Geography Reference
In-Depth Information
across national boundaries, which are also characterized by a high degree
of integration between the local and global knowledge bases (Breschi and
Malerba 1997a, b). In such fast-changing fields, innovation processes are
critically informed by new developments occurring outside of any individ-
ual firm. Therefore, technological progress benefits greatly from the active
participation in the particular technological community or context where
new developments take place (Frost 2001), even if these are geographi-
cally outside of the region. In turn, new technological opportunities will
affect the overall rate of technological growth, and global innovation flows
will privilege those locations offering the best and fastest-growing breaks.
Technological regimes characterized by new and fast-growing opportuni-
ties therefore are those which are also most expected to generate the greatest
turbulence and the largest changes in the locational or sectoral hierarchies.
5.5.2
The Limits of the Transactions Costs Spatial Classification
One of the advantages of the transactions costs classification discussed
above is that it provides an organizing framework which is capable of
dealing with the diversity of spatial concentrations that we observe. At the
same time, a weakness of this framework is that, in the transactions costs
perspective itself, hierarchies, and particularly but not exclusively firm
structures, are reduced to being a consequence of the types of transactions
costs. As such, the transactions costs approach underlying the classifica-
tion of cluster types in Table 5.1 is essentially static in nature, and exhibits
a very narrow definition of knowledge and technology. There are three
aspects to these limitations.
First, while the classification scheme presented above is essentially static,
as we have discussed, we know from all of our previous discussions that
the relationship between firm location and technology is mainly dynamic
(Bottazzi et al. 2008). This is true both in terms of industrial demographic
features such as firm entry, exit, growth, and relocation, and also in terms
of cluster life cycle features such as cluster birth, growth, decline, open-
ness, and attractiveness. The transactions costs classification scheme does,
however, offer possibilities for the inclusion of technology and innovation
components, such as learning, capability accumulation, and knowledge
creation, as additional dynamic explanations for such diversity.
Second, the transactions costs arguments applied to the perceived
impacts of knowledge inflows and outflows by all firms including MNEs,
depend to a large extent upon a narrow definition of knowledge. In the
definition of knowledge which is employed, knowledge is regarded as a
purely public good, and is therefore assumed to be non-excludable, non-
depletable, and free to be used without limits by anyone, at any time, and
