Exploring the Spatiotemporal Associations Between Ride-Hailing Demand, Visual Walkability, and the Built Environment: Evidence from Chengdu, China

Ride-hailing services have reshaped urban commuting patterns, yet the spatiotemporal mechanisms linking built environment features to ride-hailing demand remain underexplored. Existing studies often overlook the joint effects of origin–destination visual walkability. This study integrates ride-hailing GPS trajectories and geospatial data to quantify mobility patterns and built-environment indicators in Chengdu, China. A dual analytical framework combining global regression and localized modeling was applied to disentangle spatial–temporal influences of urban form and socioeconomic factors. The results reveal that population density, floor–area ratio, and housing prices positively correlate with demand, while road density and distance to city center exhibit negative associations. Visual walkability metrics show divergent effects: psychological greenery and pavement visibility reduce ride-hailing usage, whereas outdoor enclosure enhances it. Temporal analysis identifies time-dependent impacts of built environment variables on main urban area travel. Housing price effects demonstrate spatial globality, while population density and city-center proximity exhibit geographically bounded correlations. Notably, improved visual walkability in specific zones reduces reliance on ride-hailing by facilitating sustainable alternatives. These findings provide empirical support for optimizing urban infrastructure and land-use policies to promote equitable mobility systems. The proposed methodology offers a replicable framework for assessing transportation–land-use interactions, informing targeted interventions to achieve metropolitan sustainability goals through coordinated spatial planning and pedestrian-centric design.