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Sustainable Urban Healthcare Accessibility: Voronoi Screening and Travel-Time Coverage in Bangkok
(2025-12-01)
Boonprong, Sornkitja
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Punturasan, Nathapat
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Kamsing, Patcharin
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Torteeka, Peerapong
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Cao, Chunxiang
This study presents an integrated and reproducible framework for within-tier screening of potential healthcare accessibility in Bangkok. Facilities in three service tiers (primary 294 units, regular 75, referral 29) are analyzed using point-pattern diagnostics, Voronoi geometric partitions, population-weighted allocation from subdistrict controls, and cumulative network travel-time isochrones. Spatial diagnostics indicate clustering among primary care units, a near-random configuration for regular units, and modest dispersion for referral hospitals, summarized by observed-to-expected nearest-neighbor ratios of approximately 0.77, 1.05, and 1.19, respectively. Voronoi partitions translate these distributions into geometric units that enlarge with increasing inter-facility spacing, while population-weighted assignments reveal higher population-per-partition-area burdens in the outer east and southwest. Isochrone maps (5–60 min rings) show central corridors with short travel times and peripheral areas where potential access declines. Interpreted against statutory planning intent, the maps indicate broad consistency of siting with high-intensity zones, alongside residual gaps at residential fringes. Framed as repeatable indicators of access and coverage, the workflow contributes to measuring and monitoring urban health sustainability under universal health coverage and routine planning cycles. The framework yields transparent indicators that support monitoring, priority setting, and incremental adjustments within each tier. Limitations include planar proximity assumptions, uniform areal weighting, single-mode modeled travel times without temporal variation, and the absence of capacity measures, motivating future work on capacity-weighted partitions, minimal dasymetric refinements, and time-dependent multimodal scenarios.
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An Exploratory Study of Social Media Storytelling Framework for Cultural Heritage Tourism Among Youth
(2025-09-01)
Kasemsarn, Kittichai
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Nickpour, Farnaz
This exploratory study investigates how youths aged 18–25 perceive and prioritize elements of the Integrated Digital Storytelling for Social Media (IDSM) framework in cultural heritage tourism contexts, addressing critical gaps between theoretical frameworks and contemporary social media engagement requirements. Through purposive sampling at cultural heritage tourism sites in Bangkok, Thailand, questionnaires were distributed to 100 participants to examine their preferences for cultural tourism video content and validate framework elements. Cultural authenticity emerged as the paramount consideration among participants, while traditional storytelling elements demonstrated sustained relevance when adapted for social media contexts. Youth participants preferred authentic mobile phone recordings over professional production, with optimal video durations and caption-dependent storytelling for mobile consumption. TikTok emerged as the primary motivational platform despite moderate usage frequency patterns. This exploratory study contributes preliminary empirical assessment of an integrated framework specifically designed for social media applications in cultural heritage tourism contexts. The findings provide evidence-based guidelines to help practitioners develop platform-optimized content strategies that effectively engage youth audiences while maintaining cultural authenticity.
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A Zero-dimensional Mathematical Model of PM2.5 Measurement due to Daily Vehicle Density in Bangkok
(2025-05-01)
Khum-Un, Seree
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Pochai, Nopparat
Air pollution, particularly particulate matter smaller than 2.5 microns (PM2.5), has grown to be a serious issue that has an impact on people's health, especially the respiratory system. There are several studies that have found that the level of PM2.5 in the Bangkok region is high, as is how it affects individuals with respiratory illnesses. In this research, a numerical simulation of PM2.5 concentration was performed using a zero-dimensional model of PM2.5 measurement due to the daily vehicle density in Bangkok. It is evident that the wind speed and daily vehicle density have an impact on the simulated PM2.5 concentration in Bangkok. The daily density of vehicles greatly influences PM2.5 emissions. Wind speed was measured in this experiment. The hourly vehicle density in Bangkok, which was represented by calculating functions for wind speed and PM2.5 emission rate, is what produces the computed PM2.5 emission rate. The simulation includes three 24-hour scenarios: low vehicle density with medium wind speed, high vehicle density with low wind speed, and medium vehicle density with high wind speed. All of the models indicated that the PM2.5 level would drop as wind speed increased and vehicle density decreased. The daily vehicle density and wind speed are two factors that affect the PM2.5 level. Focusing, especially on wind speed, will not always lead to PM2.5 reductions. However, daily vehicle density also has a significant role in PM2.5 management. Wind speed and vehicle density influence PM2.5 concentrations, with three scenarios demonstrating that higher wind speed and lower vehicle density reduce PM2.5 levels. While wind speed helps to reduce PM2.5 levels, vehicle density also has a substantial impact on emissions. Managing PM2.5 requires addressing both daily vehicle density and wind speed, as focusing on only wind speed may not always result in reductions.
