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AND THE ROLE OF SCIENCE
IN ECONOMIC DEVELOPMENT:
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Finally, since the goal of a science park is to promote economic growth, attention must be given to the knowledge capital associated with economic growth, which is much more than the knowledge created in and around universities and science parks.
The following sections present, first, the relevant theory, including the notions of spillovers, compe-tence bloc and the experimentally organised economy. Second, the creation and diffusion of industrial knowledge are described, with academia placed in the broader context of scientific, engineering and industrial knowledge creation. Third, the science park is introduced in the context of a competence bloc, and the policy problem is defined. Finally, some cases are examined and conclusions are drawn.
Spillovers, competence blocs and economic selection
It has long been thought (e.g.Nelson, 1986; Jaffe, 1989) that scientific principles, elaborated in uni-versities and engineering schools, contribute to industrial progress as they are converted into engineer-ing applications. Some suggest, however, that scientists and university engineers do little more than encode the principles of existing applications (innovations). Others argue, in fact, that a university envi-ronment is not creative enought to support truly innovative discovery. Hence, new business ideas should be sought in experimental environments, where actors have to be innovative to survive. As new empirical studies tend to support this view, an important part of this analysis will be to give science and the uni-versity a documented role in industrial development.
From technology to industrial spillovers
A quick glance at the realities of new industry formation (Eliasson, 1995; 1996b; 1997b; 1997c) reveals that spillovers are industrial rather than technological. To reach the stage of successful industrial appli-cation, a new technology is filtered through a competitive market process which involves complex com-petencies. It should be noted that the studies reporting strong and significant technological spillovers are based on instances where such competitive screening has taken place. They do not support the idea that expanding resources to science and new technology development will automatically enhance indus-trial competitiveness and technological development. Rather, attending to the process of economic fil-tering may be the most efficient way to put industrial life into dormant innovations in academia or business. This is a matter of institutional policy.
The competence bloc
The competence bloc is the configuration of actors that initiates and stimulates the growth of an industry. They are: competent and active customers, innovators who integrate technologies in new ways, entrepreneurs who identify profitable innovations, competent venture capitalists who recognise and finance entrepreneurs, secondary markets which facilitate ownership change, and industrialists who take successful innovations to industrial scale production (Eliasson and Eliasson, 1996). A competence bloc is defined in terms of end results, a bundle of functionally related products in the market, not in terms of technologies or physical inputs,1 and its dominant function is selection of winning technical and eco-nomic solutions. This selection involves joint minimisation of two errors: allowing losers to survive too long and rejecting winners. Under such circumstances the competence bloc will develop faster than the sum of outputs of its constituent actors.
A minimal critical mass and variety is needed before a competence bloc becomes self-propelling.
The policy problem is whether policy catalysts can initiate a competence bloc and/or induce it to reach critical mass faster as well as whether such catalysts can be found in the science community.
The innovative nature of the output selected and produced within the competence bloc is limited by the competence of the customers. Competent customers are always present in innovative and advanced industries. The innovator integrates different (new and old) technologies in an innovative way.
The entrepreneur searches actively for and identifies commercially viable innovations and prepares them for market entry.2 The entrepreneur needs financing from understanding and competent venture capitalists who provide risk (equity) financing at reasonable rates. Reasonable rates require a venture
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capitalist able to understand the business proposed; such venture capitalists are extremely rare when the innovation is outside the technology range of traditional industry (Eliasson, 1997e). The venture cap-italist in turn may want to exit his investment at a good return, so that a functioning secondary (initial pub-lic offering – IPO) market is necessary. Finally, industrial competence is needed to move the invention to industrial-scale production and distribution. This entire chain of competent actors is necessary to create a viable new industry, and the industrial knowledge of the actors at each step is part of the competence specification. Together, they create the potential for increasing returns to innovative and entrepreneurial activity that characterises the experimentally organised economy (Eliasson, 1991). All actors in the com-petence bloc must be involved, and there must be a well-structured property rights system (Eliasson, 1998) which minimises the risk of predatory imitation (patents, copyright).
To summarise, the competence of the actors determines the quality of the selection. Incentives are determined within the competence bloc and depend on the presence and competence of all actors.
Competition is determined within the competence bloc and depends on the number, variety and char-acter of actors, in short the successful selection of winners.
The question of whether innovations are mainly supply/technology-driven or customer/demand-induced has long been debated. Ultimately, of course, all innovations are customer/market-tested, and technological innovations that lack customer value fail. Customers may induce innovations, and there is presumably then a market. If, instead, innovations arise spontaneously from technical change, they require that the actors in the competence bloc have the necessary incentives and can engage freely in “technolog-ical” competition to bring the innovation to the market. The variety and number of actors (due in part to incentives) determine the ability of the system to identify rather than reject winners. A steady flow of win-ners determines the level of competition that forces incumbents to reorganise or rationalise and inferior firms to exit. The question then is whether a model that integrates these actors is sufficient to explain new industry creation, or if some other externality, call it “culture”, is needed.
