Understanding Commuting Mode Choices in Bangkok: The Role of Sociodemographics and Urban Structure in Shaping Transportation Preferences

Main Article Content

Wichan Choorat
Yothin Sawangdee
Sureeporn Punpuing
Martin Piotrowski

Abstract

This study investigates commuting patterns in Bangkok between 2015 and 2023 and examines the influence of demographic, socioeconomic, and spatial factors on commuting mode choices. The microdata from the 2015 and 2023 Migration Survey from the Thailand National Statistical Office were used to identify significant shifts in age distribution, educational attainment, and employment status among commuters. The findings reveal a growing preference for private transport among older, higher-education, and higher-skilled individuals, while public transport continues to serve as a vital mode of commuting for women, employees, and lower-skilled commuters. Therefore, the development of basic infrastructure and transport systems is needed to ensure that they are equally accessible, convenient, and safe for all people. It is also essential to expand public transport routes such as buses, BTS Skytrain, and MRT subway system to the outskirts of Bangkok to reduce reliance on private cars.

Article Details

How to Cite
Choorat, W., Sawangdee, Y., Punpuing, S. ., & Piotrowski, M. . (2025). Understanding Commuting Mode Choices in Bangkok: The Role of Sociodemographics and Urban Structure in Shaping Transportation Preferences. Journal of Population and Social Studies [JPSS], 34(-), 217–235. retrieved from https://so03.tci-thaijo.org/index.php/jpss/article/view/283131
Section
Research Articles
Author Biography

Wichan Choorat, Institute for Population and Social Research, Mahidol University, Thailand

Corresponding author

References

• Aghdam, F. B., Sadeghi-Bazargani, H., Shahsavarinia, K., Jafari, F., Jahangiry, L., & Gilani, N. (2021). Investigating the COVID-19 related behaviors in the public transport system. Archives of Public Health, 79(1), Article 183. https://doi.org/10.1186/s13690-021-00702-4

• Aivinhenyo, I., & Zuidgeest, M. (2019). Transport equity in low-income societies: Affordability impact on destination accessibility measures. In K. Lucas, K. Martens, F. Di Ciommo, & A. Dupont-Kieffer (Eds.), Measuring transport equity (pp. 111–128). Elsevier. https://doi.org/10.1016/B978-0-12-814818-1.00007-X

• Ashik, F. R., Rahman, H., Zafri, N. M., Antipova, A., & Labib, S. M. (2024). Car ownership, commute distance, and commute mode choice in the dense megacity of a developing country: The direct and indirect role of the built environment. Transportation Research Record, 2678(12), 1923–1938. https://doi.org/10.1177/03611981241253578

• Chairassamee, N., Chancharoenchai, K., & Saraithong, W. (2023). How commuting choices affect physical and mental health: A case study of Bangkok, Thailand. Kasetsart Journal of Social Sciences, 44(4), 1257–1272. https://doi.org/10.34044/j.kjss.2023.44.4.30

• Chopyot, S., & Samakeetham, S. (2024). The discourse of decentralization in Thailand: A study of political, administrative, and financial aspects. International Journal of Religion, 5(12), 650–660. https://doi.org/10.61707/rwrhfw54

• Gerdsri, N., Sivara, K., Chatunawarat, C., Jaroonjitsathian, S., & Tundulyasaree, K. (2022). Roadmap for future mobility development supporting Bangkok urban living in 2030. Sustainability, 14(15), Article 9296. https://www.mdpi.com/2071-1050/14/15/9296

• Giménez-Nadal, J. I., & Molina, J. A. (2016). Commuting time and household responsibilities: Evidence using propensity score matching. Journal of Regional Science, 56(2), 332–359. https://doi.org/10.1111/jors.12243

• Iamtrakul, P., Padon, A., Chayphong, S., & Hayashi, Y. (2024). Unlocking urban accessibility: Proximity analysis in Bangkok, Thailand’s mega city. Sustainability, 16(8), Article 3137. https://www.mdpi.com/2071-1050/16/8/3137

• Iamtrakul, P., Padon, A., & Klaylee, J. (2023). Measuring spatializing inequalities of transport accessibility and urban development patterns: Focus on megacity urbanization, Thailand. Journal of Regional and City Planning, 33(3), 345–366. https://doi.org/10.5614/jpwk.2022.33.3.4

• Jinawa, L., & Thepanondh, S. (2016). Success of fuel quality improving policy in reducing benzene air concentrations in Bangkok. International Journal of GEOMATE, 11(24), 2341–2347. https://doi.org/10.21660/2016.24.1196

• Khan, M. A. M. (2021). A review of traffic-related air pollution. International Journal of Engineering, 8(6), 11761–11766. https://doi.org/10.34259/IJEW.21.806175179

• Kyaing, T. A., Lwin, K. K., & Sekimoto, Y. (2020). An investigation of socioeconomic and land use influence on car ownership in Yangon City. Journal of Disaster Research, 15(3), 416–425. https://doi.org/10.20965/jdr.2020.p0416

