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The Role of Entrepreneurial Universities within

Innovation Systems: An Overview and Assessment
Bart Van Looy1

ABSTRACT2
Nowadays one observes an increasing interest in the entrepreneurial behaviour of universi-
ties. In this contribution the role of entrepreneurial universities within national innovation
systems is situated. Specific attention is being paid to the alleged presence of unintended
side effects on the level of scientific activities, and the role of legislative framework condi-
tions that might foster a more active role of universities in terms of technology develop-
ment. After reviewing both issues, combining technological and scientific activity does not
only seem feasible, it might even be desirable given the ambitions of Europe within the cur-
rent, global, knowledge economy.

JEL CODES 03, 032, 034

Review of Business and Economics

KEYWORDS National Innovation System, Entrepreneurial Universities, Science-

Technology Interactions

I. Introduction: The Phenomenon of Entrepreneurial Universities

Collaboration between science and industry, and the phenomenon of ‘enterprising

universities’, have been studied extensively over the last few decades. This growing
interest is connected to the increasing acknowledgement of the fundamental role of
knowledge and innovation in stimulating technological performance, international
competitiveness and economic growth. Researchers in the domain of innovation
(including Freeman, 1987, 1994; Lundvall, 1992; Nelson, 1993; Nelson and Rosen-
berg, 1993; Mansfield & Lee, 1996; Mansfield, 1995; Mowery and Nelson, 1999;
Dosi, 2000) stress the role of science and the importance of interaction between a
variety of institutional actors underlying the innovative capacity and consequent
economical performance of an economical system. This more encompassing view
on innovation dynamics has resulted in a growing popularity of the ‘innovation
 The Role of Entrepreneurial Universities within Innovation Systems 63

2009 / 1
system’ concept which gained acceptance by scholars and policy makers alike as a
guiding framework to understand innovation dynamics on an aggregated level
(OECD, 1999; European Innovation Scoreboard, 2002).

Review of Business and Economics

Figure 1. National Innovation Systems: OECD (1997).

In these models, knowledge generating institutions such as universities, research

laboratories, industrial research centres and more recently government institutions
are acknowledged – besides firms and entrepreneurs – as important players in de-
veloping and stimulating the innovative capacity of a particular region or country.
Likewise, the Triple Helix model, which emerged in the second half of the 1990s
(Leydesdorff and Etzkowitz, 1996, 1998; Etzkowitz and Leydesdorff, 1997; Leydes-
dorff and Etzkowitz, 1998), emphasizes both the complementary roles of firms,
knowledge creation institutes, including universities, and governmental agencies,
as well as the importance of constructive interactions among them.

There are multiple reasons why universities are relevant actors within innovation
systems and can contribute to the national innovative capacity. First, research insti-
tutions produce information and ideas upon which the development of new prod-
ucts, processes and services can build. Secondly, research institutions can work on
 64 Bart Van Looy
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certain research agendas for a longer period of time, which can lead to the creation
of new scientific insights. The latter can over time lead to economic applications.
Notice in this respect that universities are well placed to address market failures
that occur in the field of innovation (Arrow, 1962; Freeman, 1994; Baumol, 2002).
Such market failures arise especially in relation to basic research, characterized not
only by high levels of uncertainty both in terms of technical and commercial suc-
cess, but also spanning long time frames to bear fruit (often decades). In addition,
the nature of the outcomes of innovative activity – i.e. knowledge or information –
complicates investment decisions even further (Foray, 2004). All these phenomena
pose specific challenges for private investors, who tend to refrain from becoming
involved in basic research activities. In order to avoid a loss of social welfare – due
to non investment behavior of private firms – most national innovation systems
nowadays invest considerably in basic research performed at universities and publ-
ic research institutes.

As such, knowledge institutions like universities can play a specific role related di-
rectly to the potential these institutions possess to avoid technological lock-in phe-
nomena. In order to continuously stimulate economic growth within a particular
region or nation, based on knowledge intensive entrepreneurship, its technology
portfolio should strike a balance between routine technological activities on the
one hand (these are focused on process and incremental development in the more
mature phases of the technology life cycle) and non-routine technological activities
on the other hand (these are more focused on new technology platforms and fun-
damental developments). Local/regional knowledge centers, especially universities
Review of Business and Economics

and research centers, can play a significant part in this respect. As they participate
in high level scientific research, they contribute to the generation of new knowl-
edge. Such research takes place in international research communities. The explo-
ration of new fields of knowledge3 – that can often not yet be categorized as routi-
ne activities – and the continued diffusion of this knowledge among regional actors
can be considered an essential task of knowledge centers and especially universi-
ties. This double dynamic allows knowledge centers to play a fundamental role in
regional innovation networks. These institutions are best placed to offer support in
regard to the dual challenge of local and global knowledge development (De-
backere, 2000; Van Looy et al; 2003; Lester, 2004; Debackere & Veugelers, 2005). If
a particular region fails to include this dual task as a priority in their regional inno-
vation policy, there is a long term risk of regression and growth stagnation due to
the life cycle phenomenon. It is in this context that the significance of knowledge
centres should be seen: they develop non-routine activities in research communi-
ties which participate in knowledge exchange on an international scale. As such,
universities offer regions exploration possibilities that are essential for mid to long
term innovation potential. Lester points in this respect to the importance for inno-
vation of ‘interpretative’, problem defining activities, besides analytical, problem
 The Role of Entrepreneurial Universities within Innovation Systems 65

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solving ones. When enterprises focus on the latter, it is essential that sufficient at-
tention is paid to creating an environment for exploration. In this sense, universi-
ties, as fora where new ideas can be explored and studied, are indispensable.

These reflections also imply that universities are more effective in this respect as
they are more active in scientific research. Recent research in the US as well as in
Europe confirms this relation: an explicit research focus coincides with a larger
number of enterprising activities (patents, spin-offs, contract research) (di Gregorio
& Shane (2003); O’Shea, Allen; Van Looy et al, 2005; Sapsalis et al. 2006).

