universities and R&d labs for technology scouting and idea sourcing show a higher innovation performance.
growth, Journal of International Business studies, 42 (3), pp. 362-380 30. Hamill J. and Gregory K. 1997.
Harvard Business school Press 68. Terziovski M. 2010. Innovation practice and its performance implications in small and medium enterprises
Flanders DC focuses on entrepreneurs, teachers, students, policy-makers and the general public Among the many options Flanders DC offers are:
a free online training in creative thinking, a creativity test, a brainstorm kit, invite an entrepreneur to speak in your class
Bedenkers (The Inventors) classroom competition and an online game to discover how you score as
ï How entrepreneurial are our Flemish students, Hans Crijns and Sabine Vermeulen, November 2007, published in English
following tools and training sessions ï Ondernemen. meerdan. ondernemen, an online learning platform ï Creativity Class for young high-potentials
ï Flanders DC Fellows, inspiring role models in business creativity ï Creativity Talks, monthly seminars on business creativity and innovation
innovation, which has received significant attention among strategy scholars, is beyond the scope of this report
At the end of Chapters 2 to 6, we include key learning points. These lists of learning points can be consulted as a checklist
when you are setting up a new business with your innovation partners. These learning points are gathered at the end of each chapter
so you can easily check them whenever you want a quick review of what you have learned
in Danish hospitals, including the Glostrup Hospital of the University of Copenhagen. These contacts introduced the founders to the science of sleep and the clinical practice of sleep medic ine.
learning process led by sleep experts. The QOD case illustrates that developing a successful business model that ultimately changes the industry starts with nothing more than the conviction of a well
universities, research labs, and lead-customers. New technologies thus offer opportunities for small firms even in the so-called low-tech industry such as textiles, furniture, bicycles, food, and so on
developed at universities, research labs, or large companies. Finally, small firms must make choices 32
Dingens wanted to collaborate with the University of Hasselt and knowledge partner Sirris to develop a completely new instrument The new barometer should have the same advantages of the
longer be limited to university and corporate spin-offs. Start-ups can use their organizational agility application know-how,
universities or larger, technology-savvy companies. Isobionics illustrates this point. The company took a technology to market that had been abandoned at DSM at a speed that surprised both technology
Key Learning points ï Analyzing open innovation in SMES in traditional industries starts with conceiving and
such as a learning innovation network, design networks, research programs, and so on. Design was the second step.
Examples include newsletters from universities and knowledge centers and publications of Design Vlaanderen, among others.
such as universities, research labs, and knowledge intermediaries. This strong reliance on value chain partners is partially due to the fact that most companies are active in low-and medium-tech industries
such as the Glostrup Hospital of the University of Copenhagen. After setting up an examination board
where universities would be invited to participate in the product days with their own ideas. They would also have access to factory resources
Key Learning Points Open innovation as an integral part of business model innovations In the past, the open innovation literature has focused too much on the direct benefits of open
Universities, research labs, crowds of experts, lead users, and knowledge brokers are just a few examples of potential external sources of kn owledge.
new flavors has traditionally been completed with different universities in Europe, with DSM, and with other innovation partners.
including several European universities, research labs, DSM and other value chain partners. The technology licensed from DSM is a technological plat form that can
to universities, technology labs, and commercial partners. Third, DSM was a formidable partner for Isobionics in the further development and continuous technical support of Isobionics†products.
are increasingly aware of the growing technological capabilities of universities, research labs, and high-tech start-ups.
Philips relies recurrently on new technologies from universities, specialized research labs, and high-tech start-ups. The electronic giant endeavors to be preferred the partner for
ï Small firms should do their homework before they start collaborating with large companies Some large companies are trustworthy innovation partners because they recurrently
Partners may be technology partners such as universities, research labs, or other companies but in most cases these are not the most important partners in the network.
One of the major learning points to emerge from the cases is that open innovation networks are sustainable only when the value that is jointly created is
and deepen learning about open innovation among entrepreneurs One way to accelerate the use of open innovation in small firms is to diffuse successful cases using
institutional sources (universities and university colleges (v), government and public research organizations (vi)), and other available sources (professional
and industrial associations (vii), trade fairs, exhibitions, and conferences (viii), scientific journals and trade/technical publications (ix.
