1. Co-patenting and inventive performance: in search of the proximity paradox Lorenzo Cassi Université Paris 1, CES & OST Anne Plunket Université Paris Sud 11, ADIS

2. Aim of the paper: Consider the joint impact of network and proximity factors and Contrast their impact on Collaboration through co-inventor dyad formation Inventive performance through forward citations Geographical (and other forms of) proximity and networks

3. The role of geographical proximity Knowledge diffusion and innovation are highly localized and embedded in industrial clusters Long studied through knowledge externalities and their impact on knowledge creation (Jaffe, 1989; Audretsch and Feldaman, 1996) Under what conditions individuals and firms benefit from knowledge externalities? The role of networks as Channels of knowledge diffusion Social proximity : individuals need to be embedded in networks: knowledge flows follow inter-personal links build through mobility, co-ethnicity, friendship, etc. (Almeida & Kogut, 1999; Agrawal et al., 2008; Breschi and Lissoni, 2009;) Networks are local to the extent that individuals are not very mobile (Breschi and Lissoni, 2009) Other forms of proximity mediate knowledge diffusion: organizational and technological proximity (Boschma, 2005, Nooteboom, et al. 2007) Geographical (and other forms of) proximity and networks

4. Other forms of proximity: substitutes or complements Other forms of proximity mediate knowledge diffusion organizational proximity and technological proximity (Boschma, 2005) Social, organizational and geographical proximity are substitutes: similar roles in favoring learning and knowledge sharing In sum: 1. Individuals need proximity to become connected, to share knowledge 2. Various forms of proximity may act as substitutes or complements 3. Individuals need to be embedded in networks What about network positions ? Geographical (and other forms of) proximity and networks

5. Network positions are important to access knowledge and resources: Closure positions (= within component) - Coleman, 1988 Share social proximity : have partners in common ; closure positions are highly localized (Ter Wal, 2011) Cohesive networks: reduce coordination cost and promotes trust and collaboration Risk of redundancy: similar knowledge bases and technological skills Bridging positions (=across components) - Burt, 1992 Brokerage position: link between separate components; channel across clusters Access non redundant and novel sources of information and knowledge Promote creativity and provide opportunities for novel combinations “Weak ties”: difficult to coordinate and mobilize (but possibly compensated through other forms of proximity to reduce uncertainty) Networks and knowledge

6. The proximity paradox? Network relations and proximity are “facilitators” of coordination, knowledge sharing and diffusion, they do not necessarily favor innovative performance (Boschma and Frenken, 2009) Too much proximity may be harmful for innovation Technological capabilities and cognitive/technological proximity play a more prominent role (Nooteboom, et al. 2007, Broekel and Boschma, 2011)

7. Data and network construction method EPO patents in genomics (1990-2006) – ANR Corpus genomic with OST-INRA-ADIS - from Patstat All co-inventor dyads between inventors reporting a European postal address (EU15 and Switzerland and Norway - 12,968 patents – 4406 applicants – 24,708 inventors Network built using five-year windows (links die out) : network in 1994 is built on patents published between 1990 and 1994 All ties and potential ties To avoid simultaneity biases, we consider all proximity determinants with a lag of one period We investigate only links among already active actors – bridging and intracomponent ties LinksTotal number% 1. Bridging links1,0842.59 2. New Component link24,46057.85 3. Pendant links15,47036.89 4. Intra-component link1,1202.67 Total 41,934100

8. Independent variables and controls Unit of analysis: co-inventor dyads (closure or bridging dyads) Proximity variables based on inventors’ individual characteristics (previsous period) Geographical proximity: geographical location of inventors at the NUTS 3 level - Organizational proximity Same applicant: within the same governance structure - (private company, research institutes and universities, non for-profit organizations and individuals Same organizational type: between firms or between academics Technological proximity : Jaffe Index based on IPC codes Social proximity between already indirectly connected inventors (when social distance is == 2, 3 and 4) Control variables Average and absolute degree (preferential attachement) Average and absolute experience (time since first patent) Border (neighbor countries) Number of inventors Cosure and bridging patent: Mixed ties

9. Dependent variables and estimation 1. The likelihood of collaboration How proximity (spatial, social, cognitive, organizational and institutional proximity) affect the choice of collaboration partners? Tie formation using a conditional logit model – tie versus no tie formation for any observed tie, we randomly select five possible but not realized co- inventor ties, which provide five controls for each co-inventor Dyad formation using conditional logit = f(proximity, proximity interactions, controls) 2. The value of inventions: How proximity affect the value of patents? Number of citations per patent as a proxy for the value of an invention (Harhoff, et al. 2003; Gambardella, Harhoff, and Verspagen, 2008) Citations based on patent families – 5 years - (Martinez, 2010, OECD) # forward Citations using negative binomial = f(proximity, proximity interactions, controls)