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An k-Nearest Neighbors Machine Learning Algorithm for the PM2.5 Early Warning System in Bang Khun Tian, Bangkok, Thailand
(2024-12-02)
Thongtha, Kaboon
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Pochai, Nopparat
The problem of particulate matter with a diameter of less than 2.5-10 microns, such as PM2.5-PM10 in Bangkok, affects the health of people because there are small particles that can penetrate deep into the alveoli. If there is an early warning system to warn people about the harmful levels of PM2.5 in Bangkok, such as an early warning of 2-3 days, it can help the people have time to prevent themselves. In this research, an early warning system to warn people about the harmful levels of PM2.5 in Bangkok is proposed. The air quality data of the Bang Khun Tian station, Bangkok, for 2 months, from December 1, 2020, to January 31, 2021, were selected because the area is an air-quality-worrying area. A proposed early warning system for the harmful levels of PM2.5 around Bang Khun Tian, Bangkok, was developed using the k-nearest neighbors machine learning algorithm. As the results show, the proposed technique gives an agreeable prediction for the earliest warning by 4 days.
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Analysis of Shopping Mall Tourist Satisfaction in Bangkok Using Word Cloud of Online Reviews
(2023-01-01)
Ladkoom, Kobthong
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Tarigan, Emiya Fefayosa Br
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Yasirandi, Rahmat
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Suwastika, Novian Anggis
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Anom, Rahmat Indra Pratama
The tourism industry is very important to prioritize, especially for developing countries like Thailand. The increase in tourist visits to Bangkok also triggers the potential for a rise in Bangkok tourism during the pandemic. In this study, shopping malls are one of the attractive attractions for a capital city like Bangkok. Tourist expectations of attraction must be realized so that satisfaction can be realized and created revisit. In the digitalization era, the internet's use to find and disseminate information has become commonplace. Tripadvisor.com is one of the leading review sites, which already has many reviewers, and is the case study in this research. Using Word Cloud as an analysis technique and clustering of data reviews, several important factors influence tourist satisfaction. Based on the 1186 clustered reviewers, several factors were produced, such as Place Quality, Location Access, Support Facilities, Price, and Seller Attitude. These factors can influence the decision to visit shopping malls in Bangkok because they represent tourist satisfaction.
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Does Bangkok have a central role in the dengue dynamics of Thailand?
(2020-01-13)
Xu, Zhiwei
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Bambrick, Hilary
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Pongsumpun, Puntani
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Ming Tang, I.
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Yakob, Laith
Background: Bangkok plays a central role in the commerce of Thailand. This study aimed to characterize the district-level spatial-temporal patterns of dengue in Thailand and explore if a dengue peak in Bangkok led the peaks of dengue in other Thai provinces. Methods: Monthly dengue data at district level in Thailand from January 2004 to December 2017 were obtained and used to assess the spatial and seasonal patterns of dengue in Thailand. As our seasonal decomposition and cross-correlation analyses showed that dengue in Bangkok peaked in November, which was a few months after the dengue peak in most other provinces, we used a time-series generalized linear model to explore if there was another province in which the dengue case number was most predictive of dengue case numbers in other Thai provinces. Results: The highest district-level annual dengue incidence rates (per 10,000) in the three time periods (i.e. 2004-2008, 2009-2013 and 2014-2017) were 58.08 (Samphanthawong), 85.93 (Mueang Krabi), and 66.60 (Mae Sariang), respectively. Dengue incidence rates in the western part of Northern Thailand, southern part of Central Thailand, southern part of Eastern Thailand, and Southern Thailand were higher than in other regions. Dengue in most districts of Thailand peaked in June, July or August, but dengue peaks in all districts of Bangkok occurred in November. The number of dengue cases in Nakhon Ratchasima was most predictive of the number of dengue cases in other provinces in Thailand by a one-month lag. Conclusions: Our results suggest that the dengue peak in Bangkok did not lead the peaks of dengue in other Thai provinces. Future research exploring how changes in socio-ecological factors (e.g. road network and climate factors) in Nakhon Ratchasima have affected the transmission of dengue in Thailand might shed some new light on the prevention and control of dengue.
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Spatial analysis to identify pedestrian crash zones: A case study of school zones in Thailand
(2018-01-01)
Bunnarong, Somluk
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Upala, Prapatpong
Background: In Thailand, it has the second highest road traffic fatality rate in the world at 36.2 deaths per 100,000 populations. The pedestrian crash zones are based on the road and physical environment, vehicle and driver behavior and pedestrian behavior, especially the area around the school. Therefore, this paper would like to improve safety by identifying crash area through Geographic Information Systems (GIS). Objective: The objective of this paper is to identify pedestrian crash zones of primary schools and secondary schools in Bangkok, Thailand through the spatial analysis and GIS tool. Method: The research methodology was the data collection from pedestrian-vehicle crashes in 2016 at 12 schools of 1,218 locations in Bangkok. The data analysis used GIS for geocoding the crash locations. The spatial patterns and pedestrian crash zone map were applied by Moran’s I statistic and the Kernel Density Estimation (KDE). Results: The Moran’s index showed that the accident locations within school zone were a clustered pattern considering on Moran’s Index which approached +1 and the z-scores greater than 2.58. The KDE showed that the pedestrian crash zones were different depending on the physical environment; however, the most significant areas were at urban areas, crowded areas, and intersections of arterial roads and local roads about 508 meters from the school center. Conclusion: This research could be concluded that the spatial patterns and pedestrian crash zone map will assist the transportation planners and traffic police for identifying crash locations and specific vulnerable road users, especially pedestrians and bicycle users.
