4.3.1 A Short History of Knowledge Transfer Policy in the United Kingdom

The UK government’s concern with supporting university–industry knowledge transfer began in the late 1970s, when a debate emerged on the United Kingdom’s presumed failure to exploit research (Reference Grady and PrattGrady and Pratt 2000). Institutional and cultural barriers at the time had made cooperation between academic and industrial scientists difficult, and academia lacked incentives to engage with industry. The National Research Development Corporation (NRDC), a governmental body charged with facilitating the commercialization of research produced by public R&D (particularly defense) laboratories, had been created in 1948, but it played a limited role. John Hendry’s Innovating for Failure (Reference Hendry1993), which recounts the early attempts to drive the creation of a computer industry in Manchester in the 1950s, is instructive. Despite having the new technology at the University of Manchester, an identified champion (Ferranti) and a government willing to provide funds for the enterprise, a technology industry based on computing failed to emerge, as the required interaction between the scientists and the managers at Ferranti did not take place. An industry based on computing technology did emerge in the 1980s, but at Cambridge, supported by the Cambridge colleges, and largely free from government influence (Reference Athreye, Breshanan and GambardellaAthreye 2004). This early failure to seize the opportunity in a sector where the United Kingdom had numerous advantages may have contributed to policymakers moving away from directly supporting specific technologies. Instead, policy interventions increasingly involved promoting general framework conditions for innovation, including promoting universities’ engagement with business.

Several initiatives to support university–industry interactions implemented since the mid-1970s exemplified such an indirect approach to technology policy. These included the Teaching Company Scheme, launched in 1975, which involved placing graduates in companies on projects jointly supervised by academics and company staff (Reference Senker and SenkerSenker and Senker 1994) and the LINK scheme, launched in 1986, which aimed to support collaborative research partnerships between industry and the research base (Reference Grimaldi and von TunzelmannGrimaldi and Von Tunzelmann 2002). In the early 1980s the government assigned the exclusive right to commercialize university-generated intellectual property to the British Technology Group (BTG, formed through the merger of the NRDC with the National Enterprise Board), and, a few years later, in 1985, universities were given the choice whether to commercialize academic inventions independently or to rely on the services provided by BTG.Footnote ⁸

Starting from the mid-1990s, government policy documents began to explicitly identify universities as the central focus for economic development, and to emphasize the importance of partnerships between industry, government, and the science base (OST 1993). With the move of the Office of Science and Technology (OST) from the Cabinet Office to the Department for Trade and Industry (DTI) in 1995, responsibilities for science and technology policy were centralized in a single department, which facilitated the emergence of a coordinated national policy on university knowledge transfer (Reference Grady and PrattGrady and Pratt 2000).

Reference Rosli and RossiRosli and Rossi (2016) argue that UK policymakers’ views about how universities engage in knowledge transfer, and how policy should support them, have evolved over time. Until the early 2000s, policymakers envisioned a model of university engagement that borrowed heavily from the sciences and engineering (Reference Kitagawa and LightowlerKitagawa and Lightowler 2012): innovation was viewed as a linear process whereby universities would transfer technology to business, by selling patents and licenses, performing contract research (National Committee of Enquiry into Higher Education 1997; DTI 1998), or directly commercializing their technology through spinoff companies (Reference Lockett, Wright and WildLockett, Wright, and Wild 2014).

During the 2000s, policy documents began to reflect a more nuanced view, supported by growing empirical evidence highlighting the diversity of channels through which universities engage with businesses and with other economic and social actors (Reference D’Este and PatelD’Este and Patel 2007; Reference Bekkers and Bodas FreitasBekkers and Bodas Freitas 2008; Reference Hughes and MartinHughes and Martin 2012). Having identified the drawbacks of focusing too much on patenting and on the pursuit of narrow financial returns (Lambert Review: HM Treasury 2003; Gowers Review: HM Treasury 2006; Saraga report: DIUS 2007), universities were encouraged to realize the potential of their intellectual property beyond their patent portfolio, focusing on other areas such as copyright (Hargreaves Review: BIS 2011b). They were also encouraged to focus on their comparative strengths, since different universities had different contributions to make, some as world-class centers of research excellence and players in global markets, and others primarily as collaborators engaged with local businesses, communities, and regional bodies (DTI/DFES 2005; DIUS 2008a, 2008b). It was argued that public funding should encourage such choice, by providing incentives for institutions to become more entrepreneurial, build closer links with business and the community, and have proper arrangements for exploiting the results of their work. The term “knowledge transfer” gained prominence (DES 2003; HM Treasury 2003), suggesting that universities transfer more than just technology produced by science and engineering departments, and contribute through the whole spectrum of academic disciplines.

More recently, a broader view has emerged whereby universities are seen to be part of complex ecosystems of innovation characterized by collaboration and exchange among a variety of stakeholders, aimed at addressing complex social and economic challenges (Reference Andersen, Brinkley and HuttonAndersen, Brinkley, and Hutton 2011; BIS 2015). The bidirectional and collaborative nature of the interactions between universities and businesses (or other stakeholders), is reflected in the increasing use of the term “knowledge exchange” (DIUS 2008b; BIS 2012, 2013, 2015).

Another aspect of the evolution of knowledge transfer policy concerns the level of implementation. In the first decade of the 2000s, attention was paid to the regional dimension of universities’ knowledge transfer engagement (Reference PottsPotts 2002; DES 2003; Lambert Review: HM Treasury 2003), and a new Regional Innovation Fund worth £50 million per year was set up to enable regional development agencies (RDAs) in England to support clusters, incubators and networking among scientists, entrepreneurs, managers, and financiers. However, all RDAs were closed in 2010, leading the government to abandon this regional focus (Reference Cochrane and WilliamsCochrane and Williams 2013). In the absence of regional policy institutions, the implementation of regional policies for knowledge transfer has become more difficult, and universities’ efforts to engage in knowledge transfer within their region are neither monitored nor encouraged. While numerous local enterprise partnerships (LEPs) between local authorities and businesses were established in 2011, covering all areas of England (BIS Committee 2014), how innovation and knowledge transfer policies can be implemented in the LEP context remains unclear. LEPs argue that their remit has expanded over time, and that their resources are insufficient (National Audit Office 2016). Although university representatives sit on the board of many LEPs, a recent review suggests that the relationship expected between LEPs and universities appears ill-defined and that engagement between them is patchy (BIS 2015), with LEPs lacking any firm obligation or support to help businesses connect with universities. In consequence, universities may have been discouraged from pursuing an agenda of contributing to regional development, focusing instead on different objectives (Reference Kitagawa, Sanchez-Barrioluengo and UyarraKitagawa et al. 2016). However, little empirical evidence exists at the moment to show whether this has been the case.

4.3.2 Supply-Side Policy Instruments Supporting Knowledge Transfer

Most of the policy instruments devised by the government in order to promote knowledge transfer have been targeted at universities (Science and Technology Committee 2017). The first comprehensive package, the Knowledge Exploitation Programme, was launched in 1999 and included three instruments (HEFCE 1999):

1. (i) The Higher Education Reach-out to Business and the Community (HEROBAC) Fund (£60 million allocated competitively in 1999–2004). Its aim was to help universities to build organizational capability and infrastructures to engage with business and the wider community.

2. (ii) The Science Enterprise Challenge (SEC) fund (£45 million allocated competitively in 1999–2004). It aimed to support entrepreneurially oriented education and training within universities.

3. (iii) The University Challenge Seed Fund (£60 million overall allocated via two competitions, in 1999 and 2001). It provided access to seed funds to exploit science and engineering research outcomes and support the creation of university spinouts.

The Higher Education Innovation Fund (HEIF), a permanent stream of funding to support universities’ knowledge transfer activities, was announced in 2001/2 and implemented the following year. The activities originally funded by HEROBAC, the SEC and the University Challenge Seed Fund were progressively brought within HEIF’s remit. After a marked increase between 2004 and 2008, the fund later stabilized at about £130 million per year, which is almost three times as much as it had been in 2001. The amount distributed through HEIF and parallel funding streams in Scotland, Wales, and Northern Ireland equates to approximately 2.4 percent of the recurrent government funding allocated to universities for teaching and research, and about 9 percent of the recurrent government funding allocated to research alone (Kitagawa and Lightowler 2013). Over time, HEIF has become a very important source of support for knowledge transfer activities, with about 34 percent of universities’ knowledge transfer income resulting from HEIF-funded activities (Reference Coates UlrichsenCoates Ulrichsen 2014).

HEIF’s allocation system has changed over time. Initially, funds were allocated to universities competitively on the basis of the project proposals that they presented, with the objective of helping them build capacity for knowledge transfer (Reference Kitagawa and LightowlerKitagawa and Lightowler 2012). Since 2006 this has been progressively replaced by a formula based on the income that universities accrue from knowledge transfer, so that money is channeled to the institutions that are already more commercially successful. The introduction of a minimum eligibility threshold of £250,000, an increase in the maximum award that can be received by each university (£2.85 million), and the allocation of additional funds to top performers (£6 million to twelve institutions in 2012/13 and £20 million to twenty-seven institutions in 2014/15) have also contributed to greater funding concentration since 2011 (Reference Coates UlrichsenCoates Ulrichsen 2014; Reference Day and FernandezDay and Fernandez 2015), reversing the previous trend whereby smaller institutions used to have higher income growthFootnote ⁹ (Reference Day and FernandezDay and Fernandez 2015).

In addition to HEIF, several other instruments support universities’ knowledge transfer activities. HEFCE runs the Catalyst Fund, which distributes funds competitively to projects aimed at driving innovation in higher education (£37.6 million in 2013/14) and the UK Research Partnership Investment Fund, which funds large-scale collaborative projects between universities and private partners (£136 million in 2013/14). Innovate UK also runs a number of schemes. The Knowledge Transfer Partnership (KTP) scheme, launched in 2003, is a revamped version of the Teaching Company Scheme. In 2013/14 it allocated £16.9 million. The Catapult Centres, launched in 2013, are research and technology innovation centers set up as collaborative ventures between universities and businesses, each focused on a specific area of research and technological development. The twelve “catapults” were allocated £121.30 million in 2013/14. Innovate UK also funds collaborative R&D projects and feasibility studies involving businesses and research organizations (£172.9 million in 2013/14), collaborative research in biomedicine (Biomedical Catalyst, £30 million in 2013/14), Knowledge Transfer Networks (£15.2 million in 2013/14), and Innovation and Knowledge Centres (£1.9 million in 2013/14).

The overall set of government-supported knowledge transfer schemes allocated by HEFCE and Innovate UK amounted to approximately £696 million in 2013/14, which was about 37 percent of the recurrent government funding allocated to university research in the same period (NCUB 2016a). Small funding schemes supporting knowledge transfer activities, often restricted to specific academic fields, are also implemented by the devolved governments (Reference Huggins and KitagawaHuggins and Kitagawa 2012), by many of the research councils and by selected charities such as the Wellcome Trust and the Royal Society (Lockwood 2012, cited in Reference Coates UlrichsenCoates Ulrichsen 2014).Footnote ¹⁰

Few policy instruments have been set up in support of the knowledge transfer activities of PSREs. In 2001, the government set up the Public Sector Research Exploitation Fund, awarding nineteen PSREs a total of £10 million of public venture capital to develop potential products to the point where they could be successfully marketed to the private sector. Two additional rounds of funding in 2004 and 2006 allocated a further £40 million. Since the demise of this instrument, there are no lines of funding specifically dedicated to supporting PSREs’ knowledge transfer activities.

Not all policy instruments consist of the provision of funding. The Lambert Agreements are a set of decision tools and standard agreements created in 2005 to simplify contracting for business–university collaborations. Evidence on the success of these tools is mixed: most users report that they simplify processes and provide useful information and precedents (BIS 2015); however, their use is not widespread. While universities are generally aware of these tools and 63 percent use them to some extent (Reference Tang, Wecowska, Campos and HobdayTang et al. 2009), less than 10–15 percent by value of collaborative research between universities and business is based on a Lambert-type agreement (BIS 2015). For the most valuable agreements, companies are more likely to impose their preferred contractual forms. Scotland has mandated the use of template contracts for interactions funded by the Scottish Funding Council’s innovation voucher and related schemes (BIS 2015).

A crucial nonfinancial policy instrument that affects knowledge transfer is the government regulation of IP rights. In the United Kingdom, there is no strong legislative framework regulating academic patenting, and, unlike other countries that have enacted specific laws on university IP, the assignment of IP rights over research outputs is governed by the general provisions on employee inventions contained in the Patent Law of 1977. The United Kingdom has a system of “automatic ownership,” such that the university is the first owner of the IP, which usually cannot revert to the inventor.Footnote ¹¹ However, if research is sponsored fully or in part by external contractors, parties may negotiate a different agreement on the allocation of IP rights. In some cases, the university may override existing regulations by developing internal IP rights regulations and procedures to enforce them. Issues such as the share of royalties to be assigned to the academic inventors, the rights of inventors who are PhD students, and the timing of patent filing procedures can vary widely among universities.

Mainly because of its fluidity, the policy framework around IP has not undergone radical changes over time. The main policy change, introduced in 1985, has been the possibility for universities to directly commercialize their intellectual property. This has encouraged an increase in the patenting activities of universities. In fact, UK universities tend to own a large share (over 50 percent) of patents invented by academics, similar to the U.S. (where the share is 69 percent) and unlike many other European countries, where the majority of academic-invented patents are owned by private companies; for example, Reference Lissoni, Llerena, McKelvey and SanditovLissoni et al. (2008) show that university-owned patents constitute no more than 11 percent of all academic patents in France, Italy, and Sweden.

4.3.3 Demand-Side Policies Supporting Knowledge Transfer

Business also has a vital part to play in successful knowledge transfer. A number of policies exist to support business investment in R&D, which in turn should increase businesses’ commercial demand for university research. These include (BIS 2011a):

The recent Industrial Strategy White Paper (BEIS 2017) has outlined a more proactive role for the UK government in driving industrial policy in the wake of the United Kingdom’s exit from the European Union and proposed several supply-side and demand-side interventions. On the supply side, the government has committed to increase investment in R&D by around 20 percent via an additional £4.7 billion of government R&D funding by 2020–1. Additional spending of £100 million has been committed to measures to incentivize universities to collaborate with businesses. These might include the expansion of existing mechanisms such as HEIF and KTPs, the introduction of new schemes aimed at funding industry placements for scientists, and supporting world-class clusters of research and innovation. A new Industrial Strategy Challenge Fund is planned to back technologies at all stages where the United Kingdom has the potential to take an industrial lead. This Fund will support a range of industrial R&D activities: joint research projects between business and academic researchers, graduate placements, setting up demonstrators to test near-to-market technologies in real-world environments and creating centers to bring together academic experts with entrepreneurs to promote commercialization (BEIS 2017).

On the demand side, a few measures aimed at driving up the level of business R&D investment have also been announced. These include: a review of the tax environment for R&D, a new challenge prize to support “everyday entrepreneurs” and a review of the IP system to stimulate collaborative innovation and licensing opportunities. The Science and Technology Committee (2017), while welcoming the government’s renewed emphasis on knowledge transfer, remained concerned that its previous efforts had focused disproportionately on the “supply” of research by universities rather than the level of “demand” from businesses, and that the overall R&D intensity and productivity of the UK business sector continue to be low compared to that in other OECD countries.

4.4.1 The Variety of Knowledge Transfer Activities

Knowledge transfer channels have been comprehensively classified in recent work by the National Centre for Universities and Business (NCUB 2016a, 2016b) into four categories: commercialization, problem-solving, people-based, and community-based activities. Commercialization activities include patenting, licensing research, consulting, and spinning out companies. Problem-solving activities include joint publications, joint research, consultancy services, prototyping and testing, research consortia, contract research, hosting personnel, providing informal advice, external secondment, and setting up physical facilities. People-based activities include standard-setting forums, participating in networks, attending conferences, student placements, giving invited lectures, curriculum development, sitting on advisory boards, employee training, and enterprise education. Community-based activities include social enterprises, museums and art galleries, public exhibitions, heritage and tourism, community-based sports, performing arts, school projects, and lectures for the community. While universities have been engaging in people-based and community-based activities for a long time, the literature has only relatively recently begun to acknowledge their importance in disseminating and sharing academic knowledge to the public (British Academy 2008, 2010; Reference Olmos-Peñuela, Benneworth and Castro-MartínezOlmos-Peñuela, Benneworth and Castro-Martínez 2014; Campaign for Social Science 2015).

Figure 4.4 shows the shares of academics and of PSRE staff who engage in each type of activity. Commercialization and problem-solving activities are relatively more important for PSRE staff than for academics, while the converse is true for people-based and community-based activities. This may be due, in part, to differences between fields of science, since commercialization and problem-solving are particularly important in engineering and materials science, while the arts and humanities and the social sciences, which are not represented in the set of PSREs considered in this study, lead in community-based and people-based activities respectively (NCUB 2016a). It is also apparent that both academics and PSRE staff engage far less in commercialization activities than in all other activities. In line with a large amount of evidence suggesting that IP-based activities are concentrated in a few fields, commercialization is particularly high among engineering and materials science academics, and among BBSRC-affiliated PSRE staff.

