University-Industry Collaboration and the Development of High

University-Industry Collaboration and the Development of High

Emergent and Mature Industries: The role of University-Industry
Collaborations
Isabel Maria, Bodas Freitas
Grenoble Ecole de Management, 12 rue Pierre Sémard-BP 127, 38003 Grenoble cedex 01
& DISPEA, Politecnico di Torino, Corso Duca degli Abruzzi, 24b, 10129 Torino
Email:[email protected]
Rosane Argou, Marques
Agência Brasileira de Desenvolvimento Industrial (ABDI),
Email: [email protected]
Evando Mirra de Paula e Silva
Agência Brasileira de Desenvolvimento Industrial (ABDI)
Abstract
The paper analyses the characteristics and role of university in the development of
technological capabilities in mature and emergent sectors, in New Industrialised Countries
(NIC). Based on evidence from 24 research groups in university and public research
organisation science and engineering departments in Brazil, the paper shows that the contexts
of university-industry interaction in mature and emergent sectors are diverse: informal and
professional networks tend to be underdeveloped, and support and encouragement of research
projects in emergent sectors by public research sponsors are far from timely. The role of the
student is crucial for mediating universities and firms active in emergent sectors. In light of
our results, we discuss the role of public support for university-industry collaboration to fight
economic and technological stagnation, in NIC.
1
1. Introduction
Studies in Europe and the US tend to show that for firms, collaboration with national public
research and education organisations (PREO) may reduce the uncertainties inherent in the
innovation process, expand markets, enable access to new or complementary resources and
skills, create new technological learning opportunities, and allow companies to keep abreast
of the evolution of scientific knowledge and technology (Hagedoorn et al., 2000; Lee, 2000;
Fritsch and Lukas, 2001). Therefore, collaboration with PREO is an alternative strategy
allowing firms to deepen their innovative capabilities and strengthen their international
competitiveness. This is particularly important in a context where science-based technologies,
such as biotechnology, nanotechnology, information and communication technology and
renewable energy are being developed and becoming pervasive, and where technological
interdisciplinarity and complexity, and the competitive pressures to shorten product life are
increasing (Koumpis and Pavitt, 1999; Hagedoorn, 1996; Caloghirou et al., 2003).
As the economies and indigenous technological capabilities of the New Industrialised
Countries (NIC) improve, national PREO are expected to become increasingly important for
supporting indigenous firms to move into more dynamic and high-opportunity industries
(Mathews and Hu, 2007; Mazzoleni and Nelson, 2007; Wu, 2007). Following the innovation
policies in the OECD countries, NIC governments are focusing increasingly on fostering
science-industry interactions and developing high-technology sectors (Wong et al, 2007;
Gouvea and Kassicieh, 2007). In Brazil, for instance, since 2003 policy-makers have focused
on improving technological capabilities and developing and growing its high-technology
industries (Brazilian Government, 2003; Gouvea and Kassicieh, 2007).
However, the adoption of the OECD’s best practice in technology transfer (e.g. creation of
university Technology Transfer Offices (TTOs), definition of Intellectual Property Rights
(IPR), support for university spin offs) might be less efficient to support university-industry
collaboration and the growth of national high-technology sectors in NIC (Lall, 1992; OECD,
2005; Mowery and Sampat, 2005). The design and implementation of appropriate science and
technology policies requires information on the context and characteristics of existing
university-industry collaboration (Najmabadi and Lall, 1995; Goldman et al., 1997), and an
understanding, in particular, of the specificities of PREO-industry interaction in both mature
and emergent sectors. Few studies have explored the pattern and impact of this cooperation in
NIC, and almost none has analysed the specificities of this relationship in mature and
emergent sectors. This paper is an attempt to fill this gap and to examine the characteristics of
university-industry interaction in mature and emergent industries, and to provide evidence
that will support science and technology policy-making in NIC.
2
Using data from semi-structured, face-to-face interviews with a sample of 24 coordinators of
research groups in science and engineering departments in universities and public research
organisations, first, we analyse the context of science-industry collaboration, i.e. the
motivations, goals and outputs, and main barriers to and facilitators of such collaboration in
Brazil. Second, we examine the organisational changes undertaken by PREO to improve
entrepreneurial attitudes among academic researchers. Third, we explore the specificities of
university-industry collaboration in emergent and mature sectors.
Our analysis shows that university-industry interaction has some specific industry life cycle
characteristics in terms of forms of organisation, origin of collaborative projects, and outputs,.
We show that informal and professional networks of university and industrial researchers in
emergent activities are underdeveloped compared to mature sectors and that national public
sponsorship financing procedures delay the encouragement of collaborative projects involving
firms in emergent sectors. This means that in these sectors, the roles played by students and
firms’ employees in mediating between universities and industry, and in implementing
collaborative projects are especially important. In terms of outputs, university projects with
firms in emergent sectors are often more productive and more focused on product
development than projects in mature sectors. Based on our evidence, we would argue that
public support for university-industry collaboration per se is not enough to encourage the
development and growth of high-technology national activities because the characteristics of
the technical and market knowledge and the channels of knowledge transfer are dissimilar in
mature and emergent sectors.
This paper is organised as follow. Section 2 reviews the role of PREO in the catching up
process, and the characteristics of the innovative process and the specificities of universityindustry interaction in mature and emergent industries. Section 3 examines the context of
university-industry interaction in Brazil. Section 4 presents the data and methodology used in
our analysis. Section 5 explores the pattern of the university-industry collaboration in Brazil
in terms of motivations, object and outputs, and organisational changes in PREO to facilitate
provision of assistance to and incentives for researchers to cooperate with industry. Section 6,
discusses the characteristics of university projects with firms in emergent and in mature
industrial and technological activities. Section 7 concludes the paper.
2. University-industry interaction and the technological challenges in mature and
emergent industries in NIC
2.1. University-industry interaction and the technological challenges in NIC
3
Catching-up by developing and NIC is a long, difficult and costly process of learning-bydoing and by-interacting (Dahlman et al., 1987; Lall, 1992, 1998; Hobday, 1995). Some
researchers believe that catching up to the developed countries, is particularly difficult
because of the sticky relationship between export performance and innovative capability.
Montobbio and Rampa (2005) show that in NIC innovative activities tend to be concentrated
in industries that are technologically stagnant.1 This specialisation in unsophisticated products
with low returns and high price elasticities, limits the availability of internal resources to
invest in developing skills and technology. In order to stay in the race, NIC that have
managed to accumulate a certain level of innovative capability in certain medium-high
technology industries, need continually to upgrade their capabilities and restructure the
composition of industries and exports.
Although there is no single method that can be advocated for developing the capabilities to
produce, invest, cooperate and innovate (Lall, 1992; Najmabadi and Lall, 1995; Goldman et
al., 1997), the successful catching-up processes in Germany, Japan, South Korea and Taiwan
in electronics, and in Brazil in aerospace and offshore oil prospecting, all seem to rely on the
combination of specific factors (Mazzoleni and Nelson, 2007). These include cross-border
flows of people, policies that support industrial development and protect domestic industries,
and IPR regimes that allow imitation of advanced technologies (Mazzoleni and Nelson,
2007).
