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.
翻译:在Uber和Lyft等搭乘共享平台上,人们注意到,司机有时在价格低廉时合作脱线,然后在价格上涨后因认为缺乏供应而返回。这一集体战略导致价格和现有驱动因素的周期性波动,导致可靠性和社会福利差。 我们研究一个连续的时间、非原子模型,证明这种在线/离线战略在司机之间可能形成纳什平衡,但如果市场足够密集,则导致总驱动因素报酬降低。此外,我们展示了如何设定价格底线,以有效缓解价格周期的出现和影响。