Relationship between Rural Built Environment and Household Vehicle Ownership: An Empirical Analysis in Rural Sichuan, China

Abstract

With the rapid rural urbanization and new rural construction in China, tremendous changes are occurring in rural built environments and rural household vehicle ownership. However, few studies have examined the relationship between rural built environments and rural household vehicle ownership. In this study, a questionnaire survey of 374 rural households was conducted and the built environment data of seven typical villages in rural Sichuan were collected using Geographic Information System (GIS) technology and on-site measurement. This study aimed to investigate the relationship between the rural built environment and rural household vehicle ownership in China through a multinomial logit (MNL) model. Results show that household structure attributes have the most significant relationship with vehicle ownership, followed by rural built environment attributes and the respondents' driving skills. In the process of urbanization, with increases in building density, road density, and destination accessibility, an increase in high-carbon vehicle ownership is an inevitable trend among rural households. However, low-carbon-oriented rural planning can effectively control the increase in high-carbon vehicle ownership. For example, the distance between rural households and important destinations, such as hospitals, schools, and markets, should be shortened and rural residents should be encouraged to learn to ride bicycles. Moreover, rural residents riding motorcycles can effectively reduce household car ownership.

Impact of the Built Environment and Bicycling Psychological Factors on the Acceptable Bicycling Distance of Rural Residents

“…By contrast, rural residents who like riding electric bicycles would accept short bicycling distances. This research conclusion completely illustrates the complementarity of bicycles and motorcycles for travel and the mutual replacement of bicycles and electric bicycles [63]. Table 7 shows that two of the four objective built environment indicators significantly influence the acceptable bicycling distance of rural residents.…”

“…The influence of the individual bicycling psychological factors of rural residents on their acceptable bicycling distance is significant, followed by the built environment indicators, whereas the impact of social demographic characteristics is limited. However, the socio-demographic characteristics in the relevant research literature significantly affect travel behavior [2,12,63]. This finding may be related to the characteristics of the left-behind population in rural Sichuan.…”

“…This study selected seven villages: three new concentrated villages and four traditional scattered villages. Additional details of the sample and data collection for this study are included in the current authors' previous research [62,63]. Eventually, we prepared 374 valid rural household questionnaires for this study.…”

“…Table 2 shows the basic data of the actual built environment that were measured on-site. Apart from conducting a household survey, we also measured the actual built environment basic data on-site, further details of which are included in the current authors' previous research [62,63]. Table 2 shows the basic data of the actual built environment that were measured on-site.…”

Development of Multivariate Ordered Probit Model to Understand Household Vehicle Ownership Behavior in Xiaoshan District of Hangzhou, China

“…Firstly, most studies in China mainly analyze the vehicle ownership of a single type [36][37][38], rather than discussing the correlation and transition of vehicle ownership between different types. Secondly, the ownership of electric bicycle is seldom considered in model framework [39,40]. It might be unreasonable in China, since electric bicycles have grown in popularity over the past decade and are now a substantial portion of the transportation system in most urban areas [41].…”