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

Dynamics of the Ride-Sourcing Market: A Coevolutionary Model of Competition between Two-Sided Mobility Platforms