Heterogeneity in the relationship between biking and the built environment

Abstract

Bicycling is an environmentally friendly, healthy, and affordable mode of transportation that is viable for short-distance trips. Urban planners, public health advocates, and others are therefore looking for strategies to promote more bicycling, including improvements to the built environment that make bicycling more attractive. This study presents an analysis of how key built environment characteristics relate to bicycling frequency based on a large sample from the 2012 California Household Travel Survey (California Department of Transportation, 2012) and detailed built environment data. The built environment characteristics we explore include residential and intersection density at anchor locations (home, work, school), green space, job access, land-use mix, and bicycle infrastructure availability. Analyses are conducted separately for three distinct demographic groups: school-age children, employed adults, and adults who are not employed. The key conclusion from this work is that the relationship between bicycling and some built environment characteristics varies between types of people — most dramatically between adults and children. To develop targeted policies with scarce resources, local policymakers need specific guidance as to which investments and policy changes will be most effective for creating “bikeable” neighborhoods. Our work indicates that the answer depends — at least in part — on who these bikeable neighborhoods are meant to serve.

Exploring non-linear built environment effects on the integration of free-floating bike-share and urban rail transport: A quantile regression approach

“…They argued that overcrowded areas may cause traffic congestion and road safety concerns, which is not suitable for bicycling activity. This argument has been supported by the literature discussing the relationship between the built environment and bicycling (e.g., Salon et al, 2019). Thus, formulating policies on residential densification might not be an effective method for encouraging bike-and-ride in all contexts.…”

Using city-bike stopovers to reveal spatial patterns of urban attractiveness

“…Number of recent studies have used city-bike data e.g. to identify potential locations for new stations, estimate bicycle flows and usage, understand social and demographic context or predict usage in real-time (Caulfield, O'Mahony, Brazil, & Weldon, 2017;Eren & Uz, 2020;Frade & Ribeiro, 2014;Imani, Eluru, El-Geneidy, Rabbat, & Haq, 2014;Salon, Conway, Wang, & Roth, 2019;Tran, Ovtracht, & D'Arcier, 2015;K. Wang & Akar, 2019).…”

More than Bike Lanes—A Multifactorial Index of Urban Bikeability

“…At the same time, other studies still include considerable individual effort by raters in the field who collect associated data within an area instead of using secondary data [26][27][28]. Even though some studies follow a detailed data driven approach in local or regional case studies with specific operationalizations [29,30], across most prior studies, the included data are thematically similar overall but may be defined and operationalized differently.…”

“…Other studies base weighting on single experiments [17,21] or normatively determine an overall framework [24]. As different types of infrastructure may have varying implications in different groups of cyclists [30,36], it is crucial to develop a consensual and integrative understanding of bikeability [9] and show its influence using statistical models.…”