At the same time, contributing effectively to the innovative capacity of an innova-

tion system requires a willingness of universities to become more ‘entrepreneurial’.
The notion of ‘entrepreneurial universities’ (Branscomb, Kodama & Florida, 1999;
Etzkowitz, Webster & Healy, 1998) refers to the development of the following spec-
trum of activities: more intense commercialization of research results, patent and
license activities, spin-off activities, collaboration projects with the industry, and
greater involvement in economic and social development. As such, one observes a
‘second academic revolution’4 whereby education and research become comple-
mented with service and valorization activities aimed at transferring new scientific
knowledge to economical activity realms.

Many factors have contributed to the development of the phenomenon of entrepre-

neurial universities and, at least in the US, this should be considered a logical con-
sequence of the successful involvement of universities in the 1940s, 50s and 60s5 in
domains such as the space industry, defense and energy. Shifts in the federal fi-

Review of Business and Economics

nancing policy and taxation changes for R&D expenses have contributed to more
entrepreneurship at US universities. Moreover, in the 1980s policy priorities shifted
to R&D activities that contribute to the productivity and worldwide competitiveness
of the American industry (Cohen and Noll, 1994).

Likewise, European considerations related to its competitiveness in today’s global-

ized knowledge economy, not only resulted in the well known Lisbon targets; in-
creasingly the role of universities within the European Research Area is being dis-
cussed and reflected upon (see for instance, EC Green paper, 2007; Aghion et al.,
2007; Dosi et al.; 2007). Recent recommendations published by the EC advance as
well a more entrepreneurial orientation of European universities: “Knowledge
transfer must improve in order to accelerate the exploitation of research and the de-
velopment of new products and services. To that end, European universities and
other public research institutions should be given incentives to develop skills and
resources to collaborate effectively with business and other stakeholders, both
within and across borders” (EC Green paper, p. 7).

It is self evident that research centers and universities can only achieve this status
if they acknowledge service and entrepreneurship as part of the university’s re-
 66 Bart Van Looy
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sponsibilities and translate this enterprising attitude into a more entrepreneurial

university culture, including creating the required adequate supporting transfer
mechanisms that facilitate and stimulate these enterprising activities (Bozeman,
2000; Etzkowitz, 1983, 1999; Debackere, 2000; Debackere & Veugelers, 2006).

Several studies have empirically confirmed the role of knowledge centers in regional
development (Anselin et al., 1997; Varga, 1998; 2000; Blind & Grupp, 1999; Acs et al.,
2002; Fischer & Varga, 2003). Besides direct effects, it has also been shown that the
presence of knowledge centres is taken into consideration by companies choosing a
location (E.g. Niosi and Bas, 2001). At the same time, the development of such dy-
namics imply a long term perspective: the slow emergence of high tech regions such
as Silicon Valley, Cambridge and Sophia Antipolis show that economic effects are the
result of a decades-long development process (Saxenian, 1994: O’Mara, 2005).

II. Entrepreneurial Universities: Concerns

A. Scientific and Entrepreneurial Activities at the Level of Professors:

Complementary or Contradictory?

At the same time, the increasing trend of developing entrepreneurial capabilities in

academia gave rise to several concerns related to the role of academia within
society (Gibbons, 1999; Kelch, 2002; Martin, 2001, 2002). Indeed, an explicit fear is
Review of Business and Economics

related to the impact of University-Industry cooperation on the research agendas of

university researchers (Geuna, 1999; Hane, 1999; Vavakova, 1998) and the conflicts
of commitment and interest that occur when faculty members’ full-time duties
(teaching, research, time with students and service obligations to the university)
are affected by activities stemming from involvement in company cooperation such
as consulting activities, notwithstanding the observation that most universities
have formal policies regarding and regulating this issue. The major concerns derive
from the fundamentally different reward and incentive systems of academic and
private sector research, in terms of (1) the relationship between disclosure versus
secrecy and (2) the complementarities and substitution effects between public and
private R&D expenditures (Dasgupta and David, 1987, 1994).

In terms of incentive systems, one of the cornerstones of the academic enterprise

consists of the publication of research results and the opportunity for open discus-
sions among colleagues. Companies, on the other hand, have a responsibility for
and a need to protect the value of their investments. These differences in the incen-
tive systems of public and private research create challenges with regard to the dis-
semination of information, the nature of the research conducted and the access to
research results (Hane, 1999) and are, therefore, re-opening debates on the norms
 The Role of Entrepreneurial Universities within Innovation Systems 67

2009 / 1
and values that guide academic science (see, for instance, Merton, 1968 a,b; Mitroff,
1974; Mulkay, 1976). For example, some forms of publication might be delayed or
suppressed because firms may ask universities to keep information (temporarily)
confidential. This might reduce the incentive to publish and run counter to the aca-
demic norm of open dissemination of scientific knowledge (Blumenthal et al.,
1996). Florida and Cohen (1999) referred to this as the ‘secrecy problem’ in research
universities. Empirical evidence has, indeed, shown an association between industry
support for research and restrictions regarding the disclosure of the research per-
formed. Blumenthal et al. (1996) surveyed life science faculties and companies sup-
porting these faculties. They found evidence for the fact that delaying publications
and restricting information sharing are quite common, for instance, to allow suffi-
cient time for the sponsoring company to file a patent application, to protect the fi-
nancial value of certain research results, or to avoid undermining the competitive
status of the sponsoring company. Brooks and Randazzese (1999) cite other empiri-
cal evidence of the ‘secrecy problem’ but also point to a possible effect of the re-
search institute characteristics in the sense that the best research universities seem
quite capable of protecting their traditional values of openness and seem to make
only modest concessions to the practical needs of industry.

Besides the ‘secrecy problem’, it can be noted that both individual researchers and
research institutions can develop financial interests in the specific research out-
comes, leading to a possible bias towards certain fields and activities (ACE, 2001).
This phenomenon brings us to one of the main concerns of the opponents of inten-
sifying collaborations between universities and industries, namely that the academic

Review of Business and Economics

research agenda will be ‘contaminated’ by the application-oriented needs of indus-
trial corporations – the ‘corporate manipulation thesis’ (Noble, 1977). From this per-
spective, university research is seen as characterized by an independence that
should allow academics to freely contribute to theories and models at the endless
frontier of science, in a (purely) curiosity-driven approach. The corporate manipula-
tion thesis argues that corporations interfere with the normal pursuit of science and
that they seek to control relevant university research for their own ends, rather than
allowing faculty members to advance their research agenda through the pursuit of
opportunities for federal and industrial funding.6 The changes in the university re-
search agenda are most often related to an alleged shift towards the more applied re-
search end, referred to as the ‘skewing problem’ (Florida and Cohen, 1999).

