Transcript Universities and Knowledge Clusters:

Universities and Knowledge Clusters:
Necessary but not Sufficient
Henry S. Rowen
Stanford Program on Regions of Innovation and Entrepreneurship
Professor emeritus
Stanford University
Cesaer Seminar| Norwegian University of Science and Technology | Trondheim | October 15, 2010
Five Major Developments that have Profoundly
Affected the Location of Knowledge-Intensive
Activities
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Moving information => cost nearly zero
Cost of moving goods => much reduced
Talent in Asia => better educated
Opening of Asian economies
Increased cross-border links
Knowledge-Intensive?
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Not only breakthrough knowledge creation
Also, advances within paradigms
Process knowledge: Toyota Just-in-Time
Importance of domain knowledge; e.g. health
services, legal services
• Software has been driving hardware
Why Clusters?
•
Alfred Marshall’s agglomeration economics:
- thick labor market
- specialized input producers (with increasing
returns)
- localized knowledge spillovers
• Most form via market; some initiated by government
(not always successfully)
Knowledge Clusters
Top-down versus Bottom-up
• Top-down: All those in Asia except India
• Bottom-up: US, UK, India
• Success = value-added
• High value-added: Indian software and
Taiwanese hardware; low in China’s
manufacturing (iPod: $150 vs $4) -- but good
enough
Taiwan’s Hsinchu Science-based Industrial Park
• Arguably, best government-sponsored cluster
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Two major universities, then ITRI, then Park
Develop and spin out technologies/firms: (chip foundries
UMC, TSMC) or hand to existing firms.
Politics favored smaller firms (Korea, the opposite)
Core knowledge (making chips, flat screens, batteries,
computers) went from manufacturing, to design, to
brand names (Acer, HTC)
Strong links with US (education and companies), and
to China (manufacturing and, increasingly, market)
China
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Regions in “Torch” program: notably, Zhongguancun Science Park (ZGC)
in Beijing, also in Shanghai, Shenzhen, Chengdu, Xian, Hangzhou, etc
Huge talent pool, foreign investment, universities expanding and
improving, foreign ties, Valley VCs, state-owned & private firms.
Universities close to commerce (too close); science parks, e,g, Tsinghua
Holdings Company, an arm of Tsinghua University.
ZGC: Seven parks, 12,000 high-tech firms, some major homegrown (e.g.
Lenovo), multinationals, 0.5 million tech people. Being in the capitol
helps with politics but not creativity.
China’s quest for “Independent Innovation.” Dispute over top-down vs
bottom-up); a question of the mix.
No breakthrough technology yet; catching-up rapidly in existing ones
Dubious Experiences with Science Parks
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Importance of what is inside them
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Need science + ecosystem
Tsukuba Science City: not entrepreneurial
Daejon, “Korea’s Silicon Valley” (not exactly)
North Carolina’s Research Triangle Park: ~ 70
companies with 42,000 professional workers; three
good/decent universities; a moderate success
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Wallsten: no correlation in US between science parks and
employment or venture capital
The Dubious Experience with Science Parks (cont.)
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Russia. President Medvedev: a new “Silicon Valley in Russia,”
saying:
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Bureaucracy and corruption as large obstacles
A new region (Skolkovo) with special rules:
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Exempt from major taxes
Focus on energy, information technologies, communications, biomedical
research and nuclear technologies.
Two Nobel Prize winners. A Russian: "I think that if in the final analysis there
are not two, three, four Nobel Prize laureates working in this city, it would
mean we did not achieve our goal.”
Good to have great scientists but some very successful ones, such
as Hsinchu, Bangalore, Seoul, have few
University?
Why India’s Bottom-up Success?
• Cost of moving bits of information nearly to zero
• Smart people with good (mostly BS) education and low
wages
• Foreign linkages, initially the US, then widely.
• During the “Permit Raj,” bureaucrats blocked the
imports of goods, including computers, but had trouble
blocking bits of information.
• Domain knowledge (back-office operations, health
systems, tax systems) was acquired.
