  Global supply networks in agriculture, manufacturing, and services are a
defining feature of the modern world. The efficiency and the distribution of
surpluses across different parts of these networks depend on choices of
intermediaries. This paper conducts price formation experiments with human
subjects located in large complex networks to develop a better understanding of
the principles governing behavior. Our first finding is that prices are larger
and that trade is significantly less efficient in small-world networks as
compared to random networks. Our second finding is that location within a
network is not an important determinant of pricing. An examination of the price
dynamics suggests that traders on cheapest -- and hence active -- paths raise
prices while those off these paths lower them. We construct an agent-based
model (ABM) that embodies this rule of thumb. Simulations of this ABM yield
macroscopic patterns consistent with the experimental findings. Finally, we
extrapolate the ABM on to significantly larger random and small world networks
and find that network topology remains a key determinant of pricing and
efficiency.
