Abstract
This chapter surveys the topic of Research and Development (R&D) collaboration networks which has attracted burst of attention in the last decade, both in the scientific study of such networks, and in the policy sector. In Regional Science, specific interest has been devoted to the investigation of the spatial dynamics of such networks crossing regional boundaries. Here, one fundamental consideration is that a region´s innovative capability is, on the one hand, strongly related to solid region-internal collaboration networks as main vehicle for diffusing knowledge within the region. On the other hand, it is assumed to be increasingly depending on collaborations with actors located in other regions to tap important region-external knowledge sources for enriching the regional knowledge base. Empirical research on such networks has been largely developed at the regional level of analysis within Europe, stimulated by the introduction of the European Framework Programme (FP) on Research and Technological Development aiming to support such networks. Empirical studies typically use concepts and definitions from graph theory to describe such networks and to investigate their properties, and adopt a spatial interaction modeling perspective to explore their geography. In the latter context, special emphasis is put on the identification and estimation of barriers to collaboration, such as geographical distance, but also technological, cultural or institutional effects that may hamper R&D collaborations between actors located in different regions.
Original language | English |
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Title of host publication | Handbook of Regional Science |
Editors | Manfred Fischer, Peter Nijkamp |
Publisher | Springer |
Pages | 1-19 |
Number of pages | 19 |
ISBN (Print) | 978-3-642-36203-3 |
DOIs | |
Publication status | Published - 2019 |
Research Field
- Innovation Dynamics and Modelling
Keywords
- R&D collaborations
- regional knowledge production
- innovation
- cross-region knowledge flows
- spatial networks
- spatial interaction
- network analysis