) universities (v; and public research organizations (vi. Collaborative innovation is captured by calculating the average score of the six questionnaire items registering the firm†s use of coopera tive agreements with
technology, Harvard Business school Press, Harvard: Boston: MA and Chesbrough, H. W. 2006), Open business models: How to thrive in the new innovation landscape, Harvard Business school Press, Harvard
Boston: MA 4 Van de Vrande, V.,De Jong J. P. J.,Vanhaverbeke, W. and De Rochemont, M. 2009), Open innovation in
technology, Harvard Business school Press, Harvard: Boston: MA and Chesbrough, H. W. 2006), Open business models: How to thrive in the new innovation landscape, Harvard Business school Press, Harvard
Boston: MA 7 Chesbrough, H. W. 2007), Why companies should have open business models, MIT Sloan Management
The business model ontology †a proposition in a design science approach, Ph d. Thesis University Lausanne, Ecole des Hautes Etudes Commerciales HEC. 173 p;
creating and profiting from technology, Harvard Business school Press, Harvard: Boston; and Chesbrough, H. W. and Rosenbloom, R. S. 2002), The role of the business model in capturing
Business school Press, Harvard: MA; Christensen, C. M. 1997), The innovator†s dilemma: When new technologies cause great firms to fail, Harvard Business school Press, Harvard:
MA. Christensen, C. M 1997), The innovator†s solution: Creating and sustaining successful growth, Harvard Business school Press
Harvard: MA 19 This is exactly what Mcgrath and Macmillan call discovery driven growth. Many of the issues on which she
Harvard Business school Press, Boston: MA 97 21 These conditions have been analysed in detail by Gans, J. S and Stern, S. 2003), The product market and
mean for strategy, innovation and sustainability, Harvard Business school Press, Boston, MA 28 There is a rapidly growing literature stream.
Networks of learning in biotechnology, Administrative Science Quarterly, 41,116-145 32 In 2006, Netflix, a major movie rental company, organized a crowdsourcing contest on the Internet.
sustainability, Harvard Business school Press, Boston: MA; and Allee, V. 2008), Value network analysis and value conversion of tangible and intangible assets, Journal of Intellectual Capital, 9, 1, 5-24
Authenticity, Harvard Business school Press, Boston: MA Chapter 5 35 Katila, R. Rosenberger, J. D.,Eisenhardt K. M. 2008), Swimming with Sharks:
Harvard Business school Press, Boston, MA.;and Vanhaverbeke, W.,Van de Vrande, V. and Chesbrough H. 2008.
*RSM Erasmus University E-mail: vvrande@rsm. nl Jeroen P. J. De Jong EIM Business and Policy Research
Hasselt University, Faculty of business Studies E-mail: wim. vanhaverbeke@uhasselt. be Maurice de Rochemont Eindhoven University of Technology
E-mail: m d. rochemont@tm. tue. nl February 2008 *Corresponding author Vareska van de Vrande RSM Erasmus University
Department of Strategic Management and Business Environment Room T7-33 P o box 1738,3000 DR Rotterdam, The netherlands
as startups, universities, suppliers, or even competitors to stay competitive in the long run Open innovation is thus a broad concept,
into research collaborations with universities (e g. George et al. 2002). ) Without academic research outcomes many innovations could not have been realized or would
missing external inputs into the learning process which the firm itself cannot (easily provide (Romijn and Albaladejo, 2002;
movement towards open innovation is related to a different approach of universities research labs and companies vis-Ã-vis technology and IP.
public knowledge centers (e g. universities), customers, suppliers, and investors (e g banks, venture capital firms 20 Finally, we looked at the degree firms participate by equity investments in new
The proximity of universities, research labs, large companies and lead users may play a role in the deployment of open innovation in SMES.
Harvard Business school Press: Boston, MA Chesbrough, H.,2006. Open business models: How to thrive in a new innovation
Harvard Business school Press: Boston, MA Chesbrough, H.,Crowther, A k.,2006. Beyond high tech: early adopters of open
Harvard Business school, Boston: MA Christensen, J-F.,Oleson, M. H.,Kjã r, J. S.,2005.
