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Robert Huggins and Daniel Prokop Centre for International Competitiveness, Cardiff School of Management, University of W

Universities as Knowledge Network Nodes: Key Institutional and Industrial Players. Robert Huggins and Daniel Prokop Centre for International Competitiveness, Cardiff School of Management, University of Wales Institute, Cardiff

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Robert Huggins and Daniel Prokop Centre for International Competitiveness, Cardiff School of Management, University of W

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  1. Universities as Knowledge Network Nodes: Key Institutional and Industrial Players Robert Huggins and Daniel Prokop Centre for International Competitiveness, Cardiff School of Management, University of Wales Institute, Cardiff Presentation at the ‘Making An Impact – Universities and the Regional Economy’ Conference London, 4th November, 2009

  2. Objective • The aim of the presentation is to analyse the knowledge and innovation links between UK universities and large industrial R&D performers located in the UK. • We seek to address the following questions: • Which universities possess the most developed knowledge networks with large industrial R&D players? • Which industrial players possess the most developed knowledge networks with the UK higher education sector? • Do these links impact on the performance of universities as research and knowledge commercialisation institutions? • What are the spatial patterns in terms of the regional dimensions of university links with large R&D performers?

  3. Context • Universities are increasingly viewed as key institutions in the regional economic development process and are often described as central nodes of the knowledge-driven economy. • University knowledge is increasingly viewed as almost a panacea for promoting knowledge-based economic development. • In general, universities are portrayed as forming important actors within networks of regional clusters of knowledge-based activities or systems of regional innovation. • Within the systemic view of innovation, regions are considered as ‘laboratories’ providing the crucial knowledge infrastructure for innovation. • However, although local knowledge sources are utilised in the innovation process, global (or at least ‘non-local’) knowledge pipelines are also considered to be of growing importance to innovation.

  4. Research Method • Preparation of a database of organisations – and their location - (public and private sector) that had ‘knowledge links’ with UK universities between 2005-2008. • Knowledge links defined as activities relating to: collaborative research; contract and consultancy research; patenting, licensing, and spin-outs. • Data principally collected from university documentation: annual reports; research reviews’ technology transfer reports; research and enterprise web pages. • Database of c. 10,000 organisations and their location prepared. • Analysis of database to identify those organisations listed on the UK government’s “The 2008 R&D Scoreboard: The Top 850 UK and 1400 Global Companies by R&D Investment”. • Approximately 450 companies in our database were listed on either the UK or Global R&D investment list.

  5. UK University Links with Large R&D Performing Firms (Top 20)

  6. Large R&D Performing Firms Links with UK Universities (Top 20)

  7. UK University Links with Large R&D Performing Firms by Region (University Location)

  8. Regional Location of R&D Performing Sites of Large R&D Performing Firms with Links to UK Universities

  9. % of Links With Large R&D Performers Based Outside the Region of Location (Top 20 Universities)

  10. UK University Links with Large R&D Performing Firms Within and Outside Region of Location

  11. Sector Breakdown of Large R&D Performing Firms with Links to UK Universities (R&D Investment)

  12. Total R&D Investment of Partners Linked with UK Universities (Top 20 Universities)

  13. Factors Associated with University Research and Knowledge Transfer Income (** Correlation is significant at the 0.01 level (2-tailed))

  14. Conclusions • There are strong knowledge links between leading research-intensive universities and leading industrial R&D performers in the UK. • These links benefit both players through a greater capacity to innovate and commercialise knowledge: • Those universities with a greater number of links to large R&D performers have significantly higher levels of research and knowledge transfer income compared to those with less links. • Those firms with the greater number of links to high research income universities invest more in R&D. • There is a strong regional pattern to these knowledge links: • Leading research universities in the Greater South East are better ‘placed’ to establish links with the relatively high number of industrial R&D performers located in close proximity, i.e. within the same region. • Universities in less competitive regions do not have the same density of R&D performers in close proximity, with which they can potentially forge links. • Universities in less competitive regions are ‘forced’ to cultivate links with R&D performers based at a relative distance to their own location.

  15. Conclusions (2) • Less competitive regions are generally compromised by universities that are less research intensive (on the whole) and less linked to industrial knowledge bases than their counterparts in the GSE. • Although much university knowledge transfer policy is based on establishing links with SMEs, it is clear that links with the ‘big ticket’ large R&D performers are closely connected with university performance.  • There is a clear need to better articulate policies aimed at improving the knowledge bases of relatively lagging regions.  • Clearly, the movement of knowledge infrastructure across regions is not a feasible option. • This suggests that better connecting knowledge bases across regions – both in the UK and globally – provides a more realistic option.

  16. Thank You

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