Understanding the impact of the built environment on ride-hailing from a spatio-temporal perspective: A fine-scale empirical study from China

The explosive growth of ride-hailing as a new mode of transportation worldwide has attracted great attention from both academic and planning communities. Ride-hailing services have induced profound changes in residential travel patterns. However, the mechanisms and spatio-temporal roles of the influence the built environment imposes on ride-hailing services remain unclear. Based on ride-hailing GPS data and Web map big data, in this study, spatio-temporal entropy indicators of ride-hailing travel behavior and fine-scaled built environment indicators are constructed. Based on these, global and local regression models are developed to explore the spatio-temporal impact mechanisms of various built environments and socio-economic factors on ride-hailing travel in Chengdu, China. A strong correlation is found between various types of built environment and the spatio-temporal entropy of ride-hailing travel. Specifically, whether working on weekdays or weekends, building density and education facilities impose a significant inhibitory effect on ride-hailing spatio-temporal entropy, while mixed land use, house prices, catering, corporate businesses, lifestyle facilities, tourist attractions, and distance to transit significantly increase ride-hailing spatio-temporal entropy. In addition, the uncertain geographic context and the differences in residents' activities on different days of the week cause significant spatio-temporal heterogeneity in the impact the built environment has on ride-hailing spatio-temporal entropy. Noteworthy, mixed land use exerts the strongest promoting effect on ride-hailing and a positive effect on ride-hailing pick-ups and drop-offs in the whole region. The intensity of this effect tends to decay gradually from the urban center to the periphery. Furthermore, ride-hailing can both substitute for and complement public transport. More interestingly, the study also found an “olive-shaped” social structure between the socio-economic level and the demand for ride-hailing. This study thus not only enriches the theory of spatial behavior within the context of the new era, the results also help planners to reduce car travel dependence by optimizing the built environment. This holds important practical significance for sustainable urban development.