Geography Reference
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standards, blueprints and verification procedures, all point to the impor-
tance of external sources of technical knowledge. Moreover, the sources
of technical knowledge may or not necessarily be localized. As such, inno-
vation is frequently associated with a high level of uncertainty regarding
both the nature and levels of technology and demand, and a high degree of
market turbulence. As a consequence, a lower survival rate for new firms
is likely to be associated with higher levels of innovativeness and growth
among the surviving firms (Alchian 1950). Innovations also therefore
mainly come from knowledge that does not have a routinized nature, with
new firm start-ups playing an important role, and SMEs accounting for
a large share of innovative activity. There is normally either no role or
at best only a limited presence of large MNEs in situ in the first stages of
the cluster life cycle. In later stages of development, however, where both
industry and spatial patterns have reached a certain stability, such clusters
may become attractive to MNEs, but in the early stages of the competence
based cluster, MNEs are rarely part of the story.
In the trust-led social network type, there is not necessarily any clear
hierarchical structure, and the overall coordination of the innovation
system is left to a mix of cooperation and competition. Knowledge is
largely codified and mature and develops along stable trajectories which
are mainly oriented towards process innovation. Knowledge is transmit-
ted essentially by way of informal personal contacts which are strongly
embedded in a common cultural matrix, comprised of elements of social
and political lobbying, and various backward and forward linkages. These
backward and forward linkages sometimes are intensified by the pres-
ence of MNEs. If this is the case, then the cluster evolution will also in
part depend on the nature of the transactions established by the MNEs
with both small and large local firms. As such, the structure of vertical
and horizontal linkages between MNEs and local firms may be crucial
in determining the nature and extent of the local spillovers. Even in the
same industry, clusters may be characterized either by highly vertically
integrated firms, or by stage production with significant subcontracting
linkages. The trust relationships and the role of reputation will differ con-
siderably in such different spatial and industrial settings (Guy 2009).
Reinterpreting the simple spatial types in terms of technology, knowl-
edge and innovation characteristics, allows us to uncover more subtle and
detailed aspects of firm location behaviour. In particular, in the case of
MNEs, any simple assumed correlations between local knowledge spillo-
vers, the spatial concentration of activity, and the advantages of a particu-
lar location for firm investment, do not necessarily hold. For example, in
the case of pure agglomeration, while the overall links between innova-
tion and cities are very strong (Acs 2002), the arguments relating MNEs
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