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Mitigations of flooding and soil erosions geo-disasters in Thailand and Laos due to climate change: From Mountains to Lowlands
(2017-06-01)
Bergado, D. T.
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Chaiyaput, S.
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Voottipruex, P.
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Hino, T.
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Chanmee, N.
In 2011, Thailand has suffered from devastating flooding due to climate change. During this time, 2 typhoons from the Pacific area went straight across Vietnam to Northern Laos and Northern Thailand instead of the usual path to Taiwan and Japan. Subsequently, huge flooding damaged many infrastructures and overtopped flood protection dikes of many industrial estates and educational institutions in the Central Plain of Thailand such as at Hi-Tech Industrial Estate, Bang Pain Industrial Estate. Navanakom Industrial Estate and Asian Institute of Technology, to name a few. The same phenomenon also occurred in neighboring Laos PDR which caused unusually heavy rains and widespread river flooding. Consequently, riverbank erosions accompanied by slope failures occurred at Xedon River in Pakse, Southern Laos due to saturation caused by high water levels accompanied by high velocity flow of the flooded river. To evaluate the stability of these mitigation structures, finite element and limit equilibrium methods were utilized. PLAXIS 2D software was used to analyze the slope protection schemes at low and high water levels incorporating the various supporting and reinforcing materials. Moreover, the PLAXIS 2D software was also utilized to predict the vertical deformations of improved flood control dikes with increased embankment height at different cases of flood water levels. In addition, the SLIDE software was used to predict the factor of safety by using limit equilibrium method for the various riverbank erosion protection structures. Furthermore. RESSA software was utilized to evaluate the slope stability of the erosion protection structures with geosynthetic reinforcements of Xedon riverbank in Pakse combined with gabions and mattresses. Laos PDR is mountainous with high elevations.
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Bangkok's mass rapid transit system's commuter decision-making process in using integrated smartcards
(2016-01-01)
Kaewwongwattana, Peerakan
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Panjakajornsak, Vinai
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Pimdee, Paitoon
This paper studied the decision-making process to use an integrated smartcard ticketing system by Bangkok metropolitan transit commuters. A second-order Confirmatory Factor Analysis using LISREL 9.10 was undertaken on Bangkok commuter's decision-making process on the use of an integrated smartcard system. The sample consisted of 300 Bangkok commuters obtained by accidental sampling using questionnaires with a 5-point Likert scale. The tools in the research questionnaires used scale estimation that achieved a confidence value of 0.84. The research instruments used rating scales measuring information search, alternative choices, and use decision on the 15 variables in the decision-making process which had factor loadings between 0.49 and 0.89 weight elements when sorted in descending order and overall had a high level. Use decision, alternative choices and information search had a factor of 0.89, 0.65 and 0.49, respectively. There was a good fit of the decision-making model to the empirical data (chi-square = 34.55, probability (p) = 0.94, df = 49, RMSEA = 0.00, GFI = 0.98, AGFI = 0.96, SRMR = 0.04).
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Determinates of foreign real estate investment within Thailand's special autonomous systems (SAS) of Bangkok and Pattaya city
(2015-01-01)
Teeranantawanich, Natthapat
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Fongsuwan, Wanno
Thailand's real estate laws can at times be difficult to navigate with Bangkok and Battaya's special legal status for foreign real estate investment even more so. These special autonomous systems, however thrive with both commercial and residential real estate transactions with the Board of Investment and Industrial Estates playing a key role in Thailand's growth. In 2015, Battaya alone is projected to have 10 million international and domestic visitors contributing $3.26 billion to the local economy. Japan currently leads international investing but with southeast nation economic integration in 2015, other community members will take a bigger role. As such, the researchers undertook a study to explore the various factors affecting the reasons for foreign real estate holdings. These included government policy, the economy and investment factors and social and environmental conditions. Quantitative survey input came from 301 parents of international school students, expat groups and condominium owners. Qualitative data was secured from 10 senior executives involved in real estate transactions as well as individuals from Thailand's Board of Investment promotion agency. The study revealed that due to limited ability of foreigners to hold property, other mechanisms such as nominees, Thai nationals and wives were commonly used. Additionally, foreigners were sensitive to the 6.3% land transfer tax which they considered quite high. Overall government policy, internal economic factors and the environment (flooding, etc.) and infrastructure (sea and airports, roads, power, etc.) played key roles in foreign investment decisions.

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