Figure 4.4 Shares of university and PSRE staff involved in different types of knowledge transfer activity

Source: Authors, based on data from NCUB (2016a, 2016b)

A more fine-grained analysis comparing the shares of academics (excluding those in the social sciences and the arts and humanities, for greater comparability) and the shares of PSRE staff who engage in each of the activities listed under the four main categories of commercialization, problem-solving, people-based, and community-based activities, suggests that the pattern of engagement is very similar. Academics are marginally more engaged in most activities, except for joint research, research consortia, giving informal advice, and attending conferences, while PSRE staff are marginally more active in several community-based activities. It appears that, in spite of the lack of specific policy schemes supporting PSREs’ knowledge transfer activities, PSRE staff engage with external stakeholders through a variety of channels.

4.4.2 Engagement in IP Commercialization

While commercialization of IP has historically been considered an important avenue for university–industry knowledge transfer, in practice, it involves fewer academics and generates less income than all other knowledge transfer channels. There is a substantial amount of research investigating the patterns and determinants of university patenting, licensing, and spinouts in the United Kingdom. Table 4.2 presents the evolution of a subset of indicators of IP-related activities for the period from 2003–4 to 2014–15. IP income increased at about 11 percent per year, excluding the exceptionally good performance of 2008, which was largely due to one university selling its share of a well-established company (HEFCE 2010). Income from other knowledge transfer activities increased on average by 10.9 percent per year. However, these two types of income are very different in magnitude, with income from IP accounting on average for only 2.8 percent of total annual income from knowledge transfer. The number of patents applied for and granted (both national and international filings, but not counting multiple filings of the same patent in different countries) increased on average by 5.3 percent and 8.3 percent respectively each year. From the mid-2000s there appears to have been a leveling-off in the growth of university-owned patents. This matches the experience of the U.S., another country with a long tradition of institutional IP ownership (Reference Mowery, Sampat, Fagerberg, Mowery and NelsonMowery and Sampat 2005; Reference Tang, Wecowska, Campos and HobdayTang et al. 2009). Over time, knowledge transfer offices (KTOs) have gained experience in realistically assessing inventions’ commercial and licensing potential, and have therefore become more selective in deciding whether patent applications should be made (Reference Tang, Wecowska, Campos and HobdayTang et al. 2009). As a consequence, the quality of university patents has improved, as suggested by several trends: an increase in the number of nonsoftware license agreements, an increase in the share of spinouts surviving for more than three years, and an increase in the share of patent applications that are eventually granted.

Despite the large number of universities that engage in patenting and spinning out (between 2009–10 and 2014–15, 122 universities filed at least one patent, generated income from IP, or created at least one spinout company), the bulk of these activities are concentrated in a subset of research-intensive universities with a substantial presence in engineering, materials science, biology, chemistry, and veterinary science (NCUB 2016a). In 2014–15, six institutions (3.7 percent) produced 40 percent of patent applications, and twenty-five institutions (16 percent) produced 80 percent of patent applications. The distribution of IP income is even more concentrated: just three institutions (1.8 percent) produced 41 percent of IP income, and seventeen institutions (11 percent) produced 80 percent of IP income. Twenty-seven institutions (17 percent) produced 80 percent of income from research contracts. The skewed distributions of patent income might suggest a skewed ability of institutions to produce high-quality patents, since evidence suggests that patents licensed to industry are of better quality than patents that are not licensed (Reference SterziSterzi 2013).

Figure 4.5 summarizes some of the data from Table 4.2. The number of new spinouts established each year has been quite stable (although declining in recent years), but the number of spinouts surviving at least three years has increased. While failure rates remain high and a great number of spinouts may still not survive in the long run (HM Treasury 2003), the survival rateFootnote ¹⁴ of university spinouts in the United Kingdom is high by comparison with many other countries (Reference Lawton Smith and HoLawton Smith and Ho 2006).

Figure 4.5 Patenting and spinout activities of universities

Source: Authors, based on data from HESA

One interesting aspect of Figure 4.5 is the close relationship between patents granted and spinout activity. It has been argued that patent licensing and spinning out companies are alternative modes of commercializing research results, and that one or the other will prevail depending on institutional and context conditions. International evidence suggests that those countries that have maintained an inventor-ownership model (such as Sweden and Italy) focus more on spinouts than countries that have a university-ownership model, which tend to focus on patent licensing. The University of Cambridge seems a case in point. Before its switch to the institutional-ownership model in 2005, the University of Cambridge had, for a long time, uniquely maintained a professor’s privilege system similar to that implemented in Germany and the Nordic countries. Cambridge’s historic success at spinout creation (Reference Athreye, Breshanan and GambardellaAthreye 2004) might suggest that the lack of institutional ownership acted as an incentive to commercialize research results via spinout companies instead of relying on patent licensing.

However, the analysis of patenting and spinout data over time suggests that universities that make more income from technology licensing and file more patents may also create more successful spinouts. This relationship is consistent with the skew in the generation of new science noted earlier and suggests that universities have developed a range of competencies that allow them to engage in both licensing and spinouts. A growing literature on university KTOs appears to tell a similar story. Reference Tang, Wecowska, Campos and HobdayTang et al. (2009) reported that KTOs have improved their ability to explain the commercialization processes and options to academics, and to work with academics on defining appropriate IP ownership arrangements and financial incentives. Most KTOs continually review and restructure their strategies, and promote themselves as interface organizations between the academics (and university) and external parties, including venture capitalists (Reference ChughChugh 2004). The number, experience, and knowledge of KTO staff have been found to be positively related to the number of spinouts (Reference Lockett and WrightLockett and Wright 2005; Reference Powers and McDougallPowers and McDougall 2005) and to the quality of the advice and contacts they provide (Reference Franklin, Wright and LockettFranklin, Wright, and Lockett 2001). The number of university spinouts is also positively correlated with university R&D spending, spending on IP disclosure, and the ability to develop new business (Reference Lockett and WrightLockett and Wright 2005) – but it is quite likely that these factors also determine how many patents the university can apply for. The ability to generate spinout companies also depends on university characteristics (such as institutional reputation, which makes it easier for academics to bring together resources to create spinouts, and the presence of cultures or norms that nurture entrepreneurial activity (Reference DiGregorio and ShaneDiGregorio and Shane 2003), and on external factors like the availability of local venture capital: the level of investment in firms located ten miles from a venture capital head office is double that of firms sited 100 miles away (Reference Wright, Vohora and LockettWright et al. 2004), and on individual attributes and experience (Reference Clarysse, Tartari and SalterClarysse, Tartari, and Salter 2011).

Information about the commercialization activities of PSREs is collected less systematically than information about universities’ knowledge transfer activities. Between 2003 and 2004, the Department for Business, Innovation, and Skills (BIS 2011a, 2014) carried out seven surveys of knowledge transfer activities in all the PSREs funded by government departments and by the research councils, as well as in cultural institutions and regional NHS hospital trusts. Table 4.3, drawn from the latest available study (BIS 2014), shows grossed-up estimates for the whole sector. PSREs’ commercialization activities have grown over time –the number of FTE staff in commercialization offices has grown by about 36 percent – as has business representation on their governing boards. As a group, PSREs outperform universities on a range of metrics. If we compare data from universities and PSREs in the last year for which they are available (2012–13), it is interesting to observe that while the number of patent applications by PSREs is much lower (322 versus 1,936 by universities), their probability of being granted is much higher (two-thirds versus less than half) and so is their income from licensing (£195 million versus £61 million). Consequently, the average licensing income per granted patent is much higher for PSREs (£570,175) than for universities (£64,143), although we do not have information about the distributions: it is possible that a small number of blockbuster patents account for the largest share of income, for either or both PSREs and universities.

Table 4.3 also shows that PSREs’ commercialization activities have been on the rise. Although patent applications have not increased much, the number of patents granted has increased. The number of spinouts doubled between 2008–9 and 2012–13, with PSREs owning some equity in 93 percent of these cases. Income from commercialization activities including business consultancy has also increased dramatically over time, and particularly since 2008–9. By way of contrast, a steady increase in licensing agreements (and corresponding income) in the early years has been followed by a decline in the last three years. Unlike universities, PSREs derive most of their knowledge transfer income from IP; for most of the period covered, income from IP was several times larger than income from consulting and other sources. Only in the most recent survey has the situation has changed: with IP income stable and rapid growth in other sources of knowledge transfer income, the former has dropped to only 65 percent of the latter. By contrast, universities’ income from other knowledge transfer activities is much higher than that of PSREs (£2,269 million versus £299 million), indicating that universities engage in a broader range of activities.

Figure 4.6 Patenting and spinout activities of PSREs

Source: Authors, based on data from BIS (2014)

In comparing the commercialization activities of universities and PSREs, we may wonder whether we are comparing like with like. With 161 universities, the university sector is likely to be far more diverse than the thirty-five PSREs focused narrowly on a few subject areas. A narrow focus is more likely to generate economies of specialization in research, which are much harder for universities to achieve given their broader mandate.

Data collected from two surveys by NCUB, one of academic staff (NCUB 2016a) and one of PSRE staff (NCUB 2016b), allows us to perform some comparisons. It is apparent that PSRE staff can dedicate the majority of their time to research rather than teaching and administration, which instead take up a large part of university academics’ time. Even though academics in the sciences spend on average a greater share of their time on research than academics in the social sciences and humanities, they still devote much less time to research than PSRE staff. However, while this might explain why a PSRE researcher produces more output than an academic, it still does not explain why their research enjoys greater commercial success.

PSREs’ greater success in commercialization may be explained by their greater focus on more applied, mission-oriented research. However, whether PSREs’ research is more applied than that conducted at universities is not clear. A comparison using NCUB data (2016a and 2016b) of the time allocated by academic and PSREs researchers between pure basic, user-inspired basic and applied research (as defined by the Frascati Manual, OECD 2003, pp. 77–9) suggests that the differences between research fields are greater than those between universities and PSREs: in both sectors, researchers in health and engineering spend relatively more time doing applied research, while researchers in biology, chemistry, and the natural sciences spend relatively more time doing basic research. Hence, categorizing research according to its objectives does not seem to reflect the commercialization potential of the resulting outcomes.

Another explanation might be that PSREs are more oriented to fields that are characterized by immediate commercial applicability, such as computer science and biotechnology. Data on the distribution of PSRE staff across fields of research are not collected systematically. By integrating information on the orientation of PSREs to various research fields (BIS 2015) with data on the number of staff employed in PSREs in 2012–13 (BIS 2014), we can estimate the share of PSRE staff in each field. These shares can be compared with the distribution of academics in each field in the same year. Considering only academics and PSRE staff employed in the sciences, we find that universities have greater shares of staff in medicine and in engineering and technology, while PSREs have greater shares of staff in the natural sciences (particularly biology, environmental, and sustainability studies) and in agriculture and veterinary science. While this shows different patterns of specialization in the two sectors, it is not immediately possible to deduce information about the ease of commercial applicability of the resulting research outcomes.

One reason why it is not so easy to explain the differential commercialization success of universities and PSREs is that the government is likely to have privatized, over time, exactly those PSREs whose research results could be commercialized more easily, since these would be more likely to survive without government funding. Therefore, the remaining PSREs are more likely to focus on the production of research outcomes that are less likely to generate large private returns, and which are thus more similar to the kind of research outcomes produced by universities. Academics and PSRE staff appear to have similar patterns of engagement in different channels of knowledge transfer, and to initiate interactions with external partners in similar ways. Further research in this area should adopt more fine-grained units of analysis. In particular, given that PSREs focus on narrow fields of research, their knowledge transfer performance should be compared with that of university departments or even research centers engaged in similar fields. Data at this level are currently not available systematically and would require ad hoc data collection.

4.4.3 Industry Demand for Knowledge from Universities and PSREs

Universities in the United Kingdom interact with a variety of industries. According to data from HESA, almost all universities work with organizations in the education, health and arts sectors, while three-quarters work with manufacturing. Almost every industrial sector draws on university knowledge: only five sectors approached fewer than eighty universities, and of these, only two sectors approached fewer than forty. However, when businesses are asked about their sources of knowledge for innovation, universities are not ranked highly: the most frequently cited sources of knowledge are the company itself, clients or customers, suppliers, and competitors in the same line of business (Reference Hughes and MartinHughes and Martin 2012). The fact that only 1 percent of the businesses report using the business sector alone, while 18 percent report using the business sector together with intermediaries, and over 80 percent report using some combination of sources from all three groupings, suggests that businesses use university knowledge in combination with other sources.

Data from the most recent Community Innovation Survey (BIS 2016) provide additional information about business engagement with universities. In the CIS sample of 15,091 companies,Footnote ¹⁵ between January 1, 2012 and December 31, 2014, 7 percent of the companies collaborated on innovation activities with universities or other higher education institutions, and 5 percent collaborated on innovation activities with government or public research institutes. Table 4.4 shows a cross-tabulation of information on collaboration on innovation activities with universities and government or public research institutes. A total of 729 companies collaborated with the government, 1,068 with universities, 593 with both government and universities, 136 with the government but not with universities, and 475 with universities but not the government. The vast majority of firms (13,887) collaborated with neither universities nor government.

Breaking down these data further, we find that of the CIS sample of 15,091 companies, 13 percent collaborated on innovation activities in the United Kingdom at the regional level, 19 percent collaborated at the national level, 9 percent collaborated with European countries, and 8 percent collaborated with non-European countries. However, relatively few companies collaborated with either universities or government, as can be seen from Table 4.5.

According to Reference Abreu, Grinevich, Hughes, Kitson and TernouthAbreu et al. (2008), who surveyed 1,449 UK firms, the channels most frequently used by firms to access university knowledge were the distribution of scientific knowledge through open science (publications and scientific conferences) and the appointment of graduate personnel. These far outstripped direct research collaborations between universities and firms (through research collaborations, research contracts and consultancies), while patents and licenses were used least of all. Data from HESA show differences between large firms and SMEs in the use of university IP: SMEs and non-commercial organizations generate 42 percent of universities’ non-software licensing income, 64 percent of software licensing income, and 98 percent of other IP income (including income from copyright licensing).

5.2.1 Knowledge Transfer Prior to the 2000s

The knowledge and technology transfer (KTT) activities of German universities/HE colleges and public research institutes differ, reflecting their differing missions. Based on a survey of professors at universities and Fachhochschulen plus heads of departments at public research institutes, Reference Czarnitzki, Rammer and SpielkampCzarnitzki et al. (2000) assessed the extent to which different institutions met preconditions for KTT and how much KTT they actually carried out. This analysis was further developed by Reference Edler and SchmochEdler and Schmoch (2001), and is shown in Figure 5.3.

Figure 5.3 KTT missions and activities of different institutions in German public science

Note: Adapted from Reference Rammer, Czarnitzki, Schmoch, Licht and ReinhardRammer and Czarnitzki (2000) and Reference Edler and SchmochEdler and Schmoch (2001). The size of the bubbles shows the extent of factors impeding KTT according to survey responses. FH is Fachhochschulen (universities of applied science), FhG is the Fraunhofer Association, HGF is the Helmholtz Association, MPG is the Max Planck Association, TU is the technical universities and Uni is other universities.

Information on the preconditions for KTT was derived from institutions’ mission statements supplemented by their size in terms of budgets and staff as well as their thematic orientations. These preconditions were then compared to the actual extent of KTT activities, as derived from the survey responses of almost 1,000 professors and heads of department. The extent of KTT takes into account the industry affinity of each institution’s research, its interaction with industry, staff mobility between the institution and industry, and research funding obtained from industry.

Institutions are localized on the “KTT activity map” roughly according to their missions. The Fraunhofer Association had the highest predisposition for KTT to industry and also achieved the highest extent of KTT. It was followed by technical universities as a distinct subgroup of universities that are well suited to KTT because they generally focus on subjects that are highly relevant to industry. The Helmholtz Association seemed to meet many preconditions for KTT but was less active in practice than the technical universities. There were then significant variations among other universities and universities of applied sciences in terms of preconditions for KTT. Some faced significant barriers, such as understaffed KTOs and misaligned incentives. Of all the institutions, the Max Planck Association was least active in KTT, reflecting its basic research mission within the public science system.

5.2.2 Knowledge Transfer at a Glance

5.2.3 Leading Users of Commercially Valuable Knowledge

In the Mannheim Innovation Panel (MIP), which constitutes the German part of the pan-European Community Innovation Surveys (CIS), firms are regularly asked about their innovation activities. The survey takes a representative sample of German manufacturers and selected services and its results can thus be extrapolated to all German firms in these sectors.

Among many other questions, firms are asked to report on their partners in innovation projects. As well as lead customers, suppliers, firms from the same industry and consultants, they also indicate whether they collaborate with universities, including universities of applied sciences, and public research institutes.

As can be seen in Table 5.5, of firms in the R&D service sector, 66 percent collaborate with universities and 40 percent with other public research organizations. This is followed by the pharmaceutical sector, where 54 percent of firms report collaboration with universities and 30 percent with public research institutes. Other sectors that collaborate extensively with public science include ICT equipment, vehicles, machinery, chemicals, metal, and the ICT industry.

