Monetizing digital content with network effects: A mechanism-design approach

TL;DR

This paper develops profit-maximizing mechanisms for selling digital goods with network effects, accounting for heterogeneous private values and implementing optimal allocations in dominant strategies.

Contribution

It introduces a novel mechanism-design framework for digital content monetization considering network effects and heterogeneous buyer valuations.

Findings

Optimal mechanisms allocate to highest types with positive network effects.

The model explains features like voluntary contributions and exclusivity in digital monetization.

Mechanisms are implementable in dominant strategies.

Abstract

We design profit-maximizing mechanisms to sell an excludable and non-rival good with positive and/or negative network effects. Buyers have heterogeneous private values that depend on how many others also consume the good. In optimum, an endogenous number of the highest types consume the good, and we can implement this allocation in dominant strategies. We apply our insights to digital content creation, and we are able to rationalize features seen in monetization schemes in this industry such as voluntary contributions, community subsidies, and exclusivity bids.