Surge Pricing and Two-Sided Temporal Responses in Ride-Hailing

Bin Hu, Ming Hu, Zhu Han

SSRN Electronic Journal · 2018 · 42 citations · 35 references

DOIFull text

Open access

Concepts

TL;DR

Surge pricing in ride‑hailing platforms is a pivotal and controversial subject. The study examines surge pricing from a temporal perspective, focusing on rider and driver strategic behavior and the slower driver response. The authors model two equilibrium surge patterns—skimming surge pricing (SSP) and penetration surge pricing (PSP)—and extend the analysis to spatial driver distribution and commission structures to explain rider benefits and platform outcomes. They find that SSP can benefit riders by inducing high‑value riders to wait, PSP outperforms SSP but requires driver information sharing, flat‑fee commissions boost matching and profits, and these insights guide better surge pricing practices.

Abstract

Surge pricing in ride hailing platforms is a pivotal and controversial subject. In this paper, we investigate surge pricing from a temporal perspective; in particular, we highlight the strategic behavior by riders and drivers and that drivers respond to surge pricing much slower than riders. We first identify an equilibrium pricing strategy of a short-lived sharp price surge followed by a lower price that we refer to as skimming surge pricing (SSP). We rationalize the controversial sharp surge pricing practice beyond the basic economic principle of demand and supply and show that it can benefit riders: The short-lived sharp price surge causes many high-value riders to voluntarily wait out the initial surge period, who attract additional drivers to come to the region to serve riders at a much lower price than the initial surge price. We also identify another equilibrium pattern of a low initial price followed by a higher price that we refer to as penetration surge pricing (PSP). We find that PSP equilibria are superior to SSP equilibria, but requires platforms to share demand-supply information with drivers. We extend the base model by accounting for the spatial perspective that drivers need to travel over different distances to the surge region, and gain additional insights on how the driver spatial distribution affects our results. We also show that a flat-fee commission generally increases matching volumes and platform profits compared with proportional commissions. Our findings have practical implications for platforms to improve their surge pricing practices.

References

35