Advance, in Challenges to the University, Brookings Institution Press WASHINGTON DC Cooke, P.,2006. Regional Knowledge Capabilities and open innovation:
University Press Cooper, R. G.,Kleinschmidt, E. J.,1995. Benchmarking the firm's critical success
The effects of business-university alliances on innovative output and financial performance: A study of publicly
H200703 26-1-2007 Family orientation, strategy and organizational learning as predictors of knowledge management in Dutch SMES
deindhoven University of Abstract †437 otives and management challenges de Jongb, Wim Vanhaverbekec ochemontd
asselt University, Belgium nology, The netherlands www. elsevier. com/locate/technovation ARTICLE IN PRESS chn innovation practices and whether there is a trend towards
standards, to proï t from infringements, to realize learning effects, and to guarantee freedom to operate by establish
universities, public research organizations, commercial engineers or suppliers Inward IP licensing Buying or using intellectual property, such as patents
The ï rst component reï ects the practices of employee involvement, external involve -ment and external networking.
study should encourage scholars to analyze in greater depth open innovation in SMES. First and foremost, our
Harvard Business school Press, Boston, MA Chesbrough, H.,2006. Open Business models: How to Thrive in a New
Harvard Business school Press, Boston, MA Chesbrough, H.,Crowther, A k.,2006. Beyond high tech: early adopters of open innovation in other industries.
University Press, Cambridge Singh, J.,1990. A typology of consumer dissatisfaction response styles Journal of Retailing 661, 57†99
deindhoven University of Abstract †437 otives and management challenges de Jongb, Wim Vanhaverbekec ochemontd
asselt University, Belgium nology, The netherlands www. elsevier. com/locate/technovation ARTICLE IN PRESS chn innovation practices and whether there is a trend towards
standards, to proï t from infringements, to realize learning effects, and to guarantee freedom to operate by establish
universities, public research organizations, commercial engineers or suppliers Inward IP licensing Buying or using intellectual property, such as patents
The ï rst component reï ects the practices of employee involvement, external involve -ment and external networking.
study should encourage scholars to analyze in greater depth open innovation in SMES. First and foremost, our
Harvard Business school Press, Boston, MA Chesbrough, H.,2006. Open Business models: How to Thrive in a New
Harvard Business school Press, Boston, MA Chesbrough, H.,Crowther, A k.,2006. Beyond high tech: early adopters of open innovation in other industries.
University Press, Cambridge Singh, J.,1990. A typology of consumer dissatisfaction response styles Journal of Retailing 661, 57†99
Flanders DC focuses on entrepreneurs, teachers, students, policy-makers and the general public Among the many options Flanders DC offers are:
a free online training in creative thinking, a creativity test, a brainstorm kit, invite an entrepreneur to speak in your class
Bedenkers (The Inventors) classroom competition and an online game to discover how you score as
ï How entrepreneurial are our Flemish students, Hans Crijns and Sabine Vermeulen, November 2007, published in English
following tools and training sessions ï Ondernemen. meerdan. ondernemen, an online learning platform ï Creativity Class for young high-potentials
ï Flanders DC Fellows, inspiring role models in business creativity ï Creativity Talks, monthly seminars on business creativity and innovation
innovation, which has received significant attention among strategy scholars, is beyond the scope of this report
At the end of Chapters 2 to 6, we include key learning points. These lists of learning points can be consulted as a checklist
when you are setting up a new business with your innovation partners. These learning points are gathered at the end of each chapter
so you can easily check them whenever you want a quick review of what you have learned
in Danish hospitals, including the Glostrup Hospital of the University of Copenhagen. These contacts introduced the founders to the science of sleep and the clinical practice of sleep medic ine.
learning process led by sleep experts. The QOD case illustrates that developing a successful business model that ultimately changes the industry starts with nothing more than the conviction of a well
universities, research labs, and lead-customers. New technologies thus offer opportunities for small firms even in the so-called low-tech industry such as textiles, furniture, bicycles, food, and so on
developed at universities, research labs, or large companies. Finally, small firms must make choices 32
Dingens wanted to collaborate with the University of Hasselt and knowledge partner Sirris to develop a completely new instrument The new barometer should have the same advantages of the
longer be limited to university and corporate spin-offs. Start-ups can use their organizational agility application know-how,
universities or larger, technology-savvy companies. Isobionics illustrates this point. The company took a technology to market that had been abandoned at DSM at a speed that surprised both technology
Key Learning points ï Analyzing open innovation in SMES in traditional industries starts with conceiving and
such as a learning innovation network, design networks, research programs, and so on. Design was the second step.
