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Collaboration and innovation in the US and Japan: Evidence from the

RIETI-Georgia Tech inventor survey

John P. Walsh* and Sadao Nagaoka** May 12, 2008

Correlates of Innovative Activity and Performance. Georgia Tech.Do not quote or cite without permission. Some numbers are still preliminary.

*Associate Professor, Georgia Institute of Technology**Research Counselor, Research Institute of Economy, Trade and Industry and Professor, Institute of Innovation Research, Hitotsubashi University

We would like to thank the research assistance by Naotoshi Tsukada, Wang Tingting, Hsin-I Huang, Taehyun Jung and Yeonji No.

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Innovation and Collaboration• Innovation is key to economic growth• Innovation process becoming more complex

– Open innovation– Markets for Innovation– National Innovation Systems

• Inventors and their firms need to exploit information and opportunities outside the firm in order to combine one’s own capabilities with resources from the external environment.

• While interdependent innovation seen as hallmark of the Japanese innovation system, increasingly, the US system is seen as moving toward an open innovation model (Chesbrough, 2003, Hicks and Narin, 2001)– However, need systematic data on innovation collaboration in each

country, covering broad range of indicators– Also, differences by firm and inventor characteristics in ability to exploit

outside information (Cohen and Levinthal, 1990)

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Measuring Collaboration• Prior work has often used bibliometric indicators, which

have several advantages• However, concern that there is over-emphasis on

bibliometric indicators– Need to validate bibliometrics– Also, need to capture other aspects of collaboration

process that are not readily available through bibliometric indicators

• And, need for broad industry/technology coverage– Complement to industry or technology focused

studies (bio, nano)– Examine differences across technologies to better

understand drivers and impacts of collaboration

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Inventor Surveys• Pioneered by PATVAL, followed by RIETI,

GT/RIETI• Survey inventors (rather than R&D managers)• Large sample, broad technology/industry

coverage• Comparative (JP-US, also Europe)

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The RIETI and GT/RIETI Inventor Surveys

• A survey on the inventions and the R&D projects that created them:– First such systematic survey on R&D projects in Japan and USA

• Relied significantly on the PATVAL-EU survey, but also significantly expanded it

• Japan and US surveys substantially harmonized in questionnaire and sample target

• Dual-mode (post-mail out, web or post-mail response)– Japan mail-out: Winter to Spring 07– US mail-out Summer, ‘07

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GT/RIETI Inventor Surveys• Measures

– Inventor demographics, mobility, background, and inventor motivations

– Invention process, collaboration– Business objective of R&D, R&D strategy and

performance– Uses of the patent, commercialization

• Goal:– Empirical: Map the innovation landscape– Methodological: Compare survey and bibliometric

indicators– Analytic: Study the drivers of innovation

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Primary Sampling Frame –OECD Triadic Patent Families

• Triadic Patent Families– Compiled by OECD– Sharing, either directly or indirectly, at least one priority patent

applications in three patent offices– Filed in EPO and JPO and granted in USPTO

• Advantage of using the TPF– Reduce home country bias – Focus on economically important patents (Random sampling would

result in targeting most questionnaires to economically unimportant patents. Filing in multiple jurisdictions works as a threshold)

• Disadvantage of using the TPF– Select subset of inventions, and even of patented inventions.

Likely to be biased toward commercialized inventions– Perhaps, bias against nonprofit, small, and/or independent

inventors?

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Data• Japan: 5,300 responses

– 20.6% response rate (27.1% adjusted for undelivered, ineligible, etc.)

– triadic patents: approximately 70% (over 3600) – non-triadic patents: approximately 30%– very important patents (selected from the JPO reports and the

essential patents of standards): roughly 120 patents• US: 1,900 (all triadic)

– 24.1% response rate (31.8% adjusted)• Comparisons based on triadic patent samples• Created country-technology weights to adjust for

different composition across technology in each country– Effects of the weighting quite small

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Table 1. Composition of the sampleNBER Class Sub-Category Name Japan US

