Optimizing Ride-Hailing Supply Scale and Platform Revenue: A Comparative Analysis of Commission Strategies

Ride-hailing services, an emerging model in the taxi market, have transformed passenger travel, challenging traditional taxis. However, current commission strategies on online platforms often neglect traditional taxis’ interests, reducing their willingness to accept orders. This paper explores commission strategies for platforms offering both traditional and non-traditional taxi services, aiming to optimize supply and platform revenue. We consider price-sensitive passengers and commission-sensitive drivers, constructing demand and supply functions for different services. We formulated revenue functions for ride-sharing services (comprising both ride-sharing taxis and other ride-sharing options) and traditional taxis (including ride-sharing taxis and other alternatives). We constructed a price competition game model and obtained price equilibrium solutions. By incorporating these price equilibrium solutions into the models mentioned earlier, we derived the supply-demand functions and revenue functions for ride-sharing services, with the commission rates as variables. Numerical experiments reveal that increasing ride-sharing service commissions at specific times decreases supply. Time-based commission strategies further optimize ride-sharing earnings.