Earlier empirical evidence on both problems appears to be rather scarce and of a

mixed nature. Surveys by Rahm (in Florida & Cohen, 1999) and Morgan (in Florida
& Cohen, 1999) found some empirical association between greater faculty involve-
ment in industry and increased levels of applied research. Research centers that
value the mission of improving industrial products and processes devote less of
their R&D activities to basic research than centers that do not value this industry-
oriented mission.7 Additional evidence in this respect has been reported for Norwe-
 68 Bart Van Looy
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gian university faculties (Gulbrandsen and Smeby, in Geuna and Nesta, 2003).
Here, it was found that faculties with industry funding undertook significantly less
basic research than researchers with no such external funds. In the same research
setting, approximately 20% of the researchers reported contract research to be
problematic for the autonomy and independence of their research. In this respect,
it can be noted that certain research centers have made collaboration with industry
– or involvement in business networks – an explicit part of their mission. Likewise,
certain funding mechanisms also favor cooperation between Industry and Univer-
sity, in the US, Japan and Europe (Florida & Cohen, 1999). Hence, the direction of
this relationship remains to be resolved. On the one hand, it may be that research-
ers adjust their agendas in response to an increased cooperation with industry. On
the other hand, industrial partners might, nonetheless, turn to research centers
with an application-oriented agenda rather than to centers known for performing
basic research. In the latter case, the observed effect is only a selection effect.

At the same time, several studies react to the opponents of industry involvement on
the grounds of an alleged skewing of the research agenda. Those studies show that
performing more applied research does not necessarily imply a trade-off with basic
research. For instance, data from the US National Science Board have shown that in
the 1980s, although the number of university-industry research centers almost dou-
bled, the overall share of university research, classified as basic research, remained
quite stable. Hicks and Hamilton (1999) found that the percentage of basic research
that was performed at universities remained unchanged between 1981 and 1995, a
period during which, at the same time, a sharp increase in university patenting
Review of Business and Economics

could be observed. They also reported that the number of citations for university-
industry papers was higher than for single university papers, which suggests that
university researchers may be able to enhance their scientific impact by collaborat-
ing with industry partners. Godin and Gingras (1999), when analyzing publication
data from Canadian researchers over a 15-year period (1980-1995), conclude that:
“beliefs that collaborative research (with industry) is detrimental to academic re-
search do not seem to be empirically grounded”. Similar observations are advanced
by Brooks and Randazzese (1999) within the US semiconductor industry, where a
consortium of semiconductor producers (SRC) funded university semiconductor re-
search. No indication was found that the SRC support led academics to conduct
less ‘foundational’ research (Brooks and Randazzese, 1999). Recently, Owen-Smith
(2003) highlighted the changed relationships between commercial and academic
systems. Whereas these used to be separate systems, Owen-Smith’s findings sug-
gest that commercial and academic standards for success have now become inte-
grated into what is called a hybrid regime, where achievement in one realm is de-
pendent upon success in the other. This observation has been confirmed by previ-
ous research in which the relationship between scientific performance and engage-
ment in contract research with industry was examined more systematically (Ranga
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2009 / 1
et al, 2003; Van Looy et al. 2004). The findings revealed that contract research and
scientific activities do not hamper each other: systematic engagement in contract
research coincided with increased publication outputs, without affecting the nature
of the publications involved. As resources increased, the positive relation between
both types of activities became more pronounced, pointing to a Matthew effect.

Contract research, however, represents only one type of entrepreneurial activity oc-
curring at universities. In the case of inventions, the potential conflict between pub-
lic- and private-oriented considerations in terms of diffusion of knowledge (secrecy
versus free dissemination) seems most salient. In that respect, analyzing publication
outputs of academic inventors – and comparing them to those of non-inventors –
provides additional insights into whether an academic’s entrepreneurial and scien-
tific activities can be reconciled or whether they are of a more conflicting nature.

Our own research, involving academic staff at the K.U.Leuven, confirms the find-
ings with respect to contract research: academic inventors systematically publish
more than their colleagues who are not engaged in patenting activities but who are
working in similar fields and who have comparable age and career profiles (Van
Looy et al., 2006, for further refinements and extensions, see also Callaert (forth-
coming)). These observations are in line with recently published empirical studies
which look in detail at the relationship between (scientific) publication behavior
and entrepreneurial activities, including patenting. An inspection of table 1 reveals
that no single study reports on trade-offs between both activities; on the contrary
the majority of studies clearly signals a positive relationship between inventive ac-

Review of Business and Economics

tivity (measured by involvement in patent activity) on the one hand and scientific
activity (measured by publication based indicators) on the other hand.

So while the aforementioned concerns (secrecy, skewing, ...) deserve our ongoing
attention, recent empirical assessments confirm that universities have found ways
to reconcile both activities.

B. On the Role of Legislative Framework Conditions

In terms of policy measures, the rise of the entrepreneurial university phenomenon

is often associated with the Bayh-Dole Act (1980) and the Stevenson-Wydler Act
(1980). These American legislative initiatives created transparency with respect to
the ownership of intellectual property rights originating from publicly funded re-
search; whether performed by universities or companies, the involved institutions
obtain in principle the right of ownership (for a more technical account, see
Colsaet, 2005). This new legislation was an important stimulus for adopting and/or
further professionalising intellectual property-related procedures and regulations.
Together with the rise of science-intensive fields of economical activity (like bio-
Review of Business and Economics 2009 / 1
Table 1. Overview of recent empirical studies on scientific and entrepreneurial activities of academic researchers (Based on Callaert, forthcom- 70
ing 2009).

Source Research Setting Findings

Van Looy et al. Quantitative analysis of entrepreneurial Entrepreneurial professors (involved in contract research) pub-
(Research Policy, (contract research) and scientific activities lish more than non-entrepreneurial colleagues. No skewing of
2004). of professors at K.U. Leuven, Belgium publications towards the more applied spectrum. Positive rela-
Bart Van Looy

(N = 167). tion between turnover of contract research and scientific ad-

vantage of contract researchers.

