The Influence of the Built Environment of Neighborhoods on Residents’ Low-Carbon Travel Mode

Caiyun Qian, Yang Zhou, Ze Ji and Qing Feng
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Caiyun Qian: School of Architecture, Nanjing Tech University, Nanjing 211800, China
Yang Zhou: School of Architecture, Nanjing Tech University, Nanjing 211800, China
Ze Ji: School of Architecture, Nanjing Tech University, Nanjing 211800, China
Qing Feng: School of Architecture, Nanjing Tech University, Nanjing 211800, China

Sustainability, 2018, vol. 10, issue 3, 1-26

Abstract: Motor vehicle travel is one of the causes of aggravation of CO 2 emission, environmental issues and urban problems. The advocation of low-carbon travel is necessary for the achievement of low-carbon city construction and sustainable development in the future. Many studies have shown that built environment tends to influence residents’ travel behavior, and most studies are demonstrated from the macro level of metropolis. However, from the perspective of neighborhoods, much less attention has been paid, especially in developing countries including China. This study chooses 15 neighborhoods in the main districts of Nanjing in China, taking the location of neighborhoods and residents’ socio-economic attributes into consideration, to examine the effects of residential built environment on residents’ mode choice of different travel types, and to propose the recommended values for the most significant variables. The residential built environment attributes are from three dimensions of land use, road network system and transit facilities. The method of this study is three-step and successive. Primarily, a correlation analysis model is applied to initially examine the role that residents’ socio-economic attributes and residential built environment attributes play on residents’ low-carbon travel of three different travel types respectively. Primary significant attributes from these two aspects are preliminarily screened out for the re-screening in the next step. In addition, the study uses multivariate logit regression modeling approach, with significant socio-economic attributes as concomitant variables, to further re-screen out the key variables of built environment. Furthermore, a unary linear regression model is applied to propose the recommended values for the key built environment variables.

Keywords: neighborhood; built environment; low carbon travel; correlation analysis model; multivariate logit regression model; unary linear regression model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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