Examples include newsletters from universities and knowledge centers and publications of Design Vlaanderen, among others.
such as universities, research labs, and knowledge intermediaries. This strong reliance on value chain partners is partially due to the fact that most companies are active in low-and medium-tech industries
such as the Glostrup Hospital of the University of Copenhagen. After setting up an examination board
where universities would be invited to participate in the product days with their own ideas. They would also have access to factory resources
Key Learning Points Open innovation as an integral part of business model innovations In the past, the open innovation literature has focused too much on the direct benefits of open
Universities, research labs, crowds of experts, lead users, and knowledge brokers are just a few examples of potential external sources of kn owledge.
new flavors has traditionally been completed with different universities in Europe, with DSM, and with other innovation partners.
including several European universities, research labs, DSM and other value chain partners. The technology licensed from DSM is a technological plat form that can
to universities, technology labs, and commercial partners. Third, DSM was a formidable partner for Isobionics in the further development and continuous technical support of Isobionics†products.
are increasingly aware of the growing technological capabilities of universities, research labs, and high-tech start-ups.
Philips relies recurrently on new technologies from universities, specialized research labs, and high-tech start-ups. The electronic giant endeavors to be preferred the partner for
ï Small firms should do their homework before they start collaborating with large companies Some large companies are trustworthy innovation partners because they recurrently
Partners may be technology partners such as universities, research labs, or other companies but in most cases these are not the most important partners in the network.
One of the major learning points to emerge from the cases is that open innovation networks are sustainable only when the value that is jointly created is
and deepen learning about open innovation among entrepreneurs One way to accelerate the use of open innovation in small firms is to diffuse successful cases using
institutional sources (universities and university colleges (v), government and public research organizations (vi)), and other available sources (professional
and industrial associations (vii), trade fairs, exhibitions, and conferences (viii), scientific journals and trade/technical publications (ix.
) universities (v; and public research organizations (vi. Collaborative innovation is captured by calculating the average score of the six questionnaire items registering the firm†s use of coopera tive agreements with
technology, Harvard Business school Press, Harvard: Boston: MA and Chesbrough, H. W. 2006), Open business models: How to thrive in the new innovation landscape, Harvard Business school Press, Harvard
Boston: MA 4 Van de Vrande, V.,De Jong J. P. J.,Vanhaverbeke, W. and De Rochemont, M. 2009), Open innovation in
technology, Harvard Business school Press, Harvard: Boston: MA and Chesbrough, H. W. 2006), Open business models: How to thrive in the new innovation landscape, Harvard Business school Press, Harvard
Boston: MA 7 Chesbrough, H. W. 2007), Why companies should have open business models, MIT Sloan Management
The business model ontology †a proposition in a design science approach, Ph d. Thesis University Lausanne, Ecole des Hautes Etudes Commerciales HEC. 173 p;
creating and profiting from technology, Harvard Business school Press, Harvard: Boston; and Chesbrough, H. W. and Rosenbloom, R. S. 2002), The role of the business model in capturing
Business school Press, Harvard: MA; Christensen, C. M. 1997), The innovator†s dilemma: When new technologies cause great firms to fail, Harvard Business school Press, Harvard:
MA. Christensen, C. M 1997), The innovator†s solution: Creating and sustaining successful growth, Harvard Business school Press
Harvard: MA 19 This is exactly what Mcgrath and Macmillan call discovery driven growth. Many of the issues on which she
Harvard Business school Press, Boston: MA 97 21 These conditions have been analysed in detail by Gans, J. S and Stern, S. 2003), The product market and
mean for strategy, innovation and sustainability, Harvard Business school Press, Boston, MA 28 There is a rapidly growing literature stream.
