Abstract
This paper models knowledge diffusion as a barter process in which
agents exchange different types of knowledge. This is intended to
capture the observed practice of informal knowledge trading. Agents
are located on a network and are directly connected with a small
number of other agents. Agents repeatedly meet those with whom direct
connections exist and trade if mutually profitable trades exist.
In this way knowledge diffuses throughout the economy. We examine
the relationship between network architecture and diffusion performance.
We consider the space of structures that fall between, at one extreme,
a network in which every agent is connected to n nearest neighbours,
and at the other extreme a network with each agent being connected
to, on average, n randomly chosen agents. We find that the performance
of the system exhibits clear ‘small world’ properties, in that the
steady-state level of average knowledge is maximal when the structure
is a small world (that is, when most connections are local, but roughly
10 percent of them are long distance). The variance of knowledge
levels among agents is maximal in the small world region, whereas
the coefficient of variation is minimal. We explain these results
as reflecting the dynamics of knowledge transmission as affected
by the architecture of connections among agents.
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