  An increasing number of businesses and organisations rely on existing users
for finding new users or spreading a message. One of the widely used
"refer-a-friend" mechanisms offers an equal reward to both the referrer and the
invitee. This mechanism provides incentives for direct referrals and is fair to
the invitee. On the other hand, multi-level marketing and recent social
mobilisation experiments focus on mechanisms that incentivise both direct and
indirect referrals. Such mechanisms share the reward for inviting a new member
among the ancestors, usually in geometrically decreasing shares. A new member
receives nothing at the time of joining. We study fairness in multi-level
marketing mechanisms. We show how characteristic function games can be used to
model referral marketing, show how the canonical fairness concept of the
Shapley value can be applied to this setting, and establish the complexity of
finding the Shapley value in each class, and provide a comparison of the
Shapley value-based mechanism to existing referral mechanisms.
