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UNIVERSITY-INDUSTRY COOPERATION IN
RESEARCH AND DEVELOPMENT
Yannis Caloghiroua
Nicholas S. Vonortasb
Aggelos Tsakanikasa
Krannert School of Management, Purdue University“Organizational Issues in University Technology Transfer”
Indianapolis, June 9-11, 2000
Abstract: This paper tries to investigate some of the characteristics of the University-
Industry RJVs established in Europe in the context of the European Framework
Programmes. UI-RJVs are examined against the non UI-RJVs on their duration, size,
technology areas, frequency of participation and country distribution. In addition the
objectives, benefits and problems from cooperation with Universities, are analyzed,
building on the results of a European survey of 312 firms.
Results show that there is an increasing trend in UI collaboration during the last 13
years. Universities are involved in large and longer-term consortia. Significant
participation from peripheral regions is identified along with the emergence of a small
group of Universities with involvement in a large number of RJVs.
From the firms’ perspective the primary motive for cooperation with Universities
seem to be that of accessing complementary resources and exploiting research
synergies. Firm’s impact on their knowledge base is the most important benefit from
such collaboration, whereas no problems from collaborating were found significant.
a Laboratory of Industrial and Energy Economics, National Technical University of Athens.
b Center for International Science and Technology Policy and Department of Economics, the GeorgeWashington UniversityCorresponding author Center for International Science and Technology Policy, the George WashingtonUniversity, 2013 G Street, N.W., Suite 201, Washington D.C. 20052. E-mail: [email protected]
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1.Introduction
Since the late ‘70s, in industrialized countries the relationship between industry and
academia has grown in significance. Many scholars around the world have pointed
out the increasing number of linkages, established between firms and research groups
from various universities. Studies in US (Mowery 1998, Mansfield 1996,1998
Baldwin & Link 1998, Roessner and Wise 1994), have shown not only an increasing
percentage of academic research funded by industry in the last decade but also a
steadily rise of especially UI alliances and other forms of R&D partnering. ‘’Industry
is increasingly relying on partnerships with Universities’’1, now accounting for almost
7% of University research. Studies in Japan (Fransman 1995), NIC countries (Ahn
1995), and Europe (Geuna 1997, Sanchez 1995, Tijsen et al 1997), have also
emphasized in the mechanisms that have been developed to facilitate and make more
effective the interaction between Universities and Academia and the benefits, which
can derive from such collaborations.
In contrast with the United States, the link between academia and Industry has been
rather weak in Europe (Prosser 1992). However, the last decades and especially after
the implementation of the EU Framework Programmes, an increasing trend in the
linkages developed is becoming more visible. In UK, for about 10% of the
institutions, EU funding represents more than 50% of Research Council funds (Geuna
1998). In Germany, the relative share of industrial money within the total research
budget of the university increased from 5 to 9%, between 1985 and 1995 and an
average level of 20% of the industrial share in the engineering sciences and other
technology-related sciences, was estimated (Krahmer 1998). In Netherlands in 1994, a
3,5% of Dutch industrial R&D is carried out by Universities almost doubled in
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comparison to the situation just 4 years earlier (Bureau Bartels 1994). At present the
industry funding of academic research in the OECD countries in on average 5%,
which may be considered small, but has rapidly increased in the last years and is
expected to expand further.
This paper tries to shed some light on the characteristics of university-industry
collaboration, as it has been established in the context of the European Framework
Programmes (FWPs). It draws information on a new extensive database developed at
the National Technical University of Athens, which covers the majority of cost-
sharing research programs (64 in all), that the European Commission has funded
through the first four FWPs during 1984-1998.
Although purely descriptive in its analysis, our data allows us to look at the general
trend of university-industry collaboration in subsidized research across Europe. In
particular it examines –among others- the following research questions:
• What is the trend of University-Industry relationships in the European area,
through shared-cost funding?
• Are Universities involved in longer-term collaborative efforts?
• Are Universities involved in larger consortia?
• Are there any particular technological areas that seem to attract the University
participation to a greater extent?
• Can participation of peripheral regions be considered significant, considering
the number of their educational institutions and the overall population?
In addition the results of a pan-European survey, conducted in 7 European countries
(France, UK, Italy, Spain, Sweden, Ireland and Greece) are also presented. In
1 Council of Competitiveness, April 1996
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particular we examine the objectives, benefits and problems of cooperation with
Universities. Furthermore, we analyze the effect of size, R&D intensity and scientific
capability of the firm, as a possible determinant of entering in this type of
collaboration.
