The Ride‐Hailing and Pricing Strategy Decision With the Application of Autonomous Vehicles

ABSTRACT The application of autonomous vehicles (AVs) offers a promising avenue to address the profitability challenges of ride‐hailing platforms. However, in a mixed operational model combining human drivers (HDs) and AVs, the high operating costs of AVs raise concerns about their feasibility for large‐scale commercial deployment and the design of optimal pricing strategies. To address these issues, this study develops a cooperative game‐theoretic model involving three parties: a ride‐hailing platform, an AV manufacturer, and a jointly established company. We first examine changes in platform profitability before and after AV application to identify the conditions under which adopting AVs becomes viable. We then compare the payoffs of all market participants under different pricing strategies to determine the optimal scheme that facilitates multiparty cooperation. The results indicate that introducing AVs can strengthen user‐platform stickiness and reduce wage costs for HDs. However, the platform is incentivized to adopt AVs only when the operating cost coefficient is sufficiently low. Moreover, once this cost falls below a certain threshold, a premium pricing strategy yields higher platform profitability and enables a win–win–win outcome among the platform, joint company, and manufacturer. This study advances the literature on economic decision‐making for AV deployment in the ride‐hailing sector and offers theoretical and practical guidance for pricing strategies and partnership design in the era of intelligent mobility.