IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i15p6715-d1708388.html
   My bibliography  Save this article

Willingness to Pay for Station Access Transport: A Mixed Logit Model with Heterogeneous Travel Time Valuation

Author

Listed:
  • Varameth Vichiensan

    (Department of Civil Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand)

  • Vasinee Wasuntarasook

    (Department of Civil Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand)

  • Sathita Malaitham

    (PSK Consultants, Bangkok 10400, Thailand)

  • Atsushi Fukuda

    (College of Science and Technology, Nihon University, Chiba 274-8501, Japan)

  • Wiroj Rujopakarn

    (Department of Civil Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand)

Abstract

This study estimates a willingness-to-pay (WTP) space mixed logit model to evaluate user valuations of travel time, safety, and comfort attributes associated with common access modes in Bangkok, including walking, motorcycle taxis, and localized minibuses. The model accounts for preference heterogeneity by specifying random parameters for travel time. Results indicate that users—exhibiting substantial variation in preferences—place higher value on reducing motorcycle taxi travel time, particularly in time-constrained contexts such as peak-hour commuting, whereas walking is more acceptable in less pressured settings. Safety and comfort attributes—such as helmet availability, smooth pavement, and seating—significantly influence access mode choice. Notably, the WTP for helmet availability is estimated at THB 8.04 per trip, equivalent to approximately 40% of the typical fare for station access, underscoring the importance of safety provision. Women exhibit stronger preferences for motorized access modes, reflecting heightened sensitivity to environmental and social conditions. This study represents one of the first applications of WTP-space modeling for valuing informal station access transport in Southeast Asia, offering context-specific and segment-level estimates. These findings support targeted interventions—including differentiated pricing, safety regulations, and service quality enhancements—to strengthen first-/last-mile connectivity. The results provide policy-relevant evidence to advance equitable and sustainable transport, particularly in rapidly urbanizing contexts aligned with SDG 11.2.