The general increase of U-I collaborations that has been reported by various studies
around the world is also confirmed by our data too. Results show also that a
relationship between size and duration of the RJV and the presence of a University
exists. Finally, our data detects the emerging of a small group of Universities that are
involved in a large number of RJVs and a large group of Universities with rather
limited participation.
Furthermore, data show that the primary objective from collaborating with a
University is accessing complementary resources and skills, followed by exploiting
research synergies. Also, firms benefit from such collaboration, by increasing their
knowledge base, whereas no significant problems during the collaboration were
detected. In addition, a relationship between size (in terms of sales) and scientific
capability (in terms of share of scientists) was also identified.
The rest of the paper is structured as follows: In section 2, a brief analysis of the
problems that the two parts are facing nowadays and the reasons for an emerging need
for closer interaction between Industry and Academia is presented. In section 3, the
data and the methodology that we use is described. The empirical and most important
part of this paper lies, however at the section 4, which is divided in two parts. The
first gives an overview of the RJV characteristics (UI against non U-I). The second
part, examines the objectives, benefits and problems of cooperation with Universities
and identifies possible determinants of entering in this type of collaboration. Finally,
at the last section a conclusion summary is presented.
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2.Universities and Industry in the knowledge and technology transfer process: Need
for cooperation.
Universities have always been considered as important generators of knowledge and
important agents for both technology transfer and knowledge diffusion. Focused on
more fundamental research, and due to the absence of time constraints, they could be
involved in long-term research, add to the variety of knowledge and give answers to
research questions that could improve the quality of life in society.
However, Universities face some problems especially during the last decades as the
shortages of funds due to the shrinking government support has affected the research
environment in which they operate. Secondly, as the majority of Universities is
becoming larger, a lack of flexibility in their organizational systems has been raised,
causing problems in the quality and the time of the research output/results.
Meanwhile, the institutions of higher education (HEIs) are under pressure to increase
not only the knowledge flow and the technology transfer but also the flow of people
to industry. The belief that Universities have to expand their role and become more
and more involved in the process of transfer of knowledge has become stronger.
On the other hand firms play also an important role in the knowledge creation process
but in this case knowledge is not created for knowledge’s sake. There are essential
constraints on the ability of firms to create knowledge and on the kind of knowledge
they create (Fransman, Tanaka 1995). From a business perspective, the aim is to
create knowledge that is related to market needs and adds to the company’s value and
ultimately, to profit generation. Besides, firms operate under a very significant time
constraint, as they must produce value now. This means that they can allocate rather
limited resources in creating knowledge in the future. Furthermore, there are problems
in keeping a balance between basic and applied research. Taking also into
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consideration the complex competitive situation, which is characterized by a rapid
technological change, firms tend more and more to look for outside resources to
supplement and substitute for the rather expensive in-house effort. It shouldn’t also be
underestimated that developing an international cooperation with a well-known
university creates positive image externalities for the firms involved.
The need for a fruitful collaboration seems to be a necessity. Nowadays, knowledge
doesn’t necessarily have to pass trough the public domain and money from the
industrial sector is more than welcomed. In addition the traditional line between basic
and applied research, translated into academic and industrial research, began to look
rather blurry and is becoming obsolete.
The situation however is not always ideal and the reason for this is what is described
as the ‘’two cultures’’ problem (Snow 1959, Declercq 1981). The basic argument
suggest that the normative and attitudinal differences separating universities from
industry are inexorable as they stand today and present barriers to close cooperation
between the two sectors2. Universities have different procedures and objectives,
which are not well aligned with the typical characteristics of the business culture.
Industry needs results quickly and much faster than usually University produces.
Issues related to intellectual property rights (IPR) have also been a source of tension
in their relationships. As the research results must be somehow protected so that they
can provide a competitive advantage to firms, they usually ask for secrecy or at least a
‘’time advantage’’ before publishing any results. Conflicts are created then, since the
scientific productivity and the reputation of academics is built on their publications.
2 Drucker 1973, Rosenweig 1982, Gray et al 1986, Public Policy Center for Stanford Research 1986,Geisler and Rubinstein 1989, National Academy of Sciences 1992,
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These different approaches have been the reason for the limited, up to these days,
collaboration. However these problems have began to fade away, in the light of other
obstacles that the two parts had to face. People from the industry paid more attention
to the research results of University teams and started appreciating the quality of their
work. People in Universities become attracted from shorter-term problem solving
efforts and slightly shifted away from the fundamental, ‘’heavy’’, longer-term issues.
