Geography Reference
In-Depth Information
well as for the development of multilateral networks of dissimilar but complementary
relations between MNEs and local actors (Patrucco, 2001, 2003).
On the other hand, from the perspective of inward investment, in the industries in
which the host region or cluster is technologically strong, the vibrant presence of indig-
enous companies tends to deter MNEs in the same industry from conducting substantial
levels of innovative activity in the primary technology of the industry in question. At
the same time, the strongest i rms of other industries, and particularly foreign MNEs,
might be attracted to that location for those relevant technologies, as these lines of
development for them represent diversii cation from the primary technologies of their
own industry. Since they are in another industry, they are not direct competitors of the
local leaders. Comparative strength in an industry of locally owned i rms encourages
outward investment in technological activity, but discourage the inward investment
of foreign-owned companies in the same industry: MNEs' penetration in locations
of domestic technological excellence tends to be low in most countries (Cantwell and
Kosmopoulou, 2002)
Once the dif erent types of spatial coni guration are distinguished in terms of tech-
nological regimes, structures and governances, as well as their transactional relations,
it becomes clear that the social network model ceases to be a relatively homogeneous
and consistent analytical category. Thus, in Table 8.2 the single transaction cost-based
social network typology is split into two sub-categories, namely the 'new social network'
category and the 'old social network' category.
In the new social network model technological opportunities come in the main from
sources outside the i rm and the industry sector, such as academic research. In this
kind of technological environment the type of knowledge tends to be both generic and
non-systemic, there is a high rate of market entry and exit, a strong volatility of market
shares, and a low level of market concentration. In this environment, the tacit and sticky
nature of knowledge requires geographical proximity. On the other hand, the relative
'leaky' character of new knowledge - and the high potential for spillovers - the openness
of the innovation system and the related emergence of new rules, standards, blueprints
and verii cation procedures, all point to the importance of external sources of technical
knowledge, which may not be necessarily localised. As such, innovation is frequently
associated with a high level of uncertainty regarding both technology and demand, and a
high level of market turbulence. As a consequence, a lower survival of new i rms is likely
to be associated with higher innovativeness and growth of surviving i rms (Alchian,
1957). Innovations also therefore mainly come from knowledge that does not have a
routinised nature, with new i rm start-ups playing an important role, SMEs accounting
for the bulk of innovative activity, and normally limited presence of large MNEs
in situ
,
at least in the i rst stages of the cluster life cycle.
In the old 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 codii ed and mature, it develops along trajectories
that are mainly oriented to process innovation, and it is transmitted essentially by way of
personal contacts, social and political lobbying, and backward and forward linkages, the
latter sometimes intensii ed by the presence of MNEs.
Moreover, from the perspective of geography, there is also a fundamental dif erence
in the particular systems of innovation governance between new and old social networks