Networks of learning in biotechnology, Administrative Science Quarterly, 41,116-145 32 In 2006, Netflix, a major movie rental company, organized a crowdsourcing contest on the Internet.
sustainability, Harvard Business school Press, Boston: MA; and Allee, V. 2008), Value network analysis and value conversion of tangible and intangible assets, Journal of Intellectual Capital, 9, 1, 5-24
Authenticity, Harvard Business school Press, Boston: MA Chapter 5 35 Katila, R. Rosenberger, J. D.,Eisenhardt K. M. 2008), Swimming with Sharks:
Harvard Business school Press, Boston, MA.;and Vanhaverbeke, W.,Van de Vrande, V. and Chesbrough H. 2008.
mechanisms that foster severe selection of scholars from a large base, student and researcher mobility and strong institutional complementarity with user industries.
Engineering, Faculty of engineering, University of Pisa, Largo Lucio Lazzarino 1-56122 Pisa, Italy; Email: a. bonaccorsi
Andrea Bonaccorsi is professor of economics and man -agement at the University of Pisa, Italy.
His main research interests include: the economic analysis of the dynamics of scientific knowledge, the functional theory of technology
and empirical analysis of higher education. He has recently coordinated a large project for the publication of microdata
from all European higher education institutions European competitiveness: IT and long-term scientific performance Science and Public Policy August 2011 523
-mance criteria, and learning curves What is the relationship between technological progress in this industry and scientific progress in
-ence, in both European and US universities, to list the most important technological innovations in the
University research played a key role in the growth of the US computer industry. Universi -ties were important sites for applied, as well as
-tion of graduates who sought employment elsewhere, universities served as sites for the dissemination and diffusion of innovation
throughout the industry We briefly review some of the turning points in the history of computing in which this contribution is
-tween IBM and the University of Harvard, which was established in 1939 (Moreau, 1984 Interestingly, as early as in 1946 the Moore
School of the University of Pennsylvania and the US Army sponsored a course on the theory and tech
However, the role of the university was not unam -biguous: in the same year one administrator of the
universities building their own machines, based on Von neumann or Turing architectures The role of universities greatly increased after a
commercial move by IBM. In 1954 IBM delivered the 650, a machine that was installed mainly for
Watson Jr decided that a university could benefit from a discount up to 60%on the price of the 650 if
that university agreed to offer courses in business data processing or scientific computing (Watson 1990). ) This opened the way to a large diffusion of
courses in computer science across US universities Meanwhile, US universities started to be involved in research on the component technologies underly
-ing the computer. Soon after WWII, the University European competitiveness: IT and long-term scientific performance
Science and Public Policy August 2011 526 of Illinois, Harvard and Massachusetts Institute of Technology (MIT) worked on magnetic core memo
convened by F L Bauer from the University of Mu -nich (Germany) in 1958, and COBOL was promoted
by a group of universities and computer users which held a meeting at the Computation Center of the
University of Pennsylvania in 1959. In turn, the LISP LANGUAGE was developed by John Mccarthy at MIT in 1958 (Moreau, 1984), PASCAL was devel
French researchers mostly based at the University of Marseille (Colmerauer and Roussel, 1996. As with
Universities did not play a direct sci -entific role in this massive bottom-up effort, but were a crucial element for the mass culture that
-uate studies at universities, but benefit from an envi -ronment in which new ideas are generated and
dean of the School of engineering and then provost at Stanford, promoted large military patronage in electronics and then supported graduate engineers in
the creation of new corporations (for a critical view see Lowen, 1997. Other studies have confirmed, but
how Stanford students benefitted from updates in technology provided by companies located in the area, creating two-way technology flows
and desires of (â€) university researchers eager to investigate new computing techniques Throughout its entire life, IPTO followed the rules
Universities changed their role in the early histo -ry: in the heroic period until 1959 they were directly
-mitted to fundamental research, education, scientific advice and consultancy Historical evidence on the role of the
Two university groups were active in that period in the UK, one at Man -chester and another at Cambridge.
with the Manchester University Group and delivered in 1951. A commercial computer, known as LEO was installed at a company in 1951, well before
strong linkages with universities, particularly in Paris and Grenoble, and PROS The link between academic research and indus
universities were involved directly in the produc -tion of prototypes. With the advent of the 1960s
bring a diminishing role for universities, but a re -design or their role around fundamental research
education, scientific advice and consultancy. In Europe, the academic environment was leading head-to-head with the US one until the 1960s, but
(or have their students develop software code in order to test their results. This is fa -cilitated by the fact that the test of theories can be
-ments, populated with visionary professors, hard -working Phd students, brilliant undergraduate stu -dents, rather than of corporate laboratories.
