# Spatiotemporal Heterogeneous Effects of Built Environment and Taxi Demand on Ride-Hailing Ridership
## 5 Concluding Remarks  
Although the links between the built environment and travel behavior have been widely researched, scant evidence has been provided on the heterogeneity in the links [31]. Only a few studies have attempted to identify the heterogeneous effect of the built environment on ride-hailing ridership [2; 24]. However, existing studies tend to overlook the varying scales at which different built environment variables affect ride-hailing ridership. The MGWR model is employed to address the gap by exploring the spatiotemporal effects of the built environment on ride-hailing ridership based on ride-hailing order data of all TNCs in Nanjing. Additionally, the competitive and cooperative relationship between taxis and ride-hailing is also considered. The findings help researchers and policy practitioners better understand spatiotemporal patterns of ride-hailing ridership and its relationship with built environment characteristics and further promote contextualized policies for ride-hailing allocation and urban planning. This study adds to the literature by revealing spatiotemporal heterogeneity in the determinants of ride-hailing ridership. The results of this study suggest that the MGWR model outperforms both the OLS and GWR models, highlighting the importance of utilizing different optimal bandwidths for each exogenous variable. In the MGWR model, the smallest bandwidths are observed for taxis during the morning peak, evening peak, and off-peak periods, confirming the spatial heterogeneity in the relationship between ride-hailing ridership and taxi ridership. As a result, we consider taxi ridership as a local variable in our analysis. The results suggest that metro station density, distance to CBD, road density, and bike lane density are considered local variables, whereas bus stop density, distance to the nearest bus stop, and distance to the nearest metro station are regarded as global variables. The bandwidths for population density and land use mix vary across three periods, and the spatial heterogeneity in these two variables is only observed during some specific periods. The findings of this study reveal important insights into the relationships between various factors and ride-hailing ridership. Urban planners and policy makers can benefit from understanding the spatial and temporal heterogeneity of the impact of the built environment on ride-hailing ridership, and propose targeted improvement or optimization strategies according to local conditions. It provides a theoretical basis for optimizing the urban layout and promoting the coordinated development of ride-hailing, taxis, and public transit. Specifically, we observe a positive association between taxi ridership and  
Figure 7: Spatiotemporal variations in the coefficients of distance to CBD. ride-hailing ridership across all three periods, indicating a cooperative relationship between these two modes of transportation. Furthermore, this cooperative relationship is particularly pronounced in areas with limited access to adequate public transit services. Considering the low density of suburban travel, the cost of traditional cruise taxis is higher. Therefore, more ride-hailing can be configured in the suburbs to meet the travel needs of suburban residents. In addition, a higher road density is positively associated with more ride-hailing ridership, whereas bike lane density significantly decreases ride-hailing ridership in general. Only in some areas where the current density of bike lanes is insufficient to meet travel demand does bike lane density show a positive effect on ride-hailing demand. The parameters of metro station density vary across the study area. Distance to CBD generally shows a negative effect on ride-hailing ridership in central urban areas, whereas the effect is negative in areas where public transit services are inadequate. Policy makers should reduce ride-hailing services instead of short-distance trips by bicycle.