1. LONDON CALLING: FIVE BASIC QUESTIONS ABOUT CLUSTERS MERIC S. GERTLER Department of Geography & Munk Centre for International Studies University of Toronto Presented at the Annual Meeting of the Innovation Systems Research Network, Toronto, Ontario May 5, 2005

2. CLUSTER DEVELOPMENT IN THE KNOWLEDGE ECONOMY Popular misconceptions abound Today: my own ‘top 5’ questions Evidence: 3 strands of research –Transfer of knowledge, practices across geographical, cultural/institutional divides –Canadian national cluster study: studying the transition to more knowledge-intensive production –Creative city-regions: Canada, US, Europe

3. 1. CIRCULATING KNOWLEDGE: IS ALL KNOWLEDGE LOCAL? GLOBAL? Cluster literature: implies the former Recall ‘Porter Diamond’…

4. 1. CIRCULATING KNOWLEDGE: IS ALL KNOWLEDGE LOCAL? GLOBAL?

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7. 1. CIRCULATING KNOWLEDGE: IS ALL KNOWLEDGE LOCAL? GLOBAL? Cluster literature: implies the former Global production systems literature: implies the latter –Knowledge circulation through communities of practice, epistemic communities The truth is likely somewhere in between –Knowledge of customers, competitors: not necessarily local –Knowledge that comes with capital (VC): local and interregional flows

8. WHAT REMAINS LOCAL IN THE GLOBAL ECONOMY? Local labour markets: becoming more important as loyalties shift from firm/industry to place/occupational communities Quality of place, broadly defined: anchors talented labour (hence firms) A venue for efficient circulation of specialized knowledge –Often, though not always, tacit –Intended and accidental –Importance of cultural, institutional similarity

9. 2. CAN WE ALL HAVE OUR OWN BIOTECH CLUSTER? The next ‘next big thing’ Is this realistic? Two views –‘Brookings’ view: big 5 (SF, Bos, SD, NC, Seattle) –Alternative view: bigger potential in downstream applications Perhaps public policy should emphasize diffusion, uptake instead of ‘blockbuster’ drug development Focus on niches that build on established strengths in the regional economy Is biotech ‘losing its nerve’?

10. 3. PRODUCING KNOWLEDGE: WHAT ARE UNIVERSITIES FOR? Knowledge factories or institutions of education and research? Expectations for ‘commercialization’: escalating dramatically New justification for public investment in HE: an historic break with past rationale Silver bullet for regional development? Realistic or wrong-headed?

11. RECENT RESEARCH: SURPRISING RESULTS Commercialization of university research: very few institutions make any significant money, even in US Even in city-regions with successful knowledge economies, universities do not always ‘lead the charge’ –ICT examples: Ottawa (Nortel, Newbridge); Waterloo (RIM) –Life sciences: open science, global ‘pipelines’ (vs. self- sufficiency) Broader, indirect contributions of universities to social well-being are still strong –Social returns to investment in HE equal or exceed private returns (~ 10-12 percent)

12. 4. SPECIALIZATION OR DIVERSITY? Cluster literature: implies specialization ‘Jane Jacobs’ models: benefits of diversity Specialization is risky: few regions can make it work Many of most dynamic regions have BOTH –A diverse portfolio of specializations –‘Old’ industries: basis for ‘new’ ones Can mid-size city-regions pursue such a strategy successfully? –Waterloo region: high-tech darling or diverse specialization? –Two Ontarios: GTA + mid-size S Ont centres, and ‘the rest’

13. 5. EMBODIED KNOWLEDGE: CAN WE ALL WIN THE BATTLE FOR TALENT? Talent attraction, retention (TAR) is the name of the game + : place-based strategies offer bottom-up opportunities for localities, city-regions + : induces city-regions to act on a city- regional basis

14. DARKER SIDE OF ‘TAR’ Some places: dim prospects for retention, let alone attraction Are places with ‘quality of place’ necessarily socially inclusive? In many cases, a TAR strategy is no substitute for an income/anti-poverty strategy The most dynamic creative city-regions are often ‘high-risk, high-return’ economies –Cost of living, risk of job loss: high –But earning potential, returns to educational investment: high –‘Risk-support infrastructure’ well developed – for some, not all

15. PUBLIC POLICY: A BALANCED APPROACH Talent attraction/retention + quality of place (and broader definition of ‘talent’?) Risk support infrastructure: inclusive Investment in ‘knowledge infrastructure’: broadly defined, all levels Investment in other infrastructure: transportation, water/sewer, other Realistic goals, building on established strengths

16. Thank you meric.gertler@utoronto.ca www.utoronto.ca/isrn meric.gertler@utoronto.ca