IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i22p9522-d445683.html
   My bibliography  Save this article

Influential Factors Affecting Travelers’ Mode Choice Behavior on Mass Transit in Bangkok, Thailand

Author

Listed:
  • Phattarasuda Witchayaphong

    (Transportation Engineering, School of Engineering and Technology, Asian Institute of Technology, Bangkok 12120, Thailand)

  • Surachet Pravinvongvuth

    (Transportation Engineering, School of Engineering and Technology, Asian Institute of Technology, Bangkok 12120, Thailand)

  • Kunnawee Kanitpong

    (Transportation Engineering, School of Engineering and Technology, Asian Institute of Technology, Bangkok 12120, Thailand)

  • Kazushi Sano

    (Department of Civil and Environmental Engineering, Nagaoka University of Technology, Niigata 940-2188, Japan)

  • Suksun Horpibulsuk

    (School of Civil Engineering, and Center of Excellence in Innovation for Sustainable Infrastructure Development, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
    Academy of Science, The Royal Society of Thailand, Bangkok 10300, Thailand)

Abstract

Increasing use of single or fewer occupant vehicles has increased traffic congestion and transport-related emissions. Public transport as mass transit options are increasingly being encouraged amongst travelers to use, as this is an influential strategy to improve the transport network performance. This paper presents a study based on a revealed preference survey conducted on a random sample of 4467 respondents to understand the influential factors affecting the users’ choice of mass transit in Bangkok, Thailand. This study identified an inversely proportional relationship of socio-economic and spatial attributes on public transport mode choice. The binary logit model was employed to compare the utility of private vehicles and mass transit modes. The results showed that gender, age, average income, auto ownership, total travel cost in private transport, total travel time in public transport and distance range from home to mass transit station were the factors that influenced travelers’ mode choice behavior. Moreover, to ascertain the effects of explanatory variables which influence the likelihood of Thai travelers, another binary logit model analysis was utilized by the four distance ranges condition. The studied results showed that there were few significant differences in the propensity to use mass transit. Due to the longer distance of the station, total travel time in public transport was not affected by the Thai travelers mode choice. This research will aid transport authorities and planners to gain knowledge on the impact of socio-economic and spatial behavior of public transport users on their mode choice, resulting in the development in sustainable transport in Bangkok, Thailand.

