This research endeavors to achieve three primary objectives. Firstly, it seeks to develop a measurement model capable of assessing the motorcycle riding behavior of middle-aged individuals in Thailand. The construction of this model integrates the motorcycle rider behavior questionnaire (MRBQ) with statistical and descriptive analyses. Secondly, the research examines the accuracy of the measurement model using a factor analysis approach, comprising both exploratory and confirmatory factor analyses. Lastly, the study aims to furnish the people of Thailand with a set of guidelines for self-assessment of their motorcycle riding habits. The examination involves 399 middle-aged motorcycle riders aged 35 years or older, a significant majority of whom (81%) possess the requisite licenses for motorcycle operation, with the majority (83%) accumulating over a decade of riding experience. Through analysis, a set of 39 items capturing nuanced behaviors exhibited by middle-aged motorcyclists in Thailand is identified. These items are categorized into four distinct clusters: speed violations, control errors, traffic errors, and adherence to safety equipment protocols. The utilization of the MRBQ in this study holds significant importance, as it provides valuable insights into the riding practices of the Thai population. The resultant findings hold the potential to inform safety initiatives and strategies aimed at enhancing the overall motorcycle riding experience.

Air pollution poses growing challenges to public health and urban mobility in Southeast Asia. This study investigates how air quality crises affect travel mode choices in Chiang Rai, Thailand, a secondary city experiencing seasonal PM2.5 smog episodes. A structured online survey was conducted with 406 respondents, collecting paired data on travel behaviors during non-air quality crisis (N-AQC) and air quality crisis (AQC) periods. Using a multinomial logit model (MNL), key socioeconomic and trip-related variables were analyzed to estimate mode choice probabilities. The results reveal significant behavioral shifts during an air quality crisis, with private car usage increasing from 30.30% to 34.70% and motorcycle usage decreasing from 50.20% to 42.90%. Multinomial logit models attained correct classification rates of 67.5% and 63.8%, with pseudo R² values exceeding 0.50 for both periods. These findings highlight how environmental stress alters travel behavior, especially among younger and low-income populations. The study contributes new insights from a Southeast Asian urban context, emphasizing the need for adaptive transport policies, protective infrastructure, and equity-focused interventions to promote sustainable mobility during an environmental crisis.

According to early 2020, the impact of the COVID epidemic and people's rapid awareness. The government has established projects and measures to prevent the spread of COVID-19 had a significant effect on the restaurant business that is unable to open fully, resulting in a significant drop in sales, particularly for suki or shabu buffet restaurants that normally have to "cook" and "eat" in the restaurant, directly affecting customer food consumption behavior and causing the shabu business to stall, requiring the operator to adjust. Therefore, the government projects and adaptations for dealing with such situations are essential to the consumer behavior of customers. The purpose of this research was to investigate consumer behavior regarding shabu restaurants at Mae Fah Luang University. There were several influences on consumer behavior during the COVID-19 issue. The collected data was examined by using descriptive statistics and exploratory factor analysis (EFA). Yamane's sample size total was 388 people, which was used to identify a student group from Mae Fah Luang University for this study to complete the questionnaire. The result showed the factor analysis distinguished by the Kaiser Meyer-Olkin (KMO) method was 0.916. The 16 criteria are divided into four components and the four components consist of service staff, quality of ingredients (pork, beef, chicken, seafood, food, and vegetables), location, and measures to avoid COVID-19. The resulting awareness of social distancing and the use of partition COVID-19 between other customers are most important to support the elements in deciding whether to use hotpot service restaurants or not.

Ambulance response time is a critical factor in saving lives and is heavily influenced by ambulance placement strategies. Currently, Nang Lae Subdistrict is served by only one ambulance, yet the managing agency does not systematically analyze high-frequency accident zones or areas with frequent emergency calls. This oversight raises concerns about whether the current ambulance station provides optimal coverage. To address this, call data from all ambulance dispatches over four months (July–November 2023) were analyzed. The findings revealed 96 cases within a 5-kilometer radius of Nang Lae Subdistrict Municipality and 18 cases within a 10-kilometer radius. Cluster analysis was conducted to determine optimal ambulance placement, identifying two potential locations approximately 1.55 km apart. These results can inform strategic improvements in ambulance deployment, particularly during high-demand periods such as festivals, where accident rates surge and faster response times are crucial. Additionally, the study observed instances of ambulances servicing areas beyond their designated zones, suggesting a need for better resource allocation.

Wearing a traditional Thai cotton dress is getting popular, particularly among Generation Z, which has greater access to internet media than previous generations. It is inspired by online communities, soap operas, celebrities, and fashionistas. The study aims to determine which factors of the Marketing Mix (4P) consisting of price, product, place, and promotion influence the purchasing decision of Generation Z groups by using the Best-Worst Method (BWM) proposed for solving the issue of selecting the best strategy. The information was gathered from 400 students at the Mae Fah Luang campus. The results showed that the best factor influencing customer purchasing decisions is a product and the average weight is 0.3038. It shows the products that reflect the wearer's identity and it in line with current fashion trends are of the utmost importance. The second factor is price, which shows an average weight of 0.2817. Customers in Generation z focus on a reasonable price related to a limited income. Therefore, these two factors influence buyers more than other factors.

Community-based tourism (CBT) destinations are increasingly expected to align visitor experiences with climate responsibility, yet local managers often lack product-level carbon evidence that can guide practical route redesign and service decisions. This study addresses this aggregation-to-action gap by developing a route-level carbon footprint baseline for a CBT itinerary in Ban Boonjaem, Phrae Province, Thailand. Using an exploratory and applied case study design, the study treats one completed six-hour, non-overnight itinerary as the functional unit and applies a life-cycle-informed operational boundary covering transportation, food and beverage consumption, and solid waste generated during the route test. Primary activity data were collected from one organized route test involving 20 Thai domestic volunteer tourists and were matched with relevant emission factors to estimate total and per-tourist emissions. The tested itinerary generated 0.2234 tCO2e, equivalent to 223.4 kgCO2e in total and approximately 11.2 kgCO2e per tourist per trip. Transportation was the largest emission domain, accounting for 55.89% of total route emissions, followed by food and beverage consumption at 38.55%, while waste contributed 5.56%. Together, transportation and food and beverage represented 94.44% of measured emissions, indicating that the route’s carbon profile was shaped mainly by mobility arrangements and service provisioning rather than waste generation alone. The study contributes a transparent, route-specific operational baseline for low-carbon CBT management. The findings should be interpreted as case-specific decision-support evidence rather than as a destination-wide carbon inventory or statistically generalizable estimate.