Experimental organisation and growth via competitive selection
The search for innovations is linked to the notion of a non-linear economy with phases of unpredict-able behaviour, the extent of which depends on the organisation of the economy, the variety of its knowl-edge base, incentives to search and the intensity of competition. The organisation of the competence bloc defines the nature and variety of the knowledge base and the investment opportunity set.
In the vast, non-transparent competence bloc of a successful industry, no actors are safe from devas-tating competitive entry into their markets. Incumbent firms constantly have to take precautionary action (through reorganisation and rationalisation) in anticipation of unpredictable competitive entry or risk business failure and exit. Therefore, other incumbent actors are forced to become more competitive and force exits. As a result, economic growth in the experimentally organised economy takes place as com-petitive selection through the four growth mechanisms: innovative entry, reorganisation, rationalisation and forced exit (Eliasson, 1996a, p. 45).
Ideally, a theory would be needed that captures the dynamics of reorganising production across the boundaries of existing firms through mergers and acquisitions (M&A). So far, however, no such theory exists. The model of growth through competitive selection or the experimentally organised economy makes it possible to: i)identify roles for science and the policy maker in the endogenised growth process;
and ii)characterise differences in these roles for different industries. What role does each play in the new industries developing through competitive entry such as information technology (IT) or biotechnology, on the one hand, and in the reorganisation of existing mature industries such as advanced engineering, which face intensified competition at their low performance end, on the other?
How are spillovers (competence) diffused?
The diffusion process from sources of spillovers (technical universities and advanced firms) follows four main paths: movement of competent personnel; establishment of new firms by entrepreneurs leav-ing other firms; learnleav-ing from and by subcontractors; and learnleav-ing from technological leaders. The first
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two paths are the most important. If the labour market does not work well and the conditions for entre-preneurship are not well developed, there is likely to be little formation of radically new industries. Tech-nology diffusion through subcontracting networks and simple imitation belongs more to mature industries with an established and fairly well-known body of knowledge, notably engineering industries.
In the aircraft industry, the second and third paths dominate, while in the computer and communication (C&C) industry the first and second are the most important.
For the creation of radically new industry, the competence bloc’s entire selection process is needed.
Special attention is drawn to the need for a viable, varied and competent venture capital industry, which is missing in many industrial countries, notably in Europe, so that there is little entrepreneurship outside existing industries (Eliasson, 1997e). The main competence function of venture capitalists is to identify and understand entrepreneurial winners such that they dare to supply finance at reasonable costs (Eliasson and Eliasson, 1996) Public risk capital, which is influenced by political decisions, tends to be incompetent in this kind of selection process.
In sum, putting dormant technology to work in commercial and industrial applications requires involving the entire selection process of the competence bloc so that channels of diffusion become func-tional. This, in particular, requires entrepreneurship close to advanced firms and academia and a labour market for competent people. Often supporting policy changes to remove barriers to change (deregula-tion) are needed.
Knowledge creation and diffusion
The sources of industrial and scientific knowledge are usually not the same. Science does not nor-mally concern itself with the commercial value of its discoveries. It builds knowledge, which sometimes becomes a technology. For innovative technical knowledge to become industrial and commercially via-ble, the other actors of the competence bloc have to be brought in. The economic filtering of technical innovations, in particular, is critical for the business application and success of scientific knowledge and technology.
The firm as a technical university
Once the presence of technological spillovers from advanced firms is recognised, the latter can be viewed as technical research institutes or universities (Eliasson, 1995; 1996b; 1997c). The empirical evi-dence is overwhelming. Almost the entire US IT and communications industry has been founded on spill-overs from firms (Eliasson, 1996a). To discuss industrial knowledge creation, it has to be understood how successful innovations are filtered through the economic system and surface in the form of new industry creation and how less successful innovations are sorted out and discontinued. This takes place within the competence bloc.
Five different types of production draw more or less directly on scientific knowledge. It is particularly interesting to clarify the differences between industries developing through new entry and exit and industries growing through reorganisation and rationalisation.
First, there is mature production which is potentially in crisis, exemplified by engineering industry, a mature industry with technological roots in the industrial revolution and the industrial backbone of the industrialised world, notably in Europe and Japan.
Second, there is new entry production exemplified by two sectors. One is the C&C industry, a new, well-established, but still rapidly innovating and expanding industry, and a technology which has dramat-ically reshaped the industrial landscape over the last couple of decades. The second is the the biotech-nology and health care industry, in its modern form an industry with great potential and firmly based in science.
