Network Analysis Application in Innovation Studies
Special Issue of Innovation: Management, Policy & Practice
Volume 12 Issue 1 April 2010
120 pages ISBN 978-1-921314-32-7
Editors:
John Steen and Tim Kastelle
University of Queensland Business School
Queensland, Australia
The innovation literature has a long-held tradition of using networks to understand processes of idea generation, opportunity recognition and the diffusion of knowledge. Arguably, the most dominant use of the network construct in the innovation research context is in its qualitative or metaphorical sense. For example, a study might interview a manager and ask them how important their professional network is for generating new ideas.
While this has been a productive line of enquiry, new analytical techniques in graph theory (the quantitative analysis of networks) are only just starting to be applied to innovation research. From this research we have begun to understand the importance of network structures and the relationship between agents and these structures in the process of innovation.
Initial work in this area has focused on specifying the structure of business networks. For example, there have been several papers identifying networks with a 'small world' structure (short average distance through the network combined with high levels of clustering). More recent work has started to link structural characteristics of networks to innovation performance.
As network analysis has moved forward, sophisticated techniques in probabilistic network methods, weighted network and longitudinal network analysis have created further possibilities for understanding the interactions between network structures, agents and innovation across multiple levels of analysis.
We are seeking original papers that use graph-theoretic approaches to innovation research. While preference will be given to empirical papers, insightful reviews and conceptual pieces will also be considered. All interesting applications of complex network analytics to innovation topics will be considered. Some possible topics include:
- How do innovation networks evolve?
- What is the impact of network evolution on innovation performance?
- Are intra-firm innovation networks different from inter-firm networks? If so, how? What impacts does this have on the innovation process?
- What causal factors drive the growth of innovation networks?
- Does network structure constrain or enable change within the network? How do individuals respond to these constraints or opportunities?
- How do innovation networks interact with geography? Can the structure of innovation networks provide insight into issues such as industrial clustering?
- Are there differences in the network structures across industries or countries?
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