1. Contrasts in Biotechnology and ICT Clustering: a UK Study Prof. Phil Cooke Centre for Advanced Studies & CESAGen, Cardiff University

2. Economic Geography & Spatial Knowledge (Quasi-) Monopoloy  Economic success and failure often related to agglomeration – Krugmanesque  Agglomerations caused by knowledge asymmetries – Akerlofesque  Increasing returns to tacit knowledge key to agglomeration – Polyaniesque  Clusters are knowledge markets – M&Mesque  Clusters are actually spatial knowledge (quasi-) monopolies – the Cookesque hypothesis

3. Increasing Knowledge Returns….from Corporates….to Clusters?

4. From Open Science to Open Innovation Through R&D Outsourcing  R&D Outsourcing Now Prolific  To Talent/Knowledge Quasi-Monopolies  Atlantic-Nordic NW Europe Belt (IBM map…R)  South & East China (IBM map…D more than R)  South India (d more than R)  The Coasts in US (R)  Then, Hotspots in Canada, Australia (R or R&D)

5. Regional Knowledge Capabilities: the Heart of the Regional Innovation System

6. Questions Posed  What are key motivations for clustering?  To what extent is ‘distant networking’ important?  Specifically, what aspects of proximity are key for Biotechs?  In what ways do ICT firms differ regarding proximity motivations & practices?  Do Biotechs and ICTs perform better in clusters?

7. Biotech & ICT  Biotech sample size 156 firms. Response rate 20% (32).  ICT sample size 7,600. Response rate 3% (270) Date of EstablishmentFrequencyPercentageBiotechs <1947830 1948-19701660 1971-19802493 1981-19906926 39 1991-19991244747 2000-20032391

8. Comparative Indicators

9. Comparative Partnership

10. Proximity

11. Comparative Performance

12. Conclusions  Biotech & ICT Clustering is Different  Biotechs Cluster for Research Knowledge  Biotechs Use Distant Networks for Innovation  ICTs Use Proximity for Innovation, especially National Supply Chains  ICTs do Not Particularly Seek Proximity for Research  Both Perform Better If Collaborating