Jessica Schoner

Walking for Purpose and Pleasure: Influences of Light Rail, Built Environment, and Residential Self-Selection on Pedestrian Travel

Planners are increasingly promoting active travel as a strategy to reduce auto dependence and encourage physical activity. That rail transit promotes walking to the extent that passengers typically access stations by walking is evident. However, few studies focus on the carryover effect of light rail and associated built environment features on additional pedestrian travel. This study explored the effects of light rail and the built environment on the frequency of utilitarian walking (shopping trips) and recreational walking (strolling) from 1,303 randomly surveyed residents in five corridors in Minneapolis, Minnesota. Results from two negative binomial regression models showed that after controlling for demographics, travel attitudes, and residential preferences, walking to the store was significantly associated with population density, proximity to commercial land use, and street network interruptions (cul-de-sacs and dead-end streets). Strolling was also associated with street network interruptions. The findings carry important implications for planners to capitalize on built environment improvements around new light rail projects to increase rates of walking.

Is Bikesharing Contagious?Modeling its effects on System Membership and General Population Cycling

Bikeshare systems are relatively new, highly visible additions to urban transportation systems that provide opportunities to cycle or combine cycling with other modes of transportation. The research reported here presents new evidence about the role of bikeshare systems in travel behavior on the basis of diffusion of innovation theory. The study hypothesized that bikeshare systems have spatial contagion or spillover effects on (a) the propensity of individuals to adopt bikeshare and (b) the propensity to bicycle within the general population. The first hypothesis (H1) was tested by modeling membership growth as a function of system expansion and the existing, proximate membership base. The second hypothesis (H2) was tested by using bikeshare activity levels near home in a model of household-level bicycle participation and trip frequency. The study yielded mixed results. Bikeshare membership growth appeared to be driven in small part by a contagion effect of existing bikeshare members nearby, even after controlling for system growth. However, within the general population, a significant relationship was not identified between proximity to bikeshare stations and cycling participation or frequency. These findings complement those of other recent studies of bikeshare systems, which indicated that systems are still evolving. The present findings also have implications for marketing, infrastructure investments, and future research about bikeshare operations and innovation.

Differences Between Walking and Bicycling over Time: Implications for Performance Management

This study analyzed travel behavior inventories conducted by the Metropolitan Council in the Minneapolis–Saint Paul, Minnesota, metropolitan area in 2001 and 2010 to illuminate differences between walking and bicycling over time and to illustrate the implications for performance measurement. The study focused on pedestrians and bicyclists: where they went and why, when they traveled, and what factors were associated with their trips. As measured by summer mode share, walking and bicycling increased, but differences between the modes overshadowed their similarities. The results of analysis with descriptive statistics, hypothesis testing, and multinomial logistic models showed that walkers were different from bicyclists, that walking trips were shorter and were made for different purposes, that walking and bicycling trips differed seasonally, and that different factors were associated with the likelihood of a walking or a bicycle trip. The study also showed that the journey to work question in the Census Bureaus American Community Survey tended to underestimate commuting by bicycle by a factor of 1.75 to 3.3, while it slightly overestimated commuting by walking. The increase in mode share was greater for walking than for bicycling. Walking and bicycling remained mainly urban transportation options. Older age reduced the likelihood of biking trips more than it did of walking trips, and biking remained associated with gender but walking did not. These differences called into question the common practice of treating nonmotorized transportation as a single mode. Managers can use these results to develop performance measures to track progress toward system goals in a way that address the unique and different needs of pedestrians and bicyclists.