In the international economic and technological context of the late 2000s, however, most of
these catching-up strategies are impossible for developing and NIC countries (Brahm, 1995;
Wen and Kobayashi, 2002; Gouvea and Kassicieh, 2005). The governments in these countries
are limited mainly to the implementation of policies that provide incentives and subsidies for
research and development (R&D) activities and support the development of the training,
technology and research infrastructures that are essential for particular sectors (Lall, 1992,
1998; Montobbio and Rampa, 2005; Mazzoleni and Nelson, 2007). On the one hand, World
Trade Organization restrictions do not allow NIC to protect or subsidise specific products or
firms, and on the other hand limit foreign firms’ access to their domestic markets. Moreover,
firms in developed economies are implementing increasingly strong IPR protection and
exploiting naturally occurring resources in developing and NIC countries, including the local
1
In developing countries, ‘technological activity generates export gains in high technology sectors if a
country expands its innovative activities in industries with increasing technological opportunities, in
medium technology sectors moving out from low opportunity industries losing in terms of relative
innovativeness, in low technology sectors if it is initially specialized in sectors with a greater growth of
their world share’ (Montobbio and Rampa, 2005, p. 542 ).
4
knowledge and local government incentives and R&D subsidies (Gouvea and Kassicieh,
2005).2
Therefore, in the NIC, national governments need to set effective science and technology
policies to support the entry of indigenous firms into dynamic sectors with high technological
opportunities and to enable exports of more technologically sophisticated products (Wen and
Kobayashi, 2002; Mathews and Hu, 2005; Montobbio and Rampa, 2005; Eun et al., 2006;
Wonk et al., 2007).
PREO are often seen as key actors in the process of technological catch-up in specific
industrial sectors. They can support the development of national technological capabilities
and catch up, through the provision of training for national scientist and engineers, support for
personnel exchanges involving international research centres’ researchers, experts and
students, access to international research networks where new technologies are developed,
and advanced knowledge and skills in the relevant science and engineering fields (Pavitt,
1998; Mazzoleni and Nelson, 2007; Robertson and Patel, 2007). PREO also can support and
advise firms and governments about how to develop and employ technologies so as to avoid
direct infringement of foreign IPR (Gouvea and Kassicieh, 2005; Mazzoleni and Nelson,
2007). As technological problem-solving research relies heavily on the basic sciences,
scientists and engineers with the capabilities for their mastery and who are well connected in
international networks, are fundamental for comprehensive learning by doing, by searching
and by interacting in developing and NIC (Pavitt, 1998; Mazzoleni and Nelson, 2007).
However, catching-up and accumulating technological capabilities require indigenous firms to
develop the capabilities of production, investment, linkage and innovation (Dahlman et al.,
1987; Lall, 1992). Consequently, indigenous firms need to invest in R&D in order to increase
their potential to learn and to absorb external knowledge (Hobday, 1995; Pavitt, 1998;
Eisenhardt and Martin, 2000). In developing countries, expenditure on R&D tends to be low
and to be concentrated in PREO; thus policy efforts are required to address the absorptive
capabilities of firms (Montobbio and Rampa, 2005; Wu, 2007).
On the other hand, PREO will only be able to contribute to economic development and catch
up if they focus on practical, problem-solving research projects as opposed to remaining in
their “ivory towers” of learning (Ekboir, 2003; Mazzoleni and Nelson, 2007). In particular,
2
The globalisation of production, investment and research activities in many industries may support this
process of catching up, but often creates obstacles to further technological development by developing
countries, especially in high technological opportunity industries. Foreign direct investment (FDI) is a
good means for a truncated transfer, of ‘the results of innovation rather than the innovative process
itself’ (Lall, 1992, pp. 170, 179).
5
PREO need to both foster communication and support problem-solving, and tailor and
develop technologies for a well-defined community of industry users (Ekboir, 2003). Linear
development of science and innovation by government and in PREO discourages interaction
among agents and technological accumulation (Ekboir, 2003).
In most developing and NIC, the organisation of research and education reduces the potential
of PREO to participate in knowledge development and transfer. PREO tend to be managed
centrally, regulated by government and have little incentive to transfer their technology and
huge incentives to reproduce the technologies developed in advanced countries (Ekboir, 2003;
Wu, 2007). In addition, public researchers in NIC are rarely evaluated on the quality of their
research results or the level of their interactions with other agents (Ekboir, 2003; Wong et al.,
2007). Thus, the introduction of several mechanisms (e.g. to monitor the quality of research
programmes, to decentralise decision-making to foster interaction and customisation to
industry needs and encourage risk-taking by researchers) may be needed to improve the
scientific and technologic competencies of PREO, (Ekboir, 2003; Mazzoleni and Nelson,
2007).
In some developing and NIC, measures to make universities more entrepreneurial were
implemented through the creation of TTO, licensing offices and incubators, accompanied by
the introduction of an entrepreneurial dimension in education programmes (Eun et al., 2006;
Mathews and Hu, 2007; Wong et al., 2007). Some authors argue that the combination of
central and local rewards and incentives for basic research outputs and discoveries, for the
development of entrepreneurial universities, for the diffusion of advanced technologies and
for the development of technological support infrastructures have leveraged catch up in
certain areas of technology (Wong et al., 2007; Wu, 2007). However, in some cases, science
policy objectives and instruments collide, leading to few incentives for interactions with
industry and other research organisations to find solutions to practical problems (Ekboir,
2003; Eun et al., 2006).
In sum, in order to overcome economic and technological stagnation in NIC, upgrading
PREO capabilities to provide R&D, to enable interaction with other agents, and to incubate
new knowledge-based firms seems crucial (Etzkowitz et al., 2005; Eun, et al., 2006; Wong et
al, 2007).3 Policy-makers in both developed and NIC are focusing more on policies aimed at
3
Nevertheless, transparent legislation, providing protecting for the rights to traditional knowledge and
natural resources, and stimulating industry’s technological and innovative investments, is also vital for
the further development of industries with high-technological opportunities. Gouvea and Kassicieh
(2005) stressed the importance of legislation, e.g. in the case of the Brazilian biotechnology industry,
where some collaborative projects between local firms and multinationals were cancelled due to the
6
raising the quality of PREO research and training programmes, to make their role more
entrepreneurial and positive for national economic development, and to support the growth of
high-technology activities. However, the role of universities in the development of innovative
capabilities and the characteristics of university-industry interaction may differ for mature and
emergent high-technology sectors. Below, we review the differences between mature and
emergent industries in terms of the process of building industrial innovative capabilities; we
discuss the specific role of the university in the development of industrial technological and
innovative capabilities, in light of these differences.
2.2 Innovative process in emergent and mature industries
The innovative environments of mature low and medium technology industries and emergent
high-technology industries differ considerably in terms of market and technology turbulence,
and the characteristics of knowledge inputs. Consequently, search strategies for innovative
inputs, the role of networking and collaboration for innovation development, and the
innovative outputs themselves will also differ (Utterback and Abernathy, 1975; Tushman and
Anderson, 1986; Strebel, 1987; Eisenhardt and Martin, 2000).