Suggested Citation

  • Phattarasuda Witchayaphong & Surachet Pravinvongvuth & Kunnawee Kanitpong & Kazushi Sano & Suksun Horpibulsuk, 2020. "Influential Factors Affecting Travelers’ Mode Choice Behavior on Mass Transit in Bangkok, Thailand," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:22:p:9522-:d:445683
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/22/9522/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/22/9522/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sohani Liyanage & Hussein Dia, 2020. "An Agent-Based Simulation Approach for Evaluating the Performance of On-Demand Bus Services," Sustainability, MDPI, vol. 12(10), pages 1-20, May.
    2. Rusul Abduljabbar & Hussein Dia & Sohani Liyanage & Saeed Asadi Bagloee, 2019. "Applications of Artificial Intelligence in Transport: An Overview," Sustainability, MDPI, vol. 11(1), pages 1-24, January.
    3. Hakim Hammadou & Claire Papaix, 2015. "Policy packages for modal shift and CO2 reduction in Lille, France," Post-Print hal-01533557, HAL.
    4. Buehler, Ralph, 2011. "Determinants of transport mode choice: a comparison of Germany and the USA," Journal of Transport Geography, Elsevier, vol. 19(4), pages 644-657.
    5. Wanpen Charoentrakulpeeti & Edsel Sajor & Willi Zimmermann, 2006. "Middle‐class Travel Patterns, Predispositions and Attitudes, and Present‐day Transport Policy in Bangkok, Thailand," Transport Reviews, Taylor & Francis Journals, vol. 26(6), pages 693-712, April.
    6. Cynthia Chen & Hongmian Gong & Robert Paaswell, 2008. "Role of the built environment on mode choice decisions: additional evidence on the impact of density," Transportation, Springer, vol. 35(3), pages 285-299, May.
    7. Kevin Washbrook & Wolfgang Haider & Mark Jaccard, 2006. "Estimating commuter mode choice: A discrete choice analysis of the impact of road pricing and parking charges," Transportation, Springer, vol. 33(6), pages 621-639, November.
    8. Frieden, T.R., 2010. "A framework for public health action: The health impact pyramid," American Journal of Public Health, American Public Health Association, vol. 100(4), pages 590-595.
    9. Chalak, Ali & Al-Naghi, Hani & Irani, Alexandra & Abou-Zeid, Maya, 2016. "Commuters’ behavior towards upgraded bus services in Greater Beirut: Implications for greenhouse gas emissions, social welfare and transport policy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 265-285.
    10. Eboli, Laura & Forciniti, Carmen & Mazzulla, Gabriella, 2018. "Spatial variation of the perceived transit service quality at rail stations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PA), pages 67-83.
    11. Daniel Albalate & Xavier Fageda, 2019. "Congestion, Road Safety, and the Effectiveness of Public Policies in Urban Areas," Sustainability, MDPI, vol. 11(18), pages 1-21, September.
    12. Chidambaram, Bhuvanachithra & Janssen, Marco A. & Rommel, Jens & Zikos, Dimitrios, 2014. "Commuters’ mode choice as a coordination problem: A framed field experiment on traffic policy in Hyderabad, India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 9-22.
    13. Santos, Georgina, 2017. "Road transport and CO2 emissions: What are the challenges?," Transport Policy, Elsevier, vol. 59(C), pages 71-74.
    14. Siavash Khalili & Eetu Rantanen & Dmitrii Bogdanov & Christian Breyer, 2019. "Global Transportation Demand Development with Impacts on the Energy Demand and Greenhouse Gas Emissions in a Climate-Constrained World," Energies, MDPI, vol. 12(20), pages 1-54, October.
    15. Fu, Xuemei & Juan, Zhicai, 2017. "Exploring the psychosocial factors associated with public transportation usage and examining the “gendered” difference," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 70-82.
    16. Cristian Domarchi & Alejandro Tudela & Angélica González, 2008. "Effect of attitudes, habit and affective appraisal on mode choice: an application to university workers," Transportation, Springer, vol. 35(5), pages 585-599, August.
    17. Rebeca Fontanilla Andong & Edsel Sajor, 2017. "Urban sprawl, public transport, and increasing CO2 emissions: the case of Metro Manila, Philippines," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(1), pages 99-123, February.
    18. Sohani Liyanage & Hussein Dia & Rusul Abduljabbar & Saeed Asadi Bagloee, 2019. "Flexible Mobility On-Demand: An Environmental Scan," Sustainability, MDPI, vol. 11(5), pages 1-39, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maurizio Faccio & Serena Finco & Ilenia Zennaro, 2021. "Sustainable People Home-Work Logistics: An Integrated Model of Circular Economy in the Chiampo Valley," Sustainability, MDPI, vol. 13(21), pages 1-13, October.
    2. Masanobu Kii & Yuki Goda & Varameth Vichiensan & Hiroyuki Miyazaki & Rolf Moeckel, 2021. "Assessment of Spatiotemporal Peak Shift of Intra-Urban Transportation Taking a Case in Bangkok, Thailand," Sustainability, MDPI, vol. 13(12), pages 1-16, June.
    3. Maosheng Li & Hui Xie & Panpan Shu, 2021. "Study on the Impact of Traffic Accidents in Key Areas of Rural Roads," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    4. Julio César dos Santos & Paulo Ribeiro & Ricardo Jorge Silva Bento, 2023. "A Review of the Promotion of Sustainable Mobility of Workers by Industries," Sustainability, MDPI, vol. 15(11), pages 1-18, May.