Third, there is infrastructure production, again exemplified by two sectors: one, the financial ser-vices industry, an old industry which has been completely restructured owing to C&C technology; and second, education and research, an old, academically based industry in need of product innovation and reorganisation.
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The engineering industry has been innovating for two centuries. Its knowledge base is dominantly organisational. Its leading firms engage in large-scale production, often in global distribution, and excel in integrating advanced mechanical technology, information and communications technology and new materials, most of which are developed in engineering firms. The engineering industry does not use highly educated workers extensively, except for particular applications such as advanced engineering computation and new materials development.
Advanced engineering product development, manufacturing and distribution embody a dominant organisational technology designed to integrate a number of diverse technologies. This integrated tech-nology, which is developed gradually, is holistic and largely experience-based. While its various compo-nent specialities can be taught in classrooms, crucial holistic capacities, such as those embodied in design teams in the aircraft industry, are developed and transferred on the job. Since the aircraft industry already uses the technology of future engineering industry, its engineers are attractive in the labour mar-ket (Eliasson, 1995).
The C&C industry increasingly has the same organisational technology as the engineering industry, but it also advances by breakthrough specialist technologies which have revamped the entire industry, as demon-strated by the five generations of computing, the last of which, with the merging of computing and communi-cations, is largely organisational.3 All of these specialist technologies were developed in industry laboratories4 and commercialised in new firms. Paradoxically, this industry is based almost entirely on indigenously gener-ated technology (Eliasson, 1994a; 1996d). It does not make particularly intensive use of highly educgener-ated people, but it has been extremely innovative and entrepreneurial.
Biotechnology is firmly based in new scientific discoveries and has obtained new technology directly from academia. Biotechnology in particular makes intensive use of highly educated people (Eliasson, 1994; 1996d).
The financial services industry constitutes a fourth production category because it is a pure service industry, because its product technology has been designed in academic settings, because it has been radically restructured through the use of C&C technology, and because its reorganisation is forcing radical change in the global economy. It uses highly educated people fairly intensively.
The education industry, of course, makes the greatest use of highly educated people. While most of it is in public domain and protected from competition, it is a very large industry; in Sweden in 1991, it represented more than 20% of total resources.5 As it is gradually being opened up through privatisation, not least through more education on the job, it is becoming an increasingly important industry.
The role of academia in science-based industry
While science thrives on specialisation, industry thrives by integrating specialist technologies into technologies with a potential for industrial and commercial application. Also, industry thrives on organi-sational competence, something that is not particularly characteristic of academia. While the business manager works through other people, academics do not particularly appreciate being managed (Eliasson, 1996d). As a consequence, the two environments have very different traditions and attitudes to work.
There are few instances of academically developed technologies that have formed the basis for busi-ness. The biotechnology industry is a notable exception, the only genuinely science-based industry based on entrepreneurship around academic laboratories (Eliasson and Eliasson, 1996; 1997). The aca-demic and industry laboratory environments in biotechnology are very similar, and scientists move rather freely between academia and business. It is still unclear whether this “exception”, which is rapidly becoming a big industry in the United States, depends on the technology or whether we are witnessing the first stage in the formation of a new industry. While the role of academia in engineering and the C&C industry is to furnish educated graduates, biotechnology is based on entrepreneurship linked to aca-demic discoveries and a political and acaaca-demic system that supports entrepreneurship. Silicon Valley stands as an example of a competence bloc with all the necessary actors actively contributing to the com-mercialisation of scientific discoveries.
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The standard academic story is that the role of the university in spillovers is the research it produces.
This is not true. Academic research rarely reaches industrial laboratories; the main role of academia for industry has been teaching.
The role of science parks in economic growth
New industries like biotechnology which draw directly on academic research will become increas-ingly important. Industrial laboratories will increasincreas-ingly recruit academically trained staff with a doctorate and research experience to develop their most advanced technologies, i.e.those in which wealthy indus-trial nations have to excel to remain competitive. This will mean a radical overhaul of existing attitudes, organisation and practices in western universities (Eliasson, 1994; 1996d). Many studies, furthermore, have observed a strong skill bias in technological change which will require support of education and possibly academic research (Eliasson, 1987b, 1994b; Berman et al., 1997).
Science parks
Science parks are fashionable in industrial policy discussions, as a means of creating jobs and, per-haps, exports, and more recently with the express purpose of creating technological spillovers to support long-term economic growth. They are called “industrial parks” or “technological incubators”, thereby sig-nifying a more or less “scientific” or “industrial” orientation. However most are predominantly “technical”
in orientation, and insofar as industry creation and economic growth are the goal, the prerequisites for success described above are typically missing.