The emergent industry environment is characterised by strong competition in technology and
product developments and strong market turbulence. As industries mature, and industry
standards are established, technological uncertainty decreases, competition becomes
increasingly based on costs, and on process and incremental product innovation (Utterback
and Abernathy, 1975; Strebel, 1987). Therefore, both technologies and markets evolve more
quickly in emergent than in mature industries (Eisenhardt and Martin, 2000), but there is no
evidence of innovation being less frequent among firms in mature rather than in emergent
sectors (McGahan and Silverman, 2001; Robertson and Patel, 2007).
Also, the types of knowledge inputs relevant for firms’ innovation development and,
consequently, the ways of accessing the knowledge sources, and the outputs of firms’
innovative efforts may be quite different across the industry lifecycle. Tacit and disembodied
knowledge seems to be particularly important for innovative activity in the early stages of the
industry lifecycle and, consequently; personal contacts (telephone calls, to meetings, to
demonstrations) may be decisive for knowledge transfer (Audretsch, 1998; Mangematin and
Nesta, 2001). Given the importance of disembodied knowledge and personal contacts for
absence of well defined parameters in existing legislation. In addition, policy defined programmes to
encourage technology diffusion and interactions among public and private agents and problem-solving
research rather than selection a priori of a particular technology, would seem to be required for the
process of technological catching up (Wen and Kobayashi, 2002; Ekboir, 2003). Creating appropriate
institutions throughout the process of industrial development is also crucial.
7
innovative activity, geographic proximity often characterises emergent industries (Prevenzer,
1997). Regardless of the characteristics of the knowledge, however, low absorptive capacity
forces firms to rely on personal contacts (and thus proximity) to absorb external codified
knowledge that is removed from its core competencies (Eisenhardt and Martin, 2000;
Mangematin and Nesta, 2001). There are also other factors that favour clustering at different
stages of maturity of an industry (Audretsch, 1998). In an industry’s early stages, new
knowledge inputs and resources, such as university research, seems to enhance the
agglomeration of innovative activity, while the new knowledge embodied in skilled workers
favours clustering in all phases of the industry cycle (Audretsch and Stephan, 1996).
In mature industries, firms tend to rely on embodied and codified knowledge to innovate
(Robertson and Smith, 2008). Consequently, innovation development and maintenance of
competitive advantage mainly involve the fusion of new and old technologies, which is a
demanding problem-solving activity (Robertson and Patel, 2007; Freddi, 2009). In other
words, innovation entails a development and problem-solving exercise of adaptation and
reinvention, of new sophisticated technologies, in the context of the firm’s market and
technical competencies (Freddi, 2009; von Tunzelmann, 2009). Consequently, technology
diversity seems to be characteristic of firms in mature rather than in emergent industries
(Granstrand et al., 1997; McGahan and Silverman, 2001).
Mature and emergent industries may also be unequal in terms of the patterns of search for the
knowledge and resources required to innovate. Grimpe and Sofka (2009) show that in hightechnology sectors, firms focus on searching technological knowledge either close to
university or close to suppliers; while in mature industries, firms acquire market knowledge
from customers or competitors. As Robertson and Smith (2008) argue, in mature industries,
market knowledge provides the framework for the recombination and creation of knowledge,
via a range of activities and R&D, as a problem solving activity.
Networking and collaboration may play different strategic roles in the development of
innovation, across the industry lifecycle. In mature industries, innovation involves the
‘management of knowledge bases distributed across a set of agents and institutions’
(Robertson and Smith, 2008, p. 100; von Tunzelmann, 2009). In other words, firms need to
rely on external sources for non-core technologies (Pavitt, 1984; Grimpe and Sofka, 2009).
Despite this, Freddi (2009) argues that the process of technology fusion occurs mainly in
house rather than through R&D collaboration, because the firm needs to use the new
technologies in a way that leverages its internal activities and competencies. In emergent
industries, networking and collaboration are crucial for accessing resources and searching for
8
knowledge inputs to develop specific new technologies and products (i.e. disembodied
knowledge on science and technological development and market information) (Powell et al.,
1996; Koumpis and Pavitt, 1999)
In sum, the literature would seem to suggest that emergent and mature industries differ in
terms of the characteristics of the innovation development process rather than the level of the
innovative activity. Hence, collaboration with universities may be specific to firms in mature
and in emergent activities.4 In mature industries, firms collaborate with universities mainly to
enlarge their general knowledge base and facilitate higher levels of technology integration
with embodied knowledge (Freddi, 2009). Also, since products overlap less with process
technologies in mature industries (Granstrand et al., 1997; von Tunzelmann and Acha, 2005),
PREO may support firms in complex problem-solving related to the blending of new and old
technologies and, consequently, to the development of new processes. University-industry
collaboration is expected to be initiated through contacts with established knowledge and
actor networks (Utterback and Abernathy, 1975; Tushman and Anderson, 1986). This
cooperation may focus on the manipulation of codified knowledge to produce new technical
devices and instruments (Mangematin and Nesta, 2001; Robertson and Smith, 2008; Freddi,
2009).
In emergent industry high-technology activities, cooperation with a university may be aimed
at enhancing new knowledge development. Firms may collaborate with a university to access
new knowledge developments and obtain scientific support for new product development
(Powell et al., 1996; Lee, 2000). It would be expected that such collaborations would be based
on new informal contacts where employees and students play important roles (Lam, 2005).
Spin-offs are another form of participation of universities with firms in the development of
emergent technologies (Koumpis and Pavitt, 1999). University-industry collaboration is likely
to focus on the use of disembodied knowledge and involve research students (Powell et al.,
1996; Lam, 2005) and its outcomes will be in the form of new instruments, technical devices
and eventually patents and publications (Koumpis and Pavitt, 1999; Mangematin and Nesta,
2001).
4
Nevertheless, the ability to engage in and exploit collaboration with universities efficiently, seems to
be limited to firms with high absorptive research and organisational capabilities, especially those active
in high-technology and science-based industries (Hagedoorn et al., 2000; Fritsch and Lukas, 2001).
The more basic the knowledge, the higher the absorptive capabilities and learning investments required
for firms to absorb that knowledge, regardless of the knowledge transfer channels used (Eisenhardt and
Martin, 2000).
9
In this paper we investigate whether and how university-industry collaboration in emergent
high-technology sectors differs from university-industry collaboration in mature sectors. We
analyse also the specific context of university-industry collaboration in Brazil, including the
characteristics of collaborative projects, universities’ motivations for engaging with industry,
and the organisational changes undertaken by PREO to encourage and facilitate knowledge
transfer to industry. In addressing these areas, we aim to contribute to better informed science
and technology policies in NIC, which will foster the role of PREO in industrial technology
development, especially in more technically sophisticated industries.
3. University-industry collaboration and high technology sectors in Brazil
3.1. Science and technology and competitive performance
From the 1970s to the early 1980s in Brazil, there was a significant shift in revealed
comparative advantage from primary goods to consumption goods and basic manufacturing.
