There is a fierce competition between two-sided mobility platforms (e.g., Uber and Lyft) fueled by massive subsidies, yet the underlying dynamics and interactions between the competing plat-forms are largely unknown. These platforms rely on the cross-side network effects to grow, they need to attract agents from both sides to kick-off: travellers are needed for drivers and drivers are needed for travellers. We use our coevolutionary model featured by the S-shaped learning curves to simulate the day-to-day dynamics of the ride-sourcing market at the microscopic level. We run three scenarios to illustrate the possible equilibria in the market. Our results underline how the correlation inside the ride-sourcing nest of the agents choice set significantly affects the plat-forms' market shares. While late entry to the market decreases the chance of platform success and possibly results in "winner-takes-all", heavy subsidies can keep the new platform in competition giving rise to "market sharing" regime.

翻译：双端移动平台（如Uber和Lyft）在大规模补贴驱动下竞争激烈，但其底层动态及平台间互动机制仍不明确。这些平台依赖跨边网络效应实现增长，需同时吸引用户与司机以启动市场：乘客与司机之间存在相互需求关系。我们采用具有S形学习曲线的协同演化模型，从微观层面模拟网约车市场的逐日动态。通过三种情景推演，揭示市场可能达成的均衡状态。研究结果表明，网约车选择集内部的相关性显著影响平台市场份额分配。尽管后入市场会降低平台成功概率并可能导致"赢家通吃"格局，但巨额补贴可使新平台维持竞争力，催生"市场共享"模式。