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marketing and image building by the city management in order to attract tenants to
the properties, and away from nurturing networks and new cultures. Expectations
and reward systems largely shaped by historical patterns or spatially benign sys-
tems can reinforce low institutional links, in particular those that require the
involvement of higher education and research institutions. In this way, despite
considerable investment and extensive programmes of action, there is a threat that
the area will not break away from embedded path dependency, and simply
reconfigure localities, by attempting to make spatial assets more attractive to the
next round of capital investment, rather than achieving transformative change, new
trajectories and a wider modernisation of the region.
Furthermore, as the Limits 7 and 8 explore above, the nature of governance and
critically the role of national state structures, processes, norms and goals can
significantly determine the final outcome of science city/technopolis development.
Komninos (
2002
) reflects that there ''is no doubt that the state policy for inno-
vation is a key factor. It would seem easier to create the norms and conventions of
trust and association on a national scale, taking advantage of the cultural and
political consistency of the nation, and use them for action on the global and local
scales''. And continues to argue that it is the region that ''is the level of concrete
action'', the elaboration of strategy must involve real actors and take into account
the strengths and weaknesses of specific productive systems and the real capa-
bilities of the research and academic community. Furthermore, ''Two issues that
should be stressed are the differences in the organisation of innovation systems in
different countries, and the difficulty of defining models. The institutional
framework for innovation appropriate for a nation is shaped by complex political,
economic and cultural factors forged over a long period of time. On the other hand,
in many countries a major restructuring in the state research, technology, educa-
tion, vocational training and finance institutions is necessary. This involves both
organisational and cultural changes, and the building of institutions capable to
substitute rules with conventions of trust and cooperation'' (Komninos
2002
).
'Science city' based urban development is thus a highly normative construct. It
has on many occasions been advanced as a way of replicating Silicon Valley, an
expression of a particular form of growth and production of wealth and power,
which itself has not been reproduced throughout the USA. The assumptions and
goals in this model are inherently linked to certain patterns and outcomes of
economic growth. First, it advocates a high growth outcome, both in scale and rate.
Very often this is also seen to support any national state objectives to improve
economic performance, but as outlined above, is also often rationalised through the
desire to overcome uneven spatial development, especially in peripheral areas, or
localities peripheral to main urban cores (Tokyo, Seoul, Paris, London, Madrid).
Second, it advances the notion of high value added growth with a view that this
can increase prosperity and counter-balance alternative outcomes such as low-
waged economies or cost-based competitiveness. Finally, the model places great
emphasis on spatial proximity, agglomeration effects, the creation and promotion
of milieu and clustering of activities—''New technological knowledge is usually in
such a tacit form that accessibility is bounded by geographic proximity and/or by
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