In the late 1980s and early 1990s there was a gradual elimination of some of the mechanisms
supporting industry accompanied by macroeconomic instability which weakened investment.
This situation gradually reversed, and it has become more profitable to produce and export
agricultural goods and raw materials than to produce industrial goods. “By 1998, primary
goods again represented Brazil’s top comparative advantage although it was exporting
sophisticated industrial products, such as road vehicles, and aircrafts” (OECD, 2001, pp. 142143).
Brazil currently has good technological competence in some high and medium-high
technology industries. It is either close to or at the global innovation frontier in four sectors:
agriculture; biomass (ethanol); aeronautics; and electric motors (Dahlman and Frischtak,
2005).5 Those industries that are a significant distance from the global innovation frontier
include electronic instruments and information and communication technology equipment and
related capital goods; chemical products (mainly fine chemicals); pharmaceutical products
(OECD, 2001; Dahlman and Frischtak, 2005). 6
Despite its fairly good performance in some high-technology industries, Brazil, in contrast to
some of the Asian countries such as China, Malaysia, and Thailand, has experienced small
shifts in the sectoral composition of its exports and stagnation (decrease) in export
5
According to Knight and Marques (2008, p. 104), ‘the country’s production of biofuels, agricultural
and tropical forest management, deep-see petroleum geology research and production capabilities,
aircraft production, and television content (led by Globo TV), for example, are world class.’
6
The sectors in which there is a moderate distance from the word frontier are agricultural machinery,
buses, trucks and compact cars; auto parts and white goods (cooking stoves, refrigerators, washing
machines, etc.); software (financial, administrative and security); and cosmetics.
10
performance (Montobbio and Rampa, 2005). Brazil also lags behind other NIC in terms of
science and technology inputs and scientific and inventive outputs (MCT, 2002; OECD,
2005).
In 2000, Brazil spent 1% of its GDP on R&D, only slightly less than China (1.29%) and
Russia (1.24%), but more than India (0.8%) (MCT, 2002; OECD, 2005). In 2008, Brazil spent
1.13% of its GDP on R&D as much as Russia, but less than China (1.49%) (MCT, 2009).
Despite higher spending on public R&D (53.5% in 2008) than business research, 99.2% of the
Brazilian R&D expenditures address civil rather than military areas. By the early 2000s, over
half of China’s scientists and engineers were employed in enterprises, representing a
considerable change from the early 1990s when China’s public research institutes employed
most R&D workers. Brazil has not experienced a similar reorganisation: about 60% of its
R&D is conducted by PREO (MCT, 2002, 2009; OECD, 2005). The concentration of Brazil’s
research efforts in PREO rather than private firms, and the poor adaptation of public research
funding and institutions to support growth in sectors with higher technology opportunities
accompanied by poor university-industry links are often pointed to as the main causes for the
stagnation in its export structure (MCT, 2002; OECD, 2005).
In the second half of the 1990s, Brazil’s capability to tap into international knowledge seems
to have increased substantially, with royalty payments for technology transfer from abroad
showing an increase in the period 1995 to 2000. As the technology gap has narrowed, the
opportunities to tap foreign knowledge have decreased in the early 2000s (IBGE, 2002). In
2002, the largest portion of royalties for technology transfer from abroad (64%) refer to the
provision of technical assistance services, followed by supply of technologies (31%),
licensing (4%) and use of brands (1%). During the 1990s, supply of technology and licensing
costs increased their share of payments abroad (20%) (MCT, 2002).
In terms of innovation output, Brazil registered 53 and 88 new patent applications with the US
Patent and Trademark Office (USPTO) in 1980 and in 1990 respectively. This compares with
China with 7 and 111 respectively. In 2007, Brazil registered 385 patents, while China had
4422 and Russia had 443 (MCT, 2009). Moreover, Brazil presents a lower number of patents
registered in national offices per unit of GDP when compared with developed countries
(IBGE, 2002). Among the BRICS (i.e. Brazil, Russia, India, China and South Africa), foreign
ownership of domestic patents is higher in Russia (60%), followed by China (50%) and India
(40%) with Brazil at 35% (OECD, 2005).
11
For scientific output, in 2002 Brazil was ranked 17th for number of ISI published papers, with
China 6th, Russia 9th, and India 13th. From 2001 to 2006, Brazil and China have mounted
two places in the ranking and India one place, while Russia lost five places (MCT, 2009).
Brazil also lags in number of scientist and engineers with 1.5 researchers per 1,000 active
population, with is lower than some other NIC (MCT, 2002, 2009). Moreover, the number of
Brazilian’s studying in the US grew by around 3% in 1995-2004, much lower than Chinese
(almost 5%), Indian (6%) and Russian (7%) students (OECD, 2005).
Despite a relative lagging behind in terms of science and technology inputs and outputs, large
multinational firms in Brazil refer to the quality and framework of their interactions with
universities as the main reason for their willingness to increase investment in R&D in Brazil
(ABDI and ANPEI, 2007). This study surveyed 48 multinational firms located in Brazil, from
the
automotive,
information
technology,
chemistry,
pharmaceutical,
metallurgy,
energy/electricity, electronics and telecommunications, food, hygiene, capital goods,
semiconductors, and aluminium and metals sectors. The majority (49%) were subsidiaries of
US multinationals, with French (10%) and Japanese (6%), and others nationalities making up
the remainder. Almost all (96%) had R&D investments in Brazil According to the
interviewees, 80% of these activities were for development of new products, processes and
services, and 20% were devoted to pure research of which 69% was experimental
developmental research, 18% applied research and 13% research devoted to adaptation of
products to the Brazilian market.
3.2. Innovative activity of Brazilian firms
According to the 2003 and 2005 Brazilian PINTEC innovation survey, the innovative
capability of Brazilian industry is quite high. In our sample, 20% of firms had developed a
product, 27% had developed a process and 13% had developed both types of innovation
(IBGE, 2005).
In 2003-2005, some 7% of innovative manufacturing firms (4% in the period 2001 to 2003)
7
had cooperated with other organisations to innovate. Cooperation to develop new products is
particular relevant for firms in the automobile, electronic equipment, coke, metals,
pharmaceutical and other transport equipment industries. Cooperation for process innovation
7
On average, 3-5% of product innovators innovated in cooperation with other firms or organisations,
while 90% of firms invented alone and 5% adopted new products developed by other firms. On average
2-3% of process innovations resulted from collaborations with other firms and organisations, while 69% of processes were the result of firms’ internal development efforts and 90% of firms adopted
processes developed by other firms.
12
is especially important for the automobile, electronic equipment, pulp and paper, metallurgy,
coke and beverages sectors.
For over a third (38%) of firms that cooperate for innovation, a university was the innovation
partner. Most collaborations were for R&D and product testing rather than technical
assistance, industrial design, or other activities (IBGE, 2003, 2005). Collaboration with
Brazilian universities is particularly important for the coke and oil, metals, electronic
equipment, instruments, machinery, chemicals, pharmaceutical, and printing industries.
