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Optimal pricing strategy of an on-demand platform with cross-regional passengers
Institution:1. School of Management, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China;2. School of Business Administration, Southwestern University of Finance and Economics, Chengdu, Sichuan 611130, China;3. KEDGE Business School, Marseille 13288, France
Abstract:Recent years have witnessed the emergence and prosperity of online ride-hailing, which empowers the traditional taxi industry with information technology. However, the ride-hailing platform has no direct control over drivers, one of the biggest challenges for the platform is how to balance the supply and the demand. Considering the cross-regional demand and the surge demand, this paper focuses on the pricing strategy of the ride-hailing platform, and further introduces strategies such as bonus incentive and information sharing. We find that when facing demand surging and supply shortage in one region, the platform can adopt surge pricing or bonus incentive in the adjacent region before the demand surges to balance the supply and the demand. Specially, the surge pricing strategy benefits the platform when the surge demand is high or the cross-regional demand is low, but the bonus incentive strategy has the opposite effect. The existence of cross-regional demand improves the performance of the bonus incentive strategy but reduces that of the surge pricing strategy. We further show that the platform prefers bonus incentive to surge pricing when only a small number of drivers are required to move. But bonus incentive always improves social welfare better than surge pricing. Extending to information asymmetry, information sharing can also encourage more drivers to move. However, the effect is limited such that the proportion of drivers who move will not exceed a threshold. The platform also has the incentive to share false information, which makes drivers question the credibility of the shared information. In this case, the surge pricing strategy can be used as a costly signal to verify the credibility of the information.
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