The role of abstraction is crucial here. In technical terms, ab -straction means that there are sets of definitions that
the Moore School and the University of Iowa from Aiken and Wilkes to Algol, the vast
students. The two reputational processes reinforce each other and make it credible to raise government or private money for research
it cannot be said that university research has been the source of most inventions, it has played a promi
supporting the entrepreneurial attitude of students and graduate researchers. Also, deep and radically new ideas often originated in academic environ
We identified the location of the universities at which top scientists received their academic degrees Such information can be retrieved with certainty
for 855 scientists in the case of Phd, 457 for the Master degree and 641 for the Bachelor degree (see
US universities gave the degree to future top scientists in 76.5%of observable cases against 16.6%in the case of Europe.
concentration can be observed in the case of Master degrees. These degrees require a great deal of inter
step towards the Phd for talented students. Very in -terestingly, the geographical distribution is much
good 15%of students come from Asia and 10.9 %from other countries. It seems that the US academic
graduate students from all over the world, offering Master and Phd degrees as intermediate steps towards a scientific career
In evolutionary terms, it seems that the US aca -demic system has superior properties of variety gen
end of the 1960s the US universities had already granted 89 Phd degrees to those that eventually be
in the number of degrees in US universities, while the same is not true for European universities.
This finding sheds light on the puzzle identified in the section of this paper on †Technological competitive
Area Phd degree Master degree Bachelor degree Number%Number%Number %USA 654 76.5 332 72.6 363 56.6
universities were able to attract 207 high potential candidates(+55%with respect to the previous decade), against only 37 at European institutions
-riod, probably a manifestation of the accumulation of weaknesses It is highly informative to examine the identity of
those universities that granted undergraduate and postgraduate degrees to those brilliant scientists in their early days.
the distribution of universities, because we are more interested in understanding the dynamics at the ex
Therefore we select the top 15 universities in which the top scientists have received their degree
at each of the three levels of education, i e. Phd Master, and Bachelor (see Table 4), in descending
The top 15 universities represent 56.2%of all universities granting a Phd to the 855 top scientists
for which we are able to reconstruct the information In turn, the top 15 universities represent 47.1%of
those granting the Master degree (n=457) and 41.3%of those granting the Bachelor (n=641.
The differences in the coverage rate shows that postgrad -uate education is concentrated more than undergrad
-uate. Nevertheless, the top 15 universities cover between 40%and almost 60%of the sample, a rea
-sonable proportion for our analysis We start from Phd education. A few comments are in order. First, the top ranking covers mostly US
universities, with two Europeans featuring in the 10th position (Cambridge, UK) and 14th position Edinburgh, UK) and a Canadian one in the 13th po
-sition (Toronto. Second, the distribution is highly concentrated. As stated, the first 15 universities at
-tract 56.2%of all scientists for whom we have full information. But this is not enough:
Table 4. Ranking of top 15 universities granting Phd, Master and Bachelor degrees to top scientists in computer science
Phd degree Master degree Bachelor degree Number%Number%Number %MIT 82 9. 6 47 10.3 45 7. 0
University of California at Berkeley 69 8. 1 27 5. 9 20 3. 1 Carnegie mellon University 43 5. 0 13 2. 8
Harvard university 35 4. 1 14 3. 1 25 3. 9 Cornell University 27 3. 2 12 2. 6 11 1. 7
Princeton university 26 3. 0 15 2. 3 University of Illinois 22 2. 6 12 2. 6
University of Michigan 20 2. 3 9 2. 0 18 2. 8 University of Cambridge 16 1. 9 18 2. 8
Yale university 15 1. 8 7 1. 5 14 2. 2 University of Wisconsin 14 1. 6 10 2. 2
University of Toronto 13 1. 5 7 1. 5 9 1. 4 University of Edinburgh 13 1. 5
University of Pennsylvania 13 1. 5 University of Massachusetts 8 1. 8 University of Washington 7 1. 5
University of California at Los angeles 7 1. 5 Indian Institute of technology 7 1. 5 34 5. 3
National Taiwan University 13 2. 0 California Institute of technology 12 1. 9 Technion Israel Institute of technology 11 1. 7
Brown University 10 1. 6 Total number of observations 855 457 641 Note: universities not in USA are in italics
European competitiveness: IT and long-term scientific performance Science and Public Policy August 2011 533 almost one-third of the total.
