Spatiotemporally heterogeneous willingness to ridesplitting and its relationship with the built environment: A case study in Chengdu, China

The capability of ridesplitting service to address current urban transportation problems has attracted considerable research interest in recent years. Given that ridesplitting needs an adequate user base to realize "sharing", its success highly depends on a comprehensive understanding of people's willingness of using it. However, previous studies mainly focused on the ridesplitting willingness based on questionnaire surveys at the individual level, which may help transportation network companies find potential users, but lacked studies on people's ridesplitting willingness from the perspective of the built environment and time-space integration, because the macro urban elements are difficult to be perceived by individuals and thus hard to reflect in questionnaires. Thus, this study estimates the ridesplitting willingness rate of different areas in a city at different times of the day by building a model on the shared order rate and shareability from the real-world DiDi Chuxing dataset, using Chengdu, China, as a case study. The spatial lag model (SLM) is further utilized to exam the relationship between the willingness rate, built environment and transportation-related variables. Results revealed the ridesplitting willingness rate has a significant spatiotemporal pattern between the urban centre and urban periphery and can be divided into morning peak, noon plateau, afternoon valley, night peak, and midnight valley. SLM models indicate that the ridesplitting willingness rate has a significant spatial dependency on its vicinity areas at the origin of the daytime periods or at the destination at night. The distance to urban centre, the distance to railway station, travel demand, accessibility to public transit, land use mixture, and the trip purpose are found to be the most relevant variables with the willingness rate, while the points of interest (POIs) are almost irrelevant. The findings of this study can be helpful to the future promotion of this sustainable service and formulation of policy to improve service quality.