User oriented research (including patentable inventions) is now accepted as having a
legitimate place in university research (Lee, 1996). The ground was clear for a
combination of the forces for common good.
Governments, responding to the emerging need for closer ties, took action in
facilitating the interaction between them and proceed with removing any legal
obstacles and constraints on personnel mobility, and promoting funding for
collaborative research through national research programmes.
In the European area in general, it was the launch of the European Framework
Programmes that materialized the need for a channel of communication between
actors from different countries. Aiming at pulling together the might of companies,
laboratories, universities etc. from different European countries in pursuit of common
technological goals, EC launched the first Programme ESPRIT in 1984, focusing on
the straightening of the ICT European Industry. Other initiatives like EUREKA and
COST Programmes have also been developed, but it is the FWPs that seem to gather
the majority of firms, Universities, Research Institutes and other agents from all over
Europe.
3.Data and Methodology
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The analysis that will be presented is based on a large extensive database that
has been developed in LIEE called STEP TO RJVs Databank. It includes the EU-RJV
database, which contains information on transnational RJVs that have been
established in Europe through the European Framework Programmes (EU-FWPs).
The RJVs that are included in this database have the common characteristic that at
least one member of their consortium is a firm. A selection of Programmes was also
necessary since the aim was to include Programmes that involved industrial research3.
Therefore up to 64 EU FWPs are included and the total number of projects available
reaches 6,300 RJVs. covering an extensive period of 13 years (1983-1996).
The Databank also includes the ‘’Survey database’’, which contains the results of a
questionnaire field research, which was circulated on firms that have participated in
these RJVs (EU FWPs or EUREKA ones). The questionnaire was extensive enough,
obtaining information about the corporate and business strategy, business
environment and the attitude of the firm towards the creation of new knowledge.
Additionally information about the objectives of the participation, the benefits, the
problems, as well as the appropriation of the results was also collected4. The
following section builds on these two datasets.
4.Empirical Analysis
4.1 Analysis of the EU- Research Joint Ventures
In Table A1, the number of the RJVs that have reported a starting date is
presented along with the actual number and percentage of the ones that involved at
3 Thus, Programmes whose main focus was not the creation of new technological knowledge (likeforecasting, evaluation policies etc.) were excluded, since it would be rather difficult to properlyinterpret the final results.4 The survey was conducted in seven countries (France, Greece, Ireland, Italy, Spain, Sweden, UnitedKingdom) during the period from February 1999 to July 1999. The projects included in the sample ofthe survey were a mixture of EU-funded, EUREKA and nationally funded projects.
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least one University. Generally, 65% of the collaborative R&D performed in the
specified time period included a university as a research partner.
Table A1 (around here)
The increasing trend in Universities’ participation in the European Framework
Programmes can be detected more systematically from both a linear least squares
regression on the annual number of RJVs with universities as partners (RJVwU),
against the independent variable Year, and a semi-logarithmic regression of the log of
the annual number of RJVs (lnRJVwU)5:
RJVwU = a0 + a1 Year + å (1)
ln(RJVwU) = b0 + b1 Year + å (2)
The regression results from both equations are presented in Table A2, and confirm
what the tabulated data have shown as a positive statistically significant relation is
identified.
Table A2 (around here)
RJVs are also examined on their duration. Previous studies suggest that universities
are involved in longer-term research, because of the nature of the research that they
undertake (more basic). In the specific case however, there is a bias problem since
most of the EU-RJVs follow certain rules according to each Programme, imposing an
upper limit of usually three years6. In fact only 21% of the RJVs last more than 36
months. Results show that Universities are involved in RJVs that could be
characterized as longer-term. The average duration of an RJV with a University is 34
months, whereas RJVs with no University as a partner last on average 3 months less.
The value of the median, however (36 months against 31 months) highlights best the
5 Baldwin & Link (1998) have run the same regressions for US data (NCRA)6 If the partners of a specific RJV chose to continue on a project (with the financial aid of EU), theyusually propose a second RJV (phase two or more of their project), which is however recorded as a
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effect of university participation in duration. As we mentioned earlier almost 21% of
the sample (more than 1200 RJVs) last more than 36 months, revealing thus that most
of these, long-term RJVs include a University as a member of the consortium.