Around 20% of innovative firms receive some type of public support for innovation, and 1%
receive public support for collaboration with universities. On average, innovative firms
receiving public support for innovation, benefited from 1.2 different types of public supports
surveyed in PINTEC (IGBE, 2003, 2005). The share of innovative firms receiving public
support for collaboration with a university is particularly high in electronic equipment,
machinery, metals, pulp and paper, coke and oil, pharmaceuticals, and transport equipment
(IBGE, 2005). In the early 2000s, the share of public support increased in the high-technology
sectors of pharmaceuticals, electronic equipment and instruments, and decreased in metals,
other transport equipment, paper and pulp and printing (IBGE, 2003, 2005).
As a source of information for innovation, 5% of innovative firms find university knowledge
important and 5% rate it very important. Universities are a particularly relevant knowledge
sources for the pharmaceuticals, electronic equipment, instruments, chemicals, automobile, oil
and coke, metals and beverages sectors (IBGE, 2003, 2005).
Based on data from the Community Innovation Surveys (CIS) for European countries, the
mature, scale-intensive industries (such as coke and oil, metals, pulp and paper) seem
relatively more innovative than other more technology-intensive sectors in Brazil than in
other developed countries (Fritsch and Lukas, 2001). Firms in the mature sectors for Brazil,
show high rates of collaboration with many external partners, including universities, and the
highest levels of access to public financial support for collaboration with academia. To an
extent, this might be related to the PINTEC sample; on the other hand, historically these
industries have played an important role in Brazil’s catching-up process (OECD, 2001;
Dahlman and Frischtak, 2005).
3.3 Evolution of policy measures supporting university-industry collaboration
The science and technology infrastructure in Brazil was established in the 1940s, and
developed alongside the country’s industrialisation process (Velho and Saenz, 2002).
13
However, the centrality of innovation in industry and competition policies, and the emphasis
on technology transfer in science and technology policies is relatively recent (Velho and
Saenz, 2002; Dagnino and Gomes, 2003). In 2003, industrial innovation became an explicit
objective on government’s industrial policy agenda, with the launch of Brazil’s Industrial,
Technological and Trade Policy (PITCE). The 2008 White Paper on Industrial Policy for the
Development of Production strengthened government support for industrial innovation. In
2007, the Science and Technology Plan (PACTI) stressed the importance of creating public
support for innovation in industry, and an increased role for universities in this process (Silva
and Oliveira, 2007; Erawatch, 2009).
With regard to technology transfer activities, public incentives for university-industry
collaboration through sectoral funds and public research sponsors were introduced in the
1970s in the form of collaborative Masters and Doctoral projects. At that time, public support
for university-industry collaborations was focused on the metals sector but was later extended
to sectors such as agriculture, offshore petroleum exploration and aeronautics (FINEP, 2005).
Since the 1980s, and especially in the 1990s, public support for university-industry
collaboration has grown hugely (Velho and Saenz, 2002) and in the 2000s, public support for
university-industry collaboration in high-technology sectors is being encouraged in part
because it is focused on firms’ value chains rather than branches of activity (FINEP, 2005)
In addition, government’s efforts to facilitate the institutional set up of university-industry
collaboration, which dates back to the 1970s, has been strengthened. In 2001, the Innovation
law set the general regulations for the IPR of the results of government financed research, for
shared infrastructures, and for mobility of researchers from the national state universities and
research centres to the private sector (Invernizzi, 2005). In November 2005, Law 11.196, 21,
known locally as the Good Law (Lei do Bem) provided for large financial incentives to firms
(tax deductions) for private investment in innovation, contracting of doctoral students, and
filing of patents, among other things (MCT, 2009)
In sum, despite its overall good industry innovation performance, Brazil is lagging behind in
scientific and technological outputs, its export performance is stagnant, and in some medium
and high-technology industries competitive and technological advantage are low. Brazil’s
policy-makers are preoccupied with supporting the development of technological and
innovative capabilities among national firms, growing its high-technology industries, and
involving PREO in the achievement of these goals. Some OECD best practice in terms of
incentives for industry R&D and interaction with universities have been adopted. The critical
issue relates to the motivations, objectives and organisation of university-industry cooperation
14
since it is being seen as one of the most important ways to foster innovation performance and
increase the market competitiveness of Brazilian industry, especially in the technologyintensive sectors.
4. Data and Methodology
To explore whether and how university collaboration with firms in emergent sectors differs
from collaboration with firms in mature sectors, and to analyse in detail the motivations,
objectives and organisation of university-industry collaboration in Brazil, we rely on data
collected via semi-structured, face-to-face interviews with the coordinators of 24 research
groups at universities and other PREO, in several different scientific and engineering areas.
Table 1 reports eight interviews with research departments in Physics, six in Chemistry, six in
Engineering, and three in Mathematics.
(Table 1)
Interviewees were asked first to provide general information on the department and its
relationships with industry; second, to provide specific and detailed information on one
current or recently completed collaborative project with industry. All of the interviews were
semi-structured and allowed us to collect information on the characteristics of research
departments (size, staff, papers, patents) as well as their collaborations with industry (i.e.
objectives, forms of research management, facilitators and barriers). We also asked for
detailed information on one specific project with industry, including especially origin, form of
management, financing, and output (Bozeman, 2000; Bercovitz and Feldman, 2006).
To try to categorise projects into emergent and mature sectors, we focused on the activities of
participating firms rather than project objectives. However, this classification is not perfect.
Various authors argue that there is not a match between products and technologies and for this
reason the categorisation of industries into high-technology and low-technology is
problematic (i.e. firms operating in low technology industries are also using sophisticated
technologies) (Granstrand et al., 1997; von Tunzelmann and Acha, 2005; von Tunzelmann,
2009). Still, the blending of old and new technologies seems to be confined mainly to the
mature industries, as discussed in section 2.2 (McGahan and Silverman, 2001; Freddi, 2009).
Hence, we classify emergent sector projects as those where the main activity of the
participating firm was related to the production of science-based technologies and products
while mature sector projects are those where the participating firm was not the producer of the
technologies but was a (‘knowledgeable’) user of the technologies. This categorisation allows
15
us to distinguish between long established industries (identified by national and international
statistics) and newer industries.
Of the 24 collaborative projects surveyed, ten involved firms active in emergent sectors, i.e.
firms involved in the production of information technology, biotechnology or nanotechnology
and products. Five projects involved firms in the oil industry (2 with Mathematics
departments), three involved equipment and machinery firms, one was with a firm in the
textile sector, one in the electricity sector, one in the chemical sector and one with a
telecommunications firm.
On the strength of these data, in the next section first, we analyse the context of university
interaction with industry. In particular, we examine the motivations, objectives, and barriers
to and facilitators of university-industry collaboration. Second, we analyse the auxiliary
services provided by the PREO to facilitate and encourage researchers to collaborate with
industry. Finally, focusing on the details of one specific collaborative project in each research
group, we explore the differences in projects undertaken with firms in emergent sectors and
those with firms in more mature sectors, in terms of initiating and financing, objectives, and
principal outcomes of these university-industry collaborative projects. Given the type of data
and the limited number of observations, we build on the results from cross tab ranked
Spearman's correlation coefficients and non parametric t-tests.
