Geography Reference
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3. Networkef ects on organizational performance
The ef ect of networks on the performance of organizations is a second key question in
(innovation) network research. Generally, the ef ects of having networks relations are
positive. Most studies i nd a positive relationship between the number of network rela-
tions of a i rm and its performance (see Ozman, 2009 for an overview). The same holds
for informal social networks as, for example, evidenced by the i nding that social net-
works between two people signii cantly increase the probability of knowledge spillovers
(Breschi and Lissoni 2003, 2006). At the more aggregate level of regions in the European
Union, the impact of collaboration networks on regional innovative performance has
been analysed by explaining the number of patents by knowledge inputs weighted for
the number of collaborations existing between the regions. The results show that the col-
laboration networks between regions indeed provide access for a region to the scientii c
knowledge in other regions (Hoekman et al., 2008; Maggioni et al., 2007).
The ef ect of networks on performance has been further elaborated by distinguishing
between dif erent types of knowledge. Sorenson et al. (2006) analysed US patent data
and citation rates across proximate and distant actors on three dimensions of proximity:
(1) social proximity (concerning distance between inventors in a network of patent col-
laborators); (2) geographical proximity (spatial distance between inventors); (3) organi-
zational proximity (i rm membership). They came to the conclusion that the advantages
of being geographically proximate to some knowledge source depend crucially on the
nature of the knowledge at hand. With respect to simple knowledge and very complex
knowledge, the results show that more close actors are not in a more advantageous posi-
tion, as compared to more distant actors. Simple knowledge l ows equally to actors near
and far, while complex knowledge is unlikely to dif use, no matter how proximate actors
are. With knowledge of moderate complexity, however, the outcomes show that more
close actors are in a better position to benei t from knowledge dif usion, in contrast to
more distant recipients.
However, these results should not be taken to mean that any network relation will
have a positive ef ect. Each network relation comes at a cost, both in its establishment
(search, negotiation) and its maintenance (conl ict, monitoring). In the context of inno-
vation networks, a particular risk in networking is the risk of involuntary knowledge
spillovers through which valuable knowledge leaks to other organizations. Conl icts may
arise as well. The main rationale of agents to share information and knowledge is that
they expect such favours to be reciprocal. Once an agent persistently fails to reciprocate,
the network linkages will become unstable, and will not deliver any positive ef ects. In
addition to that, too much proximity between agents in networks may lead to lock-in
situations (Boschma, 2005). Excess cognitive proximity reduces the scope for learning
(Nooteboom, 2000). Two people or organizations with the same knowledge have little
to exchange. Knowledge creation often requires dissimilar, complementary bodies of
knowledge, especially in the context of radical innovations. Cognitive proximity also
increases the risk of involuntary knowledge spillovers, especially when the new knowl-
edge cannot be fully appropriated. With respect to social proximity, socially embedded
relationships may lead to excess loyalty such that an agent puts their friends' interests
before their own (Uzzi, 1996). Moreover, long-term relationships, or too much commit-
ment may lock members of social networks into established ways of doing things, which
may be harmful for learning.
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