Abstract
The present paper analyzes development patterns in research networks and technology as well as their co-evolution by the example of the currently highly transformative German automotive industry. We therefore introduce a consistent network-based approach for measuring change in research networks and the technological composition of patents. Our results show that the applied method is particularly useful for identifying structural similarities and main structural changes in research and patent networks. Further, the investigation of the co-evolutionary processes indicates that, regarding the German automotive industry, changes in technology lead to structural changes in the research network.
Highlights
Change and dynamics in both research networks and technology are highly relevant research fields in innovation economics
There is a large number of empirical studies on measuring technological change, using a broad spectrum of approaches ranging from patent counts (Archibugi and Planta 1996) over citations (Verspagen 2007) to the analysis of keywords in documents
Currently existing network indicators tend to only depict specific aspects of the network structure and barely the network as a whole, making it difficult to look at its general structural development. This has consequences on a possible comparing view between technology development and network dynamics, as we need a deep insight into innovation system dynamics to understand technological change (Hekkert et al 2007)
Summary
Change and dynamics in both research networks and technology are highly relevant research fields in innovation economics. There is a large number of empirical studies on measuring technological change, using a broad spectrum of approaches ranging from patent counts (Archibugi and Planta 1996) over citations (Verspagen 2007) to the analysis of keywords in documents Currently existing network indicators tend to only depict specific aspects of the network structure and barely the network as a whole, making it difficult to look at its general structural development. This has consequences on a possible comparing view between technology development and network dynamics, as we need a deep insight into innovation system dynamics to understand technological change (Hekkert et al 2007)
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