Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach

Suburban sprawl has been widely criticized for its contribution to auto dependence. Numerous studies have found that residents in suburban neighborhoods drive more and walk less than their counterparts in traditional environments. However, most studies confirm only an association between the built environment and travel behavior, and have yet to establish the predominant underlying causal link: whether neighborhood design independently influences travel behavior or whether preferences for travel options affect residential choice. That is, residential self-selection may be at work. A few studies have recently addressed the influence of self-selection. However, our understanding of the causality issue is still immature. To address this issue, this study took into account individuals’ self-selection by employing a quasi-longitudinal design and by controlling for residential preferences and travel attitudes. In particular, using data collected from 547 movers currently living in four traditional neighborhoods and four suburban neighborhoods in Northern California, we developed a structural equations model to investigate the relationships among changes in the built environment, changes in auto ownership, and changes in travel behavior. The results provide some encouragement that land-use policies designed to put residents closer to destinations and provide them with alternative transportation options will actually lead to less driving and more walking.

Walking frequency, cars, dogs, and the built environment

To explain walking propensity or frequency, empirical studies have generally used two sets of explanatory variables, namely, socio-demographic variables and built environment variables. They have generally shown that both socio-demographic characteristics and built environment characteristics are associated with walking propensity. We examine the traditional walkability variables that encompass density, mix of uses, and network connectivity in New Jersey, using a statewide sample including an oversample of Jersey City. We estimate a two-stage least squares model using a conditional mixed process that combines an ordered probit model of walking frequency in the second stage based on a truncated regression of car ownership in the first stage. Our results show that built environment variables have some small effects, mainly from better network connectivity associated with increased walking frequency. One of our key findings is that built environment features also work indirectly via how they influence car ownership. In general, we find sufficient evidence that suggests fewer cars are owned in areas with more walkable built environment features. The other key variable that we control for is whether a household owns a dog. This also proved to be strongly associated with walking suggesting that dog ownership is a necessary control variable to understand the frequency of walking.     

Severity of injury resulting from pedestrian–vehicle crashes: What can we learn from examining the built environment?

This paper examines the impact of personal and environmental characteristics on severity of injuries sustained in pedestrian–vehicle crashes using a generalized ordered probit model. The data covers 2000–2004 of pedestrian–vehicle crashes taken from police incident reports for Baltimore City and supplemented with local land use, urban form and transportation information specific to the individual crash locations. The results on personal and behavioral variables confirm previous findings. Women pedestrians involved in crashes tend to be injured less frequently than their male counterparts; children have an increased likelihood of sustaining injuries and older persons are more likely to be fatally injured. Pedestrians who cross against the traffic signal, are not in a crosswalk and are involved in a crash after dark are associated with greater injury risk. Of the built environment policy variables of interest, transit access and greater pedestrian connectivity, such as central city areas, are significant and negatively associated with injury severity. These results suggest that the environmental conditions should be given more scrutiny and be an important consideration when evaluating and planning for pedestrian safety.     

The relationship between segment-level built environment attributes and pedestrian activity around Bogota’s BRT stations

Few studies have examined the relationship between micro-scale features of the built environment and street segment usage. Micro-scale features of the built environment include the width of the sidewalk, the presence of amenities such as benches and trash bins, and the presence of crossing aids such as stoplights and crosswalks. This study employs segment-level primary data collected for 338 street segments in close proximity to one of 71 bus rapid transit stations in Bogotá, Colombia. We also use secondary data to control for area-level characteristics such as density, socio-economic stratum, unemployment, and crime. Factor and regression analyses are to use identify two dimensions of the built environment that are associated with higher levels of pedestrian activity: pedestrian-friendly amenities, comprised of wider and higher quality sidewalks and the presence of amenities such as benches, garbage cans, and bike paths; and connectivity, comprised of higher levels of road density, three- and four-way intersections, and density. In addition, we find greater pedestrian activity on segments with higher development intensity, with more mix of land uses, and with more crossing aids. Although the relationships identified are not causal, they are suggestive in terms of planning successful built environment interventions.     