11 Agriculture, Food, Textiles 1.6% 0.4%

12 Coating 2.2% 1.8%

13 Gas 1.2% 0.6%

14 Organic Compounds 3.3% 3.2%

15 Resins 3.4% 4.4%

19 Miscellaneous-chemical 5.7% 12.1%

21 Communications 4.4% 7.8%

22 Computer Hardware 1.6% 2.2%

77 Computer Software 3.4% 4.8%

23 Computer Peripherals 2.1% 1.7%

24 Information Storage 3.3% 2.2%

31 Drugs 3.5% 5.3%

32 Surgery & Medical Instruments 2.3% 6.4%

33 Biotechnology 2.4% 2.1%

39 Miscellaneous-Drug&Med 1.2% 1.5%

41 Electrical Devices 2.5% 2.3%

42 Electrical Lighting 2.6% 1.7%

43 Measuring & Testing 3.0% 3.2%

44 Nuclears & X-rays 2.0% 2.0%

45 Power Systems 4.7% 4.6%

46 Semiconductor Devices 3.5% 2.9%

49 Miscellaneous-Elec. 3.3% 1.7%

51 Materials Processing & Handling 2.8% 2.9%

52 Metal Working 3.7% 2.6%

53 Motors, Engines & Parts 4.0% 2.9%

54 Optics 2.7% 2.2%

55 Transportation 2.0% 1.7%

59 Miscellaneous Mechanical 3.4% 2.2%

61 Agriculture, Husbandry, Food 2.4% 0.7%

63 Apparel & Textile 2.1% 0.5%

64 Earth Working & Wells 0.5% 0.3%

65 Furniture, House Fixtures 1.4% 0.5%

66 Heating 2.3% 0.4%

67 Pipes & Joints 1.8% 0.7%

68 Receptacles 1.5% 1.0%

69 Miscellaneous-Others 6.2% 6.4%

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Who Invents? (Career and Background)

• Demographics– Age– Percent female– Highest degree

• Workplace– Work organization at the time of invention– Mobility– Work unit at the time of invention

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Table 2 Basic profile of the surveyed inventors and their organizational affiliations

Source: RIETI Inventor Survey (2007) for Japan, Europe’s PatVal for EU (covering six countries: Germany, France, England, Italy, Spain, and the Netherlands).

Japan US EuropeSample Size 3658 1919 3818

Academic Universitygraduate (%)

85.9% 93.0 85.3

Background Doctorate (%) 12.4 44.9 34.8Female (%) 1.5 5.4 3.7Age (meanyears)

39.5 47.2 43.7

OrganizationalAffliliation

Large firm(250+)(%)

87.8 80.8 77.2

SME (%) 8.7 14.2 15.1University (%) 2.3 2.3 4.1Other 1.2 2.8 3.7

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Education/Demographics• Japan (and European) inventors have more varied

educational backgrounds.– Fewer university-educated inventors– Substantially fewer Ph.D.s

• Very small share female inventors in both countries, even relative to the share of female researchers – Japan: about 10% of R&D employees female– US: about 25%

• US inventors much older than Japanese and somewhat older than Europe

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Organizational affiliation

• Most inventors were employed by organizations

• Employees of corporations with more than 250 employees made up nearly 90% of the triadic patents in Japan and 80% in the US

• Inventors belonging to universities account for a small share of the triadic patents not only in Japan but also in the US

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Age Profile, Large Firms, US and Japan

0

0.05

0.1

0.15

0.2

0.25

0.3

20-

24

25-

29

30-

34

35-

39

40-

44

45-

49

50-

54

55-

59

60-

64

65-

69

70-

74

JAPAN US

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Age profiles

• US inventors much older (47 v. 40)• PhDs on average 1 year older (so cannot

explain the gap)• Variance in two countries similar, even if

we limit to large firms for comparability• Americans start later and stop later

– Longer to graduate, more time before getting first permanent job and later retirement age?

