Peer-to-peer (P2P) reservation platforms often struggle to manage advance-booking customers. Because supply is self-scheduled, hosts’ and customers’ incentives may be misaligned. When platforms set high prices, the asset owners (hosts) would commit their assets early—i.e., list in advance; however, it may deter advance-booking customers from reserving. Conversely, setting lower prices would discourage hosts from listing early. Moreover, a host’s decision to list also depends on matching probability, which is governed by the platform’s design and search frictions— that is, its matching efficiency. We examine when and why advance-booking customers face a supply shortfall and how the platform’s matching efficiency contributes to this outcome. We develop a two-period game-theoretic model in which the platform sets prices dynamically, and hosts choose when to list their assets. The model incorporates endogenous matching probabilities to capture real-world search frictions. To validate our theoretical insights, we analyze data from a major car-sharing platform, focusing on host listing decisions and their impact on service availability. We characterize the hosts’ optimal listing strategies in response to the platform’s prices and identify three possible outcomes: no commitment, partial commitment, and full commitment. We show that when the demand imbalance between advance-booking and just-in-time customers exceeds a threshold, the platform prefers to induce a breakdown in the advance-booking market. Counterintuitively, this threshold decreases as the platform’s matching efficiency increases, meaning more efficient platforms are more prone to such breakdowns. Peer-to-peer reservation platforms should be cautious when choosing revenue-maximizing prices during severe demand imbalances, as it can disrupt advance-booking markets. Beyond pricing, a platform designer can use matching efficiency as a strategic lever to shape outcomes. By improving matching for early listers—through visibility boosts or recommendation algorithms—platforms can better align host incentives, reduce breakdowns, and enhance service across customer segments.