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Comparing EU and U.S. Views of University Involvement in Regional Economic Development

Comparing EU and U.S. Views of University Involvement in Regional Economic Development. How Similar are EU and U.S. Views of Academic Entrepreneurship? A Report of Preliminary Explorations. Gunther Maier Vienna University of Economics and Business. Harvey Goldstein Modul University-Vienna.

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Comparing EU and U.S. Views of University Involvement in Regional Economic Development

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  1. Comparing EU and U.S. Views of University Involvement in Regional Economic Development How Similar are EU and U.S. Views of Academic Entrepreneurship? A Report of Preliminary Explorations Gunther Maier Vienna University of Economics and Business Harvey Goldstein Modul University-Vienna Edward M. Bergman Vienna University of Economics and Business Presentation at the Pecs DIME Workshop 31 March-1 April 2011

  2. Outline of Presentation SEITE 2 Brief background, motivation, research questions Methods and data Selected descriptive results, US and EU cases Explaining variation in faculty attitudes, US and EU cases Conclusions (tentative) Fußzeile

  3. Background and Motivation SEITE 3 • The ‘entrepreneurial turn’ of universities • Increasing demands placed upon IHEs • Greater autonomy • Recruiting faculty and graduate stuidents • Diversification of revenue base and sources of research funding • Academic entrepreneurship has many faces (Clark, Davies) • Here we focus on commercialization of knowledge produced in universities • Most developed in the U.S., and U.S. model envied for European universities by many Fußzeile

  4. Background and motivation • But the entrepreneurial turn has been controversial • Appropriate role(s) of universities in globalized, knowledge-based economy • Potential conflicts of interest • Loss of commitment to norm of open science? • ‘Haves and have nots’ and the allocation of resources • Faculty researchers as the agents and drivers of economic development and commercialization • So their attitudes matter in what universities choose to do and in their effectiveness Fußzeile

  5. Principal Research questions SEITE 5 • Do faculty make a distinction between university involvement to support economic development and knowledge commercialization? • What are most important explanatory factors of faculty attitudes towards each type of university activity? • Discipline • Individual characteristics • Institutional • Regional economic conditions • Are there differences between U.S. and EU faculty attitudes? Fußzeile

  6. Methods and data SEITE 6 • Stratified samples of universities and faculty in the US and selected countries of Europe. • Selected (and a common subset of) disciplines. • Random sampling of faculty stratified by rank within selected universities and disciplines (US) and all faculty from selected universities and disciplines in Europe -- Shanghai 1-500*). • Web-based survey of a set of attitudinal questions posed to faculty about their agreement or disagreement about university activities involving ED and commercialization • Responses to attitudinal questions measured on five-point Likert scale * All universities in Austria and Switzerland Fußzeile

  7. Methods and data SEITE 7 Use of descriptive statistics to show variation in attitudes by faculty characteristics, discipline, university type, and continental location Use of ordered logit models to explain variation in faculty attitudes (separate samples) Fußzeile

  8. Methods and data SEITE 8 DisciplineType* Physics Bohr Biology Bohr Chemical engineering Pasteur Computer science Pasteur Economics North History North * Classification from Donald Stokes (1997) Pasteur’s Quadrant Fußzeile

  9. Attitudinal questions My university should be actively and directly involved in assisting state and regional economic development (dependent variable) My university should be actively involved in the commercialization of university-based research (dependent variable) My university should encourage/reward faculty for engaging in proprietary research with industry funding (independent variable) To what extent is it appropriate for scholarly findings to be delayed for circulation and peer review for six months in order to benefit the private industry funding source (independent variable) Responses to questions coded on a Likert scale: (5) Strongly agree; (4) Agree; (3) Neither agree nor disagree; (2) Disagree; (1) Strongly disagree

  10. Sample of U.S. Research Universities *Based upon Carnegie Foundation for the Advancement of Teaching (2006), Classification of Institutions of Higher Education

  11. Distribution of EU faculty respondents Country Freq Percent Country Freq Percent Austria 118 6.6 Belgium 56 3.1 Switzerland 125 7.0 Czech 12 0.7 Germany 514 28.6 Denmark 71 4.0 Estonia 62 3.5 Finland 33 1.8 France 138 7.7 Greece 16 0.9 Hungary 26 1.5 Ireland 26 1.5 Italy 117 6.5 Netherlands 161 9.0 Poland 21 1.2 Portugal 16 0.9 Sweden 49 2.7 Slovenia 8 0.4 UK 229 12.7 TOTAL 1798 100.0 Fußzeile