Interestingly, universities are generally reported more frequently than public research institutes. In part, this may simply be because they outnumber public research institutes, but it also shows that universities are frequently involved in knowledge transfer activities through joint research. These activities may well exceed the patenting of university inventions by the university KTOs themselves in terms of both frequency and importance.

For public research institutes, there is also survey data on the users of their research results. In the 2009 ZEW public research institutes and universities survey, heads of institutes were asked to report on their most important user groups. Interestingly, their most important user group was universities, mentioned by 52 percent of respondents, followed by other public research institutes on 37 percent. Small and medium-sized firms and large firms were each mentioned by around one-third of respondents (see Table 5.6).

Once again, the biggest differences between public research institutes occur between Max Planck and Fraunhofer. While Max Planck heads almost exclusively report other scientific institutions as their main user group (universities and public research institutes with 84 percent and 40 percent, respectively), the Fraunhofer institutes focus unambiguously on industry, with large firms mentioned by 83 percent of heads and SMEs by 91 percent.

For the other institutions, the picture is again more mixed but public science as user dominates, except for other federal public research institutes that do not belong to one of the four major associations, where public administration is evidently the most important “client.”

5.2.4 Changes in the German Knowledge Transfer System

In the period 1998–9, the BMBF commissioned a study of knowledge and technology transfer in Germany, the results of which were published (Reference Schmoch, Licht and ReinhardSchmoch et al. 2000). In response to the study, the BMBF launched a campaign called “Knowledge Creates Markets” in 2001 with four major objectives: (i) a valorization campaign to increase patenting by public research organizations; (ii) a spinoff campaign to encourage them to found companies; (iii) a collaboration campaign to foster bilateral research agreements between public research organizations and companies; and (iv) a competence campaign to increase awareness of the potential usefulness of public science among companies. In total, the four campaigns included twenty-six sub-schemes.

Major subsequent changes with respect to KTT in Germany included the abolition of professor’s privilege and the establishment of regional “patent valorization agencies” (PVAs) intended to support university KTOs and researchers in commercializing their discoveries.

The Abolition of Professor’s Privilege

The abolition of professor’s privilege was a major change both legally and culturally. Under Clause 42 of the German employee invention law, university researchers owned inventions made in the course of their work. This was a unique legal privilege – ownership of all other inventions created in the course of employment are vested in the employer – and reflected Article 5 of the German constitution, which protects the freedom of science and research.

Under the new law, introduced in 2000, German university researchers are now required to scrutinize their research findings and report any inventions to the university – unless they decide to keep their inventions secret by not publishing or patenting. The university has four months to consider patenting any inventions so submitted. If it does not claim the invention, rights to patent and commercialize it revert to the researcher. If it does claim it, the inventor is entitled to at least 30 percent of revenues from successful commercialization, but nothing otherwise. Furthermore, the university handles the patenting process and pays all related expenses such as processing fees, translation costs, and legal expenses. University researchers retain the right to disclose the invention through publication two months after submitting it to the university. Prior contractual agreements with third parties also remained valid during a prescribed transition period.Footnote ⁵

A handful of studies have examined the effects of abolishing professor’s privilege on patenting rates and ownership patterns in Germany. Reference SchmochSchmoch (2007) found that the number of university-owned patents increased. Based on inventor lists, his data also suggest that the new law changed the propensity to invent among academics, discouraging those who had previously filed their own patents while encouraging non-patenters. In a follow-up study, Reference Cuntz, Dauchert, Meurer and PhilippsCuntz et al. (2012) showed that the share of university-owned inventions increased after 2002 while the share of individually or industry-owned university inventions decreased. Reference Von Proff, Buenstorf and HummelVon Proff et al. (2012) found that the policy change did not increase university-invented patents, but that ownership merely shifted from individual- and firm-owned patents to universities.

Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2015c) analyzed the effects of the change in law through a more rigorous micro-econometric study using the difference-in-difference methodology, comparing university-based patenting to the patenting activity of a control group of inventors before and after the change.

In essence, Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2015c) argue that university patenting cannot be compared to general patenting activity in Germany, which is dominated by inventors employed in firms. As the reward systems in firms and public science are very different, they instead aim to compare patenting by university researchers with patenting by researchers employed by public research institutes.

Choosing a good control group of inventors is clearly crucial to evaluate the impact of policy changes. Figure 5.4 shows patenting activity in Germany, with the dotted line at the top showing the overall trend.

Figure 5.4 Patenting in Germany before and after the abolition of professor’s privilege

Source: Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2015c)

The underlying data are applications filed with the German Patent and Trademark Office (DPMA) and the European Patent Office (EPO) between 1978 and 2008 involving at least one German inventor. Data were collected from PATSTAT. Treating 1995 as the baseline (100 percent), patenting grew until the year 2000 and reached about 145 percent, then fell to about 140 percent in 2002, and then grew again to reach 160 percent in 2008. However, academic patenting developed very differently. Patent filings based on university and public research institute inventions both grew from 100 percent in 1995 to roughly 110 percent in 1998, but then both fell, to 70 percent and 80 percent respectively, in 2002 when the law changed. This pattern was found by prior researchers (Reference SchmochSchmoch 2007; Reference Cuntz, Dauchert, Meurer and PhilippsCuntz et al. 2012; Reference Von Proff, Buenstorf and HummelVon Proff et al. 2012). Analysts have speculated about the reasons for the decrease: suggestions include an increasing emphasis on publication in academic performance evaluations, decreased entry into academic jobs, the end of the New Economy boom and legal uncertainty surrounding patenting in the field of biotechnology (Reference SchmochSchmoch 2007: 5–8; Reference Cuntz, Dauchert, Meurer and PhilippsCuntz et al. 2012: 21–2).

Patenting by public research institutes did at first recover slightly after the change in law, but university patenting continued to decline.

For more rigorous analysis, Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2015c) collected a panel of patent and publication data at the level of individual inventors at universities and public research institutes. The panel methodology allows one to control for individuals’ ability to commercialize research, annual macroeconomic shocks, and each researcher’s career age and publication record. Publications may serve as a control variable, reflecting potentially patentable new knowledge.

Figure 5.5 shows trends for the study group (university researchers) and the control group (public research institute researchers) as “within” demeaned average time series, that is, average patenting activity for each person over the whole panel time period is subtracted from their actual observed patenting. This wipes out differences in levels of the time series which might be due to individuals’ specific ability to patent. Here, we are more interested in changes over time rather than different levels of patenting activity among individuals. The figure shows that patenting by researchers at universities and public research institutes followed a similar trend before the law changed and diverged slightly between 1998 and 2001, when abolition of professor’s privilege was under discussion, but that they diverged strongly after abolition. While public research institute patenting first stabilized in 2005, university patenting dropped steadily until 2008.

Figure 5.5 Trends in German patenting for university and public research institute researchers (“within” transformed), 1995–2008

Source: Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2015c)Note: The lines show “within” demeaned, averaged values for university and public research institute researchers. The 2002 vertical solid line marks the date of the actual policy change. The 1998 dashed vertical line shows the date on which the first public discussion took place, according to Internet searches.

Having run micro-econometric fixed-effect panel regressions that also control for researchers’ career ages and publication records, Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2015c) conclude that the law change caused patenting by university researchers to fall by about 17 percent. Thus, the policy failed in its goal of increasing patenting. The authors argue that policymakers misperceived the incentives of university researchers. It was assumed that university researchers were mainly interested in publishing their work in academic journals and most were not interested in commercializing their research results. Instead, however, researchers who were interested in commercialization before the law changed maintained viable networks of industry contacts and often patented in collaboration with companies. These networks were disrupted by the law change, and university researchers instead had to involve university KTOs in negotiations about contract research, IP, and related collaborations.

Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2015c) argue that the cost-and-benefit schedules for university inventors have shifted because of the change in IP ownership. On the one hand, KTOs now cover the cost of patent applications and associated fees, and are also supposed to look for industry partners for commercialization. Prior to the law change, researchers had to invest effort and their own money to realize commercial opportunities. On the other hand, researchers have lost the opportunity to appropriate all revenues from their patenting activity. Prior to the law change, they could theoretically enjoy 100 percent of potential revenues; now, they obtain a 30 percent royalty on all revenues, and the universities own the other 70 percent. In addition, bargaining has become more complex as now, in addition to the researchers, the university’s KTO is involved in negotiations with the firm. The empirical results of Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2015c) suggest that the negative incentives (forgone private benefits of commercialization) outweigh the positive incentives (lower private cost of commercialization).

Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2016) separates patenting by university researchers by applicant type (see Table 5.7). Before 2002, total patenting per university inventor per year amounted to about 0.58 patent applications per year. After the law changed, this total dropped to 0.34. However, the decline causally related to the law change is about 17 percent of the initial value of 0.58 only (according to the results from Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. 2015c). More interestingly, Table 5.7 shows that a large chunk of the decline in patenting is due to a fall in patents where university researchers appear as inventors on corporate patent applications. These patents related to industry have declined by around 50 percent, from 0.45 before the law change to 0.23.

Table 5.7 University researchers’ patent activity by applicant type, 1995–2008

Applicant type	Before 2002		After 2002
	Average patents per inventor per year	Relative frequency (in percent)	Average patents per inventor per year	Relative frequency (in percent)
Industry	0.45	74	0.23	62
Individual	0.14	23	0.04	11
University	0.02	3	0.10	27
Sum	0.61	100	0.37	100
Total*	0.58		0.34

Source: Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2016)

^* Note: In total, the average number of patent applications per identified university inventor per year amounted to 0.58. However, a few patents are co-assigned to multiple types, e.g., a firm and a university file a joint patent application. These are counted for each type, so the total by type amount to 0.61 before 2002 instead of 0.58.

In addition, patents may be filed by individuals, typically university inventors themselves, or by the university. Before 2002, an average of 0.14 patents were filed individually by each university inventor, and 0.02 by each university. As can be seen in Table 5.7, these numbers basically switched around, in line with the change in the law on IP ownership. After 2002, patents filed by individuals fell to 0.04 while university-filed patents increased from close to zero to 0.10, amounting to 27 percent of total patent applications based on university inventions. Applications by individual researchers amount to just 11 percent. These are inventions where the KTO was not interested in claiming ownership or the university researcher did not report the invention to the university. Patent applications with industry are still the largest share with 62 percent. Note that universities are not required to claim ownership of the IP. They may well contract to transfer ownership to firms. The key change is that prior to 2002, the researcher was able to negotiate directly with industry, while now it is the university KTO that does so.

Patents filed along with industry applicants dropped dramatically from 0.45 to 0.23 per inventor per year. These most likely stem from direct research collaborations or contract research between industry and university researchers, strongly suggesting that the abolition of professor’s privilege reduced actual knowledge and technology transfer. The loss of private income opportunities seems to have outweighed the possible benefits in terms of the reduced cost of commercialization for researchers.

The Introduction of Patent Valorization Agencies

As part of the Knowledge Creates Markets campaign, the BMBF established patent valorization agencies (PVAs). By 2012, twenty-nine PVAs had been created, with at least one in each state (Reference Cuntz, Dauchert, Meurer and PhilippsCuntz et al. 2012). Their primary mission is to help universities commercialize their research by providing advice on patenting, licensing and forming spinoffs. They also help to find business partners and licensees.

The main public funding for the PVAs is provided through the SIGNO program of the Federal German Ministry of Economics (BMWi). Funding is assigned to universities, which then use it to request services from the PVAs. The SIGNO budget amounted to EUR 29 million between 2001 and 2003, EUR 38 million between 2004 and 2007, and EUR 29 million between 2008 and 2010. Universities must top this up through co-payments. Reference Cuntz, Dauchert, Meurer and PhilippsCuntz et al. (2012) calculated that the PVAs’ annual budgets totaled between EUR 9 and EUR 10 million in the period 2002–9.

Reference Cuntz, Dauchert, Meurer and PhilippsCuntz et al. (2012) also calculated that the revenues generated by the PVAs did not cover their cost: between 2002 and 2009, they never exceeded EUR 6 million.

It may be, however, that although the PVAs operate at a loss, their KTT activities bring indirect benefits. For instance, the foundation of more spinoff companies would not necessarily be reflected in higher PVA revenues. Researchers may be more likely to found their own companies, possibly in collaboration with a university KTO, after the establishment of PVAs and the abolition of professor’s privilege, as KTOs may now be more actively pushing commercialization through spinoffs and this process may be strengthened by the presence of the PVAs. To test this hypothesis, Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2016) investigated whether more or fewer spinoff companies have been founded since the abolition of professor’s privilege and the establishment of PVAs. They collected data by searching for identified academic inventors among the population of firm founders in Germany. The Creditreform database (the German part of Bureau van Dijk’s Orbis database) includes the names of all firm founders along with information on the foundation year, shareholdings, basic firm-level accounting, and supplemental data. Importantly, this captures not only spinoffs established by university or public research institute KTOs, but also those launched by researchers independently.

Table 5.8 summarizes their findings. Before 2002, university researchers were involved in about 46 startups per year and this number reduced to about 43 per year. The annual probability of a researcher founding a company remained constant at 4 percent. For public research institute researchers, the number of companies founded was lower and constant over time, with 29 spinoffs per year – 1 percent per researcher per year.

Table 5.8 Academic entrepreneurship before and after the 2002 policy reform (annual mean values), 1995–2008

		Startups founded per year	Startups founded per year per inventor
University researcher	Before 2002	46.43	0.04
	After 2002	42.57	0.04
PRI researcher	Before 2002	29.43	0.01
	After 2002	28.71	0.01

Source: Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2016)

Note: The sample included 1,946 patenting university researchers and 4,551 public research institute researchers.

Annual within-demeaned spinoff probabilities at the researcher level are shown in Figure 5.6. As can be seen, while average annual spinoff probabilities fluctuate, they remain broadly constant over time and are unaffected by the law change. This is in line with micro-econometric findings by Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2016). Using panel fixed-effects estimators in a difference-in-difference setup, they found no direct effect of the law change on university spinoffs. In summary, it seems that university KTOs and PVAs have not successfully pushed spinoff creation as the prime channel for commercializing academic inventions.

Figure 5.6 Average trends of spinoff activity (within demeaned)

Note: The vertical line in 2002 denotes the abolition of professor’s privilege.Source: Reference Czarnitzki, Doherr, Hussinger, Schliessler and TooleCzarnitzki et al. (2016)

5.4.1 Limits to and Opportunity Cost of KTT

Reference Czarnitzki, Glänzel and HussingerCzarnitzki et al. (2007, Reference Czarnitzki, Glänzel and Hussinger2009a) studied the growing importance of universities’ unpublished technology-relevant research and cooperation with industry. As more and more scientific researchers became active in commercializing their discoveries, policymakers and academics debated whether patenting as a channel of entrepreneurial activity might significantly reduce scientific output in the economy, with potentially detrimental implications for long-term growth, competitiveness, and employment. Productivity in science can be measured in terms of the publication output and research quality of scientists engaging in commercialization. Czarnitzki et al. combined bibliometric and technometric indicators and econometric techniques to investigate the correlation between patenting and publication output and quality for a large data set of academics active in several research fields in Germany. Their 2007 study found no overall negative correlation between patenting and the scientific output of the academics in their sample, but more detailed analysis revealed heterogeneity in patenting behavior. Whereas some patent applications might result from purely intrinsically motivated research, others were the output of specially funded contract research, especially for industry. Reference Czarnitzki, Glänzel and HussingerCzarnitzki et al. (2009a) classified academics’ patent applications into corporate patents and academic patents using applicant data, distinguishing between patents where one or more academics featured as an inventor but the patent was filed by a company and those filed by another applicant (e.g., the academic themselves or a university or public research institute). Factoring this distinction into their multiple regression models, they found that academic-filed patents did not harm academics’ scientific output, but company-owned patents were associated with (subsequent) lower publication output and also lower publication quality (as measured through subsequent citations by other academic papers). Czarnitzki et al. interpreted this as evidence that the researchers were likely to have engaged in company-relevant research for commercialization/knowledge transfer purposes and that such research could distract them from their own, original academic research.

If one accepts that company-relevant research is likely to be of a more applied nature than normal university research then intensified knowledge transfer efforts by universities may indeed partly crowd out the freely accessible knowledge produced in science in terms of (high-quality) academic publications, potentially harming technological progress and economic development in the long run.

The opportunity cost of knowledge transfer has also been documented. In general, academic patents are more basic than corporate patents, and patents by academic inventors filed along with corporations feature inventions that are based on more applied research than those academic-invention patents owned by universities, public research institutes, or academics personally (Reference Czarnitzki, Hussinger and SchneiderCzarnitzki et al. 2009b, Reference Czarnitzki, Hussinger and Schneider2012). Reference Czarnitzki, Hussinger and SchneiderCzarnitzki et al. (2011) revealed a steady decline in the quality of academic patents. They investigated forward citations received by patent applications – a measure often employed as capturing the social value of an invention, as forward citations approximate how many subsequent inventions build on the patented technology. Czarnitzki et al. compared the forward citations received for patents by German university academics with a randomly chosen control group of patents filed by corporations in the same application year and technology field. They found that in the early 1980s, the average academic patent received significantly more forward citations than the control group of corporate patents, and they took this to indicate that academic patents were more fundamental and basic, and therefore more relevant to subsequent technological progress, than corporate patents. But as efforts to foster KTT from universities to industry grew in subsequent decades, differences between the quality or social value of academic and corporate patents, as measured by forward citations, diminished. By the beginning of the 2000s, there was no longer any statistically significant difference between forward citations of academic and corporate patents. This suggests that the move toward commercialization in academia has had a negative impact on the average social value of academic activities such as patenting. The boundary between not-for-profit academic and for-profit business R&D has become blurred.

