IDEAS home Printed from https://ideas.repec.org/a/taf/transp/v37y2014i7p638-648.html
   My bibliography  Save this article

Estimation of a route choice model for urban public transport using smart card data

Author

Listed:
  • Ľudmila Jánošíková
  • Jiří Slavík
  • Michal Koháni

Abstract

This paper describes a logit model of route choice for urban public transport and explains how the archived data from a smart card-based fare payment system can be used for the choice set generation and model estimation. It demonstrates the feasibility and simplicity of applying a trip-chaining method to infer passenger journeys from smart card transactions data. Not only origins and destinations of passenger journeys can be inferred but also the interchanges between the segments of a linked journey can be recognised. The attributes of the corresponding routes, such as in-vehicle travel time, transfer walking time and to get from alighting stop to trip destination, the need to change, and the time headway of the first transportation line, can be determined by the combination of smart card data with other data sources, such as a street map and timetable. The smart card data represent a large volume of revealed preference data that allows travellers' behaviour to be modelled with higher accuracy than by using traditional survey data. A multinomial route choice model is proposed and estimated by the maximum likelihood method, using urban public transport in Žilina, the Slovak Republic, as a case study

Suggested Citation

  • Ľudmila Jánošíková & Jiří Slavík & Michal Koháni, 2014. "Estimation of a route choice model for urban public transport using smart card data," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(7), pages 638-648, October.
    • Handle: RePEc:taf:transp:v:37:y:2014:i:7:p:638-648
    DOI: 10.1080/03081060.2014.935570
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03081060.2014.935570
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03081060.2014.935570?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Laura Eboli & Gabriella Mazzulla, 2008. "A Stated Preference Experiment for Measuring Service Quality in Public Transport," Transportation Planning and Technology, Taylor & Francis Journals, vol. 31(5), pages 509-523, February.
    2. Bagchi, M. & White, P.R., 2005. "The potential of public transport smart card data," Transport Policy, Elsevier, vol. 12(5), pages 464-474, September.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    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. Mallikarjun Patil & Bandhan Bandhu Majumdar & Prasanta Kumar Sahu & Long T. Truong, 2021. "Evaluation of Prospective Users’ Choice Decision toward Electric Two-Wheelers Using a Stated Preference Survey: An Indian Perspective," Sustainability, MDPI, vol. 13(6), pages 1-22, March.
    2. Wang, Yacan & Geng, Kexin & May, Anthony D. & Zhou, Huiyu, 2022. "The impact of traffic demand management policy mix on commuter travel choices," Transport Policy, Elsevier, vol. 117(C), pages 74-87.
    3. Laura Eboli & Gabriella Mazzulla, 2014. "Investigating the heterogeneity of bus users' preferences through discrete choice modelling," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(8), pages 695-710, December.
    4. Alyamani, Ryan & Pappelis, Dimitrios & Kamargianni, Maria, 2024. "Modelling the determinants of electrical vehicles adoption in Riyadh, Saudi Arabia," Energy Policy, Elsevier, vol. 188(C).
    5. Wang, Yihong & Correia, Gonçalo Homem de Almeida & de Romph, Erik & Timmermans, H.J.P., 2017. "Using metro smart card data to model location choice of after-work activities: An application to Shanghai," Journal of Transport Geography, Elsevier, vol. 63(C), pages 40-47.
    6. Song, Shan & Wang, De & Zhu, Wei & Wang, Can, 2020. "Study on the spatial configuration of nursing homes for the elderly people in Shanghai: Based on their choice preference," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
    7. Loría, Luis Enrique & Watson, Verity & Kiso, Takahiko & Phimister, Euan, 2019. "Investigating users' preferences for Low Emission Buses: Experiences from Europe's largest hydrogen bus fleet," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    8. Beck, Matthew J. & Rose, John M., 2016. "The best of times and the worst of times: A new best–worst measure of attitudes toward public transport experiences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 108-123.
    9. Zhifeng Gao & Ted C. Schroeder, 2009. "Consumer responses to new food quality information: are some consumers more sensitive than others?," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 339-346, May.
    10. Cheng, Leilei & Yin, Changbin & Chien, Hsiaoping, 2015. "Demand for milk quantity and safety in urban China: evidence from Beijing and Harbin," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(2), April.
    11. Johannes Buggle & Thierry Mayer & Seyhun Orcan Sakalli & Mathias Thoenig, 2023. "The Refugee’s Dilemma: Evidence from Jewish Migration out of Nazi Germany," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(2), pages 1273-1345.
    12. Christelis, Dimitris & Dobrescu, Loretti I. & Motta, Alberto, 2020. "Early life conditions and financial risk-taking in older age," The Journal of the Economics of Ageing, Elsevier, vol. 17(C).
    13. Ortega, David L. & Wang, H. Holly & Wu, Laping & Hong, Soo Jeong, 2015. "Retail channel and consumer demand for food quality in China," China Economic Review, Elsevier, vol. 36(C), pages 359-366.
    14. Doyle, Orla & Fidrmuc, Jan, 2006. "Who favors enlargement?: Determinants of support for EU membership in the candidate countries' referenda," European Journal of Political Economy, Elsevier, vol. 22(2), pages 520-543, June.
    15. Tovar, Jorge, 2012. "Consumers’ Welfare and Trade Liberalization: Evidence from the Car Industry in Colombia," World Development, Elsevier, vol. 40(4), pages 808-820.
    16. Pereira, Pedro & Ribeiro, Tiago, 2011. "The impact on broadband access to the Internet of the dual ownership of telephone and cable networks," International Journal of Industrial Organization, Elsevier, vol. 29(2), pages 283-293, March.
    17. Mark Morrison & Craig Nalder, 2009. "Willingness to Pay for Improved Quality of Electricity Supply Across Business Type and Location," The Energy Journal, , vol. 30(2), pages 117-134, April.
    18. Simon P. Anderson & André de Palma, 2012. "Competition for attention in the Information (overload) Age," RAND Journal of Economics, RAND Corporation, vol. 43(1), pages 1-25, March.
    19. Mtimet, Nadhem & Ujiie, Kiyokazu & Kashiwagi, Kenichi & Zaibet, Lokman & Nagaki, Masakazu, 2011. "The effects of Information and Country of Origin on Japanese Olive Oil Consumer Selection," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114642, European Association of Agricultural Economists.
    20. Chavez, Daniel E. & Palma, Marco A. & Nayga, Rodolfo M. & Mjelde, James W., 2020. "Product availability in discrete choice experiments with private goods," Journal of choice modelling, Elsevier, vol. 36(C).

    More about this item

    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:taf:transp:v:37:y:2014:i:7:p:638-648. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GTPT20 .

    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.