Israel
• Successes
• Immigrants
• Linkages; widely, including the Valley; from 2003,
foreign funds; 55%-70% for startups
• Unique role of army in preparing elite; high-tech
military
• Government: At first startup unfriendly, then
supplied venture capital, then system became more
market-determined
• Excellent universities
Silicon Valley Ecosystem
• 100 years old (counting radio and vacuum tubes)
• “Silicon” from Bell Labs in the 1950s => a cascade of
semiconductor companies => computer ones => software =>
supporting soft infrastructure;
• Biotech, clean tech
• Eco-system: Universities, risk capital, lawyers, accountants,
expert consultants.
– Risk capital: angels, VCs, non-traditional banks
– Immigrants: ~ 50% of Valley patents 1985-2005 foreign born names
– Increasing foreign links
The early team at Tensilica: 1997-1998
>80% through personal networks
Bold
the first 15
green italics
key advisors
Stanford
Peter Nuth
John Hennessy Monica Lam
John Ruttenberg
Andy Bechtolsheim
Bob WilsonWoody Lichtenstein
Steve Tjiang
MIPS/SGI
Earl Killian
Ashish Dixit
Dror Maydan
Pavlos Konas
Gulbin Ezer
Ricardo Gonzalez
Berkeley
Richard Newton
Marines Souza
Keith Van Sickle
Kaushik Sheth
Nupur
Kurt
Keutzer
Pete
Bandel
Bhattacharyya
MacLeish
Canano
James Wei
Beatrice Fu
Albert Wang
Harvey Jones
Steve Roddy
Dave
Jorge del Calvo
Greenberg
Ranga Srinivasan
Bernie Rosenthal
Verly Flores
Dhanendra Jani
Synopsys
Intel
Masumi Takahashi
Copyright
\ - \\Copyright
© 2009,©Tensilica,
2009, Tensilica,
Inc.
Inc.
John Seely Brown on Knowledge in
the Valley
Brown: “…there is a high level of knowledge in firms
in the Valley… and also a very high level of
knowledge about the firms…..Inevitably, much of
this is also evident from outside the Valley. What
seems to be less evident from outside is any idea
of what's missing or what's coming: where the
new opportunities, the "next new thing," is likely
to come from..”
Still More on Silicon Valley
• Entrepreneur Jerry Kaplan, on handheld devices:
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PenPoint computer of his Go Corporation in 1980s (failed)
Apple’s handheld device, the Newton (failed)
Palm’s Palm Pilot (succeeded)
Microsoft’s tablet (failed)
Apple again tried with the iPad (a big hit).
• One can fail and be funded again (depending); Kaplan has
another startup.
– Proverbs, 1611: “for a just man falleth seven times, and riseth
up again.”
• Maybe Valley VCs wouldn’t fund someone with six failures,
but one or two are not necessarily fatal.
Some Silicon Valley Negatives
• High land prices, often mentioned, come from
success (and climate)
• More serious is poor public schools
• Dreadful condition of California government
(which eventually might hurt the Valley)
Universities And Knowledge Clusters
On their Insufficiency:
• US examples: high quality ones in the Mid-West: e.g.
Michigan, Wisconsin, Minnesota, Illinois without high tech
clusters. Carnegie-Mellon has an excellent computer
science department but Pittsburgh has few computer
companies
• Minneapolis versus Palo Alto winters.
• Regions lacking specialized services, venture capitalists and
lawyers, accountants, consultants.
• A favorable, perhaps accidental, event starts a process with
positive feedbacks. Once developed, other places find it
difficult to compete.
• But new technologies can have different properties
Universities And Knowledge Clusters
On Their Necessity:
• US major regions have excellent universities –
that encourage entrepreneurship: the Valley,
Boston, San Diego, Austin.
• San Diego. UC campus in 1960; within 25 years, a
major biotech region and a computer one. UCSD
played a key role in fostering companies and local
government helped.
• Timing and location were perfect.
Asian Universities And Clusters (1)
Japanese: Too remote from commerce
• R&D is mostly done in the companies - with
hierarchical structures, little worker
movement, and few new firms
• Many excellent universities but little
technology or companies come out. Faculty
consulting
• Until 2004, Japanese faculty in the national
universities (about 100) were civil servants.
Habits change slowly.
