Integrated optimization of pricing and relocation in the competitive carsharing market: A multi-leader-follower game model

Abstract

One-way carsharing, as a shared mobility service, is attracting increasing attention due to its flexibility and social benefits. Spurred by this trend, an increasing number of companies have been formed, which promotes the expansion of the carsharing market. In the presence of intensifying competitive pressure, it has become imperative for companies to determine their optimal operational strategies by adjusting their pricing and relocation strategies to ensure financially sustainable service operations. Indeed, the most urgent issue that must be addressed is the modeling of an integrated framework combining the pricing and relocation strategies of operators in a competitive market. To solve this problem, a game-theoretical multi-leader–follower model is proposed to maximize the profit of each company involved and minimize the disutility of travelers, the Nash equilibrium solution of which is obtained by developing a diagonalization algorithm framework. Specifically, in each iteration, a bilevel model is solved to obtain the best response, which is the most favorable outcome for a certain company given competing companies’ strategies. The upper level aims to determine the pricing and relocation strategy of each company, while the lower level assigns trip demand by solving a stochastic user equilibrium problem. The proposed method is applied to a hypothetical case study and a realistic example in the context of Quanzhou city, China, and its performance is demonstrated by extensive sensitivity analysis. The results show that the total profits of the market rise with the number of companies increasing, but the average profit and price drop. Through a comparison between strategies with and without relocations, it is found that relocation strategies have a significant impact on raising profits of a company with a large fleet size.