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  • 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo R&D Collaboration in robotics: A Comparison between the US and Japan
  • 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo R&D Collaboration in robotics: A Comparison between the US and Japan
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo R&D Collaboration in robotics: A Comparison between the US and Japan
  • 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo R&D Collaboration in robotics: A Comparison between the US and Japan
  • 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo R&D Collaboration in robotics: A Comparison between the US and Japan
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • R&D Collaboration in robotics: A Comparison between the US and Japan 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo
  • 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo R&D Collaboration in robotics: A Comparison between the US and Japan
  • 08/16/10 Research Center for Advanced Science and Technology, The University of Tokyo R&D Collaboration in robotics: A Comparison between the US and Japan

Eghbali-Ppt0000001.ppt Presentation Transcript

  • 1. R&D Collaboration in Robotics: A Comparison between the US and Japan   Aujain Eghbali Naohiro Shichijo Yasunori Baba The University of Tokyo, Research Center for Advanced Science And Technology, Baba Laboratory 08/16/10
  • 2. 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?
    08/16/10
  • 3. Outline
    • Background and previous work
    • Data and methods
    • Results
    • Conclusions and future research
    08/16/10
  • 4. 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)
    08/16/10
  • 5. 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)
    08/16/10
  • 6. 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)
    08/16/10 Restrain data between 1982 and 2001 CITING 38,595 CORE 38,340 CITED 144,622 Knowledge flow
  • 7. Data: description Number of patents per year
    • Higher performance of US based
    JP US Increase rate per year 114% 120%
  • 8. Data: description largest assignees in Japan and US JP largest assignees Nb patents US largest assignees Nb patents CANON KK 1659 IBM 3705 HITACHI LTD 1452 APPLIED MATERIALS INC 1942 MATSUSHITA ELECTRIC IND CO LTD 1159 MICRON TECHNOLOGY INC 1673 SONY CORP 1057 GEN ELECTRIC 1082 FUJITSU LTD 898 MICROSOFT CORP 735 MITSUBISHI ELECTRIC CORP 894 MOTOROLA INC 711 TOKYO SHIBAURA ELECTRIC CO 891 TEXAS INSTRUMENTS INC 701 TOKYO ELECTRON LTD 875 INTEL CORP 684 NIPPON ELECTRIC CO 615 HEWLETT PACKARD CO 682 FANUC LTD 575 XEROX CORP 674 HONDA MOTOR CO LTD 572 EASTMAN KODAK CO 649 FUJI PHOTO FILM CO LTD 422 ADVANCED MICRO DEVICES INC 571 SEMICONDUCTOR ENERGY LAB 370 LUCENT TECHNOLOGIES INC 489 OLYMPUS OPTICAL CO 291 SCIMED LIFE SYSTEMS INC 444 NIPPON KOGAKU KK 274 SUN MICROSYSTEMS INC 443 SUMITOMO RUBBER IND 262 WESTINGHOUSE ELECTRIC CORP 414 SHARP KK 259 BOEING CO 397 RICOH KK 256 US ARMY 381 BRIDGESTONE SPORTS CO LTD 246 PHILIPS CORP 364 SEIKO EPSON CORP 240 MINNESOTA MINING & MFG 657 EBARA CORP 231 AT & T CORP 331 TOYOTA MOTOR CO LTD 212 HEWLETT PACKARD DEVELOPMENT CO 325 YAMAHA CORP 210 UNIV CALIFORNIA 322 NISSAN MOTOR 193 LAM RES CORP 310 MINOLTA CO LTD 178 GEN MOTORS CORP 296 MAZDA MOTOR 148 MEDTRONIC INC 280 SUMITOMO ELECTRIC INDUSTRIES 146 CATERPILLAR INC 274 SANYO ELECTRIC CO 145 MASSACHUSETTS INST TECHNOLOGY 267 ALPS ELECTRIC CO LTD 142 LSI LOGIC CORP 257 KOMATSU MFG CO LTD 141 US NAVY 242 DENSO CORP 137 AGILENT TECHNOLOGIES INC 237 YAZAKI CORP 132 NORDSON CORP 233 SUMITOMO WIRING SYSTEMS 127 FORD MOTOR CO 227 DAINIPPON SCREEN MFG 121 NCR CORP 222 YASKAWA DENKI SEISAKUSHO KK 121 ADVANCED CARDIOVASCULAR SYSTEM 211
