Geography Reference
In-Depth Information
'glue'. Our study doesn't distinguish between these two concepts in the empirical survey.
However, we report these dei nitions because it's important to underline that, in the
context of this survey, social dynamics are always a fundamental dimension in the
evolutionary economic geography perspective. In our opinion, the interconnectedness
between knowledge l ows and trust relationships can't be ignored in the study of evolu-
tion of routines within districts/clusters.
According to Glückler (2007), the relation between geography and networks can
be studied in two main ways. First of all, proximity af ects network formation. The
association between district area and local network is not unidirectional: proximity
does not constrain network formation. Networks should also embrace external agents,
but social interactions should create a partial overlap between network and district
boundaries (Storper and Walker, 1989). Second, the i rm's position in the network
structure makes a dif erence. This chapter focuses especially on this statement. In order
to estimate the impact of network structure on the formation of patterns of social
interactions and on reputation distribution, it is important to evaluate the position of
each actor within the local cluster in terms of structural properties. Each actor can be
studied by mapping the social network structure and adopting some indicators, such
as relational centrality, closeness, inter-position degree, and so on (Kilduf and Tsai,
2003). On the other hand, network structural indicators are closely connected to other
ones (Kilduf and Tsai, 2003; Krackhardt, 1990) and the parallel analysis of correlation
with other factors - such as trust and reputation - is very complex and mutually inter-
dependent. Our study focuses on the dimension of relational centrality, even though
we are aware that other important dimensions exist, i gured by alternative structural
indicators. Having a good degree of centrality within the network means, for instance,
having good access to critical information, which is an important source of organiza-
tional power (Daft, 2001).
Our study aims at adding more elements to this debate with a focus on the system of
relations among three dimensions:
1. the centrality of nodes in the network structure;
2. the one-to-one trust relation;
3. the i rm's reputation as dei ned above.
Within a local network, the stock of knowledge can be shared among many i rms, cre-
ating a spread phenomenon capable of inl uencing the whole network, which can change
the reputation of many i rms involved in the network. Many authors argue that reputa-
tion is, above all, the result of complex interactions among i rms (Dentchev and Heene,
2003; Fombrun, 2001). Based on the conceptual background outlined in section 2, all the
dyadic trust relationships across local network nodes inl uence the reputation degree of
the i rms involved in the local network. The direct correlation between reputation and
trust and their impact on inter-organizational structure is signii cant and coni rmed by
the literature (Elangovan and Shapiro, 1998; Ely and Valimaki, 2003). For example, the
willingness to avoid gaining a bad reputation reduces opportunistic behaviour in the
estimated long-period relationship between two actors.
Every node is analysed in terms of four variables: centrality, relational reputation,
competence-based reputation, and economic performance, which allowed us to estimate