5. University-industry collaboration in Brazil
5.1. Motivations and technological and managerial characteristics of UniversityIndustry collaboration in Brazil
Development and transfer of new technology and development of new knowledge were the
most important motivations identified by the research departments we surveyed, for
collaborating with industry. It seems that the three missions of modern universities (education
and knowledge development and economic development) have been internalised by Brazilian
researchers. Support for the innovative capabilities of national firms was seen as the least
important motivation for collaboration with industry, reflecting the academic bias towards
scientific developments. Graph 1 shows the average order ranking of the main motivations for
research groups to engage in collaborations with industry. Motivations that load higher are
those more often found less important. 8
8
Research Coordinators were asked to rank the main motivation for industry collaboration where 1 was
most important and 4 least important.
16
(Graph 1)
The ranking of motivations to collaborate with industry reflects the objectives of universityindustry collaboration. Graph 2 shows that the most common objective of collaboration with
industry is the development of a new product or process and that improvement to an existing
product or process is the least cited reason for a university-industry collaboration.
(Graph 2)
Responsibility for the management of university-industry collaborative projects tends to be
taken by the academic researchers involved in the project (with support from administrative
staff), or shared between the university and a firm executive officer or researcher. Research
groups usually are required to comply with formal processes for managing contracts and the
rules of the funding institutions (government or firms). 9 Research groups often receive
assistance from university administration or TTO in dealing with finance, IPR and contractual
procedures.
We asked research co-ordinators, based on their experience of cooperation, the barriers to
and/or facilitators of university-industry collaboration in R&D projects. Table 2 reports the
number of research groups that identified each factor as a barrier to or a facilitator of
collaboration with industry. Proximity, public research sponsorship, TTO and similar
organisations supporting knowledge transfer, and tax incentives, were seen as facilitators of
university-industry collaboration while high technical uncertainty, bureaucracy imposed by
the sponsor, the time required by the firm, and the long-time frame of collaborative projects
were seen as barriers to the completion and success of collaborative research projects. It is
interesting that university support for project management and ownership of project results
are grey areas: an almost similar number of departments rated them as enhancing and
inhibiting university-industry collaboration.
(Table 2)
5.2. Institutional incentives for academic entrepreneurship and interaction with industry
In order to access the institutional efforts of PREO in engaging in organisational change to
facilitate university-industry collaboration, we asked research coordinators to identify whether
9
E.g., research groups collaborating with Petrobras, the Brazilian petroleum corporation, need to
comply with procedures laid down by the firm: submit proposals; when approved, organise documents
and sign a contract; manage the research according to a timetable and the steps specified in the project.
17
their organisations provided lists of services to support university-industry collaboration, and
whether these services addressed important barriers to university-industry collaboration.
Graph 3 shows the number of PREO that offer specific support for collaboration with
industry, the number of respondents that rated provision of services as important to address
barriers to collaboration, and the number of respondents that had not benefited from such
services but acknowledged their value.
(Graph 3)
Responses suggest that the most common services available to university researchers were
related to contractual and financial aspects of university-industry interaction: legal advice;
procedures for acquisition of materials/equipment; financial monitoring and control; drawing
up the contract; keeping accounts. These contractual and financial services are recognised as
supporting collaboration with industry and overcoming the barriers identified. Screening of
R&D sponsorship available for industry collaboration, development of industrial contacts, and
management of collaborative projects were provided by more than half of the organisations
surveyed. Searching and management of industry collaboration is not always seen as
facilitating knowledge transfer by their beneficiaries; however, people in organisations that
did not offer these services recognised their importance for overcoming certain barriers.
Personal and professional incentives, and help in diffusing research to industry are services
that are not widely offered by PREO in Brazil. However, university researchers consider that
the provision of services to improve industry awareness of university research and
professional incentives for collaboration would encourage greater cooperation.
Advice on patenting is rarely available and was ranked lowest among the services that would
help to address the barriers to collaboration with industry. This may be related to the passage
of the Innovation Law in 2003 which set the rules for IPR on the results of government
financed research. This creates an automatic legal framework for IPR issues.
Overall, university-industry collaboration focuses mostly on the development of new products
and processes. The main motivations for Brazilian academics collaborating with industry are
the development and transfer of new technology and new knowledge, which would seem to
indicate a more entrepreneurial attitude than is found among researchers in developed
countries. The barriers to collaboration with industry are similar to those identified for
developed countries.
18
Following the trends in the OECD countries, most Brazilian PREO provide contract and
financial advice and services, which are highly valued by researchers. Most PREO provide
some services supporting the establishment and management of industry collaboration; these
are seen as facilitating interaction with industry by researchers that do not benefit from them.
Despite the quite good provision of auxiliary management services, on the whole Brazilian
PREO have no specific incentives for individual public researchers to collaborate with
industry, which is seen as a major barrier to collaboration. Besides not adapting the
organisational incentive system to encourage collaboration with industry, PREO have also
been slow in providing services to address the information and contacts gap with universities.
Research coordinators would value the introduction of such services to raise awareness in
industry about university research, map industry’s technological capabilities and needs, as
well as the introduction of personal and professional incentives for researchers to collaborate
with industry.
6. University-Industry collaborative projects: What are the differences in projects
established with firms in emergent sectors?
To get a more rounded view of the process of university-industry cooperation, we asked the
coordinators of research groups to choose a specific collaborative project and describe its
design and main results. Ten of the 24 projects analysed involved firms active in emergent
sectors: 6 in biotechnology, 2 in nanotechnology and 3 in information technologies. Our
analysis of the differences between projects involving firms in emergent sectors and firms in
mature industries yielded some interesting results; however, some caution is needed in their
interpretation given the small number of cases. Almost all (22) of the projects analysed,
involved the use of specific university or firm machinery and equipment. Table 4 presents the
number of projects that addressed the listed objectives, for the whole sample and for the subsample of projects undertaken with firms active in emergent sectors.
(Table 4)
In the full sample of 24 projects, new product development was the objective for 14, followed
by new processes in the case of 10 projects. Four projects were aimed at the development of a
new product and a new process, three of which were undertaken by Chemistry research
groups. Only three projects focused on improvements to existing processes. In particular,
basic science research groups, especially Physics, with fewer numbers of patents but higher
licensing agreements seem more likely to collaborate with firms in emergent industries (total
number of projects with firms in emergent, reported a project with emergent sectors).
19
Projects undertaken with firms active in emergent sectors are less likely to focus on
improving processes, and to a lesser extent on the development of new processes. Relatively
more projects with firms in emergent sectors have development of a new product than
projects with firms in mature sectors. The only significant difference between emergent and
mature sector projects is the focus on improving existing processes.
Table 5 presents the origins of the 24 collaborative projects and the sub-sample of 10 projects
with firms active in emergent sectors.