  12. Descriptive results U.S.: percent disagree or strongly disagree • Overall University involvement in ED 14.9 % University involvement in commercialization 32.5 • Significant variation by discipline • University involvement in ED • Econ (20.0%) Computer science (8.0%) • University involvement in commercialization • History (57.4%) Computer science (14.5%) • Slightly higher disapproval in highest research intensity category (both activities) • Faculty in private universities more disapproving of university involvement in ED Fußzeile

  13. Descriptive results, U.S: percent disagree or strongly disagree • Previous patenting activity matters: Previous patent applicant YesNo University involvement in ED 7.3% 16.8% University involvement in commercialization 11.8 37.2 Serves as benchmark indicator Fußzeile

  14. Descriptive results, EU: percent disagree or strongly disagree • Overall University involvement in ED 16.5% University involvement in commercialization 29.9 • Variation by discipline University involvement in ED Physics (20.3) . . . . . Chemengr (7.7) University involvement in commercialization History (45.5) . . . . . . Chemengr (20.3) • Variation by EU macro-region University involvement in ED Nordic (18.5) . . . . . Mediterranean (11.1) University involvement in commercialization Mid-core (33.2) . . . . . EU-10 (19.4) Fußzeile

  15. Explaining variation in faculty attitudes: hypotheses • Discipline(Stokes) • Pasteur (+/+) • Bohr (-/-) • North (?/-) • Individual characteristics • Rank (?/-) • Experience (?/-) • Industry funding (+) • Industry consulting (+) • Patenting (+) • Belief in open science (?/-) • Institutional • Public/private (U.S) (+/?) • Research intensity (US) (-/-) • Shanghai ranking (-/-) • % ind research funding (?/+) • Invention disclosures/$ (?/+) • Medical school (?/+) • Engineering school (EU) (?/+) • Regional • PCPY (?) • LQ mfg (+/?) • Empl growth rate (-/?) • UE rate (+/?) • Mass layoffs (+/?) • Industry R&D intensity (-/+) • Region (dummies) (?/?) Fußzeile

  16. U.S.: University should be actively involved with ED Ordered logistic regression Number of obs = 368 LR chi2(34) = 113.07 Prob > chi2 = 0.0000 Log likelihood = -274.27734 Pseudo R2 = 0.1709 ------------------------------------------------------------------------------ q4_3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- chemeng | -.2774317 .4452034 -0.62 0.533 -1.150014 .5951509 econ | -.7563415 .3546252 -2.13 0.033 -1.451394 -.061289 phys | .6983022 .4222608 1.65 0.098 -.1293138 1.525918 compsci | .4787556 .4242345 1.13 0.259 -.3527287 1.31024 assoc_and_~l | -.370131 .3558061 -1.04 0.298 -1.067498 .3272361 exp014 | -.3792522 .3673767 -1.03 0.302 -1.099297 .3407929 exp1529 | .3508033 .3552857 0.99 0.323 -.3455439 1.047151 q20_yn_01 | -.1984728 .5429527 -0.37 0.715 -1.26264 .8656949 q21_yn_01 | .3097257 .2976218 1.04 0.298 -.2736023 .8930537 Q22_med | -.4257128 .3322205 -1.28 0.200 -1.076853 .2254274 Q22_high | -.4755033 .3513959 -1.35 0.176 -1.164227 .21322 q23_low | -.2448904 .5211301 -0.47 0.638 -1.266287 .7765059 q23_high | -.4866258 .557352 -0.87 0.383 -1.579016 .605764 q24_yn_01 | .7505275 .3584193 2.09 0.036 .0480386 1.453016 q2_univtype | -.3313509 .1764768 -1.88 0.060 -.677239 .0145372 aau | .3209625 .3978514 0.81 0.420 -.458812 1.100737 sh51100 | .8805435 .4182136 2.11 0.035 .0608599 1.700227 sh101200 | .8710872 .5232926 1.66 0.096 -.1545474 1.896722 sh201300 | .7532582 .4530466 1.66 0.096 -.1346969 1.641213 sh301400 | .621094 .5240402 1.19 0.236 -.406006 1.648194 sh401500 | 1.230354 .6489442 1.90 0.058 -.0415535 2.502261 researchty~n | .9602581 .4437914 2.16 0.030 .0904428 1.830073 indtotrd | 1.412329 2.779518 0.51 0.611 -4.035425 6.860083 pcpy06 | -.0117321 .0079411 -1.48 0.140 -.0272964 .0038322 lq06 | -.2433352 .4180016 -0.58 0.560 -1.062603 .5759329 totempchange | -3.099611 3.430109 -0.90 0.366 -9.822501 3.623279 indrdou~2005 | .2119454 .1427355 1.48 0.138 -.0678111 .4917019 q9_dummy_1 | -1.14908 .3386823 -3.39 0.001 -1.812885 -.4852748 q9_dummy_3 | -.7857658 .3640272 -2.16 0.031 -1.499246 -.0722855 q16_dummy_1 | -1.028757 .4500791 -2.29 0.022 -1.910896 -.1466185 q16_dummy_3 | -.8822719 .4835235 -1.82 0.068 -1.829961 .0654168 cregion_mw | -.8613339 .4304636 -2.00 0.045 -1.705027 -.0176408 cregion_ne | -.5685966 .4703256 -1.21 0.227 -1.490418 .3532246 cregion_so~h | .199895 .4282162 0.47 0.641 -.6393932 1.039183 -------------+---------------------------------------------------------------- /cut1 | -5.291281 1.413654 -8.061992 -2.52057 /cut2 | -3.701605 1.398076 -6.441784 -.9614266 ------------------------------------------------------------------------------ Fußzeile

