Associations between Public Transit Usage and Bikesharing Behaviors in The United States

Abstract

Public bikesharing systems have rapidly expanded across many cities in the United States (US). Previous studies in the literature found that, in general, bikesharing is associated with public transit ridership. However, the interdependencies between public transit usage and bikesharing behaviors have been mixed and have not been fully understood. Therefore, the objective of this research is to examine the associations between the frequency of public transit usage and the probability and frequency of bikesharing usage in the US using data from the 2017 National Household Travel Survey. The respondents were asked how many times they had used public transit and bikesharing in the last 30 days. Zero-inflated negative binomial regression models were conducted to assess the associations between the frequency of public transit usage and the probability and frequency of bikesharing usage. The results show that, in general, a one-unit increase in the frequency of public transit usage is significantly associated with a 4.0% increase in the probability of bikesharing usage and a 1.4% increase in the frequency of bikesharing usage. The significantly positive relationship between the frequency of public transit usage and the frequency of bikesharing usage is more pronounced among those living in areas with higher population density or with rail service. The empirical results demonstrate that public transit usage is significantly positively associated with bikesharing usage, and suggest policy implications that improving public transit usage tends to increase the usage of bikesharing. This study also provides significant empirical evidence for the formulation of interventions and policies targeting to promote integrated transportation systems that support multimodal transportation and mutually sustainable transport networks.

Shared Micro-Mobility Services for University Communities: A Multivariate Ordered Probit Approach

“…The explanation for this may be that shared bikes, compared with shared e-bikes and e-scooters, necessitate physical activity (no electric motor is available) and distance is influential in this decision. Further, people who have a bus stop within a walking distance of 400 m (a widely used rule of thumb for public transportation accessibility, e.g., Brand et al [ 57 ]) from their residence are more prone to be captive riders of shared micro-mobility services; a finding that elucidates that this group of people might also use public transportation for their trips which indicates a multi-modal lifestyle ( 58 – 61 ).…”

Generational Patterns of Modal Shares Across Megaregions

“…It is essential to understand young generations’ travel preferences and choices in the era of new mobility. However, in the data series of NHTS/NPTS, only the 2017 data provides variables capturing the usage of bike sharing, car sharing, and rideshare apps; see, as an example, the study by Zhang and Zhang ( 40 ). Data on toll payments are also reported inconsistently across NPTS/NHTS.…”

Understanding the determinants of young commuters’ metro-bikeshare usage frequency using big data

“…Since the first-generation of public bike systems was launched in the Netherlands in 1965, public bike systems have been widely developed in many cities around the world (DeMaio, 2009). Although the main idea underlying the development of public bike systems relates to energy saving, environmental protection and sustainable urban development, the function of bike-sharing in transportation systems may vary across cities due to different urban forms and social contexts (Zhang and Zhang, 2018). There are two main functions for bike-sharing in urban transportation systems in consideration of the relationship with other public transportation modes (Campbell and Brakewood, 2017).…”