Breschi et al. Quantitative analysis of Italian inventors’ Average publication productivity higher for inventors than for
(Revue d’Economie patent and publication activity over time control group.
Industrielle, 2005). (N = 300). Yearly observations: advantage already somehow exists before
patenting event, but increases in the years immediately after
the patent.
Meyer Quantitative analysis of publication and Patenting scientists outperform their non-patenting peers in
(Research Policy, patent activity of nano-scientists in UK terms of publication counts and citations received. Patenting
2006). (13,235 authors), Germany (22,242 authors) scientists are overrepresented among star scientists, but their
and Belgium (2652 authors) scientific advantage compared to non-inventing peers does not
hold for the star scientist sample.

Van Looy et al. Quantitative analysis of patent and Academic inventors publish more than non-inventing col-
(Research Policy, publication behavior of professors at leagues. Scientific advantage in the period after first patent
2006). K.U. Leuven, Belgium (N = 317). has been invented is larger than in the period before. In gene-
ral, inventors publish more in scientifically oriented journals
than their colleagues who are not involved in patenting.
Azoulay et al. Quantitative analysis of publication and An increase in a researcher’s publications significantly adds to
(Journal of Econ patent activity of 3862 life scientists in US. the odds of this researcher to become an inventor in the fol-
Beh. and Org, 2007). lowing year.
Source Research Setting Findings
Calderini, Quantitative analysis of patent and The probability to patent is a curvilinear function of scientific
Franzoni & Vezzulli publication behavior of Italian scientists productivity, basicness and impact: increasing for low-to-mo-
(Research Policy, 2007). over time (Material Sciences; N = 1276). derate-high values of the variables, and decreasing for high
values.
Crespo, M., & Dridi, H. Qualitative study of how UI relations impact Researchers’ involvement in projects with industry does not
(Higher Education, academic research (in-depth interviews with seem to influence the number and quality of publications. Sci-
2007). five TT officers and 28 university researchers entific benefits are even reported from these partnerships.
in Sciences, Engineering and Social Sciences Benefits stem from adopting strategies in the negotiations with
(< 6 Québec HE institutions, Canada). industrial partners (guaranteeing permission to publish), net-
working with other researchers in the same area.
Czarnitzki et al. Quantitative analysis of publication and Positive relation between patenting and publication quantity
(Research Evaluation, patent activity of over 3500 German as well as quality.
2007). researchers.
Elfenbein Quantitative analysis of the relation between Inventors’ prior scientific output is positively correlated with the
(Journal of Economic academic prestige and licensing outcome (1703 likelihood that their new technologies will be licensed.
Behavior and reports of patentable inventions by Harvard It is uncorrelated with the receipts generated by the licensed
Organization, 2007). University faculty (N = 451). technology.
Stephan et al. Quantitative analysis on patenting and Patents are positively and significantly related to the number
(Economics of publication behavior of a cross-section of publications.
Innovation and New of over 10,000 US doctorate recipients.
Technology, 2007).
Fabrizio & DiMinin Survey + quantitative analysis of patent Yearly average publication productivity higher for inventors than
(Research Policy, 2008). and publication activity over time of for non-inventors. Yearly number of publications increases fol-
US researchers (N = 400) in science and lowing a patent.
engineering disciplines. First patent not related to citations received afterwards, but
The Role of Entrepreneurial Universities within Innovation Systems

negative effect of patent stock on citations received.

71

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 72 Bart Van Looy
2009 / 1

technology), the introduction of the Bayh-Dole act undoubtedly contributed to the

strong increase of patenting activity undertaken by American universities from the
1980’s onwards (Branscomb, 1999; Mowery et al., 1998; 1999; 2001). Indeed, when
looking nowadays at patent activity undertaken by universities, the strong perform-
ance of American universities is striking. Table 2 provides an overview of universi-
ties, identified within the EPO patent system8 who have created in the last years a
patent portfolio exceeding 100 applications (published after 2000).

Table 2. Overview of most active universities within the EPO Patent System.
1 US THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
2 US BOARD OF REGENTS, THE UNIVERSITY OF TEXAS SYSTEM
3 US THE JOHNS HOPKINS UNIVERSITY
4 US MASSACHUSETTS INSTITUTE OF TECHNOLOGY
5 US WISCONSIN ALUMNI RESEARCH FOUNDATION
6 US CALIFORNIA INSTITUTE OF TECHNOLOGY
7 US THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY
8 IL YISSUM RESEARCH DEVELOPMENT COMPANY OF THE HEBREW UNIVERSITY
OF JERUSALEM
9 UK OXFORD UNIVERSITY
10 US THE REGENTS OF THE UNIVERSITY OF MICHIGAN
11 UK CAMBRIDGE UNIVERSITY
12 US THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK
13 US THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ILLINOIS
14 US TRUSTEES OF THE UNIVERSITY OF PENNSYLVANIA
15 US UNIVERSITY OF FLORIDA
16 CH ETH ZURICH
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17 US DUKE UNIVERSITY
18 US PRESIDENT AND FELLOWS OF HARVARD COLLEGE
19 US YALE UNIVERSITY
20 US THE UNIVERSITY OF NORTH CAROLINA
21 US CORNELL RESEARCH FOUNDATION, INC.
22 BE K.U. LEUVEN
23 US UNIVERSITY OF UTAH RESEARCH FOUNDATION
24 US UNIVERSITY OF SOUTHERN CALIFORNIA
25 US UNIVERSITY OF ROCHESTER
26 CH ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
27 CA THE UNIVERSITY OF BRITISH COLUMBIA
28 US UNIVERSITY OF PITTSBURGH
29 US REGENTS OF THE UNIVERSITY OF MINNESOTA
30 US UNIVERSITY OF VIRGINIA PATENT FOUNDATION
31 US THE RESEARCH FOUNDATION OF STATE UNIVERSITY OF NEW YORK
32 US NORTH CAROLINA STATE UNIVERSITY
33 US UNIVERSITY OF MARYLAND
34 US THE UAB RESEARCH FOUNDATION
35 US EMORY UNIVERSITY
36 CH UNIVERSITY OF ZURICH
Applications > 100, published from 2000 onwards.
 The Role of Entrepreneurial Universities within Innovation Systems 73

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As such, these figures suggest that adopting Bayh-Dole like legislative framework
conditions might be an interesting option for European countries in order to further
stimulate innovative activity. Economical theories on innovation provide additional
arguments in this respect. The seminal work of Arrow (1962) already pointed out
that within innovation market failures occur frequently. When one scrutinizes the
nature of technology developed by academic scientists, it becomes apparent that
these technologies are often of an embryonic nature, requiring additional invest-
ments to arrive at market applications (see Jensen, Thursby & Thursby (2003) for a
revealing account). In the case no ownership rights exist, incentive issues arise,
both on the level of the academic inventor and on the level of his/her principal (i.e.
the university). Stated otherwise, if scientific inventors are not acknowledged as
‘owners’, incentives to engage in further development efforts are absent; the
amount of follow up efforts – towards market exploitation – will be driven by vol-
untarism only. Granting IP rights on the other hand, creates entrepreneurial agency.

