IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v50y2013icp1-14.html
   My bibliography  Save this article

Evaluating the impacts of a new transit system on commuting mode choice using a GEV model estimated to revealed preference data: A case study of the VIVA system in York Region, Ontario

Author

Listed:
  • Forsey, David
  • Habib, Khandker Nurul
  • Miller, Eric J.
  • Shalaby, Amer

Abstract

The Regional Municipality of York, north of the City of Toronto, introduced a new bus service known as VIVA in 2005. This distinctly branded system operates primarily in two highly-travelled corridors and features high operating speeds, offline fare payment, advanced traveller information systems, and other ITS technologies. Although this new service has been deemed a success by many, it remains to be seen to what degree local work and post-secondary school transit use was affected by its introduction. To evaluate this, home-based work and post-secondary school trip mode choice models are estimated by using the datasets collected after the opening of the service. These models are then used to evaluate the impacts of the system on commuting mode choice preferences by using an additional dataset collected before opening the service. A GEV model is used to capture heterogeneity reflected in the RP datasets. The paper shows how modelling can be used to assess how level of service variables (e.g. travel times) can explain the impacts of new transit service. Empirical models reveal that the introduction of VIVA impacted the mode choice preference structure in the study area for work and post-secondary school trips. Also, it is shown that the improvements in transit service had greater impacts on transit mode share than the impacts of increasing traffic congestion. It is also posited that VIVA attributes such as improved branding, advertising, and communications may have caused this change in preferences.

Suggested Citation

  • Forsey, David & Habib, Khandker Nurul & Miller, Eric J. & Shalaby, Amer, 2013. "Evaluating the impacts of a new transit system on commuting mode choice using a GEV model estimated to revealed preference data: A case study of the VIVA system in York Region, Ontario," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 1-14.
    • Handle: RePEc:eee:transa:v:50:y:2013:i:c:p:1-14
    DOI: 10.1016/j.tra.2013.01.033
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856413000402
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2013.01.033?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. McDonnell, Simon & Zellner, Moira, 2011. "Exploring the effectiveness of bus rapid transit a prototype agent-based model of commuting behavior," Transport Policy, Elsevier, vol. 18(6), pages 825-835, November.
    2. Dubé, Jean & Rosiers, François Des & Thériault, Marius & Dib, Patricia, 2011. "Economic impact of a supply change in mass transit in urban areas: A Canadian example," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 46-62, January.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    4. Kiron Chatterjee, 2011. "Modelling the dynamics of bus use in a changing travel environment using panel data," Transportation, Springer, vol. 38(3), pages 487-509, May.
    5. Diab, Ehab I. & El-Geneidy, Ahmed M., 2012. "Understanding the impacts of a combination of service improvement strategies on bus running time and passenger’s perception," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 614-625.
    6. María Yáñez & Patricio Mansilla & Juan de Ortúzar, 2010. "The Santiago Panel: measuring the effects of implementing Transantiago," Transportation, Springer, vol. 37(1), pages 125-149, January.
    7. Lindsey, Marshall & Schofer, Joseph L. & Durango-Cohen, Pablo & Gray, Kimberly A., 2010. "Relationship between proximity to transit and ridership for journey-to-work trips in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 697-709, November.
    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. 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. Ikezoe, Keigo & Kiriyama, Eriko & Fujimura, Shuzo, 2020. "Car-sharing intention analysis in Japan by comparing the utility of car ownership for car-owners and non-car owners," Transport Policy, Elsevier, vol. 96(C), pages 1-14.
    3. Shen, Qing & Chen, Peng & Pan, Haixiao, 2016. "Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 31-44.
    4. Creemers, Lieve & Tormans, Hans & Bellemans, Tom & Janssens, Davy & Wets, Geert & Cools, Mario, 2015. "Knowledge of the concept Light Rail Transit: Exploring its relevance and identification of the determinants of various knowledge levels," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 31-43.
    5. Chakrabarti, Sandip, 2022. "Passively wait for gridlock, or proactively invest in service? Strategies to promote car-to-transit switches among aspirational urbanites in rapidly developing contexts," Transport Policy, Elsevier, vol. 115(C), pages 251-261.

    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. Di Ciommo, Floridea & Comendador, Julio & López-Lambas, María Eugenia & Cherchi, Elisabetta & Ortúzar, Juan de Dios, 2014. "Exploring the role of social capital influence variables on travel behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 46-55.
    2. Grigolon, Anna B. & Borgers, Aloys W.J. & Kemperman, Astrid D.A.M. & Timmermans, Harry J.P., 2014. "Vacation length choice: A dynamic mixed multinomial logit model," Tourism Management, Elsevier, vol. 41(C), pages 158-167.
    3. Shen, Qing & Chen, Peng & Pan, Haixiao, 2016. "Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 31-44.
    4. González, Rosa Marina & Marrero, Ángel Simón & Cherchi, Elisabetta, 2017. "Testing for inertia effect when a new tram is implemented," Transportation Research Part A: Policy and Practice, Elsevier, vol. 98(C), pages 150-159.
    5. Tirachini, Alejandro & Hurtubia, Ricardo & Dekker, Thijs & Daziano, Ricardo A., 2017. "Estimation of crowding discomfort in public transport: Results from Santiago de Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 311-326.
    6. Kun Gao & Minhua Shao & Kay W. Axhausen & Lijun Sun & Huizhao Tu & Yihong Wang, 2022. "Inertia effects of past behavior in commuting modal shift behavior: interactions, variations and implications for demand estimation," Transportation, Springer, vol. 49(4), pages 1063-1097, August.
    7. Cherchi, Elisabetta & Cirillo, Cinzia & Ortúzar, Juan de Dios, 2017. "Modelling correlation patterns in mode choice models estimated on multiday travel data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 146-153.
    8. Yáñez, M.F. & Raveau, S. & Ortúzar, J. de D., 2010. "Inclusion of latent variables in Mixed Logit models: Modelling and forecasting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 744-753, November.
    9. La Paix Puello, Lissy & Olde-Kalter, Marie-José & Geurs, Karst T., 2017. "Measurement of non-random attrition effects on mobility rates using trip diaries data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 51-64.
    10. María Yáñez & Elisabetta Cherchi & Benjamin Heydecker & Juan de Dios Ortúzar, 2011. "On the Treatment of Repeated Observations in Panel Data: Efficiency of Mixed Logit Parameter Estimates," Networks and Spatial Economics, Springer, vol. 11(3), pages 393-418, September.
    11. 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.
    12. 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.
    13. Wen, Chieh-Hua & Huang, Chia-Jung & Fu, Chiang, 2020. "Incorporating continuous representation of preferences for flight departure times into stated itinerary choice modeling," Transport Policy, Elsevier, vol. 98(C), pages 10-20.
    14. 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, Oxford University Press, vol. 138(2), pages 1273-1345.
    15. 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).
    16. 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.
    17. Tina Birgitte Hansen & Jes Sanddal Lindholt & Axel Diederichsen & Rikke Søgaard, 2019. "Do Non-participants at Screening have a Different Threshold for an Acceptable Benefit–Harm Ratio than Participants? Results of a Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 12(5), pages 491-501, October.
    18. 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.
    19. Tovar, Jorge, 2012. "Consumers’ Welfare and Trade Liberalization: Evidence from the Car Industry in Colombia," World Development, Elsevier, vol. 40(4), pages 808-820.
    20. 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.

    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:eee:transa:v:50:y:2013:i:c:p:1-14. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.