(Table 5)
In the full sample, we find that a third (8) were originated by firms, which identified needs
and expressed interest in collaborating with the research departments in question to support
internal R&D. Seven projects were the result of a university’s idea, where the research groups
identified and contacted possible firms to support development of new processes or improve
existing processes. The other cases were less clear cut and were based on a combination of
factors including informal and professional contacts, applications to R&D sponsors, and
doctoral research projects.
When we compare mature and emerging sectors in terms of the origins of collaborative
projects, we see that relatively fewer projects are proposed by universities to address an
industry R&D need in the case of emergent sectors. Also, fewer emergent sector projects were
based on a proposal to apply for research funding. Half of the projects with firms in emergent
sectors were initiated by firms. Students, and especially postgraduate students, are the major
link between universities and firms in emergent sectors, both because they propose new
projects and because they go to work in the firms and are aware of the importance of
universities for supporting product development. This reveals that the network of informal
and professional contacts among university researchers and emergent sector firms is less
developed than in mature sectors.
Table 6 provides information on the funding sources of these collaborative projects.
(Table 6)
The main source of finance among the projects analysed is FINEP (Funding for Studies and
Projects) which financed 11 projects, followed by CNPq (National Council for Scientific and
Technological Development), which financed 8 projects. The state funding agencies (FAPs)
20
financed only two projects. Eighteen projects also received funding from other private or
public sources, but only six were implemented without co-funding from FINEP, CNPq or
FAPs. CNPq is the national research council, under the Ministry of Science and Technology.
It is responsible for promoting science and technology development and training. FINEP is a
national body, under the Ministry of Science and Technology, responsible for managing
national sectoral funds and for supporting innovation and technology development in firms,
universities and other research organisations. FAPs are the state funding organisations; they
promote and invest in R&D, training of scientists and engineers and innovation.
Of the 10 emergent sector projects, 9 received other public and private funding, but only 4
were fully financed by these other sources; the remaining 6 were co-financed by FINEP,
CNPq, and by FAPES. Relatively more projects in emergent sectors are financed by other
sources, especially other public sources (including scholarships for PhD studies), compared to
projects in mature sectors. Thus, it seems that the main public R&D sponsors, in particular
FINEP and CNPq, do not finance fully emergent sectors projects as they finance mature
sectors projects. Hence, the funding procedures of national public research sponsors seem not
to be adapted completely to R&D objectives in emergent sectors which results in a higher
number of different types of financing sources for emergent projects than for mature projects.
Finally, we asked about the outputs of the 24 collaborative projects. Table 7 presents the
outputs for the whole sample and for the sub-sample of projects undertaken with firms active
in emergent sectors.
(Table 7)
In the whole sample, papers and post-graduate theses are the most frequent outputs of
collaborative research, followed by new products to market, patents, and new processes.
Books, improved processes, licensing and spin off creation are the least frequent outputs of
university- industry collaborative projects.
University projects with firms in emergent sector show a slightly higher average number of
outputs than projects with firms in mature sectors. Books and improved processes, and to a
lesser extent new processes, are more likely outputs of projects with firms in emergent
sectors. In particular, improved and new processes are more likely to be by-products rather
than main objectives of collaborative projects with firms in emergent industries. Projects with
emergent firms resulted in student theses, and new products more frequently than projects
with firms in mature industries.
21
In terms of initiating new projects following the finalisation of a previous project, we find that
among the 11 projects that led to a new collaborative project, 8 were based on finalising the
current project with the firm. Among the 10 projects that related to emergent sectors, 2 out of
5 finalised in the firm led to the start of a new collaboration. Finalising the project with the
firm apparently represents a reduced possibility of a new collaboration with the firm, in
emergent sectors, which might be because funding is more likely to come from other sources
than the main public research sponsors. Another explanation might be that students were the
mediators in these one-off collaborations: building the kind of trusting relationship between
university and firm, required for a new project without the presence of a mediator, may not be
achieved through a single project.
In sum, the knowledge and actors network is less developed in emergent than in mature
sectors. Projects with firms in emergent sectors are less likely to be originated by a university
or the network of informal, professional university researcher contacts. Calls for collaborative
research proposals to bid for research funding are less likely to motivate university-industry
collaboration in emergent sectors where collaborative projects are more likely to be initiated
by current graduate and post-graduate students, who may propose specific projects with firms
in emergent sectors, or by the firm via an employee that was a former post-graduate student.
Despite the small amount of information, there are indications that collaboration with
competitive mature industries might be more challenging in terms of applied research and
access to research funds, which might also explain the higher number of project proposals
from universities. Collaboration with firms in emergent sectors, on the other hand, seems
likely to focus on the application and reproduction of technologies and knowledge developed
abroad in basic sciences.10
Projects undertaken with firms in emergent industries focus more on the development of new
products and show a slightly higher average number of outputs than projects with firms in
10
Research groups in basic sciences, especially in Physics, with fewer numbers of patents but higher
licensing agreements seem more likely to collaborate with firms in emergent industries (total number of
projects with firms in emergent, and reported a project with emergent sectors) and report a slightly
lower importance of accessing research funds as the motivation for industry collaboration. This could
be interpreted as university patenting being a signalling device to attract firms in mature industries
since these types of collaboration are more reliant on university applied research competences
supporting fusion of technologies and access to public funds. Perhaps also, collaboration with firms in
emergent sectors, which are still catching up and reproducing technologies developed abroad and
developing new technologies based on the international knowledge, is mainly motivated by factors
other than access to funds, reflecting their interest in developing new technological areas, even in the
case that the departments involved have high technology transfer capabilities as measured by licenses.
22
mature activities. Improved and new processes seem often to be by-products rather than the
main goals of collaborative projects with firms in emergent sectors. Similarly, books, and to a
lesser extent, theses and new products are more frequent outputs than in projects with firms in
mature industries. However, continuing collaborative activities after the completion of a
project is less common in emergent than in mature sectors. This might be related to the fact
that students are the main mediators of this interaction, and that the main public R&D
sponsors have not fully adapted their sponsoring procedures to the objectives of R&D in
emergent sectors.
7. Conclusions
Brazil is a NIC which has achieved high technological competence in certain high and
medium-high technologies; however, it has experienced only small shifts in the sectoral
composition of its exports and its export performance has stagnated (Montobbio and Rampa,
2005). Given the acknowledged importance of university-industry collaboration in the process
of catching up in some of sectors, including in Brazil (Mazzoleni and Nelson, 2007), we have
tried to map the context of university-industry collaboration in Brazil and to explore how
PREO could support the development and growth of high-technology industries. We used
data from 24 university and PREO departments to explore the characteristics of universityindustry collaboration in Brazil, focusing especially on the differences between mature and
emergent sectors.
Our analysis provides several insights. University R&D projects with firms active in emergent
sectors are more often proposed by firms than by university researchers, and are less likely to
be wholly financed by the major public research sponsors. Informal contacts via graduate and
post-graduate students, rather than calls for collaborative projects, are crucial for mediating
between university and firm. These projects in emergent sectors tend to focus on new product
development with development of new or improved processes, and books as side outputs.
Projects with firms in emergent sectors are also relatively more productive than those with
mature industry firms.
