand. Research results revealed a significant impact of bus tariffs and fuel prices on the number of new bicycles that are diverting passengers from public transportation. The discussion may offer a different perspective on public transport policies and improve city infrastructure investments to strategically change the urban form to address social and economic issues.

The purpose of this research is to deeply examine the factors that support and hinder green economic growth in South Papua, with a specific focus on increasing awareness and capacity among local communities, developing sustainable infrastructure, and adopting clean technologies. This research utilizes a case study approach to uncover the dynamics and elements supporting the development of green economy in South Papua, particularly in Merauke Regency. Through surveys, in-depth interviews, and document analysis, data were gathered from various stakeholders, including government, communities, and the private sector. Sampling was done using purposive sampling method, ensuring the inclusion of respondents relevant to the research topic to provide a holistic understanding of the factors influencing green economy in the region. The research reveals that in Merauke Regency, the understanding of the concept of green economy among the community is still limited, highlighting the need for broader education and socialization. Factors such as government support, infrastructure availability, and community participation play a key role in driving green economic growth. However, challenges such as resource limitations and differences in perceptions among stakeholders highlight the complexity in implementing green economy. Therefore, holistic and collaborative policy recommendations need to be considered to strengthen support and effectiveness of sustainable development efforts in this region.