This study aims to explore the spatial heterogeneity of influential factors of integrated use of ride-hailing service with the metro. Using the operation data of ride-hailing services in Chengdu, China, first, an identification method of integrated ride-hailing trips is proposed. Then, the ordinary least squares (OLS) and geographically weighted regression (GWR) models are established to discern the factors that affect access-integrated ride-hailing use and egress-integrated ride-hailing use on weekdays and weekends. The model results demonstrate that the fitting effect of GWR models is superior to that of OLS models, and the coefficient estimates of each explanatory variable vary across regions. Accommodation facilities promote the access-integrated trips in the eastern area, and this positive impact for egress-integrated trips extends to the northeastern area. Tourist attractions have a positive impact on the integrated trips in the central and western regions, while they have a negative impact in the northwest and southeast regions. The research results can provide the theoretical support for the seamless connection and coordinated development of these two services.