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%PhD, by Sector, US and Japan

51.741.1

30.316.1

14.814.5

13.312.411.9

9.48.9

6.96.9

74.4

88.377.6

73.8

65.337.9

29.344.9

42.729.6

36.7

26.925.0

0 20 40 60 80 100

BiotechnologyDrugs

Organic CompoundsResins

Semiconductor DevicesMeasuring & Testing

Surgery & Medical InstrumentsAll

CommunicationsPower Systems

Computer SoftwareMotors, Engines & Parts

Materials Processing & Handling

%Yes

Japan US

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%SME, by Sector, US and Japan

14.814.6

11.88.9

8.78.2

6.55.8

5.55.0

4.93.2

1.7

28.1

23.18.6

13.5

14.217.8

18.112.7

14.36.9

3.9

16.37.5

0 5 10 15 20 25 30

Surgery & Medical InstrumentsBiotechnology

Measuring & TestingMaterials Processing &

AllComputer Software

DrugsPower Systems

Semiconductor DevicesOrganic Compounds

Motors, Engines & PartsCommunications

Resins

%Yes

Japan US

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Key sectoral differences• PhD especially high in bio and chemicals, in

both countries. Also in semiconductors in the US

• In both countries, medical instruments and bio have above average levels of SME inventors– Rates of SME inventors slightly higher in Japan for

measuring and testing– Big difference in Communications, with relatively

many SME inventors in US (16%) and few in Japan (3%)

– Drugs show similar pattern though gap is smaller

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%University or college, by Sector, US and Japan

12.26.7

6.4

4.94.9

3.52.5

2.52.5

2.32.0

1.61.2

12.8

3.53.5

7.0

5.31.9

0.0

1.32.2

2.30.00.0

1.2

0 5 10 15

BiotechnologyOrganic CompoundsMeasuring & Testing

Surgery & Medical Instruments

DrugsMotors, Engines & Parts

CommunicationsResins

Computer Software

AllMaterials Processing & Handling

Semiconductor DevicesPower Systems

%Yes

Japan US

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University Inventions• University inventions most common in biotech• Rate of university inventors is the same in each country,

even in bio and software (where US is seen as being especially strong in university inventions)

• Japan has higher rate in measuring/testing and organic compounds

• US somewhat higher in medical instruments

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Figure 1 Inventor mobility- Within 5 prior year, have you worked for another employer?

%Yes, unweighted

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Mobility (in) rates, by organization type, US and Japan

23.8

13.4

18.7

10.8

12.9

9

10.1

40

34.2

45.4

40.7

29.7

21.2

25.6

0 5 10 15 20 25 30 35 40 45 50

Other

University

Smallest firm

Small firm

Medium-sized firm

Large firm

Total

%Yes

US

Japan

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Mobility• US inventors are more than twice as likely to

have moved compared to Japanese inventors• Difference is especially large in biotechnology,

medical instruments, semiconductors and computer software

• Mobility (in) is highest for small firms in each country, though the jump in US starts with medium small (lt 250), while in Japan, it is only in the smallest firms (lt 100) that we see substantially above average mobility

• We are currently exploring the links between mobility, information flows and innovation

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Figure 6. Inventor Functional Affiliation

Note: The “Other” category includes design and engineering sectors.

64.48

17.67

8.47

3.13 1.374.88

70

14.7

52.9

7

0

10

20

30

40

50

60

70

80

IndependendR&D unit

R&D sub-unit manufacturing Softwaredeveloping

Marketing other

US JP

%Yes, weighted

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Inventor Functional Affiliation • R&D more centralized in Japan (70% of inventors in

independent R&D units v. 60% in US)• About 5% come from manufacturing in Japan (slightly

more in the US)• About 1.5% of US triadic patents come from sales and

marketing

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4.Collaboration/Sources of Information

• Collaboration plays an important role in helping a firm to exploit external capabilities and to facilitate access to new knowledge

• Collaboration– Co-assignment

• Prior work finds that such co-assignment is growing, but still quite rare (about 1.5%) (Hicks and Narin. 2001; Hagedoorn, 2003)

• But, measure limited by available bibliometrics– Cross-organizational co-Inventors– (Non-co-inventor) Collaboration partners

• Sources of Information– Suggesting Project– Contributing to Project Completion

• Financing

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Figure 13. External Co-inventors, by organization type

4.1

1.4

1.3

2

2.7

0.6

12.4

3.5

0.4

1

1.9

2.4

0.7

13

5.4

4.1

0 2 4 6 8 10 12 14

Suppliers

Customers and product users

Competitor

Non-competitor(s) within the same industry

Other firm(s)