Further studies have examined the impact of private industry funding of scientific activities on the publication of academic research results and the sharing of research materials. Reference Czarnitzki, Grimpe and PellensCzarnitzki et al. (2015a) showed that increased industry funding in Germany had hindered the dissemination of research in public science through disclosure restrictions. Arguing that the viability of modern open science norms and practices depends on public disclosure of new knowledge, methods, and materials, they sought to examine the relationship between industry sponsorship and restrictions on disclosure using individual-level data on German academic researchers. Their evidence, which controls for self-selection into extramural sponsorship, strongly supports the proposition that industry sponsorship jeopardizes the public disclosure of academic research. Academic scientists who adopt industry sponsorship are subject to more stringent contract terms that restrict the disclosure of academic research results through delay and secrecy. Controlling for scientist selection, the results show that the likelihood of such restrictions more than doubles with industry sponsorship, because firms expect proprietary benefits from their sponsorship relationships and realizing these benefits often requires disclosure restrictions that academic researchers would not otherwise impose.

These results are in line with those of Reference Czarnitzki, Grimpe and TooleCzarnitzki et al. (2015b) on access and sharing of research inputs among public scientists. The authors found that scientists who received industry funding were twice as likely to deny requests for research inputs as those who did not. Receiving external funding in general did not affect denying others access, but scientists who received external funding of any kind – from industry or elsewhere – were 50 percent more likely to be denied access to research materials by others.

In summary, active knowledge transfer does not come without opportunity cost. There is mounting evidence that the research output of public scientists is affected by their engagement in active knowledge transfer. Some may move toward more applied research, with potentially negative long-run impacts on the basic science that underpins future progress. In other cases, the dissemination of new academic knowledge may be directly impeded through disclosure restrictions imposed by private industry partners or sponsors.

5.4.2 Benefits to Business of Knowledge Transfer

While knowledge transfer can clearly have some negative impacts on the academic side, there are obvious potential benefits too. First and foremost, knowledge transfer may include private research sponsorship that enhances academic research capacities, allowing more doctoral students to be educated and so on. And even in the absence of major budget increases for public science, KTT may bring societal benefits.

The most extreme form of academic commercialization is academics’ involvement in spinoff companies. In such cases, academic research is deemed valuable enough to warrant forming a company, transferring technology to the private sector and potentially adding social value by creating jobs and generating taxable revenues. Reference Czarnitzki, Rammer and TooleCzarnitzki et al. (2014) investigated how far German academic startups grew in their first few years. They collected representative sample data from German firm foundation cohorts between 1996 and 2000 in knowledge-intensive and high-tech sectors. More than 57,000 new ventures were contacted by means of computer-aided telephone interviews, and about 20,000 interviews conducted. In their empirical analysis, Czarnitzki et al. estimated a model of company growth. They identified academic entrepreneurs among the sample of newly founded firms, and controlled for “firm survivor bias” by applying a sample selection model.Footnote ⁶ They found that academic spinoffs grew by around 3 percent more per year on average than other startups.

In a companion paper based on similar data, Reference Toole, Czarnitzki and RammerToole et al. (2015) examined how university research alliances and other cooperative links with universities contribute to startup employment growth. They argued that “scientific absorptive capacity” at the startup is critical to reap the benefits from university research alliances, but not necessarily for other university connections. They estimated the aggregate employment contribution of startup firms and attributed those employment gains to university research alliances and other university connections. They found significant contributions to employment growth from university research alliances and other university connections, but also found that scientific absorptive capacity was critical for university research alliances. Only 7 percent of startups maintained a university research alliance, but 3.4 percent of all jobs created by those firms were attributable to their alliances.

These numbers obtained from econometric regression analysis can be extrapolated to the population. For the period from 1996 to 2001, German National Account statistics show that total employment in the knowledge-intensive sectors increased by 701,000 jobs. Based on the results of Reference Toole, Czarnitzki and RammerToole et al. (2015), 453,422 of these jobs were created by 171,833 companies founded between 1996 and 2000 that survived until the end of 2001. This is about 65 percent of total net jobs in the sectors covered. Among all the startups in this cohort, it can be estimated that 51,908 companies had some kind of university connection(s) in the post-foundation period and created 223,969 jobs. Using the Heckman regression model results, Toole et al. estimate that university connections (research alliances and all others) accounted for 9.2 percent (or 20,535) of these jobs. Turning to university research alliance relationships, they calculate that a total of 11,896 startups within the population had such relationships and created a total of 72,857 jobs. The model results indicate that 3.4 percent (or 2,453) jobs can be attributed to university research alliances.

These results suggest that university connections are quite important for job growth, and university research alliances contributed substantially to job creation for those firms that had such alliances.

When it comes to innovation by established firms, studies have considered spillovers from public science in general and also benefits to companies from direct interaction with public science in the form of research collaborations.

Reference Cappelli, Czarnitzki and KraftCappelli et al. (2014) focused on “essential knowledge spillovers” that companies received from public science. While some such spillovers may be obtained from simply reading academic publications, they may also result from direct interaction through contract research or joint research collaborations. In one wave of the Mannheim Innovation Panel, firms were asked about “essential inputs for innovation” that they had received from other actors in the economy including customers, suppliers, competitors, and public science. The term “essential” was defined in the survey to mean that an input had been indispensable for the development of a new product, service or process.

Cappelli et al. related firms’ sales of market novelties to these reported spillover measures and found that essential information received from customers and public science was associated with higher sales of new products. On average, innovative firms in their sample achieved 9 percent of their sales from products that were novel in their main product market. Regression results showed that spillovers from public science pushed this share to about 13.2 percent.

In a very recent study, Reference Comin, Licht, Pellens and SchubertComin et al. (2018) analyze the case of the Fraunhofer Association, the largest applied research public research institute in Germany. They investigate whether interacting with Fraunhofer institutes in research projects affects firms’ performance and strategic orientation. To do this, they assembled a data set based on Fraunhofer’s (confidential) internal project management system and merged it with the Mannheim Innovation Panel. They found that project interaction had a strong positive effect on firms’ turnover and productivity growth. They also showed that a major driver of these positive effects is the firms’ increased share of sales from new products and an increase in the share of their workers with tertiary education. More detailed analyses reveal, among other things, that performance effects become stronger the more often firms interact with Fraunhofer and that interactions aimed at generating technology have a stronger effect than those merely intended to implement existing technologies.

In summary, the literature has shown quite clearly that (active) knowledge transfer from public science to industry has positive effects on the business sector in Germany. The documented effects range from job creation to new product sales and productivity growth. These positive effects have been found in both startup companies (including academic startups) and established companies.

6.4.1 Formal Channels in Public Research Institute and University Knowledge Transfer Contracts

Drawing on the results of the various KIAT surveys of public research organizations in the Republic of Korea (see Appendix for details), Table 6.8 shows the total number of knowledge transfer contracts in public research organizations and the share of each knowledge transfer channel. IP licensing is a more common (formal) knowledge transfer practice than sales of technologies. The share of license contracts among the total number of knowledge transfer contracts was 68.5 percent in 2014 whereas the share of technology sales was only 12 percent. However, free-of-charge licensing also accounts for a significant share of knowledge transfer contracts – 10.7 percent in 2014 – because one of the main goals of Korean public research institutes and universities is to support SMEs by providing them with free technology. As there is a large technology gap between large firms and SMEs, the government has used public research institutes and universities to improve the technological competitiveness of SMEs.

Within IP licensing, lump-sum payment dominates. While there are presently no statistics to prove this, most of the respondents in this study confirm it anecdotally. In contrast, most IP licensing in leading US universities involves running royalties. The low efficiency of the knowledge transfer market involving public research organizations in the Republic of Korea, in the sense that there is a low level of trust on both sides, makes negotiating long-term contracts involving running royalties difficult. This is bad for research organizations as running royalties, proportional to increased sales, may generate a more stable income. Conversely, no firm was willing to pay a large lump sum because of the uncertain sales potential of the transferred technology.

The total number of startups in 2014 created using technologies from public research institutes and universities was 136; the number of startups by staff (spinoffs) was 108; the number of startups by other people using public research IP was twenty-eight; and the average number of startups per institute was 0.54, which is relatively small compared to rates in the U.S. and other countries. However, several leading public research institutes created more startups: twenty-four leading public research institutes under the auspices of the National Research Council of Science & Technology (NST) created forty-one startups, and the average number per institute was 1.7 (KIAT 2016).

One special type of startup from public research institutes is the “laboratory company,” which is defined in the Special R&D Zone Promotion Act 2005. If a startup from a public research institute is located in a special R&D zone and the institute invests more than 20 percent of the capital, then it can be authorized as a laboratory company and exempt from tax for three to seven years. The technology of public research institutes can be regarded as the startup’s capital, so it is not difficult for such startups to be authorized as laboratory companies.

In 2016, there were 219 laboratory companies in the five special R&D zones (Daedeok, Daegu, Busan, Gwangju, and Jeonubuk). Due to government support and advanced technologies from public research organizations, their sales increased tenfold and their employment increased fivefold between 2009 and 2015, as shown in Table 6.9. The five-year survival rate of laboratory companies was about 64.9 percent, more than double the survival rate of normal startups (29.6 percent) (Ministry of Science, ICT, and Future Planning 2014).

6.4.2 Qualitative Evidence of Successful Knowledge Transfer

IP licensing by ETRI represents a case study of successful licensing. ETRI is the largest public research institute in terms of both R&D expenditure and license income. It earned KRW 34.6 billion from licensing in 2014 – about a quarter (24.7 percent) of the total license income of all Korean public research organizations. Its ratio of license income to total R&D expenditure is 8.4 percent – the highest ratio among Korean public research organizations.

One example of successful IP licensing at ETRI involved a company called Initech, an IT security system company that started in 1997 with two employees. Its core technology is a user authentication solution based on public-key infrastructure (PKI) which ETRI transferred to it through IP licensing in December 1999. In the late 1990s, the number of users of Internet and e-commerce increased rapidly, and so IT security in e-commerce became important. ETRI started research into authentication servers and systems in 1995, as a project for the Korean Ministry of Information and Communication. At an early stage of R&D, ETRI identified potential users of the technology, such as public financial institutions (e.g., the Korea Financial Telecommunications & Clearing Institute). Within four years, ETRI had developed an “authentication processing protocol and verification technology,” and transferred this technology to Initech.

Public-key infrastructure is the system relating to the generation, authentication, distribution and management of public-key encryption, a method of data encryption that uses different keys for encryption and decryption. It is a more secure method than its predecessor, secret-key encryption, and became widely adopted as demand from e-commerce and Internet banking increased. Even after knowledge transfer, researchers in ETRI frequently helped Initech to further develop its own system and service.

Apart from the favorable demand conditions, government policy also contributed to the success of Initech. The government recognized the PKI-based technology as the industry standard in 1999, encouraging more domestic users to adopt it. In turn, this helped the rapid growth of Internet banking and e-commerce.

Although several hundreds of technology startups existed in 2014, most remained small and did not develop a stable growth path. One of the most successful cases of a startup from a public research institute comes from the Korea Atomic Energy Research Institute (KAERI). KAERI is the third-largest public research institute in the Republic of Korea. It started to develop health-promoting functional foods focusing on boosting immunity in 1997. Researchers at KAERI recombined medicinal herbs such as dong quai, cnidium, and white woodland peony using radiation technology. It took six years to develop the original technologyFootnote ⁷ and cost KRW 1.2 billion in R&D. Researchers at KAERI were confident of the quality of their product and decided to establish a company, reaching an agreement with a private company, Kolmar Korea, in 2001. KAERI had transferred other technologies to Kolmar Korea before 2001, and so Kolmar Korea was interested in its new technology.

However, KAERI faced a difficulty as government-appointed directors on its board opposed the agreement, arguing that public research institutes should not engage in income-generating businesses and that there was no precedent for a public research institute providing funds to establish a company.Footnote ⁸ This is interesting because the government of the Republic of Korea had already enacted the Technology Transfer Promotion Act 2000 and mandated public research institutes to establish KTOs.

No company was established for three years. However, finally KAERI changed its strategy and chose technology investment, which meant that the value of KAERI’s technology was regarded as capital and so it did not have to invest any cash. This plan persuaded the government, so KAERI and Kolmar Korea co-established a company, Sunbiotech, in 2004. Sunbiotech can be classified as a joint venture, as the value of KAERI’s technology was approved as KRW 378 million and Kolmar Korea invested KRW 622 million as capital.

Sunbiotech’s sales were poor at first because the product did not obtain approval from the government as a functional health food. The company achieved total sales of between KRW 0.8 and 1.2 billion between 2004 and 2006. Finally, in 2006, it obtained approval for the product as a functional food from the Ministry of Food and Drug Safety. This was one of the first approvals in the Republic of Korea for a functional food that improves immunity. It also obtained authorization from the government as the first laboratory company under the Special R&D Zone Promotion Act 2006. Using that governmental authorization, it was able to sell its products as health-promoting, functional foods that improve immunity. It grew rapidly, with sales increasing from KRW 3.8 billion in 2007 to KRW 9.9 billion in 2008 and KRW 20.1 billion in 2009 (Reference HamHam 2015). By 2013, sales reached KRW 121.5 billion and the company’s name was changed to Kolmar BNH. It was floated on the KOSDAQ stock market in 2015.

The sales and operating profit of Kolmar BNH reached KRW 236.2 billion and KRW 34.4 billion respectively in 2015, by which time the company had 156 employees. By July 2016, its market value stood at around KRW 1 trillion. KAERI held 16.1 percent of Kolmar BNH’s stock at the time of the IPO, and earned over USD 100 million, a sum greater than the total license income of all Korean public research institutes in 2014. The case of Kolmar BNH thus shows the potential of startups and joint ventures in knowledge transfer and commercialization. Following the success of Kolmar BNH, the government of the Republic of Korea changed its attitude and started to actively support public research organization startups.

The KAERI KTO played an important role in the success of Kolmar BNH as it started to apply for Korean and international patents on the core ingredients of the product between 2000 and 2003, just three years after the start of its R&D activities. It applied for the trademark “HEMOHIM” in relation to its products in 2002.

Another factor in Kolmar BNH’s success was reputation. KAERI has a fifty-year history and is well known as the third-largest Korean public research institute, so Korean consumers trusted the product more than products from other startups. The stability and safety of the product are very important factors to consumers in the functional health food market, so the reputation of KAERI helped Kolmar BNH to survive in its early stages.

As in the case of Initech, demand also helped Kolmar BNH to succeed. As income levels in the Republic of Korea rose, people started to pay more attention to their health and the market size for functional health foods increased rapidly. Production of functional health foods in the Republic of Korea increased from KRW 700.8 billion in 2006 to KRW 1.48 trillion in 2013, and the annual growth rate was 11.5 percent during this period (Reference HamHam 2015).

A further factor explaining the company’s success was the management skill available from a private firm. A typical problem in public research organization startups is the lack of sound management skills. However, Kolmar BNH was a joint venture with the private sector, and the managers and employees of Kolmar BNH had the benefit of the management knowhow of Kolmar Korea.

6.4.3 Informal Knowledge Transfer Channels

As seen in Table 6.7, the proportion of firms that actually use formal channels is small. To detail other knowledge transfer channels, Reference Cho, Min and LeeCho et al. (2009) cite examples that do not use IP licensing or startups. We summarize those examples here.

Company SFootnote ⁹ is a leading Korean ICT firm that actively cooperates with public research organizations, but it does not use IP licensing or startup channels to transfer knowledge from them. Instead, its main knowledge transfer channel is the participation of its staff in seminars or education programs provided by public research organizations. For example, it began research into optical materials in the early 2000s, attracted by the thriving optical industry, but since it lacked basic knowledge about optical materials, it sent researchers to participate in relevant university seminars.

It also uses researchers from public research organizations as consultants. Company S has built a network of specialists, and consults them about technology trends and information in their specialized fields. To do this, it undertakes an annual program of twenty–thirty technology seminars with them. In addition, the CEO of the company holds periodic meetings with key experts. It usually consults researchers in public research organizations about the market or technology situation for emerging technology. For instance, it consulted researchers at the Korea Institute of Energy Research about the market prospects and technology when solid oxide fuel cell technology was regarded as promising.

A third knowledge transfer channel is collaborative R&D. As technological convergence/fusion has deepened, Company S has needed collaborative R&D because it does not have research capability in some technology fields. For example, it needed film-coloring technology for PDP (plasma display panel) filters, but did not have research capability in that field. It therefore collaborated with SNU to develop the technology. It obtained basic knowledge about the technology through a year of collaborative research.

