Tijdschrift voor Economische en Sociale Geografie Paper accepted for publication in TESG 100 Special Issue on Networks and Economic Agglomerations Metropolitan Regions in the Knowledge Economy: Network Analysis as a Strategic Information Tool i Authors Arno Brandt Claudia Hahn NORD/LB Regional Economics, Hannover Stefan Krätke Chair of Economic and Social Geography European University Viadrina, Frankfurt/Oder Matthias Kiese (corresponding author) Department of Geography Ludwig-Maximilians-Universität München Luisenstr. 37 D-80333 München [email protected]
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Tijdschrift voor Economische en Sociale Geografie
Paper accepted for publication in
TESG 100 Special Issue on Networks and Economic Agglomerations
Perhaps the main practical drawback of network analysis is that it is a rather expensive
information tool. Political vision and long-term leadership is thus needed to commit
resources not only to network analysis, but especially to the ensuing strategy develop-
ment and regional network management. In our case study region, it still remains to be
seen if our rich informational foundation will translate into a proper knowledge man-
agement strategy. As a final word of caution, occupation with the co-operative “network
paradigm” must not blind us to overlook competition as an important alternative source
of knowledge spillovers (Porter externalities, cf. Glaeser et al. 1992, pp. 1127 f.).
Our exercise highlights the potential of network analysis as a strategic information tool
for regional knowledge management. This methodology offers more detailed insights
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into regional network structures than the conventional analysis of regional innovative
potential as applied, for instance, by the European Regional Innovation Survey (ERIS)
in the late 1990s (cf. Sternberg 2000). While ERIS only measured ordinal intensity of
co-operations by scale and type of partner, our network analysis goes one critical step
further in disclosing co-operative linkages and measuring network parameters. How-
ever, network analysis also has its drawbacks and limitations as it hinges on the individ-
ual respondent’s limited information and subjective judgement. It can only approximate
the existence and intensity of actual knowledge flows; more in-depth case-study re-
search is needed to assess the magnitude and impact of the phenomenon, but also to
explain the reasons underlying the different network properties between the various
fields of competenceiv. Furthermore, a well-founded approach to regional knowledge
management would need more insights into obstacles to co-operation. Network defi-
ciencies uncovered in our network analysis do not necessarily mean that their removal
might lead to improved knowledge circulation; they may equally be a consequence of
an excessively heterogeneous knowledge base that might call for a finer delineation of
fields of competence. After all, our empirical exercise can only provide a snapshot of
network relationships, while secondary network analysis of patent data has already pro-
vided some insight into the evolution of narrowly defined networks of innovators. As
Glückler (2007, p. 631) points out, networks are not ends in themselves, but a means of
facilitating innovation and growth. This critical transmission between means and ends
thus remains yet another unresolved challenge that is likely to keep scholars busy for
some time to come.
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i Funding from the Metropolitan Region of Hannover-Braunschweig-Göttingen-Wolfsburg is greatfully acknowledged. The authors would like to thank Hans-Martin Zademach and three anonymous reviewers for helpful comments on an earlier draft of this paper. The usual disclaimer applies. ii Some non-response is commonly considered tolerable since each link should ideally be mentioned by both of the partners involved (reciprocation, cf. ter Wal & Boschma 2008, p. 9).
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iii As a portmanteau of mechanics and electronics, the term mechatronics denotes the fusion of convergent technologies in mechanical, electronic and computer engineering. iv The patent-based network analysis by Fleming & Frenken (2006) may serve as a good example for the bridging of quantitative and qualitative methods in regional network analysis.