Introduction to the Theme Issue
Loet Leydesdorff *,1 Philip Cooke,2 and Mikel Olazaran3
Regions can be considered as "regional innovation systems," but the question of whether and to what extent technology transfer is taking place at this or other (e.g., national and global) levels remains empirical. The theme issue contains a number of case studies of "regional innovation systems" within the European Union. Other papers elaborate on the pros and cons of the systemic approach to the technology transfer processes involved, or make comparisons across regions. In this introduction, the editors discuss the relations between regional policies, technology and innovation policies, and the integration of these different aspects into (potentially regional) systems of innovation. Under what conditions can "technology transfer" be considered as a mechanism of integration at the regional level?
keywords: development, technology, region, innovation, system
During the so-called "oil crises" of the 1970s it became apparent that advanced industrial systems can add value to their products and processes only by using their knowledge base. The realization of these competitive advantages—in comparison to so-called "low-wage" countries—required a structural adjustment of the knowledge infrastructure (OECD, 1980; cf. Freeman and Soete, 1997). For example, the institutional divides between public and private and between academia and industry carefully constructed in the post-war period could no longer be considered as functional to science-based innovation policies. The expanding sector of higher education had to be fed back into the emerging "knowledge economy."
These new ideas, sometimes dubbed "liberal neo-corporatism" because of their emphasis of cross-institutional negotiations (Rothwell & Zegveld, 1981), met with resistance from established interests and prevailing ideologies largely organized along institutional lines. For example, the universities reacted by proposing technology transfer agencies. These agencies were at that time based on a linear model of innovation. The "linear" model of innovation proclaims that science is "basic" to its applications and that therefore only the diffusion of scientific knowledge towards its applications can be stimulated. The knowledge-producing unit is initially black boxed as a source of knowledge, and not made a subject of S&T policies.
When "technology transfer" is used with reference to innovation as a
process, a systemic question can be developed. Innovation is then considered
as an operator in a process of mutual feedbacks, from which new arrangements
can be induced. These arrangements may also require institutional reform
to a greater or a lesser extent. New technologies often require structural
adjustments at the level of the social system (Freeman & Perez, 1988).
Innovation: networks, trajectories, and clusters
Comparative studies of the period following the "oil crises" (mainly guided by the Organization of Economic Cooperation and Development, the OECD in Paris) have shown that advanced industrial nations, as systems of integration, found rather different solutions to what has been called the "differential productivity growth puzzle," that is, the integration puzzle generated by the differences in growth rates among sectors of a political economy (OECD, 1964; Nelson & Winter, 1975). These differences in growth rates can largely be explained in terms of technological traditions and the corresponding differences in the labour force across sectors and among advanced industrial nations (Nelson, 1982).
Nelson & Winter (1977) suggested that a useful theory of innovation should take into account that rigidities and trajectories tend to prevail in knowledge-based innovations. Engineers are inclined to use textbooks and to elaborate the dominant designs. This trajectory perspective focuses on the recursive terms in the non-linear model, while interactive terms have to be declared from the perspective of a national system’s integration (Mowery & Rosenberg, 1979; Kline and Rosenberg, 1986). How can the integration of a knowledge-based economy be enhanced? Obviously, the model has to take different sub-dynamics into account: the declaration of both interaction and recursion turn the non-linear model into a complex dynamics. "Innovation" can then be considered as a candidate for the progressive operation of this complex system.
Specific solutions of the production growth puzzle are embedded in national cultures that can be considered as the previous states on which change in the system has to build. Japan, for example, has achieved a high level of national integration since the war. The Japanese system has therefore been characterized as a "textbook" economy (Yamauchi, 1986). Different parties reach basic agreements about planning goals in negotiations orchestrated at the level of the Ministry of Trade and Industry (MITI). However, for cultural reasons the Japanese universities were not integrated into this national consensus. Thus, university-industry relations became central to government policies in the 1980s and 1990s (Fujikagi & Nagata, 1998).
The U.S.A., with its prevailing climate of non-intervention, emphasized the obligation of universities to apply for their own patents and to use their patent portfolios. This led, among other things, to the Bayh-Dole act of 1980. The European Union, perhaps more than its global competitors, has developed a network systems approach, also because the various national systems have wished to continue to pursue their own S&T policies in parallel.
The European Union is neither a nation state nor a federation of national states. In the network of relations among national governments, corporations, and other agencies densities can be constructed across boundaries. Within these networks of various partnership relations one may reach at certain points a level of consensus that makes it efficient to codify relations further at the European level. The European Commission and the European Parliament continuously seek possibilities to reinforce these complementarities within the networks, since further codification legitimates European regulation and legislation as a symbolic confirmation of emerging, that is, sub-symbolic, developments.
