01697845

Component

Policy-makers and operators of bike share programs need information about factors that affect member use to manage systems effectively and to address questions of equity of access that have been raised in many urban areas. Using 2017 data on trips taken by 30-day and annual members of the Nice Ride Bike Share system in Minneapolis-St. Paul, the authors estimate multi-level, mixed-effect regression and multinomial logistic models to analyze the effects of neighborhood disadvantage on, respectively, (1) the frequency and duration of weekday and weekend trips by members and (2) the temporal and spatial patterns of their trips. The authors use principal components analysis to establish a standardized, composite index of neighborhood disadvantage (SNDCI). The authors use k-means clustering procedures to establish two temporal and four spatial patterns of member trips. The results show that, after controlling for station accessibility, nearby bike infrastructure, the built environment, gender, and age, members who reside in disadvantaged neighborhoods use bike share more frequently, take longer trips, and have more dispersed spatial patterns associated with more origin-destination pairs. The findings have implications for efforts to serve members in disadvantaged neighborhoods and illustrate the need for more detailed surveys of members to obtain additional information about individual characteristics associated with travel behavior.

This paper was sponsored by TRB committee ANF20 Standing Committee on Bicycle Transportation.

19-02938

English

3p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

References

Bicycling; Location; Neighborhoods; Socioeconomic factors; Vehicle sharing

Twin Cities Metropolitan Area (Minnesota)

Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors

Transportation Research Board Annual Meeting 2019 Paper #19-02938

TRIS, TRB, ATRI

Dec 7 2018 9:39AM