Geography Reference
In-Depth Information
thereby af ecting the distribution of innovative and technological activities across space
(Breschi, 2000). The balance between internal and external sources of knowledge varies
over time across and within innovating actors, either i rms or other organisations. In
fast- changing i elds innovation processes are critically informed by new developments
occurring outside any individual i rm. Particularly in such cases, therefore, technological
progress benei ts greatly from the active participation in the technological community
or context where new developments take place (Frost, 2001). Current technological
opportunities af ect the overall rate of regional technological growth, insofar as inno-
vation l ows will privilege, among core locations, those of ering the best and fastest
growing breaks. Indeed, the same concept of technological paradigm implies a close link
between technical progress, organisation and socio-economic institutions: by dei nition,
any radical innovation brings about to some extent transformations in the organisation
of markets, production and communities. Therefore, organisational and institutional
changes are inextricably associated with technological change, and diversity, both
institutional and technical, characterises evolutionary development of socio-economic
systems (Foray and Freeman, 1993).
As is discussed also in section 4, according to such an evolutionary perspective (which
provides the basic rationale for revising the cluster classii cation in a dynamic sense),
spatial typologies are not only heterogeneous, but also path dependent (Boschma and
Lambooy, 1999; Cooke et al., 1997; Dopfer et al., 2004; Iammarino, 2005; Martin and
Sunley, 2006, and Chapter 3 in this topic). Historical contingency explains the actual
existence of selection mechanisms in socio-economic processes: change is neither solely
based on structural elements subject to general rules, nor purely driven by random
ef ects. At each point in time in a system's evolution, a number of paths are theoretically
possible, but only a few will be chosen by the actors because each path must conform
to the logic of socio-economic dynamics (Schwerin and Werker, 2003; see also Hassink,
Chapter 21 in this topic).
Spatial coni gurations can thus be viewed as acting as selection mechanisms that may
provide conditions favourable to meet the new requirements of technical change, that
is, social capabilities for institutional change. Moreover, not only do the characteristics
of the selection environment and their changes inl uence the actors, but the latter also
change the environment (Cohen and Levinthal, 1990; Lambooy and Boschma, 2001).
In this evolutionary view, growth opportunities are therefore assumed to be shaped and
constrained by path dependency, that is, by the inheritance of local structural character-
istics from past knowledge accumulation and learning, and these may often be geograph-
ically determined (Boschma, 2005; Boschma and Frenken, 2006; Malmberg, 1997).
Hence, to discuss the evolutionary dynamics of spatial agglomeration variety, the
classii cation reported in Table 8.1 was extended in Table 8.2, in which the underlying
knowledge conditions of the cluster are now made explicit. This allows us to take into
account the ways in which i rms, and particularly MNEs, may interact with the indus-
trial and technological environments, and the multiple linkages between knowledge con-
ditions and regional economic growth. Thereby, it may help understand how spillovers
occur and change over time. Again, our classii catory attempt is process-driven, thereby
it assumes that each typology may be dominant but not at all exclusive, allowing for
geographical coni gurations that will actually show features of more than one category
at the same time (even more so when considered in dynamic terms).
