  If you recommend a product to me and I buy it, how much should you be paid by
the seller? And if your sole interest is to maximize the amount paid to you by
the seller for a sequence of recommendations, how should you recommend
optimally if I become more inclined to ignore you with each irrelevant
recommendation you make? Finding an answer to these questions is a key
challenge in all forms of marketing that rely on and explore social ties;
ranging from personal recommendations to viral marketing.
  In the first part of this paper, we show that there can be no pricing
mechanism that is "truthful" with respect to the seller, and we use solution
concepts from coalitional game theory, namely the Core, the Shapley Value, and
the Nash Bargaining Solution, to derive provably "fair" prices for settings
with one or multiple recommenders. We then investigate pricing mechanisms for
the setting where recommenders have different "purchase arguments". Here we
show that it might be beneficial for the recommenders to withhold some of their
arguments, unless anonymity-proof solution concepts, such as the
anonymity-proof Shapley value, are used.
  In the second part of this paper, we analyze the setting where the
recommendee loses trust in the recommender for each irrelevant recommendation.
Here we prove that even if the recommendee regains her initial trust on each
successful recommendation, the expected total profit the recommender can make
over an infinite period is bounded. This can only be overcome when the
recommendee also incrementally regains trust during periods without any
recommendation. Here, we see an interesting connection to "banner blindness",
suggesting that showing fewer ads can lead to a higher long-term profit.