University and education

Government Research Organization

External co-inventors

US JP

%Yes, unweighted

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PRO-Industry Coinvention, by firm size, US and

Japan

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Large firm Medium-

sized fir

Small firm Smallest firm

JP-Univ

JP-GovLab

US-Univ

US-GovLab

2929

Figure 14. Formal/Informal Collaborations (excluding co-inventors), by organization type

9.3

0.7

1.2

3.2

4.2

1.8

22.8

15.1

0.8

1.8

2

4.3

2

29.2

11.1

8.1

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0

Suppliers

Customers and product users

Competitor

Non-competitor(s) within the same industry

Other firm(s)

University and education

Government Research Organization

External collaborations

US JP

%Yes, unweighted

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Collaborative R&D involving co-inventions

• The level of co-inventions with external co-inventors are similar between Japan and US: slightly more than 10% of the inventions involve external inventors in both countries.

• The amount of formal or informal collaboration (excluding co-invention) is about 25% in the US and almost 30% in Japn

• However, only 1.8% of the US triadic patent have multiple assignees– Thus, bibliometrics are likely to significantly under-estimate the amount of cross-organization

invention in US (cf. Thursby, Fuller and Thursby, 2007)– Co-assignment data is less of a problem in Japan– Co-assignment higher (5-6%) in drugs, biotech and semiconductor

• In both countries, the bulk of these external co-inventors are vertically related (either suppliers or users).

• Horizontal co-inventions (collaborations among competitors) are much less common than vertical co-inventions.

• Co-inventions involving university or public laboratory researchers constitute small minorities in both countries

– University co-inventors most common in small firms, and more common among small Japanese firms compared to US

– In US, rate of university co-inventors for startups (lt100 ees and lt 5 y.o.) is 2.3% (about the same as overall average)

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Figure 15A: Sources of Information-Suggesting New Project

%High (4 or 5), unweighted

US (above)JP

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0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

High school or

lower

Tech college

or junior

college

University Master

degree

Ph.D. Total

JP: Scientific Lit Sugg. JP: Patent Lit Sugg. US: Scientific Lit Sugg. US: Patent Lit Sugg.

Sources of Information, Scientific Lit. and Patents, by education, US and Japan

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Sources of Knowledge• Four of the most important five sources of knowledge for

conception are common for Japan and US: (1)patent literature, (2)users, (3)knowledge inside a firm to which an inventor belongs, and (4)scientific and technical literature– Publications especially important for drugs and bio.

• US inventors appreciate scientific and technical literature more than patent literature while the reverse is the case for Japanese inventors

• This is true across all education levels, except for High School inventors in US and PhD inventors in Japan

• Future work will compare these survey data to bibliometric indicators of knowledge flows

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Ordered logi t estimates Number of obs = 1261 LR chi2(11) = 114.02 Prob > chi2 = 0.0000Log likelihood = -1642.9097 Pseudo R2 = 0.0335------------------------------------------------------------------------------ rb1a | Coef. Std. Err. z P>|z| [95% Conf. Interval]-------------+---------------------------------------------------------------- a3 | .0142217 .0026282 5.41 0.000 .0090706 .0193729 deg_msphd | .4281627 .1169611 3.66 0.000 .198923 .6574023 invage | -.0004678 .0006586 -0.71 0.478 -.0017586 .0008231 heteroa6a | .2752236 .08461 3.25 0.001 .1093911 .4410561 otype_big | -.6100467 .173853 -3.51 0.000 -.9507923 -.2693011 otype_small | .3325622 .2215142 1.50 0.133 -.1015976 .766722------------------------------------------------------------------------------Ordered logi t estimates Number of obs = 1224 LR chi2(14) = 137.23 Prob > chi2 = 0.0000Log likelihood = -1579.6422 Pseudo R2 = 0.0416------------------------------------------------------------------------------ rb1a | Coef. Std. Err. z P>|z| [95% Conf. Interval]-------------+---------------------------------------------------------------- a3 | .0125218 .0026308 4.76 0.000 .0073656 .017678 deg_msphd | .3552343 .1231641 2.88 0.004 .1138371 .5966316 invage | -.0006405 .0007002 -0.91 0.360 -.0020129 .0007318 heteroa6a | .2129853 .0878835 2.42 0.015 .0407369 .3852338 a7spill | .0069015 .0166438 0.41 0.678 -.0257198 .0395227 a7open | .0252147 .0193453 1.30 0.192 -.0127014 .0631308 a7public | .0884375 .0246427 3.59 0.000 .0401387 .1367364 otype_big | -.6260459 .1754483 -3.57 0.000 -.9699181 -.2821736 otype_small | .2998854 .2258635 1.33 0.184 -.1427989 .7425697------------------------------------------------------------------------------