Asian Universities And Clusters (2)
Chinese: Too close to commerce
• Earlier, research in Academy of Sciences without teaching
mission nor links to commerce. “40,000 products with none
reaching the market”
• Universities destroyed in the Cultural Revolution; then low
pay
• Pressures for results in a system without a high regard for
intellectual property protection
• Conditions improving: excellent students and increasing
research support for faculty
• More world-class science; there will be great universities; and
knowledge clusters will become stronger – but not tomorrow
Asian Universities And Clusters (3)
India: The marginal case for the necessity of
universities
• Earlier, the IITs and the IIS produced talent and
the talent produced companies, largely in the
same cities
• Most research had been done in national
laboratories
• Now, IITs are doing research, potentially with
commercial use
Industries vary in distance from
science, hence from universities
• Most of it is remote from scientific origins (semiconductors,
Internet, reduced instruction set software, etc.)
• In contrast, biotechnology firms remain close to scientific
roots
• Personal linkages. Zucker, Darby and Armstrong:
“collaborations between academic stars and firm scientists …..
[provide] direct evidence of a large, significant impact of
academic research on local industrial development.” The
scientists stay at their universities while working with their
companies
• VCs want companies close by but often scientists win. So
biotech is more widely distributed than IT
• Clean technologies. Some, such as wind, are remote from
science; but photo-voltaics need scientific advances
Universities: Don’t Count on Making
Money from Research
• Not a mission. Anyway, few universities succeed.
• In 2008, the total income in U.S. from licensing was $3.4
billion; only six got over half.
• 198 licenses generated >$1 million in income out of 15,498
licenses with income. For 84 percent of academic institutions
(in 2006), technology transfer was a net cost.
• University TLOs -- rightly-- say they have a social mission to
transfer technology to society.
• Academic standards first; then, entrepreneurship among
faculty and students
Engineering Education: Stanford
• Stanford’s Dean of Engineering
– “T”–shaped people
– Deep education + creativity, entrepreneurship, manydiscipline problems
– Learn to work in teams
– Need to keep learning
• "Breadth” got School in trouble with accreditors –
but it survived
• The Dalai Lama’s values
Scientific articles and co-authorship, 1998 and 2008
Bubble size= # of scientific
thickness of links=intensity of
collaboration, i.e. co-authorship.
Source: MEASURING INNOVATION: A NEW PERSPECTIVE
© OECD 2010
Scientific articles and co-authorship, 1998 and 2008
Bubble size= # of scientific
thickness of links=intensity of
collaboration, i.e. co-authorship.
Source: MEASURING INNOVATION: A NEW PERSPECTIVE
© OECD 2010
Trajectories
• New ideas are always needed. Clean tech and synthetic
biology are the latest hot ones; something else might
come along.
• China and India. They know how universities should
work and need to adopt them in practice.
• Returnees help
• Cross-region linkages will get only more important
Venture Capital Investments by Industry/Q2 2010
% of total
deals
19.89
139
19.68
61
15.88
229
11.59
95
6.35
71
4.93
91
3.77
31
3.16
31
2.69
23
2.63
17
2.34
27
2.17
21
2.04
16
1.44
30
0.70
7
0.58
10
0.17
7
Data from MoneyTree Report
Venture Capital Investments by Region/Q2 2010
% of total
deals
44.74%
276
10.54%
67
8.93%
95
5.85%
93
4.75%
51
4.53%
69
3.80%
44
3.46%
47
2.90%
39
2.62%
24
2.26%
16
2.00%
20
1.72%
25
0.78%
15
0.66%
8
0.21%
5
0.13%
2
0.10%
9
0.03%
1
Data from MoneyTree Report
Patents per million inhabitants, Europe, average 2005-07
Source: MEASURING INNOVATION: A NEW PERSPECTIVE
© OECD 2010
The Mobility of People and the
Importance of Immigrants
• Foreign born people have been essential
• Students from China and India mostly stay; those
returning carry valuable know-how. Win-win.
• About one-half of first-named people on Valley patents
from 1985 to 2005 were born abroad
• Mobility high in US, low in Japan and Korea
• 2001: 120,000 software workers in India on US
projects