Short-term planning and policy interventions to promote cycling in urban centers: Findings from a commute mode choice analysis in Barcelona,Spain

BackgroundCycling for transportation has become an increasingly important component of strategies to address public health, climate change, and air quality concerns in urban centers. Within this context, planners and policy makers would benefit from an improved understanding of available interventions and their relative effectiveness for cycling promotion. We examined predictors of bicycle commuting that are relevant to planning and policy intervention, particularly those amenable to short- and medium-term action.MethodsWe estimated a travel mode choice model using data from a survey of 765 commuters who live and work within the municipality of Barcelona. We considered how the decision to commute by bicycle was associated with cycling infrastructure, bike share availability, travel demand incentives, and other environmental attributes (e.g., public transport availability). Self-reported and objective (GIS-based) measures were compared. Point elasticities and marginal effects were calculated to assess the relative explanatory power of the independent variables considered.ResultsWhile both self-reported and objective measures of access to cycling infrastructure were associated with bicycle commuting, self-reported measures had stronger associations. Bicycle commuting had positive associations with access to bike share stations but inverse associations with access to public transport stops. Point elasticities suggested that bicycle commuting has a mild negative correlation with public transport availability (−0.136), bike share availability is more important at the work location (0.077) than at home (0.034), and bicycle lane presence has a relatively small association with bicycle commuting (0.039). Marginal effects suggested that provision of an employer-based incentive not to commute by private vehicle would be associated with an 11.3% decrease in the probability of commuting by bicycle, likely reflecting the typical emphasis of such incentives on public transport.ConclusionsThe results provide evidence of modal competition between cycling and public transport, through the presence of public transport stops and the provision of public transport-oriented travel demand incentives. Education and awareness campaigns that influence perceptions of cycling infrastructure availability, travel demand incentives that encourage cycling, and policies that integrate public transport and cycling may be promising and cost-effective strategies to promote cycling in the short to medium term.     

Influence of the residential and work environment on car use in dual-earner households

This paper analyses whether the decision to commute by car is influenced by built environment characteristics of residential neighbourhoods and, more especially, of work locations, taking into account interdependencies between household partners. It shows that the residential environment only affects car use among single-earners. Conversely, for all commuters, but in particular for dual-earners, characteristics of the work location affect whether they commute by car. Even in dual-earner households with two cars, work environment plays a role. We found that in cases of dual-earners with only one car, the partners with the longest commuting distances and the lowest density work locations are most likely to commute by car. Moreover, in households with young children, men are more inclined to leave the car at home. Other features relating to work also affect car commuting, including work flexibility and, especially, possession of a company car. We conclude that future policies aimed at reducing car use should place greater focus on work factors.     

Exploring built environment impacts on transit use – an updated meta-analysis

ABSTRACT

The built environment (BE) is widely accepted to influence transit use (TU). Evidence to date suggests the relationship is dependent on many factors which can be difficult to account for in quantitative studies. This creates barriers to transferring research into practice. Considering many studies together can be useful for accounting for more of the factors impacting transit use. Yet, meta-analysis of research measuring these influences was last undertaken in 2010 based on 18 studies. Since then 90 new quantitative studies have been published. These recent studies use improved methodologies and are conducted in more diverse geographies. This paper reports an improved and updated meta-analysis of built environment impacts on transit use. It compares elasticity estimates from research published pre-and post-2010 and explores the impact of new methods and a more diverse geographical representation on findings. Updated meta-elasticities range from <0.01 to 0.26; a similar range to the 2010 study. However, at the individual indicator levels, more recent results are different. Elasticities for urban density, including population, employment and commercial density, have increased significantly in studies published since 2010, as did that of land use mix. However, measures of local access, design and jobs-housing balance decreased in post-2010 studies. These results confirm the small but imprecise relationship between the BE and TU. Results also suggest that while the range of elasticity impacts is relatively consistent, new study methodologies, notably those that control for regional accessibility and self-selection, and the increasing geographical diversity in study applications, is acting to change BE-TU findings at the indicator level. Research setting and context are important to consider when using empirical results to design BE strategies to promote transit use.