An Analysis of Bike Sharing Usage: Explaining Trip Generation and Attraction from Observed Demand

Over 100 cities around the world have deployed or have plans to deploy a bike sharing system. Bike-sharing programs enable flexibility to users by providing rentals at a variety of locations, and by facilitating one-way trips. In addition, they positively impact the environment and quality of life. The main contribution of this paper is explaining the factors effecting bike sharing trip generation and attraction. Using usage data from bike sharing systems in Barcelona and Seville, census level demographic data, and the location of points of interest, the authors explain various factors effecting bike sharing usage. They employ a panel regression model estimation strategy. By using two different fixed effects models, they are able to produce consistent estimates of trip generation and attraction factors in the presence of unobserved spatial and temporal variables. The authors find that the relationship between bike sharing and alternative modes of transportation can be complicated. In some settings bike sharing competes with alternative modes of transportation, while one can also argue that in other settings bike sharing complements. Taken together, the findings strongly support the following usage scenario: bike sharing programs in Barcelona and Seville are used mainly for commuting in the morning. In the evening a larger variety of trips purposes drive usage. These evening trips are also shorter and closer to home. The results provide empirical foundation for cities and planners in understanding the key factors contributing to bike sharing usage.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 17p
  • Monograph Title: TRB 91st Annual Meeting Compendium of Papers DVD

Subject/Index Terms

Filing Info

  • Accession Number: 01365978
  • Record Type: Publication
  • Report/Paper Numbers: 12-2099
  • Files: TRIS, TRB
  • Created Date: Feb 8 2012 5:07PM