The next question then relates to who should acquire such rights, individual inven-
tors or their principal (the university)9? Situating these rights at the level of indivi-
dual inventors might result in under-investment due to risk averseness and/or the
lack of capabilities to further invest in the development of the technology. In addi-
tion, if one leaves out universities conflicts of commitment might arise between
agent and principal, with academic inventors pursuing technology development ac-
tivities while universities limit their scope to education and research. Moreover,
when situating these rights at the level of the university, it becomes feasible to ad-
dress specific concerns that stem from the nature of scientific work (e.g. rules on

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disclosure, impact on science and education). Stated otherwise, such university
specific regulations seem justified to guarantee the co-presence of multiple aca-
demic missions (Science, Education & Knowledge Transfer) and to avoid potential
conflicts (including secrecy and skewing). Notice finally that granting rights to uni-
versities creates a more transparent ‘market’ situation towards industrial partners;
being explicit on the level of terms and conditions not only seems fair from a fund-
ing perspective; it might also reduce transaction costs.10

While conceptual arguments might be advanced in favor of granting IP rights to

universities, an empirical assessment of their impact seems as relevant. Currently,
research on this issue is being undertaken within the Steunpunt O&O Indicatoren
(see for a detailed account of the Flemish case, Du Plessis et al., 2006; for a Euro-
pean comparison, Van Looy, Meyer, du Plessis & Debackere, 2007/forthcoming).
Part of the research activities addresses the question whether or not different legis-
lative framework conditions coincide with differences in terms of the amount of
technological activity undertaken by universities within a particular national inno-
vation system. Table 3 provides an overview of the countries under study and the
legislative framework conditions for the period under study (1990-2004). Notice
that for three countries (NL, UK, France) university’s rights are treated like rights
 74 Bart Van Looy
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of any employer within the jurisdiction of the country (so no specific Higher Edu-
cation Institutes (HEI) legislation in place).

Table 3. Overview of countries under study – Impact of legislative framework conditions.

Belgium The governance of Universities has become a regional responsibility (state re-
form 1991). In Flanders all IP from university researchers belongs to the uni-
versity. A similar logic has been adopted in 1998 by the French Community.
Germany Private and public employer has the rights to patent service inventions; at the
same time university professors own the patent rights to university inventions
(law on employee inventions 1994). 2001 Reform of Employee Law has ren-
dered university inventions “service inventions” which means they now be-
long to the university.
Denmark Act on Inventions at Public Research Institutions (2000) grants title to Public
Research Organizations (PRO) but allows inventor right of first refusal. Before
2000 the rights were owned by the researcher/professor.
Finland Employer has right to patent, also in the case of PRO. University inventions
are notably exceptions: the patent rights belong to the employee (1967). Fin-
land is currently changing its legislation (towards granting rights to universi-
ties).
Sweden Professor’s privilege.
Netherlands, Three countries in which legislation is general, i.e. universities are considered
France and UK as employers, which will own the rights on inventions made by staff.

Table 4. Impact of different legislative framework conditions on universities’ technological

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activity.

IP Rights Mean Std. Deviation N

Employee has right to patent invention ,4630 ,72297 47
Employer has right to patent invention 4,9846 4,66603 17
General Employer Oriented IP 1,7193 1,45154 45
Source Type III Sum of df Mean F Sig.
Squares Square
Corrected Model 564,789(a) 13 43,445 26,520 ,000
Intercept 15,105 1 15,105 9,221 ,003
HERD 4,406 1 4,406 2,690 ,104
GERD ,174 1 ,174 ,106 ,745
Year 15,458 1 15,458 9,436 ,003
IP Rights 41,105 1 41,105 25,091 ,000
Country 174,400 6 29,067 17,743 ,000
IP Rights * Country 68,486 2 34,243 20,903 ,000
Error 155,630 95 1,638
Total 1030,578 109
Corrected Total 720,420 108
R Squared = ,784 (Adjusted R Squared = ,754)
 The Role of Entrepreneurial Universities within Innovation Systems 75

2009 / 1
Table 4 reports the results obtained by applying a fixed effect econometric model
(ANCOVA) where different legislation framework conditions act as independent
variable. Business expenditures on R&D (BERD) as well as expenditures on R&D by
higher education institutes (HERD) are included as control variables. The number
of patent applications by universities figures as dependent variable.11

It becomes clear that specific HEI tailored legislative framework conditions have a
significant and considerable impact on the amount of technological activity ob-
served. Countries adopting such a legislation observe higher levels of technological
activity compared to previous periods and compared to countries in which legisla-
tion opts for the professor’s privilege (i.e. situating the ownership rights at the level
of the individual researcher)).

Not only does one observe a notable difference compared to the countries which
opt for professor’s privilege; also the difference with broader, employer oriented,
legislation is significant and outspoken. The logical next question then becomes
whether the observed differences stem from shifts in technological activity – from
one type of actor towards another, e.g. from individuals toward universities – or
whether they reveal an overall net gain in terms of technological activity within the
innovation system. Here the findings reported by du Plessis et al. (2006) are unam-
biguous for Flanders; the observed impact can indeed be interpreted as a net gain.
Likewise, for the European countries under study, no crowding out effects have
been observed; neither in terms of patent activity undertaken by individuals, nor in
terms of patent activity undertaken by firms.

Review of Business and Economics

Given the net effect one hence observes in terms of technological activity, adopting
legislative frameworks conditions that incentive universities and at the same time
take into account the specific role of scientific actors, seems highly appropriate. In-
troducing on a larger European scale such ‘best’ practices might be more beneficial
for the innovative performance of Europe than preserving the diversity currently
present within Europe.

