S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering What Drives Innovat 1 What Should Drive an Innovation Strategy? Chuck Eesley (Stanford), Edward B. Roberts (MIT), Delin Yang (Tsinghua Univ.) Strategic Management Society October, 2009 (with support of a Kauffman Foundation Dissertation Fellowship, the Tsinghua Univ. Alumni Association, and the MIT Entrepreneurship Center)
Strategic Management Society Presentation Oct. 2009, Washington DC
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S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
t Driv
es In
nova
tion?
1
What Should Drive an Innovation Strategy?
Chuck Eesley (Stanford), Edward B. Roberts (MIT), Delin Yang (Tsinghua Univ.)
Strategic Management SocietyOctober, 2009 (with support of a Kauffman Foundation Dissertation Fellowship, the Tsinghua Univ. Alumni Association, and the MIT Entrepreneurship Center)
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
t Driv
es In
nova
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New Firms Undertake Search Activity
What enables (or constrains) the adoption of an innovation strategy?
Public R&D human capital, knowledge stock and the level of VC funding
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
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Two Solutions to More Innovation in Society
Pr(It=1) = (HAt At
)/ [1/(ρθAt)] (4)
(1) existing firms doing more innovation
(2) new firms are created, a higher percentage of these innovate
5
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
t Driv
es In
nova
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Public R&D Influence on Firm Search
H1: Grant based public R&D expenditures will (via indirect effects) result in greater knowledge spillovers and greater use of an innovation strategy (with a lag) H2: Grant-based public R&D expenditures will result (via direct effects in higher prices for research inputs) in lower use of an innovation strategy (contemporaneous)
H3: Grant or contract-based public R&D expenditures will result in more scientists/engineers becoming entrepreneurs with a lag.
H4: Venture capital funding will result in greater use of an innovation strategy. (Counter-hypothesis to hypothesis 1)
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
t Driv
es In
nova
tion? Ideal Experiment
Proportion of firms adopting an innovation strategy
t
Exogenous shift in H
Ait , Ait or C(Vit, i)
t
No shift
Proportion of firms adopting an innovation strategy
The effectiveness of government incubators, seed funding, …and other such policies for funding R&D deserves further study, ideally in an experimental or quasi-experimental setting. In particular, studying the cross-country variation in the performance of such programs would be desirable, because the outcomes may depend to a great extent on institutional factors that are difficult to control for using data from within a single country.
- Bronwyn Hall 2005
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
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nova
tion?
Merged MIT and Tsinghua Dataset
Similar educational background, academic talent (engineering)
– Patents (foreign and domestic)– Product/service available in the market 3 years ago
(China)– Importance of innovation, speed to market, low cost,
other factors Detailed fundraising data US and China data on public R&D expenditures,
publications and venture capital Sources: OECD Science and Technology Indicators, 2008;
Ministry of Science and Technology, China; China Statistical Yearbooks; SDC Venture Economics Database; Asian Venture Capital Journal; Dow Jones VentureOne; Thomson ISI
Inflation and Purchasing Power Parity conversion process
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
t Driv
es In
nova
tion?
Merged MIT and Tsinghua Dataset
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
t Driv
es In
nova
tion?
Industry Breakdown
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
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Capital and Lack of Ideas
Panel B – Factors for Not Becoming an Entrepreneur
Rank (1 – 8)1 %
2 %
3 %
4 %
5 %
Difficult to raise capital
141 31
101 23
80 21
44 14 20 7
Difficult to find partners
47 10
114 26
95 25
56 17
31 10
Lack of good ideas171 37
67 15
43 12 26 8 28 9
Concept easily copied 6 1 30 747 13
60 18
76 25
Risk too great55 12
73 17
61 16
74 23
57 19
Family against entrepreneurship 8 2 16 4 12 3 25 8
41 13
Cannot leave current job 22 5 19 4 19 5 27 8
31 10
Gov. discouraged entrepreneurship at the time 9 2 17 4 20 5 12 4
20 7
Only 27% had never considered entrepreneurship.
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Standard errors are robust. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels (two-tailed). PPP GDP is used for China. Log indicates that a log transformation was done to address the skewed distribution. In parentheses, (t-1) and (t-6) indicate that the variables were lagged one year and six years, respectively
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
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Individual Level
Standard errors are robust. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels (two-tailed).
Independent Variables China only US onlyMaster's degree 0.034 (0.180) 0.125 (0.096)Doctorate degree 0.681** (0.303) 0.373*** (0.128)Work in R&D 0.442** (0.200)Work as Tech Manager -0.024 (0.211)Ever job in academia 0.118 (0.221)Family Economic Status -0.445* (0.252)Overseas Experience -0.291 (0.233)Prior acquisition 0.205** (0.104)Prior IPO 0.102 (0.173)ControlsVC funded 0.353 (0.400) 0.720*** (0.122)Angel investor funded 0.127 (0.376) 0.537*** (0.128)Beijing -0.051 (0.189)Shanghai -0.691** (0.320)Chongqing -0.845 (0.693)Shenzhen -0.020 (0.371)Mass. 0.211** (0.100)California 0.079 (0.112)N 271 1167
Expenditures are in billions of yuan, ratios and growth rates are percentages, all lagged 1 year. Controls for region and founding year are included.
Standard errors are robust. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels (two-tailed).
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
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Progress Update
National levelIndividual levelRegional levelFurther robustness checksAlternative definitions of innovationAlternative measures of R&D/funding environment
Other shifts – law/IP
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering
Wha
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Conclusion and Implications
18
Hypothesis: Supported?
H1
Increases in grant based public R&D expenditures will (via indirect effects) result in greater knowledge spillovers and greater use of an innovation strategy with a lag.
Some support
H2
Increases in grant-based public R&D expenditures lower use of an innovation strategy contemporaneous to the increase in funding.
-
H3
Increases in grant or contract-based public R&D expenditures will result in more scientists/engineers becoming entrepreneurs with a lag.
-
H4Increases in prior year venture capital funding will result in greater use of an innovation strategy. (Counter-hypothesis to hypothesis 1)
No
Institutional Level• Types of institutional support needed for innovative, high
growth firms• If evolutionary theory correct, larger impacts may be on new
firms
Individual Level• Suggestive of who to look for as cofounders
Strategy• Better understanding of environmental influences on search• Where to spend more time for early-stage, high tech founders• Active view on identification of valuable resources, difficult to
imitate
S T A N F O R D U N I V E R S I T Y • Chuck Eesley • Management Science & Engineering