Third, a mutual rein -forcement mechanism is clearly in place. Brilliant students target top universities because there they
have the opportunity to meet and to work with the best scientists. Top universities actively target tal
-ented students to confirm their reputation. Postgrad -uate education seems to be a promising candidate to
explain the success of the scientific careers of these scientists. Understanding the extraordinary success of the US Phd model in turbulent fields is therefore
a key for policy learning When examining the distribution of universities granting the Master degree the top list is slightly dif
-ferent. There are a few new entries from the USA e g. University of Massachusetts and University of
California at Los angeles), but the most interesting new entry is the Indian Institute of technology which is not a single institution but an umbrella
organization for several universities The situation changes quite drastically when we move to the Bachelor degree, the entry point for stu
-dents considering a career in computer science. In this list the Indian Institute of technology ranks se -cond, contributing with 34 undergraduate students to
the flow of future star scientists. Interestingly, here we find many more universities outside the USA
from Europe (Cambridge), Taiwan (National Taiwan University), Israel (Technion Institute of technology and Canada (Toronto Our interpretation is as follows.
The talent pool for a career in computer science is worldwide. En -try points are good universities offering strong
basic scientific knowledge but also giving brilliant students sufficient motivation to emerge. After that stage, however, future top scientists must be chan
-nelled into foreign universities, most of which are in the USA. In preparing for this migration of
talent, Asian countries have been more strategic investing heavily into the preparation of undergrad -uate students to be selected
and sent to top US uni -versities. European universities, in contrast cultivate the ambition to organize graduate educa
-tion, particularly Phd education, in isolation. They actively practice endogamy, by selecting students from internal Master programmes, which in turn se
-lect bright students from the Bachelor. With few exceptions, European postgraduate education in computer science is not globally competitive.
If it were competitive we would see more students mi -grating from Asia and the rest of the world into
Europe, instead of the USA, and we would see more students moving from the USA to Europe.
In other words, Europe seems to play a game of lim -ited mobility Patterns of disciplinary mobility
Where do top computer scientists come from, in terms of disciplinary affiliations? The data do not al
-low a full-scale analysis, because we do not have control samples of scientists in related fields.
There -fore the evidence should be interpreted in terms of overall mobility, rather than of specific discipline-to
-discipline pathways. More than half of them gradu -ated either in mathematics or engineering, not com
-puter science (see Table 5). The entry point of a scientific career is not in the specialised field, but in
some of the underlying knowledge bases, either the -oretical or technical. Also interesting is the group of
graduate students in physics who are recognized as key leaders in computer science Not surprisingly, computer science is number one
at the level of Master degrees, a stage in which some focusing is required. Still, it covers only 34.1%of
observable cases (including missing observations Finally, at the Phd stage the disciplinary affiliation of computer science dominates with 38.2%of cases
Table 5. Distribution of Phd, Master and Bachelor degrees by discipline Phd degree Master degree Bachelor degree
Number%Number%Number %Computer science 327 38.2 156 34.1 102 15.9 Engineering 116 13.6 113 24.7 165 25.7
Students may start with a degree in fundamental dis -ciplines (mathematics, physics) and find this new
-sented, students with a background in human scienc -es (literature, linguistics, psychology) and social sciences (economics) may combine their domain
Again, the European higher education systems are less equipped to deal with this kind of cognitive complementarity.
