Spatio-temporal dynamic characteristics of the substitution effect of ride-hailing travel and its multi-activity network: a case study of Chengdu

Abstract

The substitution relationship between ride-hailing and public transit significantly impacts urban transport carbon emissions. However, a quantitative analysis exploring the spatio-temporal dimensions of the substitution effect between these two modes of transport is still lacking. Furthermore, the motivations for travel and the associated activity networks remain unclear. This study proposes a spatio-temporal measure of the substitution effect of ride-hailing travels by introducing demand elasticity theory and big data technology to address these limitations. It explores the multi-activity network of the substitution effect and its community clustering features using an improved trip purpose identification method and complex network techniques. An empirical study in Chengdu, China, revealed a significant substitution influence of ride-hailing for public transport in central urban areas. Specifically, 28.69 % and 27.08 % of ride-hailing trips substituted public transport on weekdays and weekends, respectively. Regarding temporal variation, the substitution rate fluctuates dynamically with travel time and motivation changes and increases significantly during peak hours. Non-subsistence travel activities are the dominant type of substitute trips, while subsistence activities occur primarily during weekday peak hours. The complex network models reveal that the activity network of substitution effects exhibits significant spatial heterogeneity, hierarchy, and dependency characteristics. This research also confirms that differences in residents' travel patterns cause the coexistence of a monocentric and polycentric structure in the city. Furthermore, the community structure of substitute trips reveals that communities can shrink, disappear, or emerge depending on various temporal scenarios. These findings provide a basis for determining residential activity boundaries and travel circles. The study deepens the understanding of the dynamic interaction of the “substitution effect-multiple activity network-urban spatial structure” of travel modes. It provides valuable empirical evidence to enhance the competitiveness of public transport and more effectively regulate ride-hailing services. This holds significant practical value for sustainable urban development.