Geography Reference
In-Depth Information
localised (knowledge-rich) networks can even amplify or facilitate the sharing of valu-
able resources, but the seeds of success are primarily in the internal activities of cluster
i rms. This is nevertheless an issue that deserves further research, as I am suggesting in
the rest of this section.
This analysis was set within specii c empirical and methodological limits. The i rst is
that this is a single industry study. The generalisation of its results is therefore bounded
by the specii cities of the wine industry. The second is that, for the sake of simplicity,
the MRQAP analysis does not introduce control variables in the model, as discussed in
section 3. The third limitation is that this study focuses only on intra-cluster linkages,
leaving aside extra-cluster linkages, which are instead an important component of i rms'
learning processes (Amin and Thrift, 1992; Bell and Albu, 1999; Coe and Bunnell, 2003).
Finally, a further limitation is particularly important and raises interesting questions: the
cross-sectional nature of this analysis. In this respect, future research should explore the
evolution of networks in time, and look at the existence of micro-meso interactions. In
particular, it would be interesting to answer questions like: what types of initial micro-
level conditions are necessary to spark the formation of (knowledge-rich) networks that
lead to equitable forms of economic development in regional clusters? What network
structures facilitate the emergence of vibrant clusters? Thus, future research should try to
explore the interaction between several types of i rm-level characteristic and their likeli-
hood to engage in networks - including social/friendship networks - that can enhance
their economic performance and sustain processes of economic development. For
example, one could ask: under what i rm-level conditions do social linkages favour the
formation of knowledge linkages and generate a less selective environment in regional
clusters, than the one observed in this study? In sum, it would be extremely valuable to
explore the relationship between the distribution of given i rm-level characteristics (inter-
nal capabilities, degree of foreignness, size, strategic orientation, etc.) in a territory, the
structural evolution of dif erent types of network (knowledge, business, friendship, etc.)
and the patterns of economic development.
To conclude, it is hoped that, in spite of the existing limitations, this chapter serves
to spark a discussion on the need to study networks in geography (e.g. in clusters or
districts) with more analytical rigour than has been achieved in earlier studies. While
most of the cluster literature and, to some extent, policy makers, (over)emphasise the
importance of networks, still very little is known about which type of network is relevant
for economic development and which type, instead, generates just a local 'buzz' with
no tangible outcome. Also, very little is known about what micro-level mechanisms
lead to the evolution of networks that can promote processes of economic develop-
ment. Evolutionary economics seems to me to constitute the right conceptual approach
through which these issues can fruitfully be explored in the future.
Notes
1. A 'cluster' is dei ned here as a geographical agglomeration of i rms operating in the same industry, in line
with the dei nition given by Humphrey and Schmitz (1996), among others.
2. In this respect, Camagni (1991) argues that 'a link-up with a i rm located in Silicon Valley is more a link
with the Valley itself than with a special i rm, with which if otherwise located, no agreement would prob-
ably be made' (p. 140).
3. In ef ect, most of the literature has paid attention more to the ef ects of networks on i rms, than the
reverse - as suggested in Giuliani and Bell (2005).