About the size of the RJV, it has been suggested that RJVs with University members
are distinctly larger than those without. The picture from our dataset reinforces that
contention, as university participation increases perfectly with membership size.
Especially the most sizeable consortia (>21 members) are dominated almost
completely (92%) by RJVs with a university member. Furthermore the average size of
a RJV with university member is almost 8, whereas the size of a RJV without, is just
above 5 members.
A number of reasons have been proposed, explaining the reason why such a
hypothesis is confirmed. Baldwin & Link (1998) suggest that the net gains are greater
for industry participants in RJVs with a large number of partners, since the loss in
appropriable information from the university’s involvement decreases as the
size increases. Also Universities show a preference for more costly projects (and
therefore larger consortia) to absorb overhead administrative costs associated with
externally contacted research. Their findings from a study on US RJVs, concludes that
since Universities have a comparative advantage in more basic and generic type of
research, perhaps they are more likely to be involved in RJVs with a large number of
industry members, as it is projects of this type that are likely to be of greatest
industry-wide interest and have the least prospect of appropriability.
Looking at the technological areas of the RJVs that Universities are usually involved
and although the areas are somehow predefined according to the general classification
of the EU FWPs, results show that in most areas more than half of the sample
new RJV. Therefore we cannot identify projects that were a continuation of previous ones in ouranalysis.
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involves cooperation with University. The percentage of RJVs with University
member varies between 56 and 65% and the highest value is observed in the area of
Biotechnology, which is maybe one of the key technologies of the future. In addition
the amount of time for research in this area is relatively higher than all other areas and
the time lag between a discovery and commercial application (if any) is also greater.
Universities seem to possess the know-how for such R&D activities and supplement
maybe the expensive in-house R&D of the firms. Also in other related areas such as
Agriculture, Environmental protection and Resources of the sea, the presence of a
University seem to be a necessity. In fact there is evidence showing that in the
Industries that are related more or less with these areas (like Chemicals, Medicine),
over 10% of the new products and processes introduced in 1986-1994, could not have
been developed –without substantial delay- in the absence of recent academic
research (Mansfield, 1998).
A total population of 885 Universities has participated at least in one RJV in the
examined time period. The majority of them have participated only once in the EU
RJVs (37%), but there is also a 14% that has participated more than 20 times and also
a group of 12 Universities that reports more than 100 participations during the 13
years period. The population of universities that participated in the examined EU-
funded RJVs seems to be composed by a large number of agents with little
participation and a smaller group with involvement in a respectable and relatively
large number of RJVs7
More than half of these 885 Universities come from the three main countries that
dominate the participation in general too. France, UK, and Germany have a strong
7 Such a picture has been also confirmed from previous studies (Geuna 1998). In addition, evidenceshows that the research size of a University along with the scientific research productivity (measured
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educational system with some of the oldest, larger and most famous Universities in
Europe, providing the means of being involved in a large number of EU-RJVs. But
substantial representation (considering the overall population of Universities) from
‘’peripheral’’ countries like Greece, Portugal or Ireland is also observed. The fact that
one of the main aims of EU policy for the Framework Programmes is to achieve a
techno-economic convergence among different countries tends to give an advantage
to the participation of universities localized in peripheral regions. In addition evidence
shows that the ‘’due to the unintended consequences of the selection mechanisms, the
early entrants in the system tend to have advantages in repeated participation’’
(Geuna, 1998). But also, in these peripheral regions, at least until the beginning of the
90s’, it was usually government laboratories and Universities that represented the
main R&D agents and still do, especially for selected regions in these countries
(Sanchez, Tejedor 1995, examining the case of Aragon in Spain).
Finally results show also that there is a variety of Universities included in the sample,
indicating that even less prestigious departments can produce satisfactory results, as a
similar study for the US Universities has also suggested (Mansfield, Lee, 1996).
4.2. Survey results
A total population of 312 firms from 7 countries has responded in the survey,
providing usable responses8. The extent to which firms are involved in cooperation
with Universities will be used in order to relate this information with firms’
by the number of publications) have both a positive effect on the number of times an institutionparticipates in these RJVs.
8 The country distribution of the sample is as follows: Greece 88 firms, UK 73 firms, Spain 43 firms,Sweden 30 firms, Italy 30 firms, France 29 firms, and Ireland 19 firms. We are not concerned with theoverrepresentation of certain countries (especially Greece), as the unit of analysis for the specificresearch is the European firm and not a specific sub-group from the same country. However and inorder to provide reliable results, an alternative sample with a random exclusion of Greek firms,including finally only 60 firms, was also tested for all items presented here. The results remainedrobust, as no significant differences were observed.
