A network grows not only by the addition of
single members. It can jump in size by
interconnecting or merging with another network.
If two networks are of similar size, each would
see roughly the same increase in value if they
combined. You would expect them to interconnect,
and indeed, networks of comparable size do so
routinely. But when one network is much bigger
than the other, the larger one usually resists interconnecting.
If Metcalfe's Law were true, no matter what
the relative sizes of two networks, both would
gain the same amount by uniting, making the
observed behavior seem irrational [see table
below, "The Value of Interconnecting"]. If our
n
log(n) law holds
(or other laws with growth rates falling between
ours and Metcalfe's), then, as the table shows,
the smaller network would gain more than the
larger one. For example, if the larger network
is eight times as large as the smaller one, its
gain would be less than half that of the smaller
one. This clearly reduces the incentive for the
owners of the larger network to interconnect
without compensation.
This model of network interconnection is
simplistic, of course, and it does not deal with
other important aspects that enter into actual
negotiations, such as a network's geographical
span, its balance of outgoing and incoming
traffic, and any number of additional factors.
All we are trying to show is that there may be
sound economic reasons, besides raw market
power, for larger networks to demand payment for
interconnection with smaller ones. In fact,
that's a common phenomenon in real life.
Our n
log(n) law
describes best the increase in value of a single
network as it grows through acquisition of
individual members. But our law should not be
applied directly to evaluate the effects of
connecting separate networks. Another important
consideration is the degree to which groups that
value each other highly are already contained
within the networks being combined, a factor
called clustering.
When clustering is weak, the people you tend
to communicate with the most—family members,
work colleagues, fellow hobbyists, and so
on—are not on the same network you are. In
these cases, the value of connecting separate
networks can be higher than our n
log(n) law predicts.
Nonetheless, given that most networks grow
organically, with people drawing in the people
closest to them, the majority of networks are
strongly clustered. Therefore, in most networks,
n
log(n) appears to
be the best simple description of network value
in terms of the network's size.