Online ride-hailing platforms have become an important part of the transportation system in modern life, especially in large cities. Under the fierce market competition, companies need to pay more attention to the diversified customer needs. Companies provide various types of services to customers with different pricing strategies nowadays. We consider the case when the supply/demand is unbalanced among different services and propose a mix allocation threshold-based matching policy. We model the complete flow of the ride-hailing platform with the stochastic model and simplify it with fluid approximation. Then we analyze the equilibrium states under conditions of the matching thresholds. We analyze the optimal condition of maximizing total revenue in two simple scenarios and implement a...[ Read more ]

Online ride-hailing platforms have become an important part of the transportation system in modern life, especially in large cities. Under the fierce market competition, companies need to pay more attention to the diversified customer needs. Companies provide various types of services to customers with different pricing strategies nowadays. We consider the case when the supply/demand is unbalanced among different services and propose a mix allocation threshold-based matching policy. We model the complete flow of the ride-hailing platform with the stochastic model and simplify it with fluid approximation. Then we analyze the equilibrium states under conditions of the matching thresholds. We analyze the optimal condition of maximizing total revenue in two simple scenarios and implement a numerical example to show the advantage of mix allocation in a specific case.

Keywords— ride-hailing platform; on-demand matching; resource allocation; fluid approximation.