However, Company S has not used IP licensing for knowledge transfer. There has been no case of licensing or joint venture with public research institutes. It has previously concluded license contracts with firms in an advanced country, but has not licensed technology from domestic public research organizations. The main reason seems to be that as Company S has recently become a leading ICT firm in the global market, it needs world-class technology to compete, but domestic public research organizations do not offer research capability at a sufficiently high level.

Using research facilities is the second most used knowledge transfer channel in the Republic of Korea, as shown in Table 6.7. However, Company S has not used research facilities in public research organizations, presumably because it is a big firm and has most of the research facilities that public research organizations have and so does not need to use external facilities.

Company S has barely used basic research outputs from public research organizations such as reports, papers, and patents because basic research is not relevant to the company’s technology roadmap.

In sum, leading companies such as Company S primarily use public research organizations as consultants, trainers of their staff, and partners in collaborative research. However, they barely use research outputs such as papers, patents, and technologies produced by public research organizations, which might reflect the relatively low level of research capability of such organizations.

Another example of knowledge transfer channels that shows the importance of informal channels is ViroMed Inc. ViroMed was established by Professor Sun-Young Kim from SNU in 1996. Its main products include DNA, protein, and cell-based biotherapeutics that can treat incurable diseases such as diabetic peripheral neuropathy, peripheral artery disease, amyotrophic lateral sclerosis (Lou Gehrig’s disease), and thrombocytopenia.

Professor Kim received KRW 150 million in government funding as part of a leading technology development project in 1994. It was a joint project with a firm. Professor Kim’s team achieved positive results concerning DNA-based biotherapeutics in 1996. They published their results in Science in 1996 and applied for patents in 1997. After these results, Professor Kim suggested that a firm participating in the project invest and commercialize the product, but the firm refused due to the high risk in the biotherapeutics sector. Following a presentation by Professor Kim at an international conference, a UK venture capital company indicated its intention to invest in his research. Using that investment, Professor Kim established ViroMed in 1996.

ViroMed agreed to a technology export contract with Oxford Biomedica, a UK firm, in 1997, and Takara Shuzo, a Japanese firm, in 1999. On the basis of this export agreement, ViroMed was able to attract both domestic and foreign investment. It was floated on the KOSDAQ stock market in 2005. Its market value reached KRW 1.64 trillion in October 2016, following sales of KRW 7.7 billion and operating income of KRW 1.1 billion in 2015. Its market value is high compared to its sales and operating income because clinical trials of its major products have yet to be completed, even though those products are regarded as high quality. As of October 2017, some of its biotherapeutics are in phase III clinical trials (the final step before coming to market) and some are in phase II in the U.S., China, and the Republic of Korea.

Informal channels of knowledge transfer are important, as shown in the ViroMed case, which was established because a UK venture capital firm was interested in its work after learning about it at an international conference.

Another important informal channel is the use of research facilities at public research organizations. The initial capital of ViroMed was only KRW 200 million and, as such, it did not have enough money to buy research facilities. To solve this problem, SNU allowed Professor Kim and ViroMed to use its research facilities. Without such support, ViroMed would not have been able to continue its research.

A third informal knowledge transfer channel involves hiring graduate students. ViroMed started in the form of a “university company,” so Professor Kim could work with graduate students in his laboratory at SNU, thus providing ViroMed with high-quality personnel.

One distinctive feature in ViroMed’s case is that knowledge transfer to domestic firms is very hard. Unlike Korean ICT firms, Korean pharmaceutical firms have been very reluctant to invest in high-risk projects. They have been used to licensing-in foreign technology. This case shows that domestic industrial capability can affect knowledge transfer from public research organizations. Low industrial capability means that domestic firms have insufficient knowledge and are unable to properly evaluate the potential and risks of new technology. Professor Kim indicated that the most serious problem during the growth process of ViroMed was technology evaluation (Reference Cho, Min and LeeCho et al. 2009).

6.4.4 The Government-Funded Nonpracticing Entity

One distinctive feature of knowledge transfer in the Republic of Korea is the existence of a government-funded IP nonpracticing entity (NPE). This approach began in 2010 to protect domestic firms against patent infringement lawsuits by global NPEs or patent trolls. At that time, US private NPEs started buying many Korean patents from public research organizations, sparking public concern that they might use them to file IP lawsuits against domestic firms, taking advantage of the fact that most Korean firms did not seriously consider IP issues at that time. To prevent this possibility, the government decided to set up an entity serving as a pool of patents owned by Korean agents. Thus, the government and big businesses invested about KRW 58 billion and established an IP NPE with the name of Intellectual Discovery (ID), one of the first government-funded IP NPEs in the world; other countries such as Japan, China, and France have since followed suit.

Intellectual Discovery, ranked sixth globally, buys domestic and foreign patents, and had a portfolio of about 5,000 patents by 2016. Its first objective is to protect domestic firms from patent infringement lawsuits. Big firms that funded it initially and have paid license fees can use the patents that it owns. SMEs can obtain membership and license patents by paying a relatively small fee. If foreign firms or NPEs file a lawsuit against domestic member firms, ID provides them with professional help and even some patents which can be used defensively for cross-licensing. If foreign firms or NPEs violate patents that ID holds, ID can charge them with patent infringement and, on behalf of any domestic firm, negotiate for settlement and for legal process.

6.4.5 Important Factors in Knowledge Transfer

The cases cited earlier show the important factors in each type of knowledge transfer channel. The cases of Initech and Kolmar BNH show the importance of follow-on/adaptive R&D by public research institutes after initial knowledge transfer, which is consistent with the results of the qualitative analyses of Reference KimKim (2012) and Reference Lee, Kim and ParkLee et al. (2015). Furthermore, the case of Kolmar BNH shows the benefits of having a joint venture with existing firms, allowing it to draw on the management skills of the parent companies. Nevertheless, the fact that both were supported by favorable demand conditions suggests it might not be easy to obtain successful results by IP licensing or through a startup if demand conditions are poor.

The cases of Company S and ViroMed show the importance of contract/collaborative research and using facilities in the public sector for knowledge transfer from the public science base. Company S relies on collaborative R&D and consulting, whereas ViroMed relies on using research facilities in public research institutes. The Company S case suggests that the level of research capability of public research institutes may be an important success factor for knowledge transfer, as we argued in Section 6.2. The ViroMed case shows the importance of informal transfer channels such as conferences, even though firm survey data usually rank these as unimportant. It also shows that knowledge transfer from public research institutes can be more difficult in sectors where the country has relatively weak industrial capacity. This may be related to knowledge transfer from ETRI in the ICT sector being more efficient than that of public research institutes in other sectors.

Last, the establishment of ID is an institutional innovation, driven by the government of the Republic of Korea to protect domestic firms against patent infringement by hostile foreign actors.

6.5.1 Institutional Challenges

One of the first and fundamental challenges is that legal protection of IPR remains weak in the Republic of Korea. Although the country was ranked twenty-ninth among 128 countries for IPR protection in 2016 in the International Property Rights Index (IPRI), actual protection by the courts is weak compared to advanced countries. For example, the probability of the plaintiff winning a patent infringement lawsuit was 20 percent in 2011, far lower than that in the U.S. (60 percent). Furthermore, when the plaintiff did win, average damages from 2009 to 2011 were just KRW 78 million – a mere 0.77 percent of the US figure (Presidential Council on Intellectual Property 2015). The expected payout to the plaintiff was only KRW 15.6 million compared to legal costs of approximately KRW 200 million, severely decreasing the incentive to file a patent infringement lawsuit. In consequence, firms have little incentive to buy licenses or patents from public research institutes if they can obtain technology in other ways, reducing the efficiency of knowledge transfer from public research institutes and depressing the knowledge transfer market.

Weak IPR protection is a legacy of the developmental state during the catch-up period. The major knowledge transfer channel in this period was copying technology from firms in advanced countries. Korean firms did not hesitate to copy good domestic or foreign technology. Furthermore, patent lawsuits were dealt with by the ordinary courts, where judges lacked the technological expertise to analyze the issues at stake. While dozens of private knowledge transfer agents exist, their IP business is mainly geared to foreign countries; they do not usually file domestic lawsuits for patent infringement even when the IPRs of their domestic clients are violated.

6.5.2 Immature Capabilities of Government and the SMEs Sector

A second set of challenges relate to the government’s immature policies for knowledge transfer. One of the clearest examples is co-ownership of patents from publicly funded research. It is often difficult for co-owners to reach consensus about whether to license and, if so, to whom, and as a result co-owned patents tend to be underutilized or under-licensed. Thus, while co-owned patents accounted for around 10 percent of total patents in the Republic of Korea in 2013, only 2.8 percent of patent transactions involved co-owned patents. This problem is especially severe when public research institutes and private firms share a patent. As public research institutes do not have production facilities, they cannot make money directly using shared patents.

A second or related problem concerns types of license. The government has tended to encourage nonexclusive licensing to promote more and wider uses of technologies developed by public research institutes. However, this can undermine the interests of licensee firms, which will generally want to use the technology exclusively to increase their potential profits, and it also fails to offer any extra reward to first-licensee firms, which take a bigger commercial risk than follow-on firms in acquiring technology before its value has been proved in the market. Firms have therefore avoided nonexclusive licensing, reducing licensing income for the public research institutes.

The preferred form of licensing payment is a lump sum. This contrasts with the situation in the U.S., where running royalties make up around 70–80 percent of total license income for the leading universities. And even when a running royalty clause is included in the contract, firms do not usually reveal their true sales from the technology to public research institutes – a serious implementation issue and a possible case of market failure.

Other challenges for knowledge transfer in the Republic of Korea stem from the short history of its knowledge transfer system and the primary role of the government in developing that system. The R&D process in public research organizations does not fit the needs of SMEs. Until the 1990s, the major partners of public research institutes included big firms such as Samsung and LG, because their R&D capability remained weak. However, as their R&D capability has improved due to large in-house R&D investment, big firms can conduct their own R&D without the support of public research institutes. As a result, SMEs have become the major partners of public research institutes, accounting for 90.7 percent of knowledge transfer contracts with public research institutes in 2014 (KIAT 2016).

As the R&D capability of SMEs is weak, public research institutes have to develop technology to an advanced stage, until it is ready for commercialization. However, many government-supported R&D projects do not consider this issue. The normal R&D project duration is two to three years, and public research institutes usually have only completed laboratory-stage development within this period. In terms of technology readiness level (TRL),Footnote ¹⁰ SMEs need at least TRL level 7 technologies (technology demonstrated by prototypes in operational environments), but public research organizations usually tend to provide only TRL level 4 technologies (technology validated in labs). Thus, there is a serious gap in of the technology level demanded and supplied, which hinders effective commercialization of R&D conducted in public laboratories.

SMEs cannot successfully commercialize the transferred technology due to their weak R&D capability. As a result, the technology is not utilized successfully and public research organizations and SMEs tend to blame one another for this failure. It also decreases future private demand for technology from public research organizations. Government therefore needs to provide public research organizations with enough time and funds to complete the technology to a sufficient level. Otherwise, a short-termist reluctance to commit to extra spending decreases the efficiency of public R&D projects. An interviewee from ETRI said that this is a major barrier in knowledge transfer, which is consistent with the findings of several qualitative studies and case studies that emphasize the importance of follow-on/adaptive (or after-transfer) R&D being provided by public research organizations to ensure successful knowledge transfer.

6.5.3 Issues with Public Research Institutes and Universities

One problem is due in part to the specific nature of the project imposed on public research institutes in the Republic of Korea. In the project-based system, the government allocates R&D expenses, including the researchers’ salaries and overhead costs for each R&D project. The main goal of the project-based system is to increase the cost efficiency of R&D, but it generates some side effects. Researchers at public research institutes have to undertake as many R&D projects as possible to generate their own income, because the majority of R&D funding is determined by the number of R&D projects executed and the researchers’ salaries are part of the acquired R&D budget. Furthermore, given that each public research institute’s budgetary resources are proportional to the size of the R&D funding it receives, public research institutes incentivize researchers who obtain more R&D projects. Such a system induces researchers to try to obtain as many public R&D projects as possible. Thus, the average number of R&D projects per researcher per year reached as high as 4.8 in 2011 (Reference Kim and ShimKim and Shim 2013), reducing the amount of time that researchers could spend on each project and diminishing the quality and TRL of R&D results.

Public research organizations also face problems relating to the low capability of KTOs. Despite support from various government laws and projects, KTOs employ small numbers of staff and lack many important skills for successful commercialization. Furthermore, many KTOs implement a staff rotation system, making it difficult for them to accumulate the necessary skills. Incentives for KTO staff to commercialize technologies are weak – 61.8 percent of public research organizations gave no license income to any KTO staff in 2014 even if they played a role in the commercialization of technologies (KIAT 2016). The average share of license income going to KTO staff that played a role in successful commercialization in 2014 was just 3.8 percent, discouraging high-performing staff from working in KTOs. The average annual wage of KTO staff in 2014 was about KRW 34 million (less than USD 30,000), close to the national average wage and clearly insufficient to attract high-quality workers. Only 20 percent of KTOs hire professional staff such as patent lawyers.

Weak incentives for staff at KTOs are related to strong incentives for researchers. The Technology Transfer and Commercialization Promotion Act requires a minimum share of license income for researchers of 50 percent. The actual average share of license income going to researchers across public research institutes was 40.8 percent in 2014 (KIAT 2016), but this is greater than in advanced countries such as the U.S. and Germany. It seems that the government is trying to compensate researchers generously because the system for knowledge transfer remains immature, but one consequence is that little or no license income is available for KTO staff and so they have few incentives to conclude licensing deals.

The problem of weak KTO capability is exacerbated by the fact that few public research organizations are willing to provide the knowledge transfer market with high-quality technologies. Instead they prefer to commercialize their best technologies directly using their KTOs. Nevertheless, the capability of most KTOs at public research organizations is weak, except at ETRI and some leading public research institutes. Thus, public research organizations are not in a good position to fully utilize or commercialize high-quality technologies generated in-house, which decreases the efficiency of the knowledge transfer market. One private knowledge transfer agent identified this as a major problem in the Republic of Korea.Footnote ¹¹

The weak capability of KTOs is mainly due to the Republic of Korea’s short historyFootnote ¹² of knowledge transfer and commercialization. The government mandated many public research organizations to establish KTOs in the early 2000s, but it takes time for these KTOs to build capability. During this period, the government should have set up systems whereby private agents could use and commercialize high-quality technologies developed by public research organizations, but these policies are yet to be realized. Thus, this problem is one side effect of the government-driven character of the knowledge transfer system.

Weak KTO capability is related to a third challenge, which concerns the quality of patents. As KTO capability is weak, it is difficult to generate high-quality patents even when high-quality technologies exist. In particular, professionals such as patent lawyers make up only a small proportion of KTO staff, so public research organizations cannot obtain high-quality services during the patent application process. Even when public research organizations sign contracts with external professional staff for patent applications, their budget is very small compared to R&D expenses and, as such, it is difficult to obtain good services. Most interviewees said the budget per patent draft has stagnated – it has remained at about KRW 0.5–1 million (less than USD 1,000) per patent for the last twenty years. This is a very small budget compared to that in the leading global firms, which is about KRW 10 million. One interviewee argued that the budget for drafting each patent application should increase to as much as KRW 5 million – five to ten times the current level.Footnote ¹³

7.4.1 Legal Framework

The main regulation regarding the relationship between public research institutes, universities and companies in Brazil is provided by the Innovation Act (Law no. 10,973 of 2004). This law aims to promote partnerships between such institutions and companies in order to foster innovation in the country. As regards IP rights specifically, prior to the Innovation Act, the Brazilian Intellectual Property Law approved in 1996 guaranteed that universities and public research institutes would own patents generated inside the institution.

However, the Innovation Act goes much further in regulating and fostering knowledge transfer between universities, public research institutes, and companies. For the first time in Brazil, this law allowed public institutions – public research institutes or universities – to sign knowledge transfer contracts with companies, and established some basic rules for such contracts. These include rules regarding exclusive licenses, which the original version of the Act required be preceded by an open call. Recently, the Science and Technology Act (Law no. 13.243 of 2016) has changed some of the requirements for public research institutes and universities signing exclusive agreements with companies. Exclusive agreements originating from a prior partnership with a specific company have been simplified. However, this law has also introduced a series of new requirements that reduce the autonomy of a public research institute or university in negotiating such contracts.

The emphasis of the Innovation Act on fostering knowledge transfer is revealed by seven chapters dedicated to promoting the so-called “cooperative environments of innovation.” A special role is accorded to public-based research organizations – universities and public research institutes – in the cooperative production of new technologies with firms.

To ensure such engagement, the Act sets out the specific formal channels through which universities and public research institutes are expected to support firms in the production of new technologies:

• Article 4 provides for (a) sharing university and public research institute laboratories and facilities with SMEs in incubation activities, and (b) granting private companies access to laboratories, equipment and facilities for R&D activities.

• Article 6 allows universities and public research institutes to sign knowledge transfer and IP licensing contracts based on technologies developed by the institution or in partnership and establishes the basic rules for those contracts.

