Strategic responses to the aggregator platform: Pricing and information sharing

Abstract

The platform economy has increasingly enabled customers to require service online, and service providers can provide services through both self-operated and aggregator platforms, each attracting a fraction of original customers who favor it. In response to this, we aim to explore the optimal strategy for improving throughput and revenue, from the perspectives of pricing and information sharing. We develop a queueing theoretical model to examine the impact on the system throughput and revenue of different queue-length information provision policies implemented by the service provider. We characterize the equilibrium behavior of customers and investigate the optimal information sharing strategy and optimal additional fee correspondingly. We find that more information should be shared to maximize the system throughput as the market size increases. As more customers prefer the aggregator platform, a congested system may instead boost their probability of placing orders under a specific information strategy. Finally, service providers ought to abandon self-operated platforms when a significant number of customers show a preference for aggregator platforms with an intermediate market size. Our paper highlights the unintended consequences of information sharing and offers prescriptive guidance for managing such a service system within aggregator platforms.