    5. Lingjuan Chen & Yijing Zhao & Zupeng Liu & Xinran Yang, 2022. "Construction of Commuters’ Multi-Mode Choice Model Based on Public Transport Operation Data," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    6. Hiranya Sritart & Kuson Tuntiwong & Hiroyuki Miyazaki & Somchat Taertulakarn, 2021. "Disparities in Healthcare Services and Spatial Assessments of Mobile Health Clinics in the Border Regions of Thailand," IJERPH, MDPI, vol. 18(20), pages 1-24, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chakrabarti, Sandip, 2017. "How can public transit get people out of their cars? An analysis of transit mode choice for commute trips in Los Angeles," Transport Policy, Elsevier, vol. 54(C), pages 80-89.
    2. Bereitschaft, Bradley, 2020. "Gentrification and the evolution of commuting behavior within America's urban cores, 2000–2015," Journal of Transport Geography, Elsevier, vol. 82(C).
    3. Khandker M. Nurul Habib & Md. Hamid Zaman, 2012. "Effects of incorporating latent and attitudinal information in mode choice models," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(5), pages 561-576, June.
    4. Eldeeb, Gamal & Mohamed, Moataz & Páez, Antonio, 2021. "Built for active travel? Investigating the contextual effects of the built environment on transportation mode choice," Journal of Transport Geography, Elsevier, vol. 96(C).
    5. Cottrill, Caitlin D. & Brooke, Sarah & Mulley, Corinne & Nelson, John D. & Wright, Steve, 2020. "Can multi-modal integration provide enhanced public transport service provision to address the needs of vulnerable populations?," Research in Transportation Economics, Elsevier, vol. 83(C).
    6. Altieri, Marcelo & Silva, Cecília & Terabe, Shintaro, 2020. "Give public transit a chance: A comparative analysis of competitive travel time in public transit modal share," Journal of Transport Geography, Elsevier, vol. 87(C).
    7. Moeinaddini, Amin & Habibian, Meeghat, 2023. "Transportation demand management policy efficiency: An attempt to address the effectiveness and acceptability of policy packages," Transport Policy, Elsevier, vol. 141(C), pages 317-330.
    8. Bueno, Paola Carolina & Gomez, Juan & Peters, Jonathan R. & Vassallo, Jose Manuel, 2017. "Understanding the effects of transit benefits on employees’ travel behavior: Evidence from the New York-New Jersey region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 1-13.
    9. Vega-Gonzalo, Maria & Gomez, Juan & Christidis, Panayotis, 2023. "How has COVID-19 changed private car use in European urban areas? An analysis of the effect of socio-economic characteristics and mobility habits," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    10. Jin, Fanglei & Yao, Enjian & An, Kun, 2020. "Analysis of the potential demand for battery electric vehicle sharing: Mode share and spatiotemporal distribution," Journal of Transport Geography, Elsevier, vol. 82(C).
    11. Su, Qing & Zhou, Liren, 2012. "Parking management, financial subsidies to alternatives to drive alone and commute mode choices in Seattle," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 88-97.
    12. Vanoutrive, Thomas & Van De Vijver, Elien & Van Malderen, Laurent & Jourquin, Bart & Thomas, Isabelle & Verhetsel, Ann & Witlox, Frank, 2012. "What determines carpooling to workplaces in Belgium: location, organisation, or promotion?," Journal of Transport Geography, Elsevier, vol. 22(C), pages 77-86.
    13. Jahun Koo & Sangho Choo, 2022. "Identification of Causal Relationship between Attitudinal Factors and Intention to Use Transportation Mode," Sustainability, MDPI, vol. 14(24), pages 1-15, December.
    14. Qihao Liu & Yuzheng Liu & Chia-Lin Chen & Enrica Papa & Yantao Ling & Mengqiu Cao, 2023. "Is It Possible to Compete With Car Use? How Buses Can Facilitate Sustainable Transport," Urban Planning, Cogitatio Press, vol. 8(3), pages 69-83.
    15. Kamruzzaman, Md. & Baker, Douglas & Washington, Simon & Turrell, Gavin, 2013. "Residential dissonance and mode choice," Journal of Transport Geography, Elsevier, vol. 33(C), pages 12-28.
    16. Mendez Lopez, Ana & Loopstra, Rachel & McKee, Martin & Stuckler, David, 2017. "Is trade liberalisation a vector for the spread of sugar-sweetened beverages? A cross-national longitudinal analysis of 44 low- and middle-income countries," Social Science & Medicine, Elsevier, vol. 172(C), pages 21-27.
    17. Vij, Akshay & Walker, Joan L., 2016. "How, when and why integrated choice and latent variable models are latently useful," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 192-217.
    18. Chen Zhang & Xiaoming Li & Yu Liu & Shan Qiao & Liying Zhang & Yuejiao Zhou & Zhenzhu Tang & Zhiyong Shen & Yi Chen, 2016. "Stigma against People Living with HIV/AIDS in China: Does the Route of Infection Matter?," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    19. Oyewo, Ayobami Solomon & Solomon, A.A. & Bogdanov, Dmitrii & Aghahosseini, Arman & Mensah, Theophilus Nii Odai & Ram, Manish & Breyer, Christian, 2021. "Just transition towards defossilised energy systems for developing economies: A case study of Ethiopia," Renewable Energy, Elsevier, vol. 176(C), pages 346-365.
    20. Li, Jingjing & Kim, Changjoo & Sang, Sunhee, 2018. "Exploring impacts of land use characteristics in residential neighborhood and activity space on non-work travel behaviors," Journal of Transport Geography, Elsevier, vol. 70(C), pages 141-147.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:22:p:9522-:d:445683. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.