• Article 8 foresees the provision of technical services by universities and public research institutes to private firms engaged in R&D activities, such as tests, trials and calibrations, as well as technical reports.

• Article 9 allows universities and public research institutes to enter into partnership agreements with firms aimed at developing new technologies together.

To encourage university and public research institute staff (mostly government researchers) to engage in such interactions, the Innovation Act states that these institutions may be financially compensated by firms for such activities, and any of their staff involved may also be financially compensated through an additional variable payment or an “innovation stimulus scholarship.”

The Act also stipulates that each research organization should establish its own knowledge transfer and innovation policies creating guidelines for entrepreneurship, innovation, knowledge transfer, and so on. Indeed, the existence of a KTO in each public research institute or university is a requirement of the Act and it sets out the basic competences of a KTO. This was controversial, since even universities with a low technology focus were obliged to establish a KTO. The requirement was relaxed recently and the law was modified to allow KTOs to be created in association with other universities or public research institutes.

The Innovation Act represented a major change in the Brazilian landscape for innovation. However, there are still a lot of improvements to be made and a lot of uncertainty regarding its application. Prompted by concerns about uncertainty, excessive bureaucracy and overlapping laws in the Brazilian legal framework for innovation, the New Science and Technology Act (Law no. 13.243 of 2016) was recently enacted to consolidate several different pieces of legislation affecting innovation. This new act aimed to promote the modernization of the legal framework as well as reducing constraints on the implementation of university–industry partnerships.

The possibilities and stimulus mechanisms established by the Innovation Act in 2004 notwithstanding, university–industry interaction remains low in Brazil. One oft-cited barrier is the legal uncertainty that surrounds the Brazilian innovation legal framework (Reference Rapini, Albuquerque, Chaves, Silva, Souza, Righi and CruzRapini et al. 2009; Reference Closs and FerreiraCloss and Ferreira 2012; Reference RauenRauen 2016). Three particular aspects of legal uncertainty in the Innovation Act should be highlighted: (1) the management of private resources received by universities and public research institutes as compensation for their involvement in innovation activities (since they are part of central government administration, universities and public research institutes do not enjoy autonomy in managing private resources); (2) the difficulty of implementing financial compensation for university and public research institute researchers involved in innovation activities, since the law does not clearly state how such benefits should be granted; and (3) the still-limited role of KTOs – a situation that undermines their capacity to generate and implement new university and public research institute partnerships.

Recognizing the legal uncertainty in these areas, the 2016 Science and Technology Act introduced significant reforms to the Innovation Act. As regards university/public research institute–enterprise interaction, it aimed to strengthen and empower KTOs and establish clearer processes for managing private resources to reward institutions engaging in innovation activities. However, it has not clarified the law on compensation for public researchers, and so it seems unlikely to succeed in reducing the difficulties faced by universities and public research institutes in managing rewards for researchers involved in such activities.

In sum, there is still scope to improve the Brazilian Innovation Act and complementary laws and practices in order to further reduce legal uncertainty within the Brazilian innovation legal framework as regards university–industry interaction. But in any case, fostering public–private partnerships in Brazil requires changes that go beyond the modernization of innovation legislation. The solutions needed are many, but all of them are connected – at least in some way – with the creation, diffusion, and application of protocols, internal processes, and rules of conduct in government organizations, and with the capacity of government agencies to deal with conflicts of interest and risk.

7.4.2 The Main Channels of Knowledge Transfer

The most common channels for knowledge transfer are probably informal ones such as technology fairs, workshops, conferences, and seminars. Based on informal networks and contacts, these channels play an important role in the innovation landscape in many countries, not only Brazil. However, our analysis here focuses mainly on formal mechanisms for knowledge transfer, even though these are likely to be preceded by an informal approach.

The Innovation Act established the formal channels for knowledge transfer. One of the obligations of universities and public research institutes in this context is to inform the Ministry of Science, Technology, and Innovation about licensing contracts and the overall intellectual property policies of the institution. This information is collected by the Ministry every year and published in a report that contains basic information about knowledge transfer in Brazilian public research institutes and universities – the so-called FORMICTFootnote ¹¹ reports. For instance, these reports contain the number and type of knowledge transfer contracts undertaken by public organizations in the country.

Based on this information, Table 7.8 shows the most common formal channels for knowledge transfer used by the 264 public research institutes and public universities that responded to the MCTIC survey in 2014. Licensing contracts seem to be the most common knowledge transfer channel among the sample, representing more than 42 percent of total contracts signed by respondent institutions, followed by R&D agreements (25 percent) and know-how contracts (9 percent).

According to the MCTIC data, most of the licensing contracts were made with companies from Brazilian manufacturing, which represented around 30 percent of total contracts. Within manufacturing, the pharmaceutical and chemical industries were the sectors with the largest number of knowledge transfer contracts.

It is important to note, however, that the figures are distorted by the fact that the information comes from KTOs. KTOs are most likely only reporting on those contracts and agreements for which they are responsible. Since the involvement of a KTO is only mandatory in the case of licensing contracts, this channel is probably overestimated in the official data.

For the same reason, our own interview data from KTOs also probably overstate the importance of licensing. Four interviews were undertaken with major KTOs in Brazil as part of the research project for this book. We identified three main formal channels of knowledge transfer: licensing and commercialization of IP, software, and knowhow; non-disclosure agreements; and technological partnership agreements. Of these, licensing emerged as the KTOs’ main activity.

This contrasts with the results of the interviews we conducted with researchers, which identified consultancy performed by academics personally rather than agreements on the part of their universities as the main knowledge transfer channel, followed by research agreements (sponsored research) between universities and companies. The literature on knowledge transfer also emphasizes the importance of academic consultancy.

All the interviewees – KTOs and individual researchers – agreed that data management was crucial to control and improve KTOs’ activities and knowledge transfer processes. They also noted the importance of data management in enabling KTOs to comply with their obligations under the Brazilian Innovation Act, which requires them to “monitor the processing of applications and the maintenance of the institution’s intellectual property rights” and “promote and monitor the University/PRI relationship with companies.”

Despite the importance of their data management function, KTOs may hold incomplete information about universities’ knowledge transfer activities. For instance, at Unicamp the KTO (called Inova) may support the process of signing a new sponsored research contract with a company, but this is not necessary or mandatory. In fact, the internal regulations on this process do not foresee a role for the office. As a result, in 2016 Inova had information about fewer than thirty research contracts with companies undertaken by Unicamp, according its annual report.

The same thing happens in several other universities, explaining why licensing contracts appear in the official statistics as the main formal channel for knowledge transfer. But all the other evidence suggests that consultancy and research contracts are the most important channels, although there are no consolidated data to confirm this.

7.4.3 Institutional Knowledge Transfer Practices

In general, the knowledge transfer activities of the institutions whose personnel were interviewed are based on: (1) the innovation policy of the universities to which they are linked, (2) their university’s internal regulations on research and graduate activities, (3) the Brazilian Innovation Act and related regulations, (4) federal law on supporting agencies, (5) laws on academic employment, and (6) implicit policies of innovation (the “culture”) adopted by researchers and university academics.

In order to stimulate university/public research institute–enterprise interactions, the Brazilian Innovation Act obliged all public research institutes and public universities to establish their own innovation policies covering, among other things: (1) strategic objectives and guidelines for innovation; (2) entrepreneurship; (3) technological services; (4)laboratory-sharing procedures; and (5) IP rights and knowledge transfer. The Act also stipulated that universities and public research institutes should have their own KTOs fulfilling the role of intermediate agents responsible for managing the institution’s innovation policies (Brasil 2004: art. 16).

All the institutions answering our research questionnaire said they had an IP policy. The requirements of the Innovation Act are probably responsible for that in many cases, but some institutions had already established their IP policies or created KTOs before the Act. For instance, Inova, the KTO at Unicamp, was created in 2003, and UFMG has had an IP policy since 1998.

While every public university and public research institute in the country is required to have a KTO, the Innovation Act allowed institutions to share a KTO. This is probably a unique feature of the Brazilian KTOs: several of them serve more than one research organization.Footnote ¹²

It is rare for Brazilian universities and public research institutes to use other kinds of agency to support knowledge transfer or entrepreneurship. For example, liaison offices to promote partnerships with companies are not common in Brazilian institutions, and neither are funds or specific agencies geared to supporting entrepreneurship. Therefore, the KTOs sometimes take on these kinds of responsibility. For instance, some interviewees mentioned actions taken to stimulate faculty and graduate students to get involved in technology partnerships with companies and entrepreneurship, and at Unicamp the incubator and technology park come under the umbrella of Inova.

However, several authors argue that the role of Brazilian KTOs is still very limited, and, in certain cases, research institutions do not include them in the management of innovation activities (Reference Pinheiro-Machado and OliveiraPinheiro-Machado and Oliveira 2004; Reference Dos Santos, Toledo and LotufoDos Santos et al. 2009; Reference Closs and FerreiraCloss and Ferreira 2012; Reference Pereira and MelloPereira and Mello 2015; Reference Rauen, Turchi and TurchiRauen and Turchi 2017).

The explanation for the limited role of Brazilian KTOs may in part lie in their staff profile. According to the MCTI (2017), more than 50 percent of KTO staff are public servants with no previous experience in the private sector, which might be of great help in evaluating the commercial potential of or market interest in a given technology. The others are fellows, students or support employees (interns constitute almost 10 percent of all KTO staff).

Regarding KTOs’ intended role as a contact point for companies at public research institutes, this is also not so relevant since companies’ approaches to public research institutes tend to be informal or motivated by other concerns. Reference Rauen, Turchi and TurchiRauen and Turchi (2017) consulted thirteen public research institutes and over sixty public specialists in the management of public–private R&D interaction to identify, among other things, common business practices in accessing public research institutes’ knowledge transfer channels. Their interviewees reported that companies tend to approach public research institutes in four different ways to seek their R&D support:

• spontaneous demand (motivated by previous informal contacts with public research institutes’ technicians and researchers);

• response to public funding notices (especially those notices that prioritize research activities and technological development through public–private partnerships);

• contact with public research institute alumni; and

• response to support advertised by public research institutes themselves, which occurs mainly in the case of institutions that provide open-access laboratories for many different users.

In fact, several studies (Reference Porto, Kannebley Júnior, Selan and BaroniPorto et al. 2011; Reference Closs and FerreiraCloss and Ferreira 2012; Reference Rauen, Turchi and TurchiRauen and Turchi 2017) have shown that public funding announcements aimed at building partnerships between business and universities/public research institutes are very important in fostering interest among companies in formalizing partnership agreements.

Nevertheless, KTOs undertake several activities to promote university–industry interaction. All the KTOs at larger universities, for instance, release a list of their institution’s technologies that are available for licensing so that companies can find the most suitable ones for their interests.

Other activities, such as pricing technical services, agreeing the number of public research organization staff who will consult on R&D projects or the number of hours of private access to laboratories, tend to be led by public research organization researchers and technicians themselves. The role of the KTO at this negotiation stage is minimal or nonexistent.

While KTOs have limited participation in most of the public research institutes’ innovation management activities, they do make an important contribution to managing IP activities, especially drafting, registering, and filing patents. Reference Rauen, Turchi and TurchiRauen and Turchi (2017) reached this conclusion from interviews with specialists in knowledge transfer and researchers at several public research institutes in Brazil in which they asked about the role of KTOs, among other things. The identified two main reasons why KTOs have little participation in and limited influence over public research institutes’ innovation management activities. First, KTOs have limited managerial and budgetary autonomy, as they depend largely on fund transfers from and strategic decisions by public research institutes. Second, they suffer from high staff turnover and a dearth of qualified or specialized staff, because their link to government institutions obliges them to rely on public tenders in hiring new staff and they do not offer competitive salaries.

In sum, although the KTOs were expected to play an important role in mediating innovation activities with the private sector, they lack the recognition and operational flexibility necessary to carry out their tasks.

As regards incentives, the Innovation Act and subsequent legislation did provide financial incentives for universities and academics to work with companies, and, in consequence, it is now very common for both institution and individual staff to receive financial and nonfinancial compensation for their participation in innovation activities.

All the institutions we surveyed reported that professors and researchers can undertake consultancy activities for companies and can also receive additional remuneration for participating in research contracts between universities and companies. Finally, they can also receive one-third of any royalties received from licensing technologies that they helped to develop.Footnote ¹³

Regarding nonfinancial compensations, interviewees affirm that, in collaborative projects, the standard procedure is that any remaining research assets such as equipment tend to be donated to the university.

In spite of all the difficulties faced, in particular by public universities, the institutions were unanimous in reporting that these compensation mechanisms are important in stimulating engagement among teachers and researchers in developing technologies in partnership with companies. Interviewees believe that KTOs helped to empower researchers to seek new innovation projects with companies, because they felt there was a support structure in place for identifying, negotiating and managing projects.

8.2.1 Investment, Scientific Publications and Patent Applications

R&D Investment

China has become a powerhouse in R&D spending since the 2000s. In 2012, its gross expenditure on R&D (GERD) passed 1 trillion renminbi (CNY) (USD 163 billion), third behind only the U.S. and the European Union. In 2017, this number rose to a record CNY 1.76 trillion (USD 254 billion), ranking China as second in the world in terms of R&D spending after the U.S. (National Bureau of Statistics 2018). R&D intensity, the ratio of R&D expenditure divided by gross domestic product (GDP), hit a record high of 2.12 percent – a rise of 0.01 percentage points compared to 2016.

As Figure 8.1 demonstrates, the share of business R&D spending out of total R&D expenditures has kept increasing throughout the past twenty years, rising from 60 percent in 2000 to 77 percent in 2016 (China Statistical Yearbook on Science and Technology 2017).

Figure 8.1 Share of total R&D expenditures by enterprises, public research institutes, and universities in China, 2000–16

Source: China Statistical Yearbook on Science and Technology (2017)

All types of organizations devote most of their R&D investment to experimental development or applied research (Figure 8.2), but universities are the primary performer of basic research, accounting for 49.3 percent of total basic research expenditures of CNY 82.3 billion.Footnote ¹

Figure 8.2 Share of 2016 R&D expenditures in China by application

Source: China Statistical Yearbook on Science and Technology (2017)

Patent Applications

Since the 2000s, China has experienced a surge of patent applications. The total number of invention patent applicationsFootnote ² filed with China’s State Intellectual Property Office (SIPO) increased from 51,747 in 2000 to 1,338,503 in 2016. In 2017, more patent applications were filed with SIPO than the filings for the United States of America (U.S.), Japan, Republic of Korea, and Europe combined. Figure 8.3 shows domestic invention patent applications by type of entity. Enterprises have the most rapid growth in patent filings. The share of university and public research institutes in total invention patent applications increased from 14.4 percent in 1995 to 22.9 percent in 2005, before declining to approximately 19 percent from 2014. Reference Zhang and WanZhang and Wan (2008) analyzed the ownership of Chinese patents and found that public research institutes have a higher efficiency (measured by the number of patents per unit of R&D expenditure) in generating invention patents, while enterprises have higher efficiency in generating utility model patents.

Figure 8.3 Domestic invention patent applications by different types of organization, 1995–2016

Source: China Statistical Yearbook on Science and Technology (2017)

8.3.1 The Legal Framework for Knowledge Transfer in China

One of the most important laws governing knowledge transfer activities in China is the 2007 Science and Technology Progress Law, which provides the legal framework for the management of scientific and technological achievements. According to Article 20 of the Science and Technology Progress Law, intellectual property rights (IPRs) that are generated from government funding by a university or public research institute belong to the institution, except when the IP rights involve national security, the national interest, or other major social and public interests. IPRs include patents, copyrighted software, integrated circuit designs, and new plant variety rights.

While the concept of patents dates to the fifteenth century in Europe, the introduction of a system of intellectual property laws in China is very recent (Reference Kafouros, Wang, Piperopoulos and ZhangKafouros et al. 2015). China joined the World Intellectual Property Organization in 1980, paving the way for the creation of an IP system that complies with international standards (Reference Bosworth and YangBosworth and Yang 2000). Five years later, in 1985, China signed the Paris Convention for the Protection of Industrial Property and established a Patent Office, the predecessor of the current SIPO. The Chinese Patent Law was enacted in 1984 and is the governing legislation for the protection of technological inventions in China. The Patent Law came into effect in 1985 and has been amended three times, in 1993, 2001, and 2009.

Article 6 of the 2009 Patent Law regulates the ownership of inventions created by academics and researchers at universities and public research institutes during their work, or when they use materials, facilities, or equipment provided by a university or public research institute. According to the Patent Law, the inventor of inventions created as part of their work or using workplace assets has the right to be acknowledged on the patent document and receive a reward or compensation from their employer, but the employer owns the invention.

Another essential law governing knowledge transfer in China is the Law on Promoting the Transformation of Scientific and Technological Achievements (PTSTA), promulgated in 1996 and amended in 2015. The Law covers rights to scientific and technological achievements, rewards for R&D and knowledge transfer personnel, and requires universities and public research institutes to establish or obtain access to knowledge transfer agencies.

Contract law and company law also regulate knowledge transfer in China, as the relationship between the parties to a knowledge transfer agreement reflects basic contractual relations and knowledge transfer often involves enterprises as technology buyers or collaborating partners.