Predicting Patent (Technical) Value

Note: results robust to use of formal/informal collaboration

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Logistic regression Number of obs = 1319 LR chi2(9) = 103.10 Prob > chi2 = 0.0000Log likelihood = -859.96814 Pseudo R2 = 0.0566------------------------------------------------------------------------------ commyn | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]-------------+---------------------------------------------------------------- rb1a | 1.442957 .0804933 6.57 0.000 1.293511 1.609668 anycollab | 1.670405 .2309517 3.71 0.000 1.273896 2.19033 otype_big | .5809189 .1158231 -2.72 0.006 .3930102 .858672 otype_small | 1.168253 .3018477 0.60 0.547 .7040562 1.938502------------------------------------------------------------------------------

Logistic regression Number of obs = 1274 LR chi2(12) = 136.45 Prob > chi2 = 0.0000Log likelihood = -812.32975 Pseudo R2 = 0.0775------------------------------------------------------------------------------ commyn | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]-------------+---------------------------------------------------------------- a7spill | 1.101135 .0218462 4.86 0.000 1.059139 1.144796 a7open | .9093785 .019816 -4.36 0.000 .8713576 .9490584 a7public | .9798294 .0270871 -0.74 0.461 .9281522 1.034384 rb1a | 1.511976 .0892847 7.00 0.000 1.346728 1.6975 anycollab | 1.453863 .211944 2.57 0.010 1.092535 1.934691 otype_big | .5735825 .1169899 -2.73 0.006 .3845757 .8554801 otype_small | 1.092231 .2890866 0.33 0.739 .6501633 1.834875------------------------------------------------------------------------------

Predicting Commercialization

Note: inventor heterogeneity does not predict commercialization

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Figure 26. Finance Shares of R&D Projects

Note: Averages not adjusted for project size. Internal funds includes debt or equity funding

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Table 4 Funding sources: share (%) of funding for the research by organization type

Note. Large firm has 501 or more employees, Medium-sized firm has 251- 500 (250-500 in the US) employees, Small firm has 101-250 (100-249) employees, Smallest firm has 100 (99) or less employees

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Financing R&D

• More venture capital for financing of the inventions in the US

-Especially large for the smallest firms with less than 100 employees

• More government financing of the inventions in the US -Largest difference for medium sized firms

• More industry finance for the inventions of university professors in Japan

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Conclusions: SimilaritiesHigh similarity between US and Japan despite large

institutional differences:- Few female inventors- Relatively small contribution of university as inventors

and in collaborations- Inventor motivations similar (“task” motives strong)- Similar levels of cooperative R&D (co-invent and

collaboration), and similar profiles of partners

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Key differences

- High inventor mobility in US- US inventors older, more likely to have

PhD- Greater use of patents in Japan and

scientific literature in the US

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Lessons for Bibliometrics• Co-assignment significantly under-represents

cross-organization collaboration– Misses about 85% of cross-organization co-invention– Misses almost 95% of cross-organization

collaboration• Future work will analyze predictors of these

different forms of collaborations (co-assignment, cross-organizational co-invention, informal/formal collaboration), to both understanding collaboration process and put bibliometrics in context

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Future research

• Institutional and organizational drivers of these differences– For example, why are US inventors so much older?

• Implications of these differences for patent value and commercialization– For example, how does mobility affect information

flows, patent value and commercialization– What are the predictors of, and effects of, R&D

collaboration (on patent value and on commercialization)

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Questions? Comments? Suggestions?

John P. WALSHGeorgia Institute of TechnologySchool of Public Policy685 Cherry StreetAtlanta, GA 30332-0345 USAEmail: john.walsh@pubpolicy.gatech.edu