Operational modes and market structures selection in the on-demand ride-hailing platform considering matching-induced utility uncertainty

In on-demand ride-hailing platforms, participants face matching-induced utility uncertainty, a distinct phenomenon where participants cannot predict whether they will be successfully matched with counterparts. This uncertainty creates gaps between participants’ expected and realized utility, thus significantly influencing how platforms should optimize their pricing strategies to shape participants’ choices and market outcomes. To address this challenge, this paper constructs a theoretical framework of an on-demand platform ecosystem consisting of a ride-hailing platform (RP) and its upstream contract manufacturer (CM). We investigate how both parties strategically make pricing decisions to influence market structure formation and determine the optimal operational mode selection between business-to-customer (B2C) and peer-to-peer (P2P). Our comprehensive analysis reveals several key insights: 1) Regarding market structure formation, high service investment consistently leads to balanced structures across various commission rates in both operational modes. However, as service investment declines, the two modes diverge significantly: P2P mode invariably tends towards buyer markets regardless of commission rates, while B2C mode results in buyer markets only when commission rates exceed certain thresholds 2) When the platform supply chain achieves market balance, the CM exhibits a quality-profit inflection phenomenon, benefiting from increased service investment only when it surpasses a critical threshold. Below this threshold, profits paradoxically decrease as service investment improves due to intensified pricing competition at lower quality levels. 3) The RP selects the P2P mode exclusively when both service investment and commission rates are simultaneously high, otherwise strategically shifting to the B2C mode to access multiple revenue streams and reduce dependence on commission income alone. 4) The analysis extends to incorporate participant risk preferences and endogenous service investment decisions, which not only validates the core findings but also reveals how behavioral factors and strategic quality investments interact to shape market structures.