Suggested Citation

  • Varameth Vichiensan & Vasinee Wasuntarasook & Sathita Malaitham & Atsushi Fukuda & Wiroj Rujopakarn, 2025. "Willingness to Pay for Station Access Transport: A Mixed Logit Model with Heterogeneous Travel Time Valuation," Sustainability, MDPI, vol. 17(15), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:6715-:d:1708388
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/15/6715/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/15/6715/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Khanh Pham & Quynh Thi & Dennis Petrie & Jon Adams & Christopher Doran, 2008. "Households’ willingness to pay for a motorcycle helmet in Hanoi, Vietnam," Applied Health Economics and Health Policy, Springer, vol. 6(2), pages 137-144, July.
    2. Gupta, Akshay & Bivina, G.R. & Parida, Manoranjan, 2022. "Does neighborhood design matter for walk access to metro stations? An integrated SEM-Hybrid discrete mode choice approach," Transport Policy, Elsevier, vol. 121(C), pages 61-77.
    3. Varameth Vichiensan & Kazuki Nakamura, 2021. "Walkability Perception in Asian Cities: A Comparative Study in Bangkok and Nagoya," Sustainability, MDPI, vol. 13(12), pages 1-22, June.
    4. Eboli, Laura & Mazzulla, G., 2008. "Willingness-to-pay of public transport users for improvement in service quality," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 38, pages 107-118.
    5. Kar, Manaswinee & Sadhukhan, Shubhajit & Parida, Manoranjan, 2022. "Assessing commuters’ perceptions towards improvement of intermediate public transport as access modes to metro stations," Transport Policy, Elsevier, vol. 129(C), pages 140-155.
    6. Yuanyuan Guo & Linchuan Yang & Wenke Huang & Yi Guo, 2020. "Traffic Safety Perception, Attitude, and Feeder Mode Choice of Metro Commute: Evidence from Shenzhen," IJERPH, MDPI, vol. 17(24), pages 1-20, December.
    7. Das, Deepjyoti & Bhaduri, Eeshan & Velaga, Nagendra R., 2023. "Modeling commuters’ preference towards sharing paratransit services," Transport Policy, Elsevier, vol. 143(C), pages 132-149.
    8. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    9. Li, Zheng & Hensher, David A., 2011. "Crowding and public transport: A review of willingness to pay evidence and its relevance in project appraisal," Transport Policy, Elsevier, vol. 18(6), pages 880-887, November.
    10. Sajjakaj Jomnonkwao & Duangdao Watthanaklang & Onanong Sangphong & Thanapong Champahom & Napat Laddawan & Savalee Uttra & Vatanavongs Ratanavaraha, 2020. "A Comparison of Motorcycle Helmet Wearing Intention and Behavior between Urban and Rural Areas," Sustainability, MDPI, vol. 12(20), pages 1-16, October.
    11. Kang, Seongmin & Chung, Yongjin & Yang, Byungsoo & Lee, Hyukseong & Lee, Jun & Kim, Jinhee, 2024. "User preference and willingness-to-pay for operation strategies that enhance safety and convenience of E-scooter sharing services," Transport Policy, Elsevier, vol. 146(C), pages 31-41.
    12. Guan, Jinping & Chen, Kexin & Mao, Runfei & Shamshiripour, Ali & Zhang, Xiaochun & Liang, Chen & Ben-Akiva, Moshe, 2024. "The willingness to pay for the automated vehicle subscription: Insights from a car-oriented population in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 188(C).
    13. Wang, Chen & Sun, Jiayi & Russell, Roddy & Daziano, Ricardo A., 2018. "Analyzing willingness to improve the resilience of New York City's transportation system," Transport Policy, Elsevier, vol. 69(C), pages 10-19.
    14. Eldeeb, Gamal & Mohamed, Moataz, 2020. "Quantifying preference heterogeneity in transit service desired quality using a latent class choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 119-133.
    15. Walker, Joan & Ben-Akiva, Moshe, 2002. "Generalized random utility model," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 303-343, July.
    16. Solvi Hoen, Fredrik & Díez-Gutiérrez, María & Babri, Sahar & Hess, Stephane & Tørset, Trude, 2023. "Charging electric vehicles on long trips and the willingness to pay to reduce waiting for charging. Stated preference survey in Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    17. Park, Keunhyun & Farb, Anna & Chen, Shuolei, 2021. "First-/last-mile experience matters: The influence of the built environment on satisfaction and loyalty among public transit riders," Transport Policy, Elsevier, vol. 112(C), pages 32-42.
    18. Shoaib, Amna, 2025. "Addressing women's mobility challenges in the public transportation system of Lahore, Pakistan," Journal of Transport Geography, Elsevier, vol. 125(C).
    19. Mauricio Sillano & Juan de Dios Ortúzar, 2005. "Willingness-to-Pay Estimation with Mixed Logit Models: Some New Evidence," Environment and Planning A, , vol. 37(3), pages 525-550, March.
    20. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    21. Bwambale, Andrew & Uzondu, Chinebuli & Islam, Mohaimanul & Rahman, Farzana & Batool, Zahara & Isolo Mukwaya, Paul & Wadud, Zia, 2023. "Willingness to pay for COVID-19 mitigation measures in public transport and paratransit in low-income countries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
    22. Wang, Kaili & Salehin, Mohammad Faizus & Nurul Habib, Khandker, 2021. "A discrete choice experiment on consumer’s willingness-to-pay for vehicle automation in the Greater Toronto Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 12-30.
