论文标题
乘车平台的价格周期
Price Cycles in Ridesharing Platforms
论文作者
论文摘要
在Uber和Lyft等乘车平台中，可以观察到，当价格低时，驾驶员有时会脱机，然后在价格上涨后返回，由于缺乏供应，驾驶员的价格上涨。这种集体策略会导致价格和可用驱动因素的循环波动，从而导致可靠性和社会福利差。我们研究了一个连续的时间，非原子模型，并证明这种在线/离线策略可能会在驱动程序之间形成NASH平衡，但如果市场足够密集，则会导致总驾驶员的收益较低。此外，我们展示了如何设置价格地板，从而有效地减轻了价格周期的出现和影响。
In ridesharing platforms such as Uber and Lyft, it is observed that drivers sometimes collaboratively go offline when the price is low, and then return after the price has risen due to the perceived lack of supply. This collective strategy leads to cyclic fluctuations in prices and available drivers, resulting in poor reliability and social welfare. We study a continuous time, non-atomic model and prove that such online/offline strategies may form a Nash equilibrium among drivers, but lead to a lower total driver payoff if the market is sufficiently dense. Further, we show how to set price floors that effectively mitigate the emergence and impact of price cycles.
