R&D Collaboration in Robotics:A Comparison between the US

and Japan

Aujain EghbaliNaohiro Shichijo

Yasunori Baba

The University of Tokyo, Research Center for Advanced Science And Technology, Baba Laboratory

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Introduction

• Regain of attention in the field of robotics in recent years

• Relevance of Japan and US comparison: – JP+US = half of operational stocks of industrial

robots in the world– JP + US = 77.2% of USPTO patents

• Use of patent data and social network analysis: robotics innovation explained by collaboration?

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Outline

• Background and previous work• Data and methods• Results• Conclusions and future research

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Background: brief history of robotics

• 1970s: oil shock -> restructuring of automobile industry -> increase of industrial robots usage

• 1980s: reshaping with semi-conductor industry (Kumaresan, Miyazaki; 2001)

• Recent years: new technologies (mobility, bipedal walk, face and voice recognition,…) for new applications (service robots for professional use, entertainment robots, space robots,…) (reports by UNECE-IFR-JPO)

• Common sense: STILL IN EARLY PHASE OF DIFFUSION (Ishihara, Gonaikawa; 2007)

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Previous work

• Because of the non scriptable nature of tacit knowledge, knowledge spillovers depend on the position in a network and on absorptive capacity (Cohen, Levinthal, 1990 ; Powell et al, 1996)

• In Japan, collaboration has a positive impact on the quality of patents, particularly in the case of government consortia collaboration (Lechevalier et al, 2007)

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Data: construction• For the purpose of comparison, use data on

patents issued by USPTO• Keyword search: “robot” or “manipulator” (JPO)– Difficulty to define robots– Lack of specificity of the keywords

=>Query expansion: add former and later citations (Larsen, 2007)

CITING38,595

CORE38,340

CITED144,622

Knowledge flow

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Restrain data between 1982 and 2001

Data: descriptionNumber of patents per year

JP US

Increase rate per year

114% 120% Higher performance of US based

Data: descriptionlargest assignees in Japan and US

JP largest assigneesNb

patents US largest assigneesNb

patentsCANON KK 1659 IBM 3705HITACHI LTD 1452 APPLIED MATERIALS INC 1942MATSUSHITA ELECTRIC IND CO LTD 1159 MICRON TECHNOLOGY INC 1673SONY CORP 1057 GEN ELECTRIC 1082FUJITSU LTD 898 MICROSOFT CORP 735MITSUBISHI ELECTRIC CORP 894 MOTOROLA INC 711TOKYO SHIBAURA ELECTRIC CO 891 TEXAS INSTRUMENTS INC 701TOKYO ELECTRON LTD 875 INTEL CORP 684NIPPON ELECTRIC CO 615 HEWLETT PACKARD CO 682FANUC LTD 575 XEROX CORP 674HONDA MOTOR CO LTD 572 EASTMAN KODAK CO 649FUJI PHOTO FILM CO LTD 422 ADVANCED MICRO DEVICES INC 571SEMICONDUCTOR ENERGY LAB 370 LUCENT TECHNOLOGIES INC 489OLYMPUS OPTICAL CO 291 SCIMED LIFE SYSTEMS INC 444NIPPON KOGAKU KK 274 SUN MICROSYSTEMS INC 443SUMITOMO RUBBER IND 262 WESTINGHOUSE ELECTRIC CORP 414SHARP KK 259 BOEING CO 397RICOH KK 256 US ARMY 381BRIDGESTONE SPORTS CO LTD 246 PHILIPS CORP 364SEIKO EPSON CORP 240 MINNESOTA MINING & MFG 657EBARA CORP 231 AT & T CORP 331TOYOTA MOTOR CO LTD 212 HEWLETT PACKARD DEVELOPMENT CO 325YAMAHA CORP 210 UNIV CALIFORNIA 322NISSAN MOTOR 193 LAM RES CORP 310MINOLTA CO LTD 178 GEN MOTORS CORP 296MAZDA MOTOR 148 MEDTRONIC INC 280SUMITOMO ELECTRIC INDUSTRIES 146 CATERPILLAR INC 274SANYO ELECTRIC CO 145 MASSACHUSETTS INST TECHNOLOGY 267ALPS ELECTRIC CO LTD 142 LSI LOGIC CORP 257KOMATSU MFG CO LTD 141 US NAVY 242DENSO CORP 137 AGILENT TECHNOLOGIES INC 237YAZAKI CORP 132 NORDSON CORP 233SUMITOMO WIRING SYSTEMS 127 FORD MOTOR CO 227DAINIPPON SCREEN MFG 121 NCR CORP 222YASKAWA DENKI SEISAKUSHO KK 121 ADVANCED CARDIOVASCULAR SYSTEM 211

Japan co-assignees network: 1982-1987

Hitachi group

Toyota group04/08/23 9

Japan co-assignees network: 1997-2002

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US co-assignees network:1982-1987

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US co-assignees network:1997-2002

California cluster

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MIT cluster

Hypothesis• Observations:– US network more heterogeneous than JP network

(public institutions, subsidiaries of foreign companies)– US network centralization low and stable (between

4% and 5%), whereas JP high and increasing (from 9% to 14%)

• Hypothesis: heterogeneity of collaboration, in particular collaboration with public institutes, drives US innovation in robotics, whereas Japan comparatively relies on in-house knowledge

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Statistical analysis

• Dependant variable:R&D productivity: number of patents

• Control variables: Knowledge stock: past patentscollaboration effort: inventors/patentsCollaboration experience: time elapsed since first collaborative patentCollaborator quality: number of patents of collaborator