tradition of Phd education is one of subordination to established disciplinary boundaries, rather than of
to learn, to have good colleagues and students, to strengthen their CV and to increase their reputation
move from assistant professor to associate professor to full professor in different affiliations, or equiva -lent levels in other academic systems, for academi
surprising that top universities try to attract top sci -entists, what is impressive is the extreme concentra
The first 15 universities account for 1051 moves, or 33.7%of the total number of
Even more impressive, the first four universities namely MIT, Stanford, Berkeley and Carnegie Mellon, account for 544 moves,
at just these four universities. Alternatively, assum -ing multiple career steps within these four universi
-ious universities on the career decisions of top scien -tists. We find this finding impressive and highly
to academic careers and investigate four career tran -sitions: from postdoctoral researcher to assistant professor (or researcher in other academic systems
or equivalent), from assistant to associate, from as -sociate to full professor, from full professor to an
these scientists become associate professors after five years, and full professors after another five years. On the average, they become full professors
competition among universities to attract the best young researchers, then the best young professors Without strong competition among universities
Table 7 Ranking of top 15 affiliations (only academic positions) in total number of positions over career
Institution Number MIT 174 Stanford university 166 University of California at Berkeley 102 Carnegie mellon University 102
University of Illinois 59 University of Maryland 58 Cornell University 52 University of Washington 45
University of Pennsylvania 44 Harvard university 44 Princeton university 44 University of Texas 44 University of Massachusetts 42
Brown University 41 University of Toronto 34 Note: universities not in USA are in italics
Table 8 Descriptive statistics of duration of stay in academic career positions Duration of career steps
Number Min Max Mean Std dev As postdoctoral researcher 68 0 7 1. 81 1. 499
As assistant professor 412 0 36 4. 89 5. 33 As associate professor 336 0 40 5. 39 4. 175
As full professor 348 0 44 11.51 9. 05 European competitiveness: IT and long-term scientific performance
Science and Public Policy August 2011 536 career paths would be slower on average. It is be
-cause competitors are ready to offer good prospects that all universities, subject to their budget con
-straints and reputation layer, try to compete. On the other hand, top scientists have large opportunity
costs: if they lose opportunities the value they lose is very large, so they will not accept offers that they
consider below their opportunity cost. The higher the reputation, the larger the opportunity costs In other words, we may think of this career pat
-tern as a dynamic equilibrium, in which all talented scientists are allocated to universities that make best
use of their talent, and all universities allocate their budget in the best possible way.
If top scientists re -ceive better offers, they move. If universities in -crease their reputation
and have extra budget, they try to improve the quality of their potential candi -dates.
Rapid career opportunities are the outcome of this dynamic Patterns of international mobility Finally, for a subsample of 786 scientists we have
been able to track the countries in which they took permanent positions. On average, they moved in
-teraction between universities and companies, and between companies and large (public and private customers. On the side of industry,
Universities can contribute to this ecology in two main ways: by producing top class research
and education, and by pushing entrepreneurial ef -forts of researchers to the market. European coun
Implications for higher education policy The interesting question is now whether this search regime has been compatible with the institutional
features of European higher education in the relevant historical period, and why. The answer is negative A search regime characterized by a turbulent rate of
based on peer review, a competitive Phd education system, cross-disciplinary mobility and industry†academia mobility (Bonaccorsi, 2011.
our data, top scientists move from the university that awarded their Bachelor degree to the USA, fight to
enter top class universities as students, change affili -ations several times in their career, combine differ
competition for students and researchers worldwide Knowing how severe these demands are, top class universities fight to attract the best students and try
to offer the best conditions to professors. But Euro -pean universities have not been attractive for top
computer scientists and increasingly have also be -come less attractive for students. Among well -reputed old European universities, just a few have
international visibility at the top These findings support the importance of foster -ing the reform agenda for European universities
This will require dedicated efforts to build up globally competitive Phd programs, more transpar -ent and competitive recruitment procedures for re
-searchers, larger mobility of researchers. The creation of the European Research Council has been an important step in this direction,
but more is need -ed. The situation is rapidly changing, with these is -sues on top of the reform agenda in many European
put pressure on European higher education systems in the near future Implications for innovation policy In the relevant historical period most European
institutional learning on which it was possible to capitalize. The entrepreneurial process started much later in Europe, partly because of the lack of compe
-vice companies the learning curve, in the same peri -od, was much less favourable. Consistent with this
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