  When a new product or technology is introduced, potential consumers can learn
its quality by trying the product, at a risk, or by letting others try it and
free-riding on the information that they generate. We propose a dynamic game to
study the adoption of technologies of uncertain value, when agents are
connected by a network and a monopolist seller chooses a policy to maximize
profits. Consumers with low degree (few friends) have incentives to adopt
early, while consumers with high degree have incentives to free ride. The
seller can induce high-degree consumers to adopt early by offering referral
incentives - rewards to early adopters whose friends buy in the second period.
Referral incentives thus lead to a `double-threshold strategy' by which low and
high-degree agents adopt the product early while middle-degree agents wait. We
show that referral incentives are optimal on certain networks while
inter-temporal price discrimination (i.e., a first-period price discount) is
optimal on others, and discuss welfare implications.