10. Network tie formation regressions

11. (1)(2)(3)(4)(5)(6)(7)(8) VARIABLESClosure Bridge Geographical proximity0.815***0.469***0.683***0.681***0.729***0.684***0.608***0.684*** [19.24][9.75][18.69][18.82][21.70][21.26][15.01][21.27] Same applicant1.460***4.342***5.400***4.027***0.3663.218***2.698***2.610*** [4.88][16.94][8.07][16.38][1.08][3.65][10.95][10.21] Same type0.347*2.372***0.389*-0.011-0.075-0.0680.698*-0.458 [2.04][5.95][2.53][-0.02][-0.78][-0.74][2.17][-1.40] Technological proximity2.884***2.871***3.347***2.631***1.734***1.818***1.756***1.468*** [8.47][8.62][9.23][5.24][7.67][7.82][7.75][4.61] Geographical proximity x same applicant-0.690***-0.573*** [-10.27][-7.24] Geographical proximity x Same type0.397***0.146** [5.92][2.70] Technological proximty x Same applicant-1.932*-0.887 [-2.22][-0.75] Technological proximity x Same type0.5510.567 [0.83][1.24] Border-1.706***-1.672***-1.599***-1.626***-1.201***-1.176***-1.178***-1.174*** [-7.93][-8.41][-8.91][-8.97][-9.62][-9.81][-9.77] Degrees - Avrg0.954***1.009***0.972***0.986***-0.683***-0.667***-0.657***-0.663*** [5.40][5.87][5.89][5.90][-5.24][-5.23][-5.17] Degrees - Abs.diff.-0.237**-0.264**-0.274**-0.268**0.325***0.333***0.331***0.333*** [-2.67][-3.01][-3.26][-3.17][3.72][3.86][3.84][3.85] Experience - Abs.diff-0.376+-0.319+-0.292-0.2870.327**0.310**0.307**0.311** [-1.92][-1.74][-1.63][-1.59][2.75][2.69][2.64][2.68] Experience - Avrg-0.187+-0.211*-0.201*-0.206*-0.121-0.124+-0.127+-0.125+ [-1.79][-2.08][-2.04][-2.08][-1.60][-1.67][-1.71][-1.67] Observations11,584 11,656 Log Likelihood-650.8-679.6-700.5-703.6-1244-1269-1265-1269 D.F.10 Chi2707.4679.0723.3721.3924.0797.5796.5792.0 Dep.Vartype Robust z-statistics in brackets *** p<0.001, ** p<0.01, * p<0.05, + p<0.1 Tie formation

12. (9)(10)(11)(12) VARIABLESClosure Social proximity (= 2)2.689***5.460***6.573***4.680*** [5.91][5.42][15.03][12.14] Social proximity (= 3)1.592**6.023***3.998***3.181*** [2.86][6.42][11.51][7.85] Social proximity (= 4)0.4684.174***3.454***2.380*** [0.99][3.47][9.13][4.81] Geographical proximity0.720***0.430***0.371***0.409*** [10.30][9.21][7.46][8.48] Same applicant1.744***2.057***4.136***2.289*** [4.59][4.98][6.70][5.43] Same type0.3710.3870.325-0.150 [1.34][1.60][1.28][-0.64] Technological proximity0.923+1.843**0.6780.795 [1.78][2.86][1.31][1.57] Social proximity (= 2) x Geographical proximity-0.700*** [-5.86] Social proximity (= 3) x Geographical proximity-0.448*** [-3.63] Social proximity (= 4) x Geographical proximity-0.620*** [-5.63] Social proximity (= 2) x Technological proximity0.055 [0.04] Social proximity (= 3) x Technological proximity-3.660** [-3.05] Social proximity (= 4) x Technological proximity-2.216 [-1.35] Tie formation with social proximity

13. Tie formation with social proximity - cont Social proximity (= 2) x Same applicant-3.752*** [-5.44] Social proximity (= 3) x Same applicant-2.376*** [-3.51] Social proximity (= 4) x Same applicant-2.780*** [-3.91] Social proximity (= 2) x Same type1.980*** [3.64] Social proximity (= 3) x Same type0.664 [1.09] Social proximity (= 4) x Same type0.738 [1.13] Border-2.555***-2.075***-2.222***-2.194*** [-4.92][-6.12][-5.18][-5.68] Degrees - Avrg0.154-0.065-0.012-0.060 [0.57][-0.25][-0.05][-0.23] Degrees - Abs.diff.-0.0310.0020.0400.064 [-0.23][0.01][0.28][0.47] Experience - Abs.diff0.4360.694*0.618*0.612* [1.33][2.28][2.00][2.06] Experience - Avrg-0.168-0.229-0.134-0.190 [-1.12][-1.63][-0.90][-1.37] Observations11,584 Log Likelihood-254.3-278.1-261.2-276.3