8.3.2 Amendments to the PTSTA Law in 2015

The PTSTA Law of 1996 was amended in 2015 for three reasons. First, several articles of the Law were outdated as a result of significant changes in the Chinese economy. Second, many provinces had experimented with various policies to stimulate knowledge transfer and the amendments were designed to enact the most effective policies into law. Third, universities and public research institutes in China lacked adequate incentives to transfer technology because of the institutional setting and rules defined in the 1996 Law.

Under the 1996 Law, a university or public research institute was required to report to and obtain approval from the Ministry of Finance or the State-Owned Asset Supervision and Administration Commission in order to license or otherwise dispose of IP. Universities and public research institutes did not have full owner’s rights, and consequently were less motivated to promote knowledge transfer. Furthermore, after they transferred IP assets, any revenue they earned from the transfer had to be paid to the Ministry of Finance.

The amendment dealt with these issues. Under Article 18 of the amended PTSTA Law, universities and public research institutes established by the state have the right to dispose of their scientific and technological achievements, including the right to transfer technologies. However, the price agreed on by both parties in negotiation or auction and the name of the scientific and technological achievements must be disclosed to the public. Furthermore, universities and public research institutes can keep the revenue from knowledge transfer and are not required to pay it to the Ministry of Finance.

Before the amendment, knowledge transfer was not used as a performance measure for universities and public research institutes. In contrast, the amendment has made knowledge transfer a legal obligation for Chinese universities and public research institutes. Article 17 of the amended Law stipulates that public research institutes and universities established by the state are required to strengthen the management, organization and coordination of the transformation of scientific and technological achievements, prepare an annual report on their achievements in transforming science and technology, and set up a knowledge transfer organization and process.

In May 2016, the State Council announced implementation details for the PTSTA Law in a Program on Promoting Scientific and Technological Achievements, Transfer and Transformation to promote the disclosure and exchange of information on scientific and technological achievements. Specific actions under this program included:

• Setting up a coordination mechanism for industry, universities and public research institutes so they can cooperate fully to promote knowledge transfer.

• Creating a commercialization base for scientific and technological achievements.

• Strengthening the transfer of scientific and technological achievements into market-oriented services, including building a national technology trading network platform and offering knowledge transfer services at the regional level.

• Promoting scientific and technological innovation and entrepreneurship through the development of “maker spaces” to open up the scientific and technological resources of universities and public research institutes to the public.

• Training professional knowledge transfer personnel.

Almost every provincial government has enacted regulations to implement the provisions of the amended PTSTA Law. For example, several provinces increased the proportion of knowledge transfer revenue that can be used to reward R&D and knowledge transfer or set up special scientific and technological achievement funds. In Jiangsu Province the fund was valued at CNY 2 billion in 2014. Provincial governments were often bolder than the central government in promoting knowledge transfer because they considered knowledge transfer to be an important driver of local economic growth.

To fulfill the legal obligations stipulated in the amended PTSTA Law, China’s universities and public research institutes adopted up to seven actions to facilitate knowledge transfer, although some universities and public research institutes implemented some of these actions before the amended Law, for instance, to reflect provincial policies or known best practice.

1. 1. Increasing rewards and compensation for inventors and knowledge transfer contributors. Article 45 of the amended Law requires that no less than 50 percent of the net profit from knowledge transfer should be given as a reward or compensation by universities and public research institutes to the inventors and others who made significant contributions to the transfer, including knowledge transfer officers. This provision greatly incentivized knowledge transfer by universities and public research institutes. Nearly all universities and public research institutes have reformed their reward regulations since 2015. Many now give up to 70 percent of net profits from successful transfer to the inventors and related contributors. In 2015, the Drug Research Institution of the Chinese Science Academy paid nearly CNY 12 million to inventors and knowledge transfer contributors.

2. 2. Setting up knowledge transfer organizations. China’s public research institutes have set up knowledge transfer organizations that are either associated with several national-level organizations, such as the National Technology Transfer Center or the National Technology Transfer Demonstration Institution, or cofounded with local governments or enterprises. Successful examples include the Hunan University of Chinese Medicine, which transferred its newly developed Chinese traditional medicine to pharmaceutical enterprises and earned revenue of CNY 68 million. The transfer eventually resulted in the development of enterprises with annual revenues of several hundred million renminbi and created several leading brands of biomedical products in Hunan Province. Another example is the Central South University of Forestry and Technology. The University provided a feasibility study of bamboo plywood production, factory planning, process design for workshops, technical training, preproduction technical guidance and many other technical services to more than 400 bamboo plywood enterprises which together achieved total output valued at more than CNY 20 billion. A third example is Changzhou University, which signed twenty-two knowledge transfer agreements with twenty major manufacturers of phosphorus chemical products and obtained a total income of over CNY 20 million.

3. 3. Implementing performance evaluation systems. Many universities and public research institutes have established performance evaluation systems to motivate knowledge transfer staff. By contributing to knowledge transfer, staff can be promoted to senior management positions and have the opportunity to pursue a promising career path.

4. 4. Marketing of information on scientific and technological achievements. Universities and public research institutes participate in exhibitions organized by governments and other commercial organizations to exchange information with enterprises and investors, introduce their scientific and technological achievements, negotiate with potential buyers, and disseminate information about their scientific and technological achievements on their websites to attract potential partners.

5. 5. Permission for academics to take a leave of absence to start a business. Before the 2015 amendment to the PTSTA Law, universities and public research institutes did not encourage academics to work part-time to assist a firm to transfer licensed university technology or take a leave of absence to start their own businesses. However, the 2016 implementation details to the PTSTA Law allow academics to do so. The policy requires universities and public research institutes to establish their own systems to manage academics while they are on leave, and should keep the faculty position of academics for up to three years for those who take a leave of absence to create new businesses.

6. 6. Policies on spinoffs. Many universities and public research institutes have introduced new initiatives to permit and encourage students to start their own businesses. On-the-job and off-the-job entrepreneurship by professionals and technicians in universities and public research institutes are also encouraged. For example, according to the Knowledge Transfer Regulation of Zhejiang University, faculty and students can invest in companies, using their scientific and technological achievements and proprietary technology.

7. 7. Strengthening cooperation between universities, public research institutes and local industry. In addition to the policies identified above to provide incentives for academics to engage in knowledge transfer, policy has also encouraged knowledge transfer via university–industry collaboration. A common channel is to establish a joint research institute that offers technology services to local industries. In this collaborative model, local governments offer land, funds, and buildings while universities and public research institutes offer their scientific and technological achievements, R&D capabilities, management teams, and equipment. Local governments are eager to support this model due to expectations that collaboration will promote local economic growth.

China has formulated four other types of policy to promote university–industry research linkages. One consists of policies to establish strategic alliances for industrial technology innovation. The first fifty-six alliances were set up in 2010 and focused primarily on promoting industrial technology innovation. Many were led by universities and public research institutes. Once scientific and technological progress was made, new technologies could be transferred smoothly from universities and public research institutes to industry through the alliances.

The second policy type relates to the reform of the National Science and Technology Plan. Industrial development projects that are funded under the Plan are required to include enterprises in the research and in the development of research agendas. Currently, enterprises participate in nearly 90 percent of projects under the Plan and lead nearly 50 percent of science and technology projects.

The third policy category establishes national technology innovation platforms or Innovation Centers to promote university–industry research cooperation on nationally strategic industrial technologies. The first center, the National High-Speed Train Technology Innovation Center, located at Qingdao City in Shandong Province, was established in September 2016. In the same year, the Ministry of Industry and Information began creating other National Manufacturing Innovation Centers to advance industrial innovation capacity. Nearly fifteen such centers were planned to be established by 2020.

The fourth policy category consists of science parks, which are an important tool for Chinese innovation policy (Reference Lai and ShyuLai and Shyu 2005; Reference Jongwanich, Kohpaiboon and YangJongwanich et al. 2014). In 1991, the State Council established the Torch Program, which accelerated the establishment of science and industry parks across China. The number of university science parks increased from forty-two in 2004 to 115 in 2014 (Torch Report 2016). These science parks offer various incentives to encourage investment and the formation of new firms:

• New firms are exempt from corporate income tax for two years.

• Licenses are waived for the importation of materials and parts used in producing products for export.

• Revenue from knowledge transfer is only taxable after the first CNY 300,000.

• Intangible assets such as intellectual property can be factored into a company’s registered capital.

• The science parks can provide professional intermediary services such as legal services, human resource management services, and marketing support.

Several studies have confirmed the contribution of university–industry research cooperation in China to universities’ revenue, firms’ innovative capacity and regional economic development (Reference Liu and ShiLiu and Shi 2009; Reference Ng and LiNg and Li 2009; Reference Yang and LingYang and Ling 2009; Reference Li, Ren and WuLi et al. 2010; Reference Kafouros, Wang, Piperopoulos and ZhangKafouros et al. 2015; Reference Fu and LiFu and Li 2016; Reference Hao, Pan and ZhaoHao et al. 2016).

Reference QuanQuan (2010) surveyed R&D laboratories in companies that interact with universities in Beijing. His results show that firms have different motivations that prompt different collaboration activities. The most frequently cited incentive for firms to collaborate with universities is to build a positive public image. In addition, companies sponsor research projects as a cost-effective way of keeping abreast of relevant new discoveries in China. Companies will outsource R&D to a university to reduce costs. But the most attractive factor for cooperation, according to the survey, is access to high-quality graduates. A large proportion of employees and interns in corporate R&D laboratories are graduates of partner universities. Reference Wang, Hu, Li, Li and LiWang et al. (2015a) conducted a survey on the factors that affect the success of academic–industry collaborations. They found that collaboration output was affected by not only the university’s reputation and research capability, but also by the breadth and depth of the collaboration.

8.4.1 The Technology Market

Recently, China has made great progress in developing its technology market. Based on information from the technology trading information service platform and Innovation Relay Center networks, China has established a unified and open platform to publish information about resources for knowledge transfer. In 2016, universities and public research institutes signed 90,573 contracts for knowledge transfer and research cooperation. The total value of these contracts was CNY 106.52 billion. Between 2009 and 2016, universities and public research institutes combined accounted for approximately 10 percent of the total value of knowledge transfer contracts (see Table 8.2).

There are several successful examples of the development of technology markets. The Xi’an S&T Market opened in 2011 and has facilitated knowledge transfer transactions worth more than CNY 110 billion, organized information exchange activities, and served more than 25,000 enterprises. The Zhejiang Online Technology Market, opened in 2002, uses network information technology and e-commerce technology to disseminate information on the supply of and demand for technologies. By the end of November 2013, Zhejiang Online Technology Market had 94,319 members, including enterprises, universities, and public research institutes; listed 63,944 technical problems from enterprises, and published 153,771 scientific and technological achievements. The number of signed contracts from the period of 2002–2013 amounted to 28,929, worth CNY 25.245 billion. The Online Technology Market has become an important platform for technology trading in Zhejiang Province.

8.4.2 University–Industry Research Cooperation

Reference Brehm and LundinBrehm and Lundin (2012) explored university–industry collaboration activities and innovation outputs in China between 1998 and 2004 involving 20,000 large and medium-sized companies. They found that Chinese universities’ revenue from knowledge commercialization activities has increased over time.

Reference LanLan (2006) categorizes research contracts between universities and public research institutes and companies in China into four types: contracts for technology development, knowledge transfer, technology consulting, and technology services. Among the four types of contract, technology development was the most common, accounting for more than 30 percent of the total contract value. Reference Liu and JiangLiu and Jiang (2001) discuss the methods obtained by Tsinghua University to pursue knowledge transfer since 1995, which include establishing a university–industry cooperation committee to provide services for member companies, setting up funding for collaborative research, and building an online information system to update research findings and enterprise requests. Reference Wang and MaWang and Ma (2007) researched how Tsinghua University dealt with the IPRs created through collaborative R&D projects with multinational companies. They describe four types of contract: (1) commissioned projects, in which an enterprise provides the research funding and the university conducts the research using its own equipment and manpower; (2) joint research projects, in which senior researchers from the university participate in the research and the enterprise provides research funding, equipment and engineers; (3) joint development projects, in which the university provides researchers and an enterprise provides equipment and engineers, with development funding coming from a third party; and (4) joint research organizations, in which both parties provide funds, equipment, and researchers.

The most recent data for 2015 show that universities and enterprises in China jointly performed more than 88,000 R&D projects for a total value of CNY 66.65 billion (Ministry of Science and Technology 2017). The universities and enterprises established 2,276 post-doctoral fellowships and 10,191 joint research institutions between them. According to the Ministry of Commerce (2015), by 2015, foreign firms had established more than 2,400 R&D laboratories in China. Many foreign firms established joint R&D programs, laboratories, training centers, technical innovation alliances, and so on with universities and public research institutes. These institutions play an increasingly important role in the Chinese innovation system, and an indispensable role in knowledge transfer.

8.4.3 Patent Transfer and Licensing

Scholarly studies have identified a positive correlation between government expenditures on science and technology at the provincial level and the number of patent licensing contracts held by local universities in the same region (Reference Rao, Meng and XuRao et al. 2013). This supports the efforts of provincial governments to fund local research capabilities and suggests that proximity may influence knowledge transfer in China, as found in the U.S. and Europe.

Reference Wang, Liu, Ma and ChenWang et al. (2015b) argue that licensing universities’ technologies can contribute substantially to the subsequent innovation performance of licensee firms. The more licensing activities a licensee firm performs, the greater its subsequent innovative performance.

The sale (assignment) and licensing of patents owned by Chinese universities has increased steadily. The number of patent ownership transfers and licenses grew from 1,810 in 2010 to 4,839 in 2016 (Figure 8.4), with a notable increase between 2014 and 2016 that could be due to the implementation of the 2015 PTSTA Law. The total value of transactions increased from CNY 359 million in 2010 to CNY 1215.43 million in 2016 (Figure 8.5), and the average transaction value increased from CNY 198,000 to CNY 251,000.

Figure 8.4 Number of patent transfers and licenses by universities, 2010–16

Source: China Statistical Yearbook on Science and Technology (2017)

Figure 8.5 Value of patent ownership transfers and licenses by universities, 2010–16 (million CNY)

Source: China Statistical Yearbook on Science and Technology (2017)

The total number of knowledge transfer agreements (including the sale or assignment of patents, patent licensing, and other non-patent-related knowledge transfer activities) showed a similar upward trend (Figures 8.6 and 8.7). The total number of knowledge transfer agreements by universities increased from 8,408 in 2008 to 10,517 in 2014 and the total annual value of transactions in the same period grew from CNY 3.05 billion to CNY 4.01 billion, with the average transaction value increasing from CNY 3.63 million to CNY 3.82 million (Figure 8.7). A comparison between Figures 8.4 and 8.6 suggests that non-patented knowledge transfer accounts for the majority of the agreements, which include contract research and consulting services. In addition, a comparison of Figures 8.5 and 8.7 indicates that non-patent-related knowledge transfer is a considerably larger income source for universities than patent-related knowledge transfer.

Figure 8.6 Total annual knowledge transfer agreements by universities, 2008–14

Source: Statistical Data of Science and Technology Activities in Colleges and Universities

Figure 8.7 Total annual value of knowledge transfer agreements by universities, 2008–14 (million CNY)

Source: Statistical Data of Science and Technology Activities in Colleges and Universities

Table 8.3 shows the patenting activities of the most important 1,497 universities in China in 2015. These universities applied for 109,445 invention patents, were granted 54,868 invention patents and signed 2,695 contracts involving patent transfer with a total value of CNY 2.77 billion. Over the period 2011–15, the total value of all types of knowledge transfer transactions exceeded CNY 19.6 billion.

Although universities and public research institutes have made tremendous progress in terms of knowledge transfer, they are still challenged by relatively low efficiency in terms of the amount of knowledge transferred per unit of R&D expenditure, understaffing and a lack of knowledge transfer professionals. The Patent Investigation Report (2015) surveyed 7,424 enterprises, 436 universities and 455 public research institutes in China. More than half of the surveyed universities and public research institutes categorized themselves as “carrying out basic research, obtaining a few patents” and that “patent licensing is limited” (Table 8.4). Approximately 25.4 percent of universities and 32.4 percent of public research institutes surveyed responded that they “carry out applied research, obtain many patents, and obtain revenue from patent licensing.”

Table 8.5 gives the “exploitation rate” for patents owned by enterprises, universities, public research institutes, and individuals, which is defined as the number of patents used to make, use, offer to sell, sell, or import patented innovations or being sold to others divided by the total number of patents. Table 8.5 shows a clear difference between universities, public research institutes, and enterprises. In 2014, the average exploitation rate of patents in force was 57.9 percent, but the rate among enterprises exceeded that average by approximately 10 percentage points. The exploitation rate of public research institutes was 16 percentage points lower than the average at 41.6 percent, while the rate for universities was only 9.9 percent. The low exploitation rate by universities (which includes patents that are only offered for sale) may be due to the low quality of patents, a lack of professionals specialized in knowledge transfer, and/or the lack of incentives to transfer technology before the 2015 amendments to the PTSTA Law.