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objectives, benefits, and problems from collaboration, along with some other
characteristics (such as size, R&D intensity and scientific capability).
4.2.1 Objectives, benefits and problems from cooperating with Universities.
Firms were asked to estimate the extent to which they were involved in cooperative
R&D agreements with different types of organizations, universities included. A Likert
scale from 1 to 5 was used, where 1 meant no involvement in cooperation with the
specific agent, and 5 indicated strong involvement. Table B1 shows all possible
organizations that the firms might cooperate, along with some descriptive statistics.
Table B1 (around here)
Cooperation with Universities is estimated higher (mean value of 3,5), indicating that
most firms tend to be involved in such a type of cooperation to the largest extent,
higher than any other type of collaboration. At the second place of preference, with a
difference of 0,62 is cooperation with client firms. In an alternative way of examining
the data, over 57% of the respondents ranked cooperation with Universities with a
degree of 4 and 5, whereas the second most popular response (client firms), received
39% of the firms.
In an effort to identify possible country differences, since our sample comes from 7
different European countries, analysis of variance was performed. Results showed that
it is Swedish firms that are involved in cooperation with Universities to a greater
extent, more than all other countries. Firms from Ireland, Spain and France, seem to
use this type of cooperation to the smaller extent. On the other hand, firms from Italy,
UK and Greece seem to follow a rather similar pattern in terms of cooperation with an
educational institution, since no significant differences in their means were observed.
A number of Pearson r correlation matrices were computed in order to identify
possible association of the extent to which firms are involved in cooperation with
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Universities (COOPUNIV from now on) and the firm’s objectives, benefits and
problems from collaboration. The results are presented in a unified table (Table B2)9.
Table B2 (around here)
When examining the objectives from cooperative R&D, a total number of 8 variables
were found significantly correlated with COOPUNIV, all with a positive sign. More
specifically, the strongest significant correlation exists between COOPUNIV and
access to complementary resources and skills. Also significant at the level of 0,01 are
the correlations with the objectives of research synergies leading to cost savings or
improvements in R&D productivity and R&D cost sharing. This group of three
variables, which is highly related with cooperation with Universities, composes one
dimension of the objectives from cooperative R&D, which seems to describe the cost
and resources in the R&D of the firms. Another set of two variables are also
significant at the 0,01 level: Technological learning and keeping up with major
technological developments, which clearly describe the technological development of
the firms. Thus, both the R&D and the technological development of the firms are
highly related with cooperation with Universities. The funding seems to be also
related with COOPUNIV at the level of 0,01 while at the level of 0,05 a couple of
objectives are also positively correlated: Controlling future market development and
avoiding loss of information to competitors.
Analysis of the results10 has shown that firms seem to benefit from cooperative R&D
in three-dimensional way. More specifically there are benefits that contribute to the
Knowledge base of the firm. Improvement of unit’s technological and organizational
capabilities, exploitation of complementary resources, new knowledge
9 Due to space limitations only the significant correlations are presented. All results are available bythe authors.
10 Factor analysis
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acquisition/creation and acceleration of research are the components of this
dimension. The second dimension could be referred as the Product Development
Impact on the firm, including benefits of development or improvement of products
(new or existing) and the subsequent effect on profitability and market share. Finally,
the third dimension captures the effect on the process development of the firm, as a
firm may benefit from cooperative R&D in a way of developing or improving new or
existing processes. These three variables (named KNOWBASE, PROCDEV,
PRODDEV) are both correlated with cooperation with Universities. The strongest
relationship exists however in the knowledge base of the firm. The more a firm
cooperates with Universities the more it increases the impact on its knowledge base.
Finally a correlation between various problems that can occur during cooperation
provided no significant results, revealing a very optimistic picture, since firms do not
seem to face any problems when they cooperate with Universities.
In order to further analyze the objectives, benefits and problems from cooperation in
R&D and in particular examine the effect of cooperation with Universities, we also
proceeded with an additional analysis by performing a series of t-tests. The sample
was divided in two different sets: Those that tend to cooperate with Universities in a
greater extent and therefore have estimated this type of collaboration with 4 or 5 in
the relevant question, and those that do not cooperate with Universities so much, and
therefore have estimated it with 1 or 2. The previous results were confirmed also with
these tests, since significant differences between the two sets were observed more or
less in the variables that a significant correlation has been also identified.