14. Inventive performance - Citations regressions

15. (2)(3)(4)(5)(12)(13)(14)(15) VARIABLESClosure Bridge Geographical proximity0.011-0.001-0.026-0.0280.0060.0100.1030.012 [0.18][-0.01][-0.57][-0.61][0.12][0.21][1.53][0.25] Same applicant0.3370.494-2.6010.557+-0.460-3.1160.2740.387 [0.87][1.55][-0.89][1.72][-0.49][-1.32][0.84][1.18] Same type0.669+0.4110.5955.270+0.925***0.886***0.2314.611* [1.78][0.89][1.61][1.87][3.43][3.32][0.57][2.54] Technological proximity10.587*10.995*7.76417.515***5.132*2.8165.739*11.004** [2.34][2.44][1.31][3.36][2.10][1.01][2.51][2.59] Technological proximity sq-7.086*-7.380*-5.562-11.616**-3.928*-2.239-4.253*-7.652* [-2.26][-2.37][-1.33][-3.28][-2.24][-1.10][-2.50][-2.51] Geographical proximity x same applicant-0.069 [-0.78] Geographical proximity x Same type-0.085-0.201* [-0.93][-2.22] Technological proximty x Same applicant7.8111.1659.443 [0.95] [1.37] Technological proximty sq x Same applicant-4.648-5.988 [-0.82][-1.22] Technological proximity x Same type-12.814-10.548+ [-1.61][-1.89] Technological proximity sq x Same type8.3516.966+ [1.49][1.71] Border0.5360.3290.4390.498-0.707+-0.683-0.604-0.722+ [0.73][0.47][0.64][0.75][-1.70][-1.63][-1.41][-1.74] Degrees - Avrg1.158*** 1.152***1.131***-0.158-0.132-0.192-0.128 [3.46][3.50][3.43][3.39][-0.40][-0.34][-0.50][-0.35] Degrees - Abs.diff.-0.313+ -0.319*-0.326*0.0420.0400.0350.043 [-1.92][-1.94][-1.98][-2.04][0.21][0.20][0.18][0.22] Experience - Abs.diff-0.622*-0.629*-0.633*-0.667*-0.524+-0.522+-0.554+-0.545+ [-2.14][-2.17] [-2.31][-1.72][-1.70][-1.85][-1.82] Experience - Avrg0.0450.0630.0610.0710.1980.1660.1680.179 [0.26][0.37][0.36][0.43][1.13][0.94][0.95][1.00] # inventors per patent-1.010**-0.991*-0.981*-0.957*-0.000-0.005-0.012-0.005 [-2.60][-2.55][-2.56][-2.48][-0.00][-0.02][-0.04][-0.02] Closure and briging patent1.068**1.041**1.042**1.041**-0.239-0.190-0.269-0.181 [2.81][2.76][2.78][2.76][-0.71][-0.57][-0.80][-0.55] Constant-6.330***-6.555***-5.274*-8.960***-3.243**-2.488+-3.013*-5.337** [-3.56][-3.68][-2.35][-4.23][-2.65][-1.87][-2.53][-3.25] Observations1,070 1,065 Log Likelihood-466.0-465.9-465.6-465.2-470.4-470.0-469.3-469.8 D.F.23 24 23242324 Robust z-statistics in brackets *** p<0.001, ** p<0.01, * p<0.05, + p<0.1