We show also that, following the trend in OECD countries, Brazilian PREO provide
contractual and financial services, which are considered very important by researchers to
support interaction with industry. Some PREO also provide support for the establishment and
management of university-industry collaboration. Despite this good provision of services
supporting university entrepreneurship and interaction with industry, there are no
organisational incentives in place in Brazilian PREO to encourage collaboration with industry
(or the researchers do not recognise them). Despite policy recommendations, incentives
23
systems are evolving only slowly, as everywhere else. PREO are slow to provide services
related to increasing industry awareness of university research. Efforts to address these
shortcomings would foster university-industry interaction, especially in emergent sectors
where networks are poorly developed.
Studies in developed countries, mainly Europe and the US, show that the main motivation for
universities to collaborate with industry is development of new knowledge and access to
facilities, equipment, and research funds and job placements for post-docs and other students
(Lee, 2000; Lam, 2005). Our limited evidence suggests that despite organisational incentives
frameworks have not been properly adapted, Brazilian research groups collaborate with firms
mostly for entrepreneurial reasons such as supporting the development and transfer of new
technologies and knowledge to industry. This may imply a more entrepreneurial attitude of
Brazilian researchers than of researchers in developed countries. Further research is needed
that exploits different methods of enquiry.
Our evidence allows us to derive some policy implications. In Brazil, technological
opportunities in most dynamic sectors can benefit from the huge demand in mature sectors
and from PREO competences (Robertson and Patel, 2007). However, as our evidence shows,
these opportunities are being appropriated mostly by large firms in mature sectors rather than
supporting the growth of emergent sector firms. Brazilian PREO are supporting innovation
and technological development in mature sectors with which they have established contacts
and to which public research sponsoring seems to be tailored. Hence, as suggested in the
literature, lack of technological, financial and market capabilities among firms in emergent
sectors, delays in adapting public research sponsoring frameworks and poor PREO sensitivity
to these industries seems to be holding back the growth of emergent sectors (OECD, 2001;
Knight and Marques, 2008).
Adoption of technology transfer best practices and the reinforcement of the budget of national
research councils will not be enough to support development and growth of sophisticated
industries. Revision of national public research funding and institutions to support growth in
sectors with higher technology opportunities and to build university-industry networks around
specific technologies and sectors are required. Additional to efforts of network building and
of mapping the technological capability in industry and university, specific public
programmes focusing on the technological development of a potential field, interesting for the
established network, are also required. Effort into the revision of incentives frameworks and
career rules of researchers and lecturers may also help raising the quality of research and
training in basic sciences and consequently encourage university-industry interaction. Besides
24
national or federal efforts for network building, the technology transfer services in PREO
might also want to invest in mapping the industrial actors and needs in emergent sectors and
diffusing their specific university expertise to this population of firms. Moreover, PREO can
leverage on the national specific technological programmes to support excellence of their staff
competences by providing extra incentives for interaction with industry and university applied
research oriented to indigenous user industries.
However, the national research system on its own cannot foster the emergence and growth of
technological capabilities, especially in high-technology sectors. The development of
dynamic emergent sectors involves a process of capability building within firms, which
requires upgrade of internal skills, production and R&D activities (Dahlman et al., 1987; Lall,
1992, 1998; Hobday, 1995). These issues, which are not addressed in this paper, are very
important for investment and development in high-technology industries. In particular,
government policies should target the development of human skills, technological
infrastructures, and the creation of macroeconomic stability, selective industry incentives and
market and non-market institutions such as laws, IPR policies, standards, codes of good
business practice, and so on (Dahlman et al., 1987; Lall, 1992; Gouvea and Kassicieh, 2005;).
Finally, a focus on national policies targeting high-technology industries may be ineffective
because, combined with the technological characteristics of these industries, they may work to
reinforce over-investment and excessive competition (i.e. abnormal excess capacity, high
sunk costs, and sustained subnormal profits), especially because national governments
worldwide often tend to target the same high-technology industries (Brahm, 1995).
25
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Table 1. Number of Cases per Disciplinary Area
Total number of
collaborative cases
Collaborative cases with firms active in
emergent sectors
Physics
8
5
Chemistry
3
1
Mathematics
6
4
Engineering
6
1
Discipline
31
Table 2. Barriers and Facilitators of university-industry collaboration
Location of the university
Public Research sponsoring
TTOs and similar offices
Tax incentives
Administrative support to project management
Ownership of project's results (patents)
Long-term projects
Time required by the firm
Uncertainty
Bureaucracy
Facilitators
18
17
15
10
10
8
4
2
0
0
Barriers
2
4
6
5
7
11
12
11
13
20
32
Table 4. Objectives of the 24 specific projects analysed
EMERGENT
SECTOR
New product development
14
7
New process development
10
3
Services/use of equipment
3
2
Training of firms' employees
1
1
Improved process *
3
0
Improved product
0
0
Other objectives
3
2
Total number of projects
24
10
Note: * significant at 10%. All the differences are not significant.
ALL
33
Table 5. The origin of the collaborative project
ALL
Firm contacted university
8
University contacted the firm/ propose a project a
7
Co-application to R&D sponsoring a
6
Students theses and projects a
6
Informal contacts
4
Employee training
1
Conferences
1
Note: a significant at 15%. All the differences are not significant.
EMERGENT
SECTOR
5
1
1
4
1
1
0
34
Table 6. Forms of financing of the University- Industry collaborative projects
EMERGENT
SECTOR
Finep
11
4
CNPq
8
3
Fapes
2
1
Other sources
18
9
Private
10
5
Public a
12
7
Average number of sources
1.79
2
Total number of projects
24
10
** a Significant at 15%. All the differences are not significant.
ALL
35
Table 7. Outputs of the 24 University- Industry collaborative projects
EMERGENT
SECTOR
Theses
20
9
Publications
19
8
New product
13
6
Patent application by the PREO
12
5
New process
9
5
Spin-off
8
4
Services
7
4
Licensing
6
2
Improved process a
4
3
Books**
3
3
Average number of outputs
4.2
4.9
**Significant at 5%; a Significant at 15%. All the differences are not significant.
ALL
36
Graph 1. Motivations of the research groups to engage in collaboration with industry
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Support the innovative
capacity of the firm
Access funds
Development of new
knowledge
Development and
transfer of a new
technology
Note: Research coordinators were asked to identify by order of importance the main motivation to
collaborate with industry. Being 1 the most important motivation and the 4 the least important.
37
Graph 2. The three more common types of university-industry collaboration
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
development of a development of a
new product
new process
providing
services/use of
equipment
training of
firms'employees
improved
process
improved product
38
Graph 3. The Offer of supporting services to University-Industry collaboration
univ. offer
25
univ offer & R find important
univ do not offer & R would appreciate
20
15
10
5
0
Law counselling
Procedures f or
acquisit ion of
mat erial
Cont ract set t ing
Financial
monit oring
Account ing support
Screening of R&D
Develop indust rial
Manag. collab.
sponsoring
cont act s
project s
U_I communicat ion Dif f usion U research
channels
areas
Pat ent ing
Incent ives f or U
counseling
researchers t o
collaborat e
39