III. Conclusion

In this contribution, we highlighted the role universities can play within innovation
systems. Two specific concerns have been discussed in more depth; the occurrence
of unintended side effects that might jeopardize scientific activities, and the role of
legislative framework conditions that might foster a more active role of universities
in terms of technology development. With respect to the first point, it became ap-
parent that reconciling scientific and technological activities within academia is
feasible. With respect to the second issue, more technological activity is being ob-
 76 Bart Van Looy
2009 / 1

served when installing university (HEI) specific legislative framework conditions.

The net effect of the observed impact even suggests that more technological activ-
ity within universities is not only feasible, it might even be desirable given the am-
bitions of Europe within the current, global, knowledge economy.

NOTES

1. Bart Van Looy is professor at K.U.Leuven in the field of Innovation and Organization at
the department of Managerial Economics, Strategy and Innovation, Faculty of Economics
and Applied Economics. His current research focuses on organizing innovation (com-
pany level) and regional innovation systems: Entrepreneurial Universities and Science –
Technology interactions are focal points of attention in this respect. Bart Van Looy is
publishing on these topics in journals like Research Policy, Journal of Product and Inno-
vation Management, Organization Studies, R&D Management, Scientometrics, Journal of
Technology Transfer and Academy of Management Journal. Contactinfo: Naamsestraat
69, B-3000 Leuven, Phone: +32 16 326901, Fax: +32 16 326732, Bart.Vanlooy@econ.
kuleuven.be
2. Acknowledgements: The research reported in this article builds on several years of re-
search supported by the EC (DG Research), VRWB and the Flemish Government (Steun-
punt O&O Indicatoren/Expertise Centrum O&O Monitoring). Conducting this research
over the last decade has been – and still is – a joint activity involving many colleagues. I
want to mention and thank explicitly Julie Callaert, Koenraad Debackere, Mariette Du
Plessis, Catherine Lecocq, Martin Meyer, Paolo Landoni, Reinhilde Veugelers, Rudi Cuy-
vers, Martin Hinoul, Tom Magerman, Bruno Cassiman, Xiaoyan Song, Caro Vereyen and
Bert Peeters for their involvement and contributions to the insights and findings re-
ported in this paper.
Review of Business and Economics

3. Innovative economic activities imply a process of cross-fertilization in which different

knowledge domains are involved. Knowledge centers with a large variety of disciplines
consequently have greater potential for cross-fertilization. By further developing this
potential, they can greatly contribute to preventing the risks of technological mono-
cultures.
4. During the first academic revolution (19th century) research became a part of universi-
ties activity profile.
5. One could even go back to the 19th century to explain the phenomenon of entrepreneur-
ship at universities; see Hane, 1999; Kodama and Branscomb, 1999; Rosenberg and Nel-
son, 1994 for historical overviews extending longer time frames.
6. For a recent overview on this debate within the field of Medicine, see Kelch (2002); with
respect to policies adopted in order to address potential conflicts of interest within this
field, see Drazen and Curfman, 2002.
7. Centers that see improving industrial products and processes as part of their mission
spend about 19% of their R&D activities on basic research, while university centers that
do not consider this important devote about 61% of their R&D activities to basic re-
search (Florida & Cohen, 1999).
8. Universities have been identified based on the sector allocation methodology developed
by Steunpunt O&O Indicatoren, see Van Looy, B., Du Plessis, M. & Magerman T. (2006).
9. One could also envisage a situation whereby such rights are situated at levels above the
principal of the inventors (e.g. a patent organization for a region or country as a whole).
This would only make sense if economies of scale are important; these are however
 The Role of Entrepreneurial Universities within Innovation Systems 77

limited (and relate to IP procedures). Moreover, by de-multiplexing relationships, new

2009 / 1
conflict situations (both within and between involved organizations) can and probably
will arise like witnessed in the past in the both the UK (BTG) and the US (NRC); see for
a revealing account on this issue, Mowery & Sampat (2001).
10. Whether it will actually do, will of course depend on the behavior of negotiating part-
ners.
11. University owned patents are identified by means of the sector allocation methodology
developed by Van Looy, Du Plessis & Magerman (2006).

REFERENCES

ACE, American Council on Education, 2001, Report examining Challenges facing Research Col-
laborations between Industry and Universities, Report ACE Division of Government & Pub-
lic Affairs.(http://www.acenet.edu/news/press_release/2001/06june/bhef.release.html)
Acs, Z.J., Anselin, L., & Varga, A. 2002. Patents and innovation counts as measures of
regional production of new knowledge. Research Policy, 31(7).
Aghion P., Dewatrimont, Hoxby, C., Mas-Colell & A. Sapir 2007, why reform Europe’s
universities. Bruegel Policy brief. Issue 2007, 4.
Anselin, L., Varga, A., Acs, Z., (1997), “Local geographic spillovers between university re-
search and high technology innovations,” Journal of Urban Economics 42 (3), 422-448.
Arrow K.J. (1962) Economic welfare and the allocation of resources for invention. The rate
and direction of inventive activity: economic and social factors. Princeton NJ, Princeton
University Press.
Azoulay, P., Ding, W., Stuart, T. E., 2007a, “The determinants of faculty patenting behavior:
Demographics or opportunities,” Journal of Economic Behavior and Organization, 63 (4),
599-623.