  17. U.S.: University should be involved with commercialization Ordered logistic regression Number of obs = 369 LR chi2(33) = 140.87 Prob > chi2 = 0.0000 Log likelihood = -299.71501 Pseudo R2 = 0.1903 ------------------------------------------------------------------------------ q6_3 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- chemeng | .4748916 .4930311 0.96 0.335 -.4914316 1.441215 econ | 1.013096 .3852081 2.63 0.009 .2581022 1.76809 phys | 1.454683 .4425455 3.29 0.001 .5873103 2.322057 bio | .9267482 .4290077 2.16 0.031 .0859086 1.767588 compsci | 1.126667 .4461066 2.53 0.012 .252314 2.00102 exp014 | -.4108497 .3109265 -1.32 0.186 -1.020254 .1985551 exp1529 | -.3286829 .3405442 -0.97 0.334 -.9961373 .3387715 q21_yn_01 | .5432864 .2866428 1.90 0.058 -.0185233 1.105096 Q22_med | -.1825356 .2992453 -0.61 0.542 -.7690455 .4039743 Q22_high | .5574893 .3570385 1.56 0.118 -.1422933 1.257272 q23_low | -.5298477 .3484824 -1.52 0.128 -1.212861 .1531652 q24_yn_01 | .620841 .3464784 1.79 0.073 -.0582441 1.299926 sh150 | -1.312808 .7261972 -1.81 0.071 -2.736129 .110512 sh51100 | -.6776288 .7990957 -0.85 0.396 -2.243828 .8885699 sh101200 | -1.002501 .6771356 -1.48 0.139 -2.329663 .32466 sh201300 | -1.279875 .5553299 -2.30 0.021 -2.368301 -.191448 sh301400 | -.2977393 .4458374 -0.67 0.504 -1.171564 .5760859 researchty~n | -.8939407 .5383451 -1.66 0.097 -1.949078 .1611964 indtotrd | -4.386909 2.794892 -1.57 0.117 -9.864796 1.090978 lq06 | .4791063 .4035064 1.19 0.235 -.3117517 1.269964 lqchange | -2.039148 1.187414 -1.72 0.086 -4.366436 .2881405 ue06 | -.3349613 .192625 -1.74 0.082 -.7124994 .0425767 totempchange | 1.911899 3.019159 0.63 0.527 -4.005543 7.829341 indrdou~2005 | -.1459849 .1397301 -1.04 0.296 -.4198509 .1278811 layoffs | 127.6204 42.27056 3.02 0.003 44.77164 210.4692 q9_dummy_1 | -1.70505 .3224376 -5.29 0.000 -2.337016 -1.073084 q9_dummy_3 | -1.025515 .340981 -3.01 0.003 -1.693825 -.357204 q16_dummy_1 | -.6725623 .3854949 -1.74 0.081 -1.428118 .0829938 q16_dummy_3 | -.5302978 .431227 -1.23 0.219 -1.375487 .3148916 cregion_mw | .3121079 .4157213 0.75 0.453 -.5026909 1.126907 cregion_so~h | .4247333 .3393699 1.25 0.211 -.2404194 1.089886 med_school | .2802773 .2937893 0.95 0.340 -.295539 .8560937 inv_rate | 1.116077 .5469235 2.04 0.041 .0441266 2.188027 -------------+---------------------------------------------------------------- /cut1 | -3.014562 1.321474 -5.604604 -.4245202 /cut2 | -1.818177 1.3146 -4.394745 .7583907 ------------------------------------------------------------------------------ Marshall‘s Dilemma

