National Center for Smart Growth Research Works

Now showing 1 - 4 of 4

The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis
(2014) Liu, Chao; Ding, Chuan; Lin, Yaoyu; Wang, Yaowu
The empirical data were selected from Washington-Baltimore Regional Household Travel Survey in 2007-2008, including all the trips from home to workplace during the morning hours. The model parameters were estimated using the simultaneous estimation approach and the integrated model turns out to be superior to the traditional multinomial logit (MNL) model accounting for the impact of employer attitudes towards green commuting. The direct and indirect effects of socio-demographic attributes and employer attitudes towards green commuting were estimated. Through the structural equation modelling with mediating variable, this approach confirmed the intermediary nature of car ownership in the choice process.
Understanding the Role of Built Environment in Reducing Vehicle Miles Traveled Accounting for Spatial Heterogeneity
(2014) Liu, Chao; Ding, Chuan; Wang, Yaowu; Xie, Binglei
In recent years, increasing concerns over climate change and transportation energy consumption have sparked research into the influences of urban form and land use patterns on motorized travel, notably vehicle miles traveled (VMT). However, empirical studies provide mixed evidence of the influence of the built environment on travel. In particular, the role of density after controlling for the confounding factors (e.g., land use mix, average block size, and distance from CBD) still remains unclear. The object of this study is twofold. First, this research provides additional insights into the effects of built environment factors on the work-related VMT, considering urban form measurements at both the home location and workplace simultaneously. Second, a cross-classified multilevel model using Bayesian approach is applied to account for the spatial heterogeneity across spatial units. Using Washington DC as our study area, the home-based work tour in the AM peak hours is used as the analysis unit. Estimation results confirmed the important role that the built environment at both home and workplace plays in affecting work-related VMT. In particular, the results reveal that densities at the workplace have more important roles than that at home location. These findings confirm that urban planning and city design should be part of the solution in stabilizing global climate and energy consumption.
Reclassification of Sustainable Neighborhoods: An Opportunity Indicator Analysis in Baltimore Metropolitan Area
(2013) Knaap, Elijah; Knaap, Gerrit; Liu, Chao
The “Sustainable neighborhoods” has become widely proposed objective of urban planners, scholars, and local government agencies. However, after decades of discussion, there is still no consensus on the definition of sustainable neighborhoods (Sawicki and Flynn, 1996; Dluhy and Swartz 2006; Song and Knaap,2007; Galster 2010). To gain new information on this issue, this paper develops a quantitative method for classifying neighborhood types. It starts by measuring a set of more than 100 neighborhood sustainable indicators. The initial set of indicators includes education, housing, neighborhood quality and social capital, neighborhood environment and health, employment and transportation. Data are gathered from various sources, including the National Center for Smart Growth (NCSG) data inventory, U.S. Census, Bureau of Economic Analysis (BEA), Environmental Protection Agency (EPA), many government agencies and private vendors. GIS mapping is used to visualize and identify variations in neighborhood attributes at the most detailed level (e.g census tracts). Factor analysis is then used to reduce the number of indicators to a small set of dimensions that capture essential differences in neighborhood types in terms of social, economic, and environmental dimensions. These factors loadings are used as inputs to a cluster analysis to identify unique neighborhood types. Finally, different types of neighborhoods are visualized using a GIS tool for further evaluation. The proposed quantitative analysis will help illustrate variations in neighborhood types and their spatial patterns in the Baltimore metropolitan region. This framework offers new insights on what is a sustainable neighborhood.
Mapping Opportunity: A Critical Assessment
(2014) Knaap, Elijah; Knaap, Gerrit; Liu, Chao
A renewed interest has emerged on spatial opportunity structures and their role in shaping housing policy, community development, and equity planning. To this end, many have tried to quantify the geography of opportunity and quite literally plot it in a map. In this paper we explore the conceptual foundations and analytical methods that underlie the current practice of opportunity mapping. We find that opportunity maps can inform housing policy and metropolitan planning but that greater consideration should be given to the variables included, the methods in which variables are geographically articulated and combined, and the extent to which the public is engaged in opportunity mapping exercises.

National Center for Smart Growth Research Works

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