16. (6)(7)(8)(9) VARIABLESClosure Social proximity (= 2)-1.064+-0.017-0.631-1.730*** [-1.88][-0.01][-0.86][-3.71] Social proximity (= 3)-1.275+-11.024*-1.576+-1.818*** [-1.89][-2.26][-1.70][-3.52] Social proximity (= 4)-1.677*6.789-2.125*-2.077*** [-1.99][1.43][-2.09][-3.34] Degrees - Avrg1.418***1.401***1.338***1.318*** [4.18][3.90][3.95][3.90] Degrees - Abs.diff.-0.318+-0.283+-0.314+-0.299+ [-1.95][-1.73][-1.92][-1.81] Geographical proximity-0.108-0.005-0.008-0.007 [-0.85][-0.10][-0.17][-0.16] Same applicant0.4180.3951.410+0.385 [1.28][1.17][1.80][1.18] Same type0.5190.5150.600-0.346 [1.42] [1.59][-0.40] Technological proximity8.851*9.5978.919+8.965* [1.98][1.40][1.94][1.97] Technological proximity sq-5.938+-5.465-6.007+-6.006+ [-1.95][-1.05][-1.91][-1.92] Border0.7220.7600.5750.560 [1.03][1.12][0.88][0.85] Experience - Abs.diff-0.763*-0.896**-0.765*-0.756* [-2.47][-2.74][-2.46][-2.43] Experience - Avrg0.0700.0810.1040.102 [0.43][0.50][0.63][0.62] # inventors per patent-0.979*-1.005*-0.929*-0.928* [-2.45][-2.55][-2.34][-2.36] closure and briging1.225**1.232**1.177**1.222** [3.11][3.27][3.10][3.19] Social proximity (= 2) x Geographical proximity0.103 [0.75] Social proximity (= 3) x Geographical proximity0.154 [0.84] Social proximity (= 4) x Geographical proximity0.102 [0.41]

17. Social proximity (= 2) x Technological proximity-2.330 [-0.25] Social proximity (= 2) x Technological proximity sq0.488 [0.07] Social proximity (= 3) x Technological proximity29.740* [2.12] Social proximity (= 3) x Technological proximity sq-22.057* [-2.24] Social proximity (= 4) x Technological proximity-24.607+ [-1.69] Social proximity (= 4) x Technological proximity sq15.560 [1.46] Social proximity (= 2) x Technological proximity-2.330 [-0.25] Social proximity (= 2) x Technological proximity sq0.488 [0.07] Social proximity (= 2) x Same applicant-1.251 [-1.59] Social proximity (= 3) x Same applicant-0.340 [-0.33] Social proximity (= 4) x Same applicant0.049 [0.04] Social proximity (= 2) x Same type1.158 [1.36] Social proximity (= 3) x Same type0.115 [0.10] Social proximity (= 4) x Same type0.119 [0.10] Constant-5.038**-5.289*-5.323**-4.466* [-2.88][-2.10][-2.82][-2.43] Observations1,070 Log Likelihood-461.1-458.7-459.8-460.1 D.F.283128 Robust z-statistics in brackets *** p<0.001, ** p<0.01, * p<0.05, + p<0.1

18. Conclusion Results confirm previous studies on: Collaboration and knowledge flows Social, organizational and geographical proximity are substitutes Outside the governance structure, organizational and geographical proximity are complements The various forms of proximity strongly explains the formation of networks and geography remains important even after controlling for other forms of proximity Innovative performance and the proximity paradox Geographical and organizational proximity is not significant Too close social proximity is negative for closure ties Technological proximity has a key role; it has an inverted u-shape Less close proximity is more beneficial for bridging ties

19. Thank you very much for your attention!

20. Country PatentInventors fractionalcumulativefractionalcumulative AT213,26844419,83427 BE612,171983897908 CH467,131554871,33896 DE3630,55138795717,755776 DK510,832193865,75874 ES185,92818603606 FI168,36662402405 FR1816,3764073456,833491 GR17,834535 IE57,4215118119 IT358,171193767,67772 LU0,25111 NL845,3827971341,421357 NO105,83299200201 PT9,193832 SE426,51303758,33767 UK2241,4167733639,53687 others1301,4673214252,584354 Total12968483252437924708 Inventors and patent by country (fractional and cumulative counting)

21. Citations include self-citations

22. Closure tiesBridging ties VariableNMeanSDMinMaxNMeanSDMinMax Citations10700.230.900910650.230.8709 Degrees - Avrg10702.120.520.693.5110651.820.490.693.60 Degrees - Abs.diff.10701.710.8703.9510651.530.8203.93 Geographical proximity1070-2.662.44-7.3001065-3.372.47-7.990 Same applicant10700.590.490110650.260.4401 Same type10700.290.450110650.420.4901 Technological proximity10700.730.200110650.710.2101 Technological proximity10700.570.290110650.550.2801 Border10700.030.180110650.090.2801 Experience - Abs.diff10701.540.500.692.7110651.610.450.692.74 Experience - Avrg10701.140.7702.7110651.220.7302.77 # inventors per patent10701.950.371.102.9410651.910.461.103.85 Closure and briging patent10700.080.270110650.140.350.001 Social proximity (=2)10700.670.4701 Social proximity (=3)10700.160.3701 Social proximity (=4)10700.090.2801