Abstract
Using data provided by a ride-hailing platform, this paper examines the factors that affect taxi driver response behavior to ride-hailing requests. The empirical investigation from a driver’s perspective is of great importance for ride-hailing service providers, given that approximately 40% of the hailing requests receive no response from any driver. To comprehensively understand taxi driver response behavior, we use a rich dataset to generate variables related to the spatio-temporal supply-demand intensities, the economic incentives, the requests’ and the drivers’ characteristics. The results show that drivers are more likely to respond to requests with economic incentives (especially a firm subsidy), and those with a lower spatio-temporal demand intensity or a higher spatio-temporal supply intensity. In addition, drivers are more likely to respond to requests involving rides covering a greater geographical distance and to those with a smaller number of repeated submissions. The drivers’ characteristics, namely, the number of requests received and the number of requests responded, however, have relatively little impacts on their response probability to the current request. Our findings contribute to the related literature and provide managerial implications for ride-hailing service providers.
Highlights
The rapid development of the Internet and mobile communication technology has promoted the integration of online technology and offline businesses, creating a brand-new business model, i.e., the Online to Offline (O2O) business [1]
In addition to the spatio-temporal dynamics, we examined whether economic incentives are effective in increasing the driver response rate
The two types of economic incentives are not equivalent: firm subsidies have a much larger effect on driver response behavior than do passenger premiums. This result possibly occurred because the subsidies are randomly offered by the ride-hailing platform, while passenger premiums are determined by the passengers
Summary
The rapid development of the Internet and mobile communication technology has promoted the integration of online technology and offline businesses, creating a brand-new business model, i.e., the Online to Offline (O2O) business [1]. This subsection provides some model-free evidence regarding the relationship between the temporal and spatial supply-demand imbalances and driver response rate to ride-hailing requests. This motivates us to examine driver response behavior from a spatio-temporal perspective. The response rate is relatively low in the early peak hours (i.e., 06:00–10:00), the late peak hours (i.e., 16:00–18:00), and the evenings (i.e., 20:00–22:00) During these periods, the ride-hailing demand (and the imbalance between supply and demand) is extraordinarily high; many requests are ignored by the drivers. The number of repeated submissions, has a large negative impact on driver response probability (b^6 = -0.370, p < 0.001), because drivers may infer that requests repeatedly submitted to the ride-hailing platform tend to be less attractive They are less likely to respond to these requests. The average AUC for the 100 times of random sampling runs is 78.4%, which is fairly good
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