• Losiri, C., Nagai, M., Ninsawat, S., & Shrestha, R. P. (2016). Modeling urban expansion in Bangkok Metropolitan Region using demographic–economic data through cellular automata-Markov chain and multi-layer perceptron-Markov chain models. Sustainability, 8(7), Article 686. https://doi.org/10.3390/su8070686

• Luiu, C., Tight, M., & Burrow, M. (2018). Factors preventing the use of alternative transport modes to the car in later life. Sustainability, 10(6), Article 1982. https://www.mdpi.com/2071-1050/10/6/1982

• McDonald, C. C., & Mirman, J. H. (2022). Achieving transportation equity: How can we support young people’s autonomy and health in a rapidly changing society? Journal of Adolescent Health, 70(5), 701–702. https://doi.org/10.1016/j.jadohealth.2022.02.007

• Miao, Q., Bouchard, M., Chen, D., Rosenberg, M. W., & Aronson, K. J. (2015). Commuting behaviors and exposure to air pollution in Montreal, Canada. Science of The Total Environment, 508, 193–198. https://doi.org/10.1016/j.scitotenv.2014.11.078

• Natchaphon, B. (2024, September 13). Krung Thep baeng phuenthi yang ngai: Son nai yu? Khet chan nok, chan klang, chan nai, ma du kan [How is Bangkok divided? Which zones are outer, middle, and inner districts?]. Sanook.com. https://www.sanook.com/campus/1426579/

• National Statistical Office. (2016). Rai-ngan kan samruat kan yai thi thi 2558 [The 2015 Migration Survey]. https://www.nso.go.th/nsoweb/storage/survey_detail/2023/20230501004434_35447.pdf

• National Statistical Office. (2024). Rai-ngan kan samruat kan yai thin khong prachakon Phō̜.Sō̜. 2566 [The 2023 Migration Survey]. https://www.nso.go.th/nsoweb/storage/survey_detail/2024/20240308121915_29708.pdf

• Neto, R. S., Duarte, G., & Paéz, A. (2015). Gender and commuting time in São Paulo Metropolitan Region. Urban Studies, 52(2), 298–313. https://doi.org/10.1177/0042098014528392

• Pereira, R. H. M., & Schwanen, T. (2015). Commute time in Brazil (1992–2009): Differences between metropolitan areas, by income levels and gender (Discussion Paper No. 192). Institute for Applied Economic Research (IPEA). https://repositorio.ipea.gov.br/bitstream/11058/5140/1/DiscussionPaper_192.pdf

• Pourhashem, G., Malichová, E., Piscová, T., & Kováčiková, T. (2022). Gender difference in perception of value of travel time and travel mode choice behavior in eight European countries. Sustainability, 14(16), Article 10426. https://www.mdpi.com/2071-1050/14/16/10426

• Prasartkul, P., Thaweesit, S., & Chuanwan, S. (2018). Prospects and contexts of demographic transitions in Thailand. Journal of Population and Social Studies, 27(1), 1–22. https://doi.org/10.25133/JPSSv27n1.001

• Punyamurthy, C., & Bheenaveni, R. S. (2023). Urbanization in India: An overview of trends, causes, and challenges. International Journal of Asian Economic Light, 11(1), 9–20. https://doi.org/10.36713/epra12473

• Rachele, J. N., Kavanagh, A. M., Badland, H., Giles-Corti, B., Washington, S., & Turrell, G. (2015). Associations between individual socioeconomic position, neighbourhood disadvantage and transport mode: Baseline results from the HABITAT multilevel study. Journal of Epidemiology and Community Health, 69(12), 1217–1223. https://doi.org/10.1136/jech-2015-205620

• Rahman, H., & Ashik, F. R. (2020). Is neighborhood-level jobs-housing balance associated with travel behavior of commuters? A case study on Dhaka City, Bangladesh. GeoScape, 14(2), 122–133. https://doi.org/10.2478/GEOSC-2020-0011

• Roos, J. M., Sprei, F., & Holmberg, U. (2020). Sociodemography, geography, and personality as determinants of car driving and use of public transportation. Systems Research and Behavioral Science, 10(6), Article 93. https://doi.org/10.3390/bs10060093

• Saigal, T., Vaish, A. K., & Rao, N. (2023). Gender gap in travel behaviour and public opinion on proposed policy measures: Evidence from India. International Social Science Journal, 73(247), 51–71. https://doi.org/10.1111/issj.12391

• Sharma, A., & Chandrasekhar, S. (2016). Impact of commuting by workers on household dietary diversity in rural India. Food Policy, 59, 34–43. https://doi.org/10.1016/j.foodpol.2015.11.005

• Sun, Z., & Zacharias, J. (2020). Do housing tenure and public transport provision matter in automobile use in bedroom suburban communities? Evidence from Beijing. Journal of Housing and the Built Environment, 36, 241–262. https://doi.org/10.1007/s10901-020-09748-2

• Thongchaithanawut, M., & Tangchonlatip, K. (2019). Population dynamics in the Bangkok Metropolitan Region during the period 2014–2016. Journal of Demography, 35(2), Article 1313. https://doi.org/10.56808/2730-3934.1313

