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Research continues to reveal the benefits of nonmotorized travel modes such as walking and bicycling. Therefore, identification of the factors that nurture these activities is essential in developing sustainable urban planning policies and designs. Among those factors are the built environment characteristics of the place of residence. To date, research on the role of the built environment in nonmotorized travel has focused on neighborhood-level factors. However, people do not stay within their neighborhoods; they live and work at a regional scale and travel to various destinations and distances each day. Nonetheless, little is known about the impact of built environment factors at larger spatial scales on nonmotorized travel behavior. Guided by the principles of the ecological model of behavior, this study investigates the role of the built environment at hierarchical spatial scales in nonmotorized travel behavior. Multilevel Structural Equation Models have been developed to comprehensively examine the complex links between the built environment and individuals’ nonmotorized travel. Findings indicate that built environment factors at multiple spatial scales can influence nonmotorized travel behavior. Thus, to promote walking and bicycling, more effective policies are those that include multilevel built environment and land use interventions and consider the overall physical form of urban areas.
Jina Mahmoudi; Lei Zhang. Impact of the Built Environment Measured at Multiple Levels on Nonmotorized Travel Behavior: An Ecological Approach to a Florida Case Study. Sustainability 2020, 12, 8837 .
AMA StyleJina Mahmoudi, Lei Zhang. Impact of the Built Environment Measured at Multiple Levels on Nonmotorized Travel Behavior: An Ecological Approach to a Florida Case Study. Sustainability. 2020; 12 (21):8837.
Chicago/Turabian StyleJina Mahmoudi; Lei Zhang. 2020. "Impact of the Built Environment Measured at Multiple Levels on Nonmotorized Travel Behavior: An Ecological Approach to a Florida Case Study." Sustainability 12, no. 21: 8837.
Taxis remain a key asset for urban mobility despite the tremendous growth of modern mobility-on-demand service providers such as Uber and Lyft. A fundamental understanding of the factors that impact the taxi demand is essential for planning an effective multi-modal transportation system, and can also shed lights on new on-demand services. This study addressed a gap in literature by investigating the correlation between demand for taxi, land use patterns, and accessibility to other modes using detailed GPS and GIS information collected from the Washington D.C. metropolitan area. The results of the models showed a strong link between demand for taxi, land use patterns, and accessibility to other modes. Mixed land use did not show a strong correlation with taxi demand. The study also found that the taxi mode is likely to complement metro trips, but compete with bus trips, although both of these modes of travel are considered public transit. Airport trips were found to be the most important source for taxi travel. These findings were further supported by the time-of-day and seasonality analysis.
Zhuo Yang; Mark L. Franz; Shanjiang Zhu; Jina Mahmoudi; Arefeh Nasri; Lei Zhang. Analysis of Washington, DC taxi demand using GPS and land-use data. Journal of Transport Geography 2018, 66, 35 -44.
AMA StyleZhuo Yang, Mark L. Franz, Shanjiang Zhu, Jina Mahmoudi, Arefeh Nasri, Lei Zhang. Analysis of Washington, DC taxi demand using GPS and land-use data. Journal of Transport Geography. 2018; 66 ():35-44.
Chicago/Turabian StyleZhuo Yang; Mark L. Franz; Shanjiang Zhu; Jina Mahmoudi; Arefeh Nasri; Lei Zhang. 2018. "Analysis of Washington, DC taxi demand using GPS and land-use data." Journal of Transport Geography 66, no. : 35-44.