  18. EU: University should be actively involved in ED Ordered logistic regression Number of obs = 1453 LR chi2(28) = 349.80 Prob > chi2 = 0.0000 Log likelihood = -1170.9338 Pseudo R2 = 0.1300 ------------------------------------------------------------------------------ q18a_135_rev | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- Contract | -.1982618 .1465082 -1.35 0.176 -.4854126 .088889 exp0_14 | -.100019 .1937699 -0.52 0.606 -.4798011 .279763 exp15_29 | .1950201 .1912957 1.02 0.308 -.1799127 .5699528 companies_01 | .4544623 .1538127 2.95 0.003 .1529949 .7559297 consult_01 | .5803924 .4871522 1.19 0.233 -.3744084 1.535193 patent_01 | .2510551 .3320711 0.76 0.450 -.3997924 .9019026 sh150 | -.5869855 .2791903 -2.10 0.036 -1.134188 -.0397826 sh51100 | -.274859 .2099454 -1.31 0.190 -.6863444 .1366265 dat3_gd~2006 | .0005808 .0007651 0.76 0.448 -.0009188 .0020805 lqmfg2007 | -.1958273 .1798087 -1.09 0.276 -.548246 .1565913 ltu_une~2006 | -.0103031 .027826 -0.37 0.711 -.0648411 .0442349 dat3_dgdpk~6 | 1.814915 .7019396 2.59 0.010 .4391385 3.190691 disc_chemeng | -.3445999 .3673951 -0.94 0.348 -1.064681 .3754813 disc_econ | .4266993 .2312067 1.85 0.065 -.0264574 .8798561 disc_phys | -.3899635 .1883641 -2.07 0.038 -.7591502 -.0207767 disc_bio | -.1707391 .1922553 -0.89 0.374 -.5475526 .2060745 disc_compsci | -.0826346 .2177126 -0.38 0.704 -.5093433 .3440742 q18d_12_rev | -2.013996 .1450839 -13.88 0.000 -2.298355 -1.729636 q18d_3_rev | -.9640724 .1419829 -6.79 0.000 -1.242354 -.685791 engineering | .4141597 .1237149 3.35 0.001 .171683 .6566364 medical | .1957439 .1395925 1.40 0.161 -.0778523 .4693401 vet_med | .0903484 .2126964 0.42 0.671 -.3265289 .5072258 agriculture | .1149499 .1758128 0.65 0.513 -.2296369 .4595367 leru | -.1649175 .2078027 -0.79 0.427 -.5722033 .2423683 student_rate | .0054982 .0081438 0.68 0.500 -.0104633 .0214598 rt_project~s | -2.10891 2.14983 -0.98 0.327 -6.322499 2.104679 ind_medite~n | .4879523 .1712736 2.85 0.004 .1522621 .8236424 ind_nordic | .4077062 .4139763 0.98 0.325 -.4036725 1.219085 -------------+---------------------------------------------------------------- /cut1 | -2.484297 .3992082 -3.26673 -1.701863 /cut2 | -1.186142 .3943788 -1.95911 -.4131738 ------------------------------------------------------------------------------ Marshall‘s Dilemma

  19. EU: University should be involved in commercialization Ordered logistic regression Number of obs = 1288 LR chi2(30) = 333.67 Prob > chi2 = 0.0000 Log likelihood = -1184.3367 Pseudo R2 = 0.1235 ------------------------------------------------------------------------------ q18f_135_rev | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- Contract | -.0187228 .1477087 -0.13 0.899 -.3082264 .2707809 exp0_14 | -.0613874 .129457 -0.47 0.635 -.3151186 .1923437 companies_01 | .4686737 .1462108 3.21 0.001 .1821057 .7552416 consult_01 | .9914511 .4640323 2.14 0.033 .0819645 1.900938 patent_01 | .0641408 .321093 0.20 0.842 -.5651899 .6934715 sh150 | .1743528 .3514192 0.50 0.620 -.5144162 .8631218 sh51100 | .0849283 .2706132 0.31 0.754 -.4454638 .6153205 sh101200 | -.2537065 .1849187 -1.37 0.170 -.6161404 .1087275 sh201300 | -.0843806 .185476 -0.45 0.649 -.4479069 .2791456 dat3_gd~2006 | -.000974 .0007483 -1.30 0.193 -.0024407 .0004927 lqmfg2007 | -.0974941 .2037375 -0.48 0.632 -.4968122 .301824 ltu_une~2006 | -.0501626 .0306209 -1.64 0.101 -.1101784 .0098532 dat3_dgdpk~6 | 1.590551 .705247 2.26 0.024 .2082918 2.972809 dat3_ue~2007 | .0019042 .0020592 0.92 0.355 -.0021318 .0059402 disc_chemeng | .0748903 .3526597 0.21 0.832 -.6163099 .7660906 disc_econ | .2489602 .2174119 1.15 0.252 -.1771592 .6750797 disc_phys | .5311514 .1919219 2.77 0.006 .1549914 .9073113 disc_bio | .6132367 .1954137 3.14 0.002 .230233 .9962405 disc_compsci | .5059075 .2178277 2.32 0.020 .078973 .932842 q18d_12_rev | -2.035372 .1495323 -13.61 0.000 -2.328449 -1.742294 q18d_3_rev | -.8280905 .1373886 -6.03 0.000 -1.097367 -.5588138 engineering | .2475711 .1243221 1.99 0.046 .0039043 .4912378 medical | .0781089 .1584178 0.49 0.622 -.2323844 .3886022 vet_med | .0490411 .2139271 0.23 0.819 -.3702483 .4683306 agriculture | -.1953275 .173464 -1.13 0.260 -.5353108 .1446558 leru | .2588938 .2338298 1.11 0.268 -.1994041 .7171918 student_rate | -.0018907 .0079877 -0.24 0.813 -.0175462 .0137649 rt_project~s | .5348898 2.251375 0.24 0.812 -3.877723 4.947503 ind_medite~n | .3415111 .1987393 1.72 0.086 -.0480108 .7310331 ind_nordic | .3520397 .3986547 0.88 0.377 -.4293092 1.133389 Marshall‘s Dilemma

