Impact of Network Structure on New Service Pricing

Abstract

We analyze a firm’s optimal pricing of a new service when consumers interact in a network and impose positive externality on one another. The firm initially provides its service for free, leveraging network externality to promote rapid service consumption growth. The firm raises the price and starts earning revenue only when a sufficient level of consumer interactions is established. Incorporating the local network effects in a nonstationary dynamic model, we study the impact of network structure on the firm’s revenue and optimal pricing decision. We find that the firm delays the timing of service monetization when it faces a more strongly connected network despite the fact that such a network allows the firm to monetize the service sooner by resulting in faster consumption growth. We also find that the firm benefits from network imbalance; that is, the firm prefers a network of consumers with varying degrees of connections to that with similar degrees of connections. We also study the value of knowing the network structure and discuss how such knowledge impacts the firm’s profitability. Our analyses rely on the techniques from algebraic graph theory, which enable us to solve the firm’s high-dimensional dynamic pricing problem by relating it to the network’s spectral characteristics.