4.2.1 Cooperation with Universities and corporate firms’ characteristics.
Next we examine the effect of several corporate characteristics of the firm and the
propensity to cooperate with Universities. Size, in terms of employees and sales,
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R&D intensity (usually referred as technological intensity), and finally share of
scientists, are tested against the involvement of a firm in cooperation with an
educational institution11. The sample was stratified and divided according to the
variable in test, and analysis of variance (one way ANOVA) was performed in order
to identify possible difference and therefore conclude in a factor determining the
collaboration with Universities or not.
Results show that the there seems to be no indication of a relationship between size
(in terms of employees) and the propensity to cooperate with Universities. However if
we examine size based on the sales, then significant differences do occur: The firms
that sell by average over 1 billion Euros tend to cooperate more often with
Universities than SMEs.
Analysis has also proved that R&D intensity (computed as R&D expenditures / Sales)
has no significant impact on the propensity to cooperate with Universities. Therefore
it seems that there is no relationship between technological intensity and frequency of
cooperation with Universities.
On the other hand, significant differences in the sample were observed when the share
of scientists (measure of the ‘’scientific capability’’ of the firms) was tested. In
particular, results show that the firms with rather limited scientific personnel (below
5%) differ significantly from almost all other groups, whereas there is no difference
between groups with a share of scientists above 10%. A positive correlation between
the share of scientists and cooperation with universities was also identified indicating
a contention that the more the scientific capability of the firm, the more it cooperates
11 In this case we decided to use the alternative sample that we have mentioned earlier, because of thefact that data for the Greek firms were of higher quality than the data from other countries. This couldcause some problems with the interpretation of the results, taking into consideration also the fact thatthere was already an overrepresentation of firms from Greece. However, analysis with the primarysample set has been also run and the results remained robust, indicating that results are not affected by
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with Universities. This is not surprising taking into consideration that one of the major
elements in collaborating is trust. Given that most of the scientific personnel are
graduates of Universities, they have probably established relationships, formal or
informal, with people in University (professors or colleagues working in various
research teams. Therefore, common understanding, allows for the effective promotion
of collaborative research efforts.
5. Conclusions
The aim of this paper was to investigate university – industry collaboration in the
context of the European Framework Programmes. Furthermore we aimed in
identifying –from the firms’s perspective- the objectives, benefits and problems from
cooperation with Universities.
Analysis of the RJVs, showed that the trend of the collaborative research activities
within the context of FWPs is steadily increasing. The same contention is proved for
the RJVs, which involved at least one university member, as an increasing
relationship was confirmed.
Even though there has been a shift from longer - term issues, to shorter, problem
solving research, Universities seem to be a necessity in consortia, which last beyond
three years. Taking into consideration also the fact that most of the EU RJVs are by
nature at a pre-competitive stage (and therefore more basic), it is not surprising
finding out that Universities are involved in the longer-term RJVs. In addition there
are areas like Biotechnology, where only in few cases, no University was involved.
As the size of the RJV increases, the probability of a university partner also increases
Universities are therefore involved in larger consortia.
the Greek overrepresentation, anyhow. For scientifically accuracy though, we insisted on presenting theresults of the ‘’alternative’’ sample
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In terms of frequency of participation, it was identified that a small group of
Universities were involved in a large number of RJVs. Taking into consideration their
multi-department structure and the human resources available, such a finding is rather
an expected one. But the largest group consisted of Universities, which have
participated in few RJVs. However, it was noticed that more than 870 European
educational institutions have at least once participated in these RJVs, indicating the
widespread involvement of them in the specific mechanism of collaboration with the
industrial sector. Especially, that fact that Universities from less favored regions
(Greece, Portugal etc.) have grabbed the opportunity of being part of this knowledge
creation and transfer process, indicates the effect of the FWPs in maybe achieving the
convergence and social cohesion that is much desired12.
From the firms’ aspect, it was also confirmed that Universities are by far the most
popular type of organization to cooperate with. In addition, the benefits referring to
the knowledge base of the firms, but also to what can be summed up as the product
development, were found significant.
Firms’s major objectives from cooperation with Universities are accessing
complementary resources and skills, achieving research synergies that would increase
their R&D productivity, and keeping up with major technological developments. But
the possibility of obtaining extra funding through this type of cooperation is also
significant. An optimistic conclusion has also come up, since no problems related
with the specific type of collaboration, have been identified.