  20. Are EU University Faculty More (or Less) Supportive than U.S. Faculty of Academic Entrepreneurship? • Considerable pressure and high expectations from EC and national governments to stimulate university-based knowledge to help close the „knowledge economy“ gap with the U.S. (Lisbon Objectives, European Research Area, etc) • Research universities beginning to benefit from renewed policy attention, after 50 years of comparatively heavy focus on mass education • Universities have recently gained „Bayh-Dole“ capabilities and installed TTOs, although professors previously held such privileges (Swedish and Italian professors still do) • Renewed stress on „intangible assets“ locked away in universities

  21. Results/tentative conclusions 1. Attitudes towards university involvement in ED and commercialization are different for both U.S. and EU 2.a. For university involvement in ED (U.S. case) • Individual and institutional characteristics strongest • Patenting, open science, public univ, 2nd tier • Regional economic conditions hardly matter • Discipline (other than economics) does not matter • Consensual? 2.b. For university involvement in commercialization (U.S.) • Discipline and attitudes towards open science strongest • Faculty in regions undergoing restructuring more favorable • Mfg concentration falling, high level mass layoffs • Entrepreneurial culture (invention disclosures/$) Fußzeile

  22. Results/tentative conclusions 2.c. For university involvement in ED (EU case) • Individual: privind funding, open science (-) • Institutional: engineering, not first tier unis • Regional: PCPY (+), Mediterranean 2.d. For university involvement in commercialization (EU) • Discipline • Individual: open science, privind ties • Institutional: engineering Explanatory power of all models is modest (pseudo R2) • Responses from attitudinal questions often are unreliable >> noise • ‘Objective’ factors not as important; harder to measure factors related to socialization and culture Fußzeile

  23. Results/tentative conclusions 3. Despite more pressure in EU (playing catch-up), differences between US and EU cases are small • Distinction between attitudes towards ED and commercialization are very similar Percent disagree/strongly disagree U.S.EU ED 14.9 16.5 Commercialization 32.5 29.9 • Both US and EU • Individual factors and discipline matter less for ED • Regional economic conditions more important for commercialization Fußzeile

  24. Results/tentative conclusions • Why don’t regional economic conditions matter that much? • H: Faculty are members of ‘multiple communities’ that span region • H: Faculty attitudes are formed earlier (e.g., in graduate school) and may not be so malleable even when one’s environment changes • Why do individual factors trump institutional factors? • H: An entrepreneurial climate in an institution is created by self-selection in recruitment, rather than through organizational change Fußzeile

  25. Results/tentative conclusions • Will/should university faculty become drivers of innovation for their regions? • In U.S and EU they will be one set of actors, but not the dominant ones • In EU maybe less likely to obstruct commercialization • A number of norms and values conflict with AE are still strongly valued • Open science • Academic freedom • Knowledge as a ‘public good’ • Avoidance of conflicts of interest (but less concern in EU) • As universities take the ‘entrepreneurial turn’, trend towards separate organizational structure and rules Fußzeile

  26. Defining University Research Options & Origins: The Quadrants EU: ERC US: NSF EU: FPs (national labs) US: NIH/DOD/DOE Mass Education Corporate & private R&D

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