  Empirical research on world cities often draws on Taylor's (2001) notion of
an 'interlocking network model', in which office networks of globalized service
firms are assumed to shape the spatialities of urban networks. In spite of its
many merits, this approach is limited because the resultant adjacency matrices
are not really fit for network-analytic calculations. We therefore propose a
fresh analytical approach using a primary linkage algorithm that produces a
one-mode directed graph based on Taylor's two-mode city/firm network data. The
procedure has the advantage of creating less dense networks when compared to
the interlocking network model, while nonetheless retaining the network
structure apparent in the initial dataset. We randomize the empirical network
with a bootstrapping simulation approach, and compare the simulated parameters
of this null-model with our empirical network parameter (i.e. betweenness
centrality). We find that our approach produces results that are comparable to
those of the standard interlocking network model. However, because our approach
is based on an actual graph representation and network analysis, we are able to
assess cities' position in the network at large. For instance, we find that
cities such as Tokyo, Sydney, Melbourne, Almaty and Karachi hold more strategic
and valuable positions than suggested in the interlocking networks as they play
a bridging role in connecting cities across regions. In general, we argue that
our graph representation allows for further and deeper analysis of the original
data, further extending world city network research into a theory-based
empirical research approach.

Physics and Society;Social and Information Networks