  • 9. Japan co-assignees network: 1982-1987 Hitachi group Toyota group 08/16/10
  • 10. Japan co-assignees network: 1997-2002 08/16/10
  • 11. US co-assignees network:1982-1987 08/16/10
  • 12. US co-assignees network:1997-2002 California cluster 08/16/10 MIT cluster
  • 13. 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
    08/16/10
  • 14. Statistical analysis
    • Dependant variable:
      • R&D productivity: number of patents
    • Control variables:
      • Knowledge stock: past patents
      • collaboration effort: inventors/patents
      • Collaboration experience: time elapsed since first collaborative patent
      • Collaborator quality: number of patents of collaborator
    • Independent variables:
      • Centrality: Betweenness
      • Private collaborators: Number of private partners
      • Public collaborators: Number of public partners
    08/16/10 Country Nb firms Nb patents Nb collaborations US 1,051 52,977 1,366 JP 294 23,449 2,216
  • 15. Results: control variables 08/16/10 Variable 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***   Statistics ll -33267 -9060 -24094 -32991 -8955 -23958 legend: * p<0.05; ** p<0.01; *** p<0.001
  • 16. Results: full model 08/16/10 Variable 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***   Statistics ll -32943 -8929 -23915 legend: * p<0.05; ** p<0.01; *** p<0.001
  • 17. 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
    08/16/10
  • 18. 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
    08/16/10
  • 19. 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)
    08/16/10
  • 20. Segmentation
  • 21. 08/16/10 Summary statistics US Variable   Obs Mean Std. Dev. Min Max               nb_patents 10500 5.045429 17.54859 0 536 nb_collabo~s 10500 0.1300952 0.989048 0 52 past5nbpat~s 10500 14.57857 55.10923 0 2161 collab_eff 10500 1.654067 1.139967 0 14 collab_exp 10500 0.1194047 0.5540516 0 6.891626   collab_qual 10500 0.1087432 0.3999567 0 4.19728 betweenness 10500 0.0248316 0.1861695 0 2.317018 priv_collab 10500 0.3291429 2.865737 0 161 pub_collab 10500 0.0562857 0.4176932 0 15       JP Variable   Obs Mean Std. Dev. Min Max               nb_patents 4118 5.694269 14.98807 0 211 nb_collabo~s 4118 0.5381253 1.991085 0 52 past5nbpat~s 4118 19.89728 55.6101 0 812 collab_eff 4118 2.02114 1.31471 0 11.4 collab_exp 4118 0.736933 1.394093 0 7.380256   collab_qual 4118 0.4733358 0.7569229 0 3.640879 betweenness 4118 0.2055984 0.6398561 0 3.164199 priv_collab 4118 2.249393 7.723213 0 156 pub_collab 4118 0.0529383 0.4223704 0 10
  • 22. Results: correlations 08/16/10 K_stock collab_eff collab_exp collab_qual betweenness priv_collab pub_collab K_stock 1 collab_eff 0.0031 1 collab_exp 0.4262 0.145 1 collab_qual 0.3823 0.1864 0.7516 1 betweenness 0.3711 0.0889 0.5094 0.4679 1 priv_collab 0.4076 0.0572 0.6406 0.5822 0.3938 1 pub_collab 0.1024 0.0384 0.2835 0.121 0.2031 0.075 1
  • 23. 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)
    08/16/10
  • 24. 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?
    08/16/10