Review of Business and Economics

Baumol, W.J., The Free-Market Innovation Machine, Princeton University Press, Princeton,
2002
Blind, K. & Grupp, H. (1999), “Interdependencies between the Science and Technology Infra-
structure and Innovation Activities in German Regions: Empirical Findings and Policy
Consequences”, Research Policy, Vol. 28, No. 5: 451-468.
Blumenthal, D., Campbell, E.G., Causino, N., et al., 1996, participation of life-science faculty
in research relationships with industry, New England Journal of Medicine 335, 1734-
1739.
Bozeman, B. (2000), “Technology transfer and public policy: A review of research and
theory.” Research Policy, 29, 627-655.
Branscomb, L.M., Kodama, F., and Florida, R., 1999, Industrializing Knowledge: University-
Industry Linkages in Japan and the United States (London, MIT Press).
Brooks, H., and Randazzese, L.P., 1999, University-industry relations: the next four years
and beyond, In: L.M. Branscomb, and J.H. Keller (Editors), Investing in Innovation:
Creating an Innovation Policy that works (MIT Press, Cambridge, Massachussets and
London, England) pp. 361-399.
Calderini, M., Franzoni, C., & Vezzulli, A. (2007), “If star scientists do not patent: The effect
of productivity, basicness and impact on the decision to patent in the academic world,”
Research Policy, 36(3), 303-319.
Callaert J. Forthcoming/ Multi-Tasking in academic environments. PhD Dissertation Fac.
Economie & Bedrijfswetenschappen, K.U.Leuven
Cohen, L.R., Noll, R.G., 1994, Privatising Public Research, Scientific American 271, 72-77.
 78 Bart Van Looy

Crespo, M., & Dridi, H., 2007, “Intensification of university-industry relationships and its
2009 / 1

impact on academic research,” Higher Education, 54(1), 61-84.

Czarnitzki, D., Glänzel, W., Hussinger, K. 2007, “Patent and publication activities of German
professors: An empirical assessment of their co-activity,” Research Evaluation, 16(4),
311-319.
Dasgupta, P., David, P.A., 1987, Information disclosure and the economics of science and
technology, In: G. R. Feiwel (Editor), Arrow and the Ascent of Modern Economic Theory
(N.Y.University Press) pp. 519-542.
Dasgupta, P., David, P.A., 1994, toward a new economics of science, Research Policy 23, 487-
521.
Debackere, K. (2000), “Academic R&D as a Business: Context, Structure and Processes,” R&D
Management, Vol. 30, No. 4: 323-329.
Di Gregorio D., Shane S., (2003), Why do some universities generate more start-ups than
others?, Research Policy, 32, 209-227.
Dosi G., Llerena P. & Labini M.S. (2006) The relationships between science, technologies and
their industrial exploitation: An illustration through the myths and realities of the so-
called ‘European Paradox’. Research Policy, Volume 35, Issue 10, December 2006, Pages
1450-1464
Dosi, G. (2000) Innovation, Organization and Economic Dynamics (Edward Elgar Publishers,
Cheltenham, UK).
Du Plessis M., Van Looy B., Debackere K., Magerman T. (2005) Assessing Academic Pat-
enting Activity: The case of Flanders. Paper presented at the Triple Helix Conference,
Turin, May 2005.
Elfenbein, D.W. (2007), “Publications, patents, and the market for university inventions,”
Journal of Economic Behavior & Organization, 63, (4), 688-715.
Etzkowitz H. (1999) Bridging the Gap: The evolution of Industry-University links in the
United States. In Branscomb et al. (eds.) Industrialising Knowledge. MIT Press.
Etzkowitz, H. & Leydesdorff, L. (1997), “Introduction to special issue on science policy
Review of Business and Economics

dimensions of the Triple Helix of university-industry-government relations,” Science and

Public Policy, Vol. 24 No. 1: 2-5.
Etzkowitz, H. (1983) Entrepreneurial scientists and entrepreneurial universities in American
Academic Science. Minerva, 21, 271-288.
Etzkowitz, H., Webster, A., and Healey, P., 1998, Capitalizing Knowledge: New Intersections
of Industry and Academia (Albany, State University of New York press).
European Commission (1995), “Green Paper on Innovation.”
European Innovation Scoreboard 2002, Cordis Focus, December 2002.
Fabrizio, K.R., & DiMinin, A. 2008, “Commercializing the laboratory: Faculty patenting and
the open science environment,” Research Policy, 37(5), 914-931.
Fischer, M.M., & Varga, A. (2003), “Spatial knowledge spillovers and university research:
Evidence from Austria.” Annals of Regional Science, 37 (2): 303-322.
Florida, R. & Cohen W. (1999). Engine or infrastructure? The University Role in Economic
Development. In: Industrializing Knowledge. University-Industry Linkages in Japan and
the United States. Branscomb L., Kodama, F. & Florida R. (eds.) MIT Press
Foray, D. (2004). Economics of Knowledge. Cambridge, US and London, UK: MIT Press.
Freeman, C. (1994) the economics of technical change, Cambridge Journal of Economics 18,
463-514.
Freeman, C., (1987), Technology Policy and Economic Performance (Pinter, London).
Geuna, A., 1999, The changing rationale for university research funding: Are there negative
unintended consequences?, Paper 33 (SPRU Electronic Working Paper Series, Sussex
University, Falmer, Brighton).
 The Role of Entrepreneurial Universities within Innovation Systems 79

Gibbons, M., 1999, science’s new social contract with society, Nature 402, C81-C84.

2009 / 1
Gulbrandsen, M., & Smeby, J.C. (2005), “Industry funding and university professors’ re-
search performance,” Research Policy, 34, 932-950.
Hane, G., 1999, Comparing university-industry linkages in the United States and Japan, In:
L.M. Branscomb, F. Kodama and R. Florida (Editors), Industrializing Knowledge: Univer-
sity-Industry linkages in Japan and the United States (MIT Press, London) pp. 20-61.
Hicks, D., & Hamilton, K. (1999), “Does university-industry collaboration adversely affect
university research?” Issues in Science and Technology, 15(4), 74-75.
Jensen R., Thursby J. & Thursby M. (2003) Disclosure and licensing of university inventions:
‘The best we can do with the s**t we get to work with’, International Journal of Industri-
al Organization, 21, 1271-1300.
Kelch, R.P., 2002, maintaining the public trust in clinical research, The New England Journal
of Medicine 346, 285-287.
Lester, R.K., Piore, M.J. (2004). Innovation-The Missing Dimension. Harvard University
Press.
Leydesdorff, L. & Etzkowitz, H. (1996), “Emergence of a Triple Helix of University-Industry-
Government Relations”, Science and Public Policy, Vol. 23, No. 5: 279-286.
Leydesdorff, L. & Etzkowitz, H. (1998), “Triple Helix of Innovation: Introduction”, Science
and Public Policy, Vol. 25, No. 6: 358-364.
Lundvall, B.A. (1992). National Systems of Innovation: Towards a Theory of Innovation and
Interactive Learning. London: Pinter Publishers.
Mansfield, E., (1995). Academic research underlying industrial innovations: sources, charac-
teristics, and financing. The Review of Economics and Statistics, 55-56.
Mansfield, E., Lee, J.Y., 1996. The modern university: contributor to industrial innovation
and recipient of industrial support. Research Policy, 25, 1047-1058.
Martin, B.R., 2001, The changing social contract for science and the evolution of the univer-
sity, In: A. Geuna, AJ. Salter, W.E. Steinmueller, Y.E. Hoffman (Editors), Science and In-

