National Center for Smart Growth

Permanent URI for this communityhttp://hdl.handle.net/1903/21472

The National Center for Smart Growth (NCSG) works to advance the notion that research, collaboration, engagement and thoughtful policy development hold the key to a smarter and more sustainable approach to urban and regional development. NCSG is based at the University of Maryland, College Park, housed under the School of Architecture, Planning, and Preservation, with support from the College of Agriculture & Natural Resources, the A. James Clark School of Engineering, the School of Public Policy, and the Office of the Provost.

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    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.
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    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.