Size, in terms of sales, seems to be important, as it was proved that the largest selling
firms tend to cooperate more often with Universities. Also significant was the share of
19
the scientific personnel, since the more a firm is staffed with this type of personnel the
more possible to be involved in this type of cooperation.
Finally, among the seven countries for which data were available, it was found that
firms located in Sweden are involved in cooperation with educational agents more
than all other countries. On the contrary, firms from Ireland seem to rarely use this
type of collaboration. Greek, British and Italian firms follow a similar pattern of
behavior with a relatively extensive involvement.
6. References
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2. Baldwin W.L., Link A.N., ‘’Universities as research joint venture partners: does
size of the venture matter’’ International Journal of Technology Management, Vol 15
No 8, 1998.
3. Bureau Bartels, ‘’R&D networks of Dutch Companies’’, 1994
4. Council of Competitiveness ‘’Endless Frontier,Limited Resources: US R&D
Policy for Competitiveness, Washinghton DC, 1996.
5. Declercq G.V. ‘’ A third look at the two cultures: The new economic
responsibility of the University’’ International Journal of Institutional Management in
Higher Education 5 (2) 1981, pp.117-122
6. Drucker P.F. ‘’Science and industry, challenges of antagonistic interdependence,
Science 204, 1973, pp. 808-815.
7. Fransman M, Tanaka S. “Government, globalisation and Universities in Japanese
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20
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22
Table A1: Allocation of the RJVs based on the starting date.
YearNumber ofRJVs
RJVs with at least oneUniversity Year
Numberof RJVs
RJVs with at leastone University
1983 9 5 56% 1990 500 329 66%1984 54 35 65% 1991 423 284 67%1985 79 43 54% 1992 797 548 69%1986 284 156 55% 1993 574 366 64%1987 137 85 62% 1994 666 449 67%1988 275 151 55% 1995 439 248 56%
1989 294 203 69% 1996 1401 938 67%
Total 593213 3840 65%
Table A2: Universities as research partners between 1983-1996.
Variables RJVwU ln(RJVwU)
Intercept -97827,7(-5,05)**
-556,2(-6,05)**
Year 49,31(5,07)**
0,28(6,1)**
R2 0,66 0,74N 14 14t-statistics reported in parentheses** denotes significance at the 0,01 level.
13 The total number of RJVs is not 6300, as the starting date wasn’t available for the whole sample.
23
Table B1: Estimation of the extent of cooperation with various organizations14
Type of organization Mean Std Dev Min MaxPublic research institution 2,74 1,47 1 5University 3,46 1,35 1 5Supplier firm 2,33 1,44 1 5Client firm 2,84 1,48 1 5Competitor firm in the same geographic market 1,77 1,15 1 5Competitor firm in different geographic markets 2,11 1,33 1 5Other firms 2,53 1,38 1 5Other organizations 2,18 1,30 1 5N=288
Table B2: Correlation results
COOPUNIVObjectives from cooperative R&D (N=285)
R&D cost sharing Cor.Coef. 0,180**Sign.(2 tailed) 0,002
Access to complementary resources and skills Cor.Coef. 0,260**Sign.(2 tailed) 0,000
Research synergies leading to cost saving or improvements inR&D productivity
Cor.Coef.0,243**
Sign.(2 tailed) 0,000Technological learning Cor.Coef. 0,197**
Sign.(2 tailed) 0,001Keeping up with major technological developments Cor.Coef. 0,223**
Sign.(2 tailed) 0,000Obtain funding Cor.Coef. 0,196**
Sign.(2 tailed) 0,001To avoid unintended loss of information to competitors Cor.Coef. 0,133*
Sign.(2 tailed) 0,025Benefits from cooperative R&D (N=281)
KNOWBASE Cor.Coef. 0,318**Sign.(2 tailed) 0,000
PROCDEV Cor.Coef. 0,121*Sign.(2 tailed) 0,042
PRODDEV Cor.Coef. 0,190**Sign.(2 tailed) 0,001
*Correlation is significant at the 0.05 level (2-tailed).**Correlation is significant at the 0.01 level (2-tailed).
14 Reliability analysis performed in this question in order to examine the validity of the scale that wasused, resulted in a value of cronbach alpha of 0,67, indicating very good reliability.
