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Erschienen in:
Innovation Policy and High-Tech Development: An Introduction Kapitel lesen Erstes Kapitel lesen

2012 | OriginalPaper | Buchkapitel

7. The Politics of Innovation: Analysing Inter-organisational Networks Around German Innovation Policy Advisory Bodies

verfasst von : Matthias Orlowski

Erschienen in: Innovation Policy and Governance in High-Tech Industries

Verlag: Springer Berlin Heidelberg

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Abstract

As part of the High-Tech Strategy for Germany, the German Federal Government established the Council for Innovation and Growth (CIG) and the Industry-Science Research Alliance (ISA). Besides consulting with the government, these advisory bodies were designed to improve connectivity between industry, science, and politics. A systemic approach suggests that the bodies should preferably be staffed with representatives of various economic sectors and different societal subsystems to enhance the integration of the innovation system and to assure a balance of interests within the advisory boards. Based on an analysis of interlocking directorates that allows the operationalisation of relations between organisations, this chapter explores whether these criteria have been met in the constitutions of the two advisory bodies. Results indicate a preponderance of certain economic interests in the network. Furthermore, numerous links beyond CIG and ISA exist among the organisations participating in the three subsystems, which weaken the significance of the integrating function of CIG and ISA.

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Vorheriges Kapitel Innovation Switzerland: A Particular Kind of Excellence
Nächstes Kapitel Power Games in Space: The German High-Tech Strategy and European Space Policy
Fußnoten
1
According to German law, corporations exceeding a certain number of employees are obliged to install an advisory board which monitors the board of directors.
 
2
The affiliation matrix X has all persons of the dataset in the first column and all organisations in the first row. Cells indicate the affiliation of a person with an organisation by 1 and contain 0 otherwise. The multiplication of the transposed matrix X’ (that is the same matrix but with organisations in rows and persons in columns) with X results in a so-called adjacency matrix that has all organisations in rows as well as in columns. The cells of this affiliation matrix indicate the number of shared board members (the intensity of their connection). See Wasserman and Faust (Wasserman and Faust 1994) and Faust (Faust 2005) for details on this procedure.
 
3
It is not plausible that the communication between two organisations increases proportional to the number of shared board members. Therefore, the intensity of connections (the number of shared members) is not interpreted here. Furthermore, since an interlock is only considered as a channel of communication without stating whether organisation A communicates with B or vice versa, links are considered undirected. All that matters here is whether a connection exists (indicated by 1 in the adjacency matrix) or not (indicated by 0).
 
4
Two independent coders were asked to assign all organisations to the 19 categories of the variable branch. Intercoder reliability according to Perreault and Leigh (Perreault and Leigh 1989) was high. It was 0.99 for the coding of “purpose” and 0.98 for “branch”.
 
5
The technology intensity of particular branches was derived from the ratio of research and development expenses to production output and value added within the particular industries, according to the OECD’s classification of industries based on technology (OECD 2005).
 
6
The network’s density d is the share of realised links L (here: observed interlocks) in all possible links between all nodes (here: organisations) in a network. Since the connections are considered unweighted and undirected, the maximum number of links is given as g(g-1)/2 where g is the number of nodes in the network. Therefore d = 2L/g(g-1) (Wasserman and Faust 1994).
 
7
Path length is the number of links on the shortest connection between two nodes in a network.
 
8
The block model simply sorts the nodes of the adjacency matrix according to a variable that provides information about nodes’ characteristics. One can thus analyse the network components that only consist of nodes with the particular characteristic used to “block” the model or those parts of the network that link different blocks.
 
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Metadaten
Titel
The Politics of Innovation: Analysing Inter-organisational Networks Around German Innovation Policy Advisory Bodies
verfasst von
Matthias Orlowski
Copyright-Jahr
2012
Verlag
Springer Berlin Heidelberg
Buch
Innovation Policy and Governance in High-Tech Industries

Print ISBN: 978-3-642-12562-1

Electronic ISBN: 978-3-642-12563-8

Copyright-Jahr: 2012

DOI
https://doi.org/10.1007/978-3-642-12563-8_7

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