Data Collection and Econometric Analysis of the Demand for Non-motorized Transportation

In this project, a latent class model was derived with a class assignment mechanism based on the latent bicycle status of the respondent. Two segments were identified: more-skilled and experienced cyclists, versus less-skilled- and non-cyclists. The two segments have different sensitivities to the factors that may encourage or discourage riding a bike. For instance, slope inclination is considered almost 3 times as bad by less-skilled cyclists. Heavy traffic affects twice as much to less-skilled cyclists, who also consider rain to be 2.4 times more bothersome (and snow almost 4 times more bothersome) than more-skilled cyclists. On the other hand, bike lanes are 1.6 times more appreciated by less-skilled cyclists. Because in cycling route decisions there is no direct monetary cost involved, to analyze differences in the taste parameters the authors have proposed to use the ratio of the marginal rate of substitution with respect to travel time. In addition, the diminishing negative effect of a hilly topography (slope inclination) was measured as a function of the physical condition of the cyclist. In terms of policy recommendations, the results suggest that the provision of bike lanes may encourage an increase in the modal share of cycling, especially among those individuals using a bike infrequently, or mostly for recreational purposes. This project also examined the performance of several ridership prediction models, including the Negative Binomial regression and time-series models such as SARIMA and SARIMAX. Using cycling counts for Portland, the authors show that the SARIMAX model that includes weather conditions (temperature and precipitation) as explanatory variables performs best in out-of-sample prediction. Future research in State Space models is needed to overcome the problems of SARIMAX when predicting ridership in periods with really poor weather. In sum, both the discrete choice and time series analyses coincide in that poor weather conditions are indeed a main determinant for discouraging cycling as a transportation alternative.

  • Record URL:
  • Supplemental Notes:
    • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Cover title: Data Collection and Econometric Analysis of the Demand for Nonmotorized Transportation.
  • Corporate Authors:

    Cornell University

    School of Civil and Environmental Engineering
    Ithaca, NY  United States  14853

    University Transportation Research Center

    City College of New York
    Marshak Hall, Suite 910, 160 Convent Avenue
    New York, NY  United States  10031

    Federal Highway Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590

    Research and Innovative Technology Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Daziano, Ricardo A
    • Motoaki, Yutaka
  • Publication Date: 2014-1


  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Appendices; Figures; Photos; References; Tables;
  • Pagination: 85p

Subject/Index Terms

Filing Info

  • Accession Number: 01530945
  • Record Type: Publication
  • Contract Numbers: 49997-35-24
  • Created Date: Jul 11 2014 10:03AM