The regional dimension
The literature on science parks focuses on the physical and geographical dimensions, thereby unfor-tunately ignoring important economic factors. Innovations or new technologies are often assumed to dif-fuse mechanically along a direct path. The definition of a science park, as formulated by the European Commission’s Directorate General XIII, appears to be widely used, not least in Sweden: “A science park is normally a development project involving a site which: is in physical proximity to or has operational links with one or more institutions of higher education or centres of advanced research; is designed to encourage the formation and growth of knowledge-based firms; facilitates, through active intervention, the transfer of technology from the research and academic institutions on site to the firms and organisa-tions based on the park or its surroundings (Sprint Programme DGXIII).” A competence bloc may coincide with a region. This would be the case if Bavaria and Schwaben (Munich and Stuttgart) were only special-ised in making luxury cars, but this is not the case. Bavaria also has the German C&C competence bloc, while Silicon Valley has the world’s dominant C&C and biotechnology competence blocs. While geo-graphical proximity matters (Mercedes, BMW, Porsche, Audi and Bosch are all within commuting dis-tance), the integration of technology and competence increasingly occurs over large distances via C&C technology, and the more so the closer the activity to standardised industrial-scale production and dis-tribution. Virtual reality is, in fact, rapidly becoming an industrial reality. A geographical or regional defi-nition of a competence bloc or an industrial park shuts out awareness of various important aspects by assumption.
The rationale for a science park is its organisation as a source of spillovers (externalities). Such spillovers may, however, be dormant and need to be activated. Entrepreneurs to put them to industrial use may be lack-ing. Hence, a science park is best viewed as an “intermediator” between academia and industry with respect to technical or other services produced in academia. It must cover the entire competence bloc to complement the competencies academia lacks. Many of its tasks require business knowledge and experience.
Strategic or spontaneous spillovers
A distinction should be made between deliberate (planned or strategic) and spontaneous spill-overs. By definition, a science park embodies a strategy to support the generation of spillspill-overs. It is a currently fashionable policy to commercialise the technology in a stagnant defence industry. However, it
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is questionable whether strategic spinoffs can be “better” than spontaneous ones. They have often failed dramatically. The issue is whether the best practice is to improve conditions for spontaneous spillovers or to try to select and commercialise particular technologies: “picking winners”. On the basis of the argu-ments advanced here, it is much more efficient policy to ensure that all actors in the competence bloc are present rather than to encourage and/or support particular industries or to attempt to commercialise particular technical innovations.
Spillovers and economic growth
To link academia and the science park to economic growth, it is necessary to recall the four funda-mental mechanisms of economic growth: innovative entry, reorganisation, rationalisation and forced exit.
The table below identifies the principal role of a science park as an intermediator between academia and technology diffusion mechanisms.
The European Commission’s definition of a science park is inappropriate if the purpose of the sci-ence park is to function as a catalyst for economic growth. It is too technical and too physically and geo-graphically defined. To be economically meaningful, the science park has to be more broadly defined to include all the actors and institutions of the competence bloc.
Case studies
The best way to give credibility to the argument presented above is to support it by case studies.
These are taken from the engineering industry, from C&C technology, from biotechnology and from finan-cial services. Two, Kockum’s off-shore systems and helium recycling in the United States, have not been reported elsewhere and are described in greater detail.
Mature industry, possibly exiting production The aircraft and submarine industry
Aircraft and submarines have a very long life,6 are very complex and are developed and manufac-tured under very complex circumstances. Today, aeroplanes or submarines cannot be designed, devel-oped and manufactured in a single firm. Production is subcontracted via the market; its organisation is often called integrated production (Eliasson, 1995; 1996b). Integrated production requires a holistic approach, and the productivity potential depends largely on choosing the right organisational mix. Since aeroplanes are modernised at least two or three times over their life cycle, a designer who allows for easy repair and modernisation makes the product cost-efficient over its life cycle.
The aircraft and submarine industry, furthermore, are top integrators of advanced forms of three technologies: mechanical technology, electronics and new materials. The organisational and technologi-cal integration in the production of large, complex long-lived products stands at the top of the engineer-ing industry technology; it has been developed and implemented in advanced firms, not in academia.
The complexity of the integration, furthermore, makes it virtually impossible directly to imitate success-ful solutions. Both advanced competence per se and the relatively satisfactory protection from easy imi-tative competition suggests that the advanced industrial countries will orient their production in this
“complex” direction. This means that the role of advanced engineering firms as a university in terms of
Role of universities Role of science park Channels of diffusion/Role of government
Supply of educated and talented people Functioning markets for competence
(“labour market”)
Supply of research results Intermediary Institutions (incentives): patents, imitation University entrepreneurs
(new establishment)
Functioning competence bloc