The development of on-demand ridesharing platforms has reshaped commuters' travel behavior, enabling commuters to decide whether to become ridesharing drivers or passengers in real time. To examine the impact of commuters' decisions and ridesharing platform's strategies on the equilibrium state in the morning commute problem, this paper formulates an equilibrium framework to characterize commuters' mode choice and travel time choice behavior based on the bottleneck model. The mismatch problem and commuters' heterogeneous preference for the ridesharing mode are considered. An analytical sensitivity analysis is conducted to discuss how the market share of ridesharing mode changes with the platform's pricing strategies based on the equilibrium state. The optimal strategies for profit and market share maximization are also studied. Under derived conditions, we find that the supply of ridesharing drivers must be coordinated with the passenger demand when the optimal state is achieved. The numerical results are further demonstrated to verify the analytical findings. Our analyses provide insights for pricing strategies of the ridesharing platform.

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