Geography Reference
In-Depth Information
This chapter is well embedded in the evolutionary economics literature because it consid-
ers i rm heterogeneity and selectivity as elements that strongly condition the nature of
development in regional clusters. In this sense it is intrinsically dif erent from previous
works in this i eld, where scholars have tended to emphasise the 'collective' nature of
inter- i rm interactions in clusters.
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This study i nds that knowledge networks, which are
formed by more selective mechanisms than business networks, tend to have strong but
unevenly distributed ef ects on the performance of cluster i rms.
The chapter is organised as follows: section 2 elaborates the conceptual framework.
Section 3 presents the data and the methodology of analysis. Section 4 reports and dis-
cusses the empirical results and i nally section 5 concludes and provides suggestions for
further research.
2.
What type of networks for what type of development?
Networks: an overview of the literature
Networks contribute signii cantly to learning processes, provide contexts for innovation, create
knowledge spillovers, facilitate information transfers between small and large-scale i rms, and
provide social infrastructure to accelerate technological change and industrial innovation.
Studies have demonstrated the role and importance of networks in a variety of economic con-
texts. (Murphy, 2003, p. 176)
Starting from the 1930s, the concept of networks has occupied a prominent place in
diverse i elds of research such as anthropology, psychology, sociology and molecular
biology. In the i eld of organisational behaviour, Roethlisberger and Dickson (1939)
described and emphasised the importance of informal networks in organisations,
and network analysis has become an academic discipline after the inl uential work of
Harrison White in the 1970s (e.g. White, 1970, 1992). Social networks are dei ned as 'a
set of nodes (e.g. persons, organisations, etc.) linked by a set of social relationships (e.g.
friendship, transfer of funds, overlapping membership of a specii c type)' (Laumann et
al., 1978, p. 458).
In the past two decades, networks have been increasingly studied in economics and
related i elds (e.g. regional studies, innovation studies, etc.), as also highlighted by
Smith-Doerr and Powell (2003). The 'relational turn' in economic geography does itself
centre around the concept of networks. At the end of the 1980s, following from Piore
and Sabel's (1984) l exible specialisation theory, networks became incorporated into the
various dei nitions of industrial agglomerations. For example, in 1988, Scott dei ned
industrial localities as:
agglomerations [of producers] that coalesce out of the dense networks of transactional interre-
lations that form as the social division of labour deepens and as particular groups of producers
are brought into intense and many-sided interaction with one another. (p. 31)
In a similar vein, Camagni (1991) dei ned the innovative milieu as 'the set, or the complex
network of mainly informal social relationships in a limited geographical area, [. . ..],
which enhance the local innovative capability through synergetic and collective learning
processes' (p. 3).