Review of Business and Economics

novation: Rethinking the Rationales for Funding and Governance (Edward Elgar Publish-
ers).
Merton, R.K., 1968, the Matthew effect in science. the reward and communication systems
of science considered, Science 159, 56-63.
Mitroff, I., 1974, norms and counter-norms in a select group of Apollo moon scientists,
American Sociological Review 39, 579-95.
Mowery D. and Ziedonis A., 2002 Academic patent quality and quantity before and after the
Bayh-Dole Act. Research Policy, 31, 399-418.
Mowery D., Nelson R., Sampat N. & Ziedonis A., 1999 The effects of the Bayh-Doyle Act on
US University Research and Technology Transfer. In: Branscomb et al. (Eds.). Industrial-
ising Knowledge. MIT Press.
Mowery D., Nelson, R., Sampat B. and Ziedonis A., 2001. The growth of patenting and
licensing by U.S. universities: an assessment of the effects of Bayh-Dole Act of 1980. Re-
search Policy, 30, 99-119.
Mowery D.C & Sampat B. (2005) The Bayh-Dole Act of 1980 and University-Industry Tech-
nology Transfer: A model for other OECD governments? Journal of Technology Transfer,
30, 115-127.
Mowery D.C. & Sampat B.N. (2001) Patenting and licensing university inventions: lessons
from the history of the research corporation. Industrial and Corporate Change, p. 317-
355.
Mowery, D.C., and Nelson, R.R., 1999, Sources of Industrial Leadership (Cambridge Univer-
sity Press, Cambridge)
 80 Bart Van Looy

Mulkay, M., 1976, the mediating role of the scientific elite, Social Studies of Science 6, 445-
2009 / 1

470.
Nelson, R.R. & Rosenberg, N. 1993. Technical Innovation and National Systems. In R.R.
Nelson (Ed.), National Innovation Systems. A comparative Analysis: New York: Oxford
University Press, Inc.
Nelson, R.R. 1993. National Innovation Systems: A Comparative Analysis. New York: Oxford
University Press Inc.
Niosi, J., & Bas, T.G. (2001), “The competencies of regions – Canada’s clusters in biotechnol-
ogy.” Small Business Economics, 17 (1-2): 31-42.
Noble, D., 1977, America by Design: Science, Technology and the Rise of Corporate Capital-
ism (Oxford University Press, New York).
O’Mara M. P. (2005), Cities of knowledge: Cold war science and the search for the next Sili-
con Valley. Princeton University Press.
OECD (1997), National Innovation Systems. Paris.
OECD (1999), University Research in Transition, OECD STI-Report (OECD Publications,
France).
O’Shea R., Allen T., Chevalier, A. & Roche F. (2005) Entrepreneurial orientation, technology
transfer and spinoff performance of U.S. universities. Research Policy, Volume 34, Issue 7,
September 2005, Pages 994-1009.
Owen-Smith, J. (2003), “From separate systems to a hybrid order: Accumulative advantage
across public and private science at research one universities,” Research Policy, 32(6),
1081.
Sapsalis, E., Van Looy, B., van Pottelsberghe, B., Callaert, J., Debackere, K. (2005), On the
Patenting Performance of European Universities. Paper presented at the Triple Helix.
Conference, Turin.
Saxenian, A. (1994), “Regional advantage – Culture and Competition in Silicon Valley and
Route 128,” Boston: Harvard Business School Press.
Review of Business and Economics

Stephan, P.E., Gurmu, S., Sumell, A.J., & Black, G. 2007, “Who’s patenting in the university?
Evidence from the survey of doctorate recipients,” Economics of Innovation and New
Technology, 16(2), 71-99.
Van Looy B., Du Plessis M. & Magerman T. 2007. Data production methods for hamonized
patent statistics: Patentee sector allocation, 94p. Eurostat Working Paper – KUL/MSI
Working paper.
Van Looy, B., Callaert J. & Debackere K. (2006), Publication and Patent Behaviour of aca-
demic researchers: conflicting, reinforcing or merely co-existing. Research Policy. 35, 4,
596-608
Van Looy, B. Debackere, K. van Pottelsberghe, B. Callaert, J., Lecocq, C. Landoni, P., Sapsalis,
E., Galland, P. (2004). DWTC project: Regional development through knowledge-driven
entrepreneurship: The role of knowledge generating institutions.
Van Looy, B., Callaert, J., Debackere, K., & Zimmermann, E. (2003), „Patent-related indicators
for assessing knowledge-generating institutions: Towards a contextualised approach.” Jour-
nal of Technology Transfer, Vol. 28: 53-61.
Van Looy, B., Debackere K. & Andries P. (2003), “Policies to stimulate regional innovation ca-
pabilities via university-industry collaboration: an analysis and assessment.” R&D Manage-
ment, 33, 2, 209-229.
Van Looy, B., Ranga, M., Callaert, J., Debackere, K., & Zimmermann, E. (2004), “Combining
Entrepreneurial and Scientific Performance in Academia: Towards a compounded and
reciprocal Matthew Effect?” Research Policy, Vol. 33: 425-441.
 The Role of Entrepreneurial Universities within Innovation Systems 81

Van Looy B., Meyer M., du Plessis M. & Debackere K. 2007. The impact of legislative

2009 / 1
framework conditions on the patenting behavior of universities: an empirical assessment.
Presented at the Triple Helix Conference, Singapore.
Varga, A. 1998. University Research and Regional Innovation. A Spatial Econometric Analy-
sis of Academic Technology Transfers. Kluwer Academic Publishers.
Varga, A. 2000. Local academic knowledge transfers and the concentration of economic
activity. Journal of Regional Science, 40(2).
Vavakova, B., 1998, the new social contract between governments, universities and society:
has the old one failed?, Minerva 36, 209-228.

Review of Business and Economics