    23. Varameth Vichiensan & Vasinee Wasuntarasook & Titipakorn Prakayaphun & Masanobu Kii & Yoshitsugu Hayashi, 2023. "Influence of Urban Railway Network Centrality on Residential Property Values in Bangkok," Sustainability, MDPI, vol. 15(22), pages 1-25, November.
    24. repec:xrs:meawpa:02009 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    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. Tinessa, Fiore & Román Garcia, Concepción & Simonelli, Fulvio & Papola, Andrea & Pagliara, Francesca, 2024. "How public transport users would react to different pandemic alert scenarios in the post-vaccine era? An analysis of preferences and attitudes of the users in the metropolitan area of Naples (Italy)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 190(C).
    2. Kapatsila, Bogdan & Bahamonde-Birke, Francisco J. & van Lierop, Dea & Grisé, Emily, 2023. "Impact of the COVID-19 pandemic on the comfort of riding a crowded bus in Metro Vancouver, Canada," Transport Policy, Elsevier, vol. 141(C), pages 83-96.
    3. Basnak, Paul & Giesen, Ricardo & Muñoz, Juan Carlos, 2022. "Estimation of crowding factors for public transport during the COVID-19 pandemic in Santiago, Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 140-156.
    4. Jia, Wenjian & Chen, T. Donna, 2023. "Investigating heterogeneous preferences for plug-in electric vehicles: Policy implications from different choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    5. Beeramoole, Prithvi Bhat & Arteaga, Cristian & Pinz, Alban & Haque, Md Mazharul & Paz, Alexander, 2023. "Extensive hypothesis testing for estimation of mixed-Logit models," Journal of choice modelling, Elsevier, vol. 47(C).
    6. Eldeeb, Gamal & Mohamed, Moataz, 2022. "Consumers oriented investments in transit service quality improvements: The best bang for your buck," Research in Transportation Economics, Elsevier, vol. 94(C).
    7. Barrientos, Manuel & Lavin, Felipe Vasquez & Ponce Oliva, Roberto D., 2020. "Assessing the Incorporation of Latent Variables in the Estimation of the Value of a Statistical Life," EfD Discussion Paper 20-22, Environment for Development, University of Gothenburg.
    8. Chorus, Caspar & van Cranenburgh, Sander & Daniel, Aemiro Melkamu & Sandorf, Erlend Dancke & Sobhani, Anae & Szép, Teodóra, 2021. "Obfuscation maximization-based decision-making: Theory, methodology and first empirical evidence," Mathematical Social Sciences, Elsevier, vol. 109(C), pages 28-44.
    9. Cai, Yangqian & Moreno, Ana Tsui, 2024. "Identifying non-universal heterogeneity of preferences of leisure cyclists for rural highway environments: A latent-class model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).
    10. Kim, Seheon & Rasouli, Soora, 2022. "The influence of latent lifestyle on acceptance of Mobility-as-a-Service (MaaS): A hierarchical latent variable and latent class approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 304-319.
    11. Daziano, Ricardo A., 2015. "Inference on mode preferences, vehicle purchases, and the energy paradox using a Bayesian structural choice model," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 1-26.
    12. Malte Welling & Ewa Zawojska & Julian Sagebiel, 2022. "Information, Consequentiality and Credibility in Stated Preference Surveys: A Choice Experiment on Climate Adaptation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 82(1), pages 257-283, May.
    13. Daina, Nicolò & Sivakumar, Aruna & Polak, John W., 2017. "Modelling electric vehicles use: a survey on the methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 447-460.
    14. Amaya, Johanna & Encarnación, Trilce & Delgado-Lindeman, Maira, 2023. "Understanding Delivery Drivers’ Parking Preferences in Urban Freight Operations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    15. Scorrano, Mariangela & Danielis, Romeo, 2021. "Active mobility in an Italian city: Mode choice determinants and attitudes before and during the Covid-19 emergency," Research in Transportation Economics, Elsevier, vol. 86(C).
    16. Joan L. Walker & Moshe Ben-Akiva, 2011. "Advances in Discrete Choice: Mixture Models," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 8, Edward Elgar Publishing.
    17. Strazzera, Elisabetta & Meleddu, Daniela & Atzori, Rossella, 2022. "A hybrid choice modelling approach to estimate the trade-off between perceived environmental risks and economic benefits," Ecological Economics, Elsevier, vol. 196(C).
    18. Wang, Qingyi & Wang, Shenhao & Zheng, Yunhan & Lin, Hongzhou & Zhang, Xiaohu & Zhao, Jinhua & Walker, Joan, 2024. "Deep hybrid model with satellite imagery: How to combine demand modeling and computer vision for travel behavior analysis?," Transportation Research Part B: Methodological, Elsevier, vol. 179(C).
    19. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    20. Parmar, Janak & Saiyed, Gulnazbanu & Dave, Sanjaykumar, 2023. "Analysis of taste heterogeneity in commuters’ travel decisions using joint parking– and mode–choice model: A case from urban India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:17:y:2025:i:15:p:6715-:d:1708388. 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.