Differentiated Service Pricing Strategies for Ride Hailing Considering Rational Inattentive Passengers

Abstract

Considering the ambiguity of passengers’ perception of the real service level of ride hailing, this paper establishes a bi-level optimization model for the pricing strategies of differentiated services on ride-hailing platforms based on the theory of rational inattention. It explores the pricing mechanism of ride-hailing platforms for two optimization objectives (profit maximization and social welfare maximization) under three service strategies (providing both high and low differentiated services, providing a single low service, and providing a single high service). The model is solved using a combination of the particle swarm optimization (PSO) algorithm and the method of successive averages (MSA). Numerical examples have verified the effectiveness and robustness of the model and algorithm. The results show that under three strategies, the platform profit shows a trend of first increasing and then decreasing with the increase in the unit information cost. To ensure maximum profit, the platform should disclose the service information of ride hailing as much as possible but also maintain the unknownness of ride-hailing services appropriately. When the goal is to maximize social welfare, when the unit information cost is low, compared with providing a single service strategy, a differentiated service strategy can better meet the differentiated choices of drivers and passengers, thereby ensuring higher social welfare. As the unit information cost increases, the platform needs to reduce the service prices to attract rational inattentive passengers to choose ride-hailing services, thereby improving social welfare. The results can provide references for ride-hailing platforms in formulating pricing strategies for differentiated services.