The Nonlinear and Threshold Effect of Built Environment on Ride-Hailing Travel Demand

The Nonlinear and Threshold Effect of Built Environment on Ride-Hailing Travel Demand

Blog Article

While numerous studies have explored the correlation between the built environment and ride-hailing demand, few have assessed their nonlinear interplay.Utilizing ride-hailing order data and multi-source built environment data from Nanjing, China, this paper uses the 30-40mmHg machine learning method, eXtreme Gradient Boosting (XGBoost), combined with Shapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDPs) to investigate the impact of built environment factors on ride-hailing travel demand, including their nonlinear and threshold effects.The findings reveal that dining facilities Eleuthero Root have the most significant impact, with a contribution rate of 30.75%, on predicting ride-hailing travel demand.Additionally, financial, corporate, and medical facilities also exert considerable influence.

The built environment factors need to reach a certain threshold or within a certain range to maximize the impact of ride-hailing travel demand.Population density, land use mix, and distance to the subway station collectively influence ride-hailing demand.The results are helpful for TNCs to allocate network ride-hailing resources reasonably and effectively.