• Independent variables:– Centrality: Betweenness– Private collaborators: Number of private partners– Public collaborators: Number of public partners

Country Nb firms Nb patents Nb collaborations

US 1,051 52,977 1,366

JP 294 23,449 2,216

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Results: control variablesVariable Control_All Control_JP Control_US

Collaboration Control All

Collaboration Control JP

Collaboration Control US

R&D productivity

K_stock .00177*** .00377*** .00164*** .00101*** .00228*** .00085***collab_eff 0.0134 -0.0197 .0245** -0.00385 -.0605*** .02*collab_exp .103*** .0884*** .0859***collab_qual .271*** .209*** .346***_cons .313*** .583*** .235*** .332*** .641*** .24*** ln_r_cons .995*** .991*** 1.05*** 1.04*** 1.08*** 1.11*** ln_s_cons 1.6*** 1.27*** 1.75*** 1.59*** 1.25*** 1.77*** Statisticsll -33267 -9060 -24094 -32991 -8955 -23958

legend: * p<0.05; ** p<0.01; *** p<0.001 04/08/23 15

Results: full modelVariable Full_All Full_JP Full_US R&D productivity K_stock .00099*** .00243*** .00129***collab_eff -0.00503 -.0643*** .0206*collab_exp .0835*** .082*** .087**collab_qual .267*** .211*** .386***betweenness .168*** .147*** .126*priv_collab -.00584*** -.00564*** -.0457***pub_collab .0669*** -0.0459 .102***_cons .334*** .641*** .243*** ln_r_cons 1.06*** 1.13*** 1.12*** ln_s_cons 1.61*** 1.3*** 1.78*** Statisticsll -32943 -8929 -23915legend: * p<0.05; ** p<0.01; *** p<0.001

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Conclusions

• Share of US companies in robotics R&D productivity is increasing and US robotics is more diverse

• US collaboration network is more heterogeneous• US innovation driven by collaboration with public

partners, JP innovation driven by knowledge stock

• Suggestion:– Japan: configuration for industrial robots– US: configuration for more science based robots

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Possible implications

• Japan: locked in past configuration?• US: configuration=advantage for tomorrow ?• Reconfiguration: Japanese strategist and policy

makers should encourage open innovation in robotics (few attempts at present)

• Important role of start-ups in an open innovation context (Nelson, 1993 ; Kamoshida, 2005) => Japanese policy makers should promote start-ups

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Limitations and future research

• Use co-citation network of patents to derive technology segments

• University/company collaboration particular in Japan: difficulty of finding data

• Possible exclusion of start-ups in our data– iRobot (US) (8 patents)– Tmsuk (JP) (2 patents)

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Segmentation

20

USVariable Obs Mean Std. Dev. Min Max nb_patents 10500 5.045429 17.54859 0 536nb_collabo~s 10500 0.1300952 0.989048 0 52past5nbpat~s 10500 14.57857 55.10923 0 2161collab_eff 10500 1.654067 1.139967 0 14collab_exp 10500 0.1194047 0.5540516 0 6.891626 collab_qual 10500 0.1087432 0.3999567 0 4.19728betweenness 10500 0.0248316 0.1861695 0 2.317018priv_collab 10500 0.3291429 2.865737 0 161pub_collab 10500 0.0562857 0.4176932 0 15 JPVariable Obs Mean Std. Dev. Min Max nb_patents 4118 5.694269 14.98807 0 211nb_collabo~s 4118 0.5381253 1.991085 0 52past5nbpat~s 4118 19.89728 55.6101 0 812collab_eff 4118 2.02114 1.31471 0 11.4collab_exp 4118 0.736933 1.394093 0 7.380256 collab_qual 4118 0.4733358 0.7569229 0 3.640879betweenness 4118 0.2055984 0.6398561 0 3.164199priv_collab 4118 2.249393 7.723213 0 156pub_collab 4118 0.0529383 0.4223704 0 10

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Summary statistics

Results: correlations

K_stock collab_eff collab_expcollab_qual

betweenness

priv_collab

pub_collab

K_stock 1collab_eff 0.0031 1collab_exp 0.4262 0.145 1collab_qual 0.3823 0.1864 0.7516 1betweenness 0.3711 0.0889 0.5094 0.4679 1priv_collab 0.4076 0.0572 0.6406 0.5822 0.3938 1pub_collab 0.1024 0.0384 0.2835 0.121 0.2031 0.075 1

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Previous work: robotics• Japan=“Robot Kingdom” (Schodt, 1980). From karakuri

dolls to humanoid robots (Hornyak, 2006)• Shift in Innovation trajectory, but slow response in

Japan: need for promotion of university industry joint activities (Kumaresan, Miyazaki, 2001)

• Positive interaction of search depth and search scope in the study of 124 robotic firms (Katila Ahuja, 2002)Diversity of search processes enhances performance

• In Japan, collaboration has a positive impact on the quality of patents, particularly in the case of government consortia collaboration (Lechevalier et al, 2007)

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Previous work: patent data and social network analysis

• Patent data widely used because (Schmookler, 1966):– Available– Provides much useable information

• Use of patent data to proxy innovation output has limitations (Griliches,1990), but relatively not so high in robotics (Grupp et al, 1990)

• Because of the non scriptable nature of tacit knowledge, knowledge spillovers depend on the position in a network and on absorptive capacity (Cohen, Levinthal, 1990 ; Powell et al, 1996)

• Collaboration => higher innovation performance?

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