The objective of this study is to explore the relationship between changing weather conditions and tourism demand in Thailand across five selected provinces: Chonburi (Pattaya), Surat Thani, Phuket, Chiang Mai, and Bangkok. The annual data used in this study from 2012 to 2022. The estimation method is threshold regression (TR). The results indicate that weather conditions proxied by the Temperature Humidity Index (THI) significantly affect tourism demand in these five provinces. Specifically, changes in weather conditions, such as an increase in temperature, generally result in a decrease in tourism demand. However, the impact of weather conditions varies according to each province’s unique characteristics or highlights. For example, tourism demand in Bangkok is not significantly affected by weather conditions. In contrast, provinces that rely heavily on maritime tourism, such as Chonburi (Pattaya), Phuket, and Surat Thani, are notably affected by weather conditions. When the THI in each province rises beyond a certain threshold, the demand for tourism in these provinces by foreign tourists decreases significantly. Furthermore, economic factors, particularly tourists’ income, significantly impact tourism demand. An increase in the income of foreign tourists is associated with a decrease in tourism in Pattaya. This trend possibly occurs because higher-income tourists tend to upgrade their travel destinations from Pattaya to more upscale locations such as Phuket or Surat Thani. For Thai tourists, an increase in income leads to a decrease in domestic tourism, as higher incomes enable more frequent international travel, thereby reducing tourism in the five provinces. Additionally, the study found that the availability and convenience of accommodation and food services are critical factors influencing tourism demand in all the provinces studied.

This research presents a comprehensive model for enhancing the road network in Thailand to achieve high efficiency in transportation. The objective is to develop a systematic approach for categorizing roads that aligns with usage demands and responsible agencies. This alignment facilitates the creation of interconnected routes, which ensure clear responsibility demarcation and foster efficient budget allocation for road maintenance. The findings suggest that a well-structured road network, combined with advanced information and communication technology, can significantly enhance the economic competitiveness of Thailand. This model not only proposes a framework for effective road classification but also outlines strategic initiatives for leveraging technology to achieve transportation efficiency and safety.

The purpose of the article is to present the current situation in the rail freight transport in Thailand and the direction of changes in this area. Firstly, Thailand statistics in volume of freight transport by rail and modal share of freight transport have been presented. Afterwards, problems and obstacles in railway operational practices and in using rail transport services have been identified to improve railway system in Thailand and the outcome was assessed in terms of railway capacity and utilization. The findings were used to outline the direction of changes in rail freight transport. The results show that the rail transport capacity in double-track would increase by 48% (at present by 15.5% and as plan by 30%) and the ratio by rail transport to total freight transport would increase from at present by 1.87% to 10% in 2037.

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 was designed to study the push and pull motivational factors affecting the foreign backpackers travel behavior towards Full Moon Party in Koh Phangan District, Surat Thani Province. In the sample 300 foreign backpackers aged 18 or older were included, who came to attend the Full Moon Party solely for vacation purposes and not for any work or income generating activities. The study was executed using a structured questionnaire. The statistical tools for the analysis of the data included, but were not limited to, frequency counts, computed percentages, means, standard deviations, chi-square analysis, one- way ANOVA, and Pearson correlation at the 0.05 level of significance. The research demonstrated that with respect to the first-time foreign visitors in Thailand to attend the Full Moon Party, then, they have habitually stayed at the resorts and the bungalows. It was a general observation that such visitors preferred to seek out information on the Internet, social websites as well as tourism websites. Their activities included horse riding, general activities, seeing natural sights including waterfalls and mountains, going for mountain hikes, participating in physically hard and risky outdoors activities, and nighttime activities. Tourists are sufficiently motivated to visit Thailand for its various appealing attributes, as revealed by the analysis. Furthermore, 10 motivational components were identified with 24 variables; Push Motivation Components: (1) Escape and Novelty Seeking, (2) Feel Free, (3) Open the World, and (4) Social Need. Pull Motivation Components: (1) Party, (2) Unique, (3) Only for Myself, (4) Sea Lover, (5) Diversity, and (6) Loner. Demographic characteristics for example gender, age, marital status, education level, occupation, and place of residence were also studied. The push factors, as well as the pull factors of travel, were found to co-relate with the behavior of female foreign backpackers on the other hand where both were significant.