Real trip costs: Modelling intangible costs of urban online car-hailing in Haikou

Prearranged and on-demand ride services that match passengers and drivers using smartphone applications over a network have developed rapidly across the world. However, the maximum efficiency of the entire hailing demand market and the driver deserve further attention to identify potential improvements. This paper makes the first attempt to conduct a quantitative analysis of the intangible costs generated from ridesourcing trips using an observed ridesourcing dataset provided by Didi Chuxing, including the waiting time costs attributable to waiting for the passenger and the future opportunity costs of different Trip Order Markets. Then, a quantitative method is developed to calculate the specific value of the above intangible costs of each ridesourcing trip. The results show that the average cost of a trip drops by 9.64% when intangible costs are considered, and a large difference exists among the values under various spatial-temporal conditions. In addition, the relative relationship between two types of intangible costs shows a large discrepancy in some sensitive areas. The findings of this study can help transit agencies better understand ridesourcing service and develop strategies for setting reasonable prices and allocating capacity.