The same study also provides data on the rate of patent sales and licensing (Tables 8.6 and 8.7), defined respectively as the number of patents sold or licensed divided by the total number of patents. This may be a better indicator of the use of university patents because it excludes patents that are only offered for sale and possibly never taken up. The results demonstrate the relatively low efficiency of knowledge transfer through patents by universities and public research institutes. In 2014, the average rate of patent sales was 5.5 percent. The rate of patent sales by enterprises and individuals exceeded 5 percent, while the rate of sales was 3.5 percent for public research institutes and 1.5 percent for universities. The average rate of patent licensing was 9.9 percent. The rates of licensing by enterprises and individuals were equal to or slightly higher than the national average, compared to 5.9 percent for public research institutes and just 2.1 percent for universities. The total of patent sales and licensing rates is only 3.5 percent for universities (suggesting that only 3.5 percent of university patents were taken up by companies), but considerably higher for public research institutes, at 9.4 percent.

Reference Tan, Liu and HouTan et al. (2013) studied patent licensing contracts signed by Chinese universities in 2011. There were 1,359 licensing contracts involving 1,352 university patents, of which 1,202 (88.4 percent) were invention patents. Most licensing contracts were exclusive, and licensed patents were mostly for inventions in the field of chemistry (organic chemistry, polymers), physics and instruments. Additionally, only 10 percent of Chinese universities had licensing activities, and most were affiliated with the 211 Project. Other universities, which received less government financing and support, cannot be compared to 211 Project universities in terms of patenting activities. Most licensees were enterprises and were located in the eastern regions, including Shanghai, Jiangsu, and Guangdong provinces.

8.4.4 Science Parks

In 1988, the first Chinese national-level science park was established in Beijing, which is the predecessor of the Zhongguancun Science Park. After thirty years’ development, the number of national-level science parks had increased to 168 by the end of 2018. By the end of 2017, the gross domestic product produced within the national-level science parks amounted to CNY 9.52 trillion, accounting for 11.5 percent of the Chinese total GDP. In 2017, there were 52,000 high-tech companies operating in the 168 national-level science parks, 38.2 percent of the national total. Half of the incubators and “maker spaces” are located in national-level science parks (Reference ZhangZhang 2018).

Reference Zou and ZhaoZou and Zhao (2014) discuss a typical university science park in China, TusPark, which is tied to the top university in China, Tsinghua University. TusPark is considered to be part of the Zhongguancun High-Tech Science Park (the first and largest cluster of semiconductor, computer, and telecommunications firms in China) and therefore enjoys many preferential policies thanks to the established relationship between Zhongguancun High-Tech Science Park and the government. However, TusPark has its own strategy and preferences. For example, bolstered by the university’s reputation and research capacity, TusPark is home to joint R&D laboratories between Tsinghua University and world-renowned enterprises.

Reference TanTan (2006) and Reference Todo, Zhang and ZhouTodo et al. (2011) studied the evolution and achievements of Zhongguancun Science Park. Reference TanTan (2006) argues that the Zhongguancun Science Park has been an example of innovation driven by knowledge transfer from leading research institutions to companies. Groups of professionals acted as risk takers and were involved in an early experiment to establish non-state-owned firms in the region. Reference Todo, Zhang and ZhouTodo et al. (2011) emphasize the role of science parks as an efficient channel to promote technology diffusion from multinational enterprises to domestic firms in China. As Reference Todo, Zhang and ZhouTodo et al. (2011) note, Zhongguancun Science Park has become a cluster of R&D centers for multinational enterprises. By the end of 2005, forty-three of the top 500 corporations worldwide had located their R&D centers in the Zhongguancun Science Park, and most of them had a collaborative R&D laboratory with local universities.

Reference Cai and LiuCai and Liu (2015) discuss another successful university science park, Tongji University Creative Cluster. It is separate from Zhangjiang Hi-Tech Park in Shanghai, which is the state-level high-tech park in Shanghai, hosting many high-tech manufacturing firms just as Zhongguancun Science Park does in Beijing. Playing to the advantages of Tongji University and the characteristics of the enterprises in the cluster, Tongji Creative Cluster targets startups active in knowledge-intensive services. Once these startups become larger and mature, they may be integrated into the Zhangjiang Hi-Tech Park.

A few studies provide evidence regarding the contribution of science parks to knowledge flow and regional innovation capacity. For example, Reference Jongwanich, Kohpaiboon and YangJongwanich et al. (2014) used a provincial-level panel data set over the 1997–2009 period to study links among firms, public research institutes, and science parks. They found that science parks had a significantly positive impact on regional innovation capacity in terms of various measures, including a positive innovation-enhancing effect from R&D cooperation between industries and universities.

9.3.1 Policies for Public Research

The public research sector in all countries has multiple goals, commonly consisting of training individuals in useful skills, including the ability to absorb, understand and replicate leading-edge knowledge produced abroad, providing assistance to industry, and producing new discoveries, some of which may have commercial applications.

The DST is not directly responsible for higher education, but has developed mechanisms to boost university research capacity, including the Researcher Rating Scheme, the 200-strong SA Research Chair Initiative, sixteen Centres of Excellence and five Centres of Competence. These receive generous funding and entail a mix of open and directed selection. The National Research Foundation implements these programs, and, in the case of the last three, requires beneficiaries to report on industry and community impacts. In addition, there are a large number of industry-endowed professorial positions (chairs) in mining, engineering, and agricultural sciences as well as chairs funded by state-owned enterprises in roads, water, and telecommunications.

To provide necessary skills, the DST invested heavily in the universities, as well as in the CSIR, the National Facilities and the National Research Foundation. Between 2010–11 and 2014–15, the number of researchers at universities increased by 36.5 percent, from 32,571 to 44,457, compared to a small decline at public research institutes.Footnote ³

The CSIR had a history of “knowledge transfer” through organizational development and transfer (Reference BassonBasson 1996), but its effectiveness declined in the 1980s, leading to a restructuring during the 1990s around strategic business units.

The Higher Education National Funding Formula allocates baseline funding to universities and includes a “publication output” variable that supports science (essential for understanding advances in knowledge) through funding for approved types of publication. This provided funding of ZAR 3 billion (approximately USD 250 million) in 2016.

The Innovation Fund provided competitive funding for research with commercial applications. It initially allocated three-year grants for predefined research areas and encouraged knowledge sharing by prioritizing awards to consortia of universities, science councils, and industry. This restriction was subsequently eased so that any research proposal with commercial applications could be supported. As of 2009, the Innovation Fund was merged into the new Technology Innovation Agency.

Innovation Fund projects that resulted in successful commercialization include microwave technology for egg sterilization and the Smartbolt^TM rock stress detection device. A costly but unsuccessful project was the Joule electric vehicle, abandoned after the prototype failed to elicit funds for production.

Other publicly funded ventures included four Biotechnology Regional Innovation Centres, structured as single-purpose not-for-profit companies. The combined funding for the Innovation Fund and the Biotechnology Research Centres was approximately ZAR 300 million (± USD 30 million) per year. No evaluative study is available on the contribution of the Innovation Fund or the Biotechnology Research Centres to measures of potential commercial outputs such as IP, startups, or job creation.

The South African Research Chairs Initiative was established in 2006 by the DST and the National Research Foundation with the goal of expanding the research and innovation capabilities of South African universities by attracting and retaining high-quality researchers and increasing the output of master’s and doctoral graduates. The initiative has been successful in fostering cutting-edge research, retaining skills in the country and contributing to the stock of doctoral graduates (Reference Fedderke and VelezFedderke and Velez 2013).

9.3.2 Policies for the Business Sector

From a systems perspective, policy should improve the innovative capabilities of firms. This often takes the form of subsides to encourage firms to invest in capability-building activities such as R&D or to provide skills that would otherwise not be provided by the market. To support firm capabilities, the South African government provides an R&D tax incentive that is designed to boost private sector R&D spending (DST 2015b). Firms initially filed a post hoc claim that would be verified by the DST, but this system was open to misuse. After four rounds, it was replaced with a preapproval model that required detailed submission of the intentions and expected outcomes of corporate R&D. This process appears to have deterred many would-be applicants, particularly SMMEs (small, medium, and micro-enterprises), reflecting a tension between a user-friendly incentive regime and company willingness or capacity to engage in a detailed submission process.

The government has used industrial policy to correct market failure, such as the National Foundry Technology Network to provide skills training, knowledge transfer, and diffusion of state-of-the-art technologies. The 2015–17 iteration of the industrial policy aims to strengthen “linkages between knowledge production, utilisation and innovation and industrial growth” (DTI 2015: 69). The Industrial Policy Action Plan supports R&D-led industry development programs for titanium metal powder manufacturing, fuel cell development, and additive manufacturing. All three are focal areas of the Ten-Year Innovation Plan (DST 2008).

An agency of the DTI, the South Africa Bureau of Standards Design Institute, seeks to use “the broad nature and bridging capacity of design to address the existing innovation chasm by linking R&D with the user, the market, the social environment for the benefit of the country’s socio-economic growth.” To this end, support is given to SMMEs and individuals to move from idea to prototype. The Institute has set up the Transnet Design, Innovation, and Research Centre for SMMEs to research and develop innovative and commercially viable ideas. This is largely a private-to-private knowledge development channel that partially involves universities and public research institutes, for instance, for micro-satellite development.

9.3.3 Policies to Support Linkages between Public Research and Businesses

A common assumption is that the public research sector in South Africa is failing to transfer knowledge with commercial value to the business sector. For example, the annual surveys of the Global Entrepreneurship Monitor (GEMS 2016) find that South African experts believe that universities are not playing a sufficiently constructive role in facilitating knowledge transfer and stimulating innovation. This next section examines the possible causes of low rates of knowledge transfer from the public research sector to firms and then describes policies aimed at addressing those causes.

Failures in Knowledge Transfer

There are two main potential causes of failure. First, the public research sector could be producing very few discoveries with commercial applications. This could occur as a result of a failure in the design of the public research sector, for instance, if there are few incentives for academics to conduct research of potential commercial value (Reference Zhang, Goldberg, Kaplan, Kuriakose, Goldberg and KuriakoseZhang et al. 2011) or to take part in knowledge transfer activities. Reference Sibanda and KaplanSibanda (2009) identified an absence of an entrepreneurial culture among researchers at public research institutes, while Reference Goldberg and KuriakoseGoldberg and Kuriakose (2011) found that insufficient attention was given to the needs of startups, especially business services and IP management. In a study of university research centers, Reference CooperCooper (2011) argued that knowledge transfer was problematic as long as universities focus on “own” research, rather than committing to use-inspired basic research, even though there was strong evidence that research group survival and use-inspired research (on the MIT and Stanford models) went hand in hand. In other words, the nature of the research was a strong determinant of its future commercial value, resonating with similar results in studies by Reference Fedderke and VelezFedderke and Velez (2013) and the National Research Foundation (2016) . Reference Kruss, McGrath, Petersen and GastrowKruss et al. (2015) claim that a policy emphasis on “Big Science, knowledge transfer and the growth of niche competences and capabilities” has created “islands of innovation,” but prevented the widespread diffusion of public research knowledge to industry. The consequence is large variation by sector in the relevance of public research to industry.

Second, the public sector could be producing commercially valuable outputs that are not taken up by firms for a number of reasons: lack of communication between the public and private sectors (network failure), a shortage of funding to support the activities of firms to develop discoveries into commercial products or processes (finance failure), or public research discoveries not meeting the requirements of firms, particularly if firms lack the internal capabilities to exploit them (demand failure).

Reference KrussKruss (2008a) found very few new knowledge networks in evidence in South Africa’s research-oriented universities. The capacity and desire on the part of industry to forge research and innovation partnerships were generally limited. In a subsequent study, Reference KrussKruss (2008b) argues that the lack of commercialization of research arises from a combination of network failure and a lack of “interactive capability” with industry.

Reference KahnKahn (2006, Reference Kahn2013, Reference Kahn2016) identified the influence of the linear innovation model on policy (instead of an innovation system model) as underlying poor performance in knowledge transfer. Ideographic research based on case studies in South Africa found that poor performance is partly due to a lack of two-way communication between public research and firms. Instead, there is implicit adherence to a linear model of innovation whereby scientists follow their own research interests, often in basic research such as the Square Kilometre Array radio telescope. This is reflected in the high proportion of South African gross expenditures on R&D (GERD) for basic research, currently standing at 26.7 percent. Although “blue sky” research can, over time, result in commercial products or processes, such research is rarely of short-term value to firms. Reference Zhang, Goldberg, Kaplan, Kuriakose, Goldberg and KuriakoseZhang et al. (2011: 14) noted that the influence of the linear model was made worse by the fact that the DST was a science-driven organization whose staff had little knowledge of industrial practice.

Reference De WetDe Wet (2001) introduced the idea of the “technology colony” to explain low rates of knowledge transfer in South Africa. This idea became known as the “innovation chasm” due to a lack of funding (finance failure) for early-stage commercialization. Reference Zhang, Goldberg, Kaplan, Kuriakose, Goldberg and KuriakoseZhang et al. (2011) question the reality and utility of the construct of an innovation chasm and suggest that the problem could be due to demand failure, arguing that policy gave insufficient attention to strengthening the absorptive capacity of firms. Reference KaplanKaplan (2011) used patent data to show that mining equipment was the only industry where local expertise was at the technology frontier. Reference Phaho and PourisPhaho and Pouris (2008), in a study of original equipment manufacturers (OEMs) in the automotive sector, determined that most OEMs failed to take steps to improve their capabilities. They did not conduct in-house R&D, did not engage in innovation activities that were new to the market, and did not use government incentives to improve their competitiveness through technology diffusion or intelligence. Reference Fongwa and MaraisFongwa and Marais (2016) studied knowledge transfer in a developing region of South Africa and found that the rate at which knowledge was transferred through the available channels was strongly influenced by the absorptive capacity of firms.

9.4.1 Informal and Contractual Knowledge Transfer

South African automotive OEMs mainly rely on universities as providers, where needed, of highly qualified personnel, rather than as partners in use-oriented research collaboration that could upgrade their technological capabilities (Reference KrussKruss 2008b).

In the “low” technology wine sector, Reference Cusmano, Morrison and RabelottiCusmano et al. (2010) found that the relationships between industry and public research were based on a mix of informal contacts and industry-commissioned research. Reference Kruss, Visser, Aphane and HauptKruss et al. (2012) reported that most academics interact with the outside community through traditional mechanisms such as training and capacity development, conferences and workshops, action research, contract research, demonstration projects, and services. Consultancy and entrepreneurial engagement was less common, informal, indirect, and not knowledge-intensive. From the industry side, there was low demand for knowledge from, or direct cooperation with, universities on the part of larger innovating firms, but stronger demand from a smaller number of R&D-performing firms.

9.4.2 IP-Mediated Knowledge Transfer

In the six years prior to the promulgation of the Public Research IP Act in 2008, Reference KaplanKaplan (2009) found that there was a dearth of economic studies on the IP system and low awareness of the value of knowledge transfer to the resource industries. IP activity between 2001 and 2007 was low, with only twenty-one patent-based startups produced by the public research sector. Reference Alessandrini, Klose and PepperAlessandrini et al. (2013) note that formalized knowledge transfer is still emerging in local universities and public research institutes.

A case study of three firms active in the southern node of the telemetry sectoral system of innovation (Reference KahnKahn 2014) found that two firms made extensive use of government innovation incentives, while one maintained independence. The case studies show the initial importance of mentorship and academic research to the startup pioneers. As the companies matured they shifted their search for knowledge exchange toward their own value chains. This autonomous behavior accords with the international pattern revealed through innovation surveys.

In a study of the patenting activity of academics, Reference Lubango and PourisLubango and Pouris (2007) concluded that most academic inventors or co-inventors had prior experience with firms or state-owned enterprises. Reference Rorwana and TengehRorwana and Tengeh (2015) surveyed thirty-six academics with research projects with industry and employed at a single university of technology to identify the effect of different factors on their participation in commercialization activities. They report that the personal interest of the academics in innovation had the largest effect on their participation in commercialization activities. No results were reported on the use of IP.

9.4.3 Case Studies

Four case studies (see Box 9.1) of sectoral innovation systems show that the main channels for knowledge transfer in South Africa are informal methods and research agreements. The case studies are based on desk research and interviews.

The four case studies fall into two groups. The first two, on oil and gas and platinum group metals, display similar hub-and-spoke models with universities, with the main companies (Sasol and Anglo-American Platinum) forming the hubs. Interviews revealed that neither company relied on the flow of research information from universities for its core business. The other two cases, for pulp and paper and viticulture, resemble triple helixes, with universities, companies, and government contributing to research of commercial value. None of the cases exhibits demand-led characteristics; all are supply-side driven, although capacity development is an important goal.

Reference Breschi, Malerba, Breschi and MalerbaBreschi and Malerba (2005) stress the importance of networking and other forms of knowledge exchange in sectoral innovation systems. They note that these systems evolve organically and cannot easily be developed through government fiat. Sasol was a state initiative, although its evolution into a research-led organization was driven internally. Including the Centres of Competence within a sectoral system seems to be left to an evolutionary process.