• Traffic and Transportation Department. (2024). Satiti charatrot pi 2566 [Traffic statistics in 2023]. Bangkok Metropolitan Administration. https://traffic.bangkok.go.th/TrafficINFO/StatBook/2566/2566small.pdf

• Truong, L. T., & Somenahalli, S. V. C. (2015). Exploring frequency of public transport use among older adults: A study in Adelaide, Australia. Travel Behaviour and Society, 2(3), 148–155. https://doi.org/10.1016/j.tbs.2014.12.004

• Uteng, T. P. (2021). Chapter Two – Gender gaps in urban mobility and transport planning. In R. H. M. Pereira & G. Boisjoly (Eds.), Advances in Transport Policy and Planning (Vol. 8, pp. 33–69). Academic Press. https://doi.org/10.1016/bs.atpp.2021.07.004

• Verma, P., Jangra, R., & Kaushik, S. (2024). Geospatial measurement of urban sprawl and land transformation using multi-temporal datasets: A case study of Sonipat-Kundli urban agglomeration. Sustainable Environment, 10(1), Article 2366556. https://doi.org/10.1080/27658511.2024.2366556

• Wethyavivorn, P., & Sukwattanakorn, N. (2019). Problems and barriers affecting sustainable commuting: Case study of people’s daily commute to Kasetsart University, Bangkok, Thailand. IOP Conference Series: Earth and Environmental Science, 329(1), Article 012011. https://doi.org/10.1088/1755-1315/329/1/012011

• Whittle, C., Whitmarsh, L., Nash, N., & Poortinga, W. (2022). Life events and their association with changes in the frequency of transport use in a large UK sample. Travel Behaviour and Society, 28, 273–287. https://doi.org/10.1016/j.tbs.2022.04.007

• Wilinski, K., & Pathak, S. (2022). Mobility in the developing country. The case study of Bangkok Metropolitan Region. Communications - Scientific Letters of the University of Zilina, 24(3), A112–A122. https://doi.org/10.26552/com.C.2022.3.A112-A122

• Witchayaphong, P., Pravinvongvuth, S., Kanitpong, K., Sano, K., & Horpibulsuk, S. (2020). Influential factors affecting travelers’ mode choice behavior on mass transit in Bangkok, Thailand. Sustainability, 12(22), Article 9522. https://doi.org/10.3390/su12229522

• Wong, L. P., Alias, H., Aghamohammadi, N., Ghadimi, A., & Sulaiman, N. M. N. (2017). Control measures and health effects of air pollution: A survey among public transportation commuters in Malaysia. Sustainability, 9(9), Article 1616. https://www.mdpi.com/2071-1050/9/9/1616

• Yatmar, H., Ramli, M. I., Pasra, M., Gusfiadi, & Dharmowijoyo, D. B. E. (2021). The impact of socio-demographic and activity-travel participation variables on mode choice preference of sub-urban commuters: A case study on the new railway operation in Maros-Makassar line. In B. S. Mohammed, N. Shafiq, S. R. M. Kutty, H. Mohamad, & A.-L. Balogun (Eds.), ICCOEE2020. Lecture Notes in Civil Engineering (Vol. 132, pp. 945–955). Springer Singapore. https://doi.org/10.1007/978-981-33-6311-3_107

• Yue, L., Niedzielski, M. A., & O'Kelly, M. E. (2024). Modal disparity in commuting efficiency: A comparison across educational worker subgroups in Shanghai. Cities, 147, Article 104790. https://doi.org/10.1016/j.cities.2024.104790

• Zakaria, A. M., Kamaluddin, N. A., Hashim, W., & D’Agostino, C. (2024). Age-inclusive transit environments: An exploration of public transportation systems for elderly. Environment-Behaviour Proceedings Journal, 9(28), 149–158. https://doi.org/10.21834/e-bpj.v9i28.5906

• Zhang, J. (2020). Residential location and commuting mode choices: Intrahousehold interaction modeling and its implications for energy policy. In J. Zhang (Ed.), Transport and Energy Research (pp. 155–175). Elsevier. https://doi.org/10.1016/B978-0-12-815965-1.00007-7

• Zhang, N., & Yang, Q. (2024). Public transport inclusion and active aging: A systematic review on elderly mobility. Journal of Traffic and Transportation Engineering (English Edition), 11(2), 312–347. https://doi.org/10.1016/j.jtte.2024.04.001

• Zhang, Y., Zheng, S., Sun, C., & Wang, R. (2017). Does subway proximity discourage automobility? Evidence from Beijing. Transportation Research Part D: Transport and Environment, 52, 506–517. https://doi.org/10.1016/j.trd.2016.11.009

• Zhao, X., Zhang, Z., Guo, W., Zhou, Y., Papaix, C., & Sun, Q. (2022). Evidence-based smart transition strategies for long-distance commuters in Beijing. Frontiers in Future Transportation, 3, Article 884949. https://doi.org/10.3389/ffutr.2022.884949

• Zhou, H., & Gao, H. (2020). The impact of urban morphology on urban transportation mode: A case study of Tokyo. Case Studies on Transport Policy, 8(1), 197–205. https://doi.org/10.1016/j.cstp.2018.07.005