IDEAS home Printed from https://ideas.repec.org/a/bla/ecinqu/v56y2018i3p1777-1787.html
   My bibliography  Save this article

Urban Transportation Mode Choice And Trip Complexity: Bicyclists Stick To Their Gears

Author

Listed:
  • Joseph F. Wyer

Abstract

Commuters' lives have become more complicated with rising income. In my model, transportation mode choices are made simultaneously with the choice of whether to make multiple stops. Using travel behavior data, I estimate the model using an error components logit (ECL) specification to account for commuters' unobserved preferences for particular modes and find that omitting unobserved preferences underestimates value of travel time relative to the crossing‐components ECL. The estimated model predicts that increased trip complexity causes substitution away from public transit to automobiles, with the exception that bicyclists transition only to more complex trips and do not change transportation modes. (JEL R41, C25)

Suggested Citation

  • Joseph F. Wyer, 2018. "Urban Transportation Mode Choice And Trip Complexity: Bicyclists Stick To Their Gears," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1777-1787, July.
  • Handle: RePEc:bla:ecinqu:v:56:y:2018:i:3:p:1777-1787
    DOI: 10.1111/ecin.12524
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/ecin.12524
    Download Restriction: no

    File URL: https://libkey.io/10.1111/ecin.12524?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
    ---><---

    References listed on IDEAS

    as
    1. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    2. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    3. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    4. David Hensher & April Reyes, 2000. "Trip chaining as a barrier to the propensity to use public transport," Transportation, Springer, vol. 27(4), pages 341-361, December.
    5. Bhat, Chandra R. & Sardesai, Rupali, 2006. "The impact of stop-making and travel time reliability on commute mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(9), pages 709-730, November.
    6. Joan L. Walker & Moshe Ben-Akiva & Denis Bolduc, 2007. "Identification of parameters in normal error component logit-mixture (NECLM) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1095-1125.
    7. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-719, November.
    8. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    9. Bowman, J. L. & Ben-Akiva, M. E., 2001. "Activity-based disaggregate travel demand model system with activity schedules," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 1-28, January.
    10. Bhat, Chandra R. & Singh, Sujit K., 2000. "A comprehensive daily activity-travel generation model system for workers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(1), pages 1-22, January.
    11. Ye, Xin & Pendyala, Ram M. & Gottardi, Giovanni, 2007. "An exploration of the relationship between mode choice and complexity of trip chaining patterns," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 96-113, January.
    12. Bhat, Chandra R., 1997. "Work travel mode choice and number of non-work commute stops," Transportation Research Part B: Methodological, Elsevier, vol. 31(1), pages 41-54, February.
    13. Small, Kenneth A., 2012. "Valuation of travel time," Economics of Transportation, Elsevier, vol. 1(1), pages 2-14.
    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. Sottile, Eleonora & Tuveri, Giovanni & Piras, Francesco & Meloni, Italo, 2022. "Modelling commuting tours versus non-commuting tours for university students. A panel data analysis from different contexts," Transport Policy, Elsevier, vol. 118(C), pages 56-67.
    2. Wang, Rui, 2015. "The stops made by commuters: evidence from the 2009 US National Household Travel Survey," Journal of Transport Geography, Elsevier, vol. 47(C), pages 109-118.
    3. Stephane Hess, 2014. "Latent class structures: taste heterogeneity and beyond," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 14, pages 311-330, Edward Elgar Publishing.
    4. Solomon Tarfasa & Roy Brouwer, 2013. "Estimation of the public benefits of urban water supply improvements in Ethiopia: a choice experiment," Applied Economics, Taylor & Francis Journals, vol. 45(9), pages 1099-1108, March.
    5. Siikamaki, Juha & Layton, David F., 2007. "Discrete choice survey experiments: A comparison using flexible methods," Journal of Environmental Economics and Management, Elsevier, vol. 53(1), pages 122-139, January.
    6. Zidan Mao & Dick Ettema & Martin Dijst, 2018. "Analysis of travel time and mode choice shift for non-work stops in commuting: case study of Beijing, China," Transportation, Springer, vol. 45(3), pages 751-766, May.
    7. Krueger, Rico & Bierlaire, Michel & Daziano, Ricardo A. & Rashidi, Taha H. & Bansal, Prateek, 2021. "Evaluating the predictive abilities of mixed logit models with unobserved inter- and intra-individual heterogeneity," Journal of choice modelling, Elsevier, vol. 41(C).
    8. 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.
    9. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.
    10. Tinessa, Fiore & Marzano, Vittorio & Papola, Andrea, 2020. "Mixing distributions of tastes with a Combination of Nested Logit (CoNL) kernel: Formulation and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 1-23.
    11. Fredrik Carlsson, 2003. "The demand for intercity public transport: the case of business passengers," Applied Economics, Taylor & Francis Journals, vol. 35(1), pages 41-50.
    12. Hess, Stephane & Train, Kenneth E., 2011. "Recovery of inter- and intra-personal heterogeneity using mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 973-990, August.
    13. 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).
    14. Wang, Xuehong & Bennett, Jeff & Xie, Chen & Zhang, Zhitao & Liang, Dan, 2007. "Estimating non-market environmental benefits of the Conversion of Cropland to Forest and Grassland Program: A choice modeling approach," Ecological Economics, Elsevier, vol. 63(1), pages 114-125, June.
    15. Laura Mørch Andersen, 2013. "Obtaining reliable Likelihood Ratio tests from simulated likelihood functions," IFRO Working Paper 2013/1, University of Copenhagen, Department of Food and Resource Economics.
    16. Huang, Yuqiao & Gao, Linjie & Ni, Anning & Liu, Xiaoning, 2021. "Analysis of travel mode choice and trip chain pattern relationships based on multi-day GPS data: A case study in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 93(C).
    17. Mohammed H. Alemu & Søren B. Olsen, 2017. "Can a Repeated Opt-Out Reminder remove hypothetical bias in discrete choice experiments? An application to consumer valuation of novel food products," IFRO Working Paper 2017/05, University of Copenhagen, Department of Food and Resource Economics.
    18. Richard G. Newell & Juha Siikamäki, 2014. "Nudging Energy Efficiency Behavior: The Role of Information Labels," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 1(4), pages 555-598.
    19. Xin Guan & Xin Ye & Cheng Shi & Yajie Zou, 2019. "A Multivariate Modeling Analysis of Commuters’ Non-Work Activity Allocations in Xiaoshan District of Hangzhou, China," Sustainability, MDPI, vol. 11(20), pages 1-19, October.
    20. Heiss, Florian & Winschel, Viktor, 2008. "Likelihood approximation by numerical integration on sparse grids," Journal of Econometrics, Elsevier, vol. 144(1), pages 62-80, May.

    More about this item

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

    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:bla:ecinqu:v:56:y:2018:i:3:p:1777-1787. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/weaaaea.html .

    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.