Two strands of activities have been particularly focal to the development
of the EU during the 1980s and 1990s. First, the so-called "Research, Technology
and Development" (RTD) networks were stimulated in a series of three-year
Framework Programs designed to create a science and technology infrastructure
across Europe. Second, regional development has been enhanced by so-called
"structural funds" intended to stimulate the cohesion in the economy of
the European Union by transferring substantial resources to so-called "less
favoured regions." While the first program was aimed primarily at the most
advanced parts of the European system using the idea of adding surplus
value by constructing knowledge networks across sectors and borders, the
latter program aimed to enable the poorer and less science-intensive regions
to participate more fully in these developments.
A "Europe of regions"?
The Single Act of 1986 emphasized science as a cultural heritage of Europe and as a means to promote European integration. In 1988, four advanced European regions—Baden-Württemberg, Catalonia, Lombardy, and Rhône-Alpes—concluded the so-called "four motors agreement," in which they claimed priority for regional innovation policies, thus combining the two rhetorics prevailing at the EU level. Might the relative weakening of the national state, which the process of Europeanization entails, provide leverage for regional aspirations in advanced economic systems? Could the relative success of Belgian regionalization in solving national and linguistic tensions provide a model for new forms of governance within the larger European framework?
Can regions function as innovation systems? (Oughton and Landabaso, this issue). If so, under what conditions would one expect this to be the case? Lundvall (1988) elaborated on Freeman’s (1987) notion of a Japanese "national innovation system" by stressing local user-producer relations as the main system of reference for the specification of innovations temporarily shielded from market pressures. The nurturing of these relations at the cultural level would, in his opinion, help to create niches in which innovative efforts could be incubated and developed to such a level that existing "lock-ins" in hitherto dominant technologies might be circumvented (Bruckner et al. 1994).
If the nation states, however, are no longer necessarily the single
frame of reference for these processes of integration, can a region then
be a candidate? Note that this assumption is merely hypothesized: does
the region provide a better or an additional framework to integration alongside
innovation at national levels, at the level of specific technologies, at
sectoral levels or within clusters? Who are the "innovation organizers"
within an innovation system? Are these national identities or increasingly
(additionally?) sub-symbolic network systems? A series of empirical questions
can be raised in this conection.
Innovation systems and technology transfer
Whereas national systems of production and distribution can be defined unambiguously (for example, using the data of national bureaus of statistics), the boundaries of national systems of innovation are less clear (Lundvall, 1992; Nelson, 1993). Does the national system change in accordance with its defined borderlines? How do science and technology—implying developments at the global level—and external market pressures mould and influence these national systems? The assumed functionality of user-producer relations for enhancing innovation can be assessed with reference to different systems.
For example, one may wish to focus on regions within one country, or across European boundaries (e.g., neighbouring regions like Alsace/Lorraine and Baden-Württemberg). Thus, the conceptualization places the research question on the agenda of the relevant system of reference for technology transfer, and requires one either to accept the functionality of existing frameworks of integration or to seek to redefine them.
Similarly, the issue of regionalization emerged on the political agenda on the other side of the Atlantic Ocean. Various state governments began to develop their own science, technology, and innovation policies during the 1980s. The Silicon Valley experience, for example, challenged the imagination of local policy makers. As the legitimation of interest-free basic science eroded, state interests were increasingly brought into play when issues of innovation policy came on the agenda in Washington, D.C.
The allocation of national research centers, for example, can be considered important for regional developments in a knowledge-based economy. Can science-based technologies serve as vehicles for leapfrogging in the competition from a relatively backward position? To what extent are economic resources and political legitimation convertible into organizing "scientific centres of excellence," and vice versa? Is Silicon Valley unique, or would it be possible to create similar conditions in other parts of the country? (Saxenian 1994).
Note how the regional issue has thus become an instrument for the deconstruction of institutionally established hierarchies, both in the U.S. and in Europe. However, perhaps differently from the U.S., regionalization in Europe can also mobilize resources like cultural traditions and, sometimes, national language communities and political identities as in the case of Flanders or Catalonia.
In the meantime, Scotland and Wales have obtained a measure of autonomy within the U.K.; and the Basque Country seems to have been more successful than other Spanish regions in reorganizing its industrial structure. The German Länder have always had means to pursue their regional interests. In Italy, with a strong regional tradition, the regionalization of Europe provided local governments with options to accentuate their existing profiles still further.
At other places (e.g., in France) the regions were only weakly defined
in political terms, but the increased opportunity to obtain European funding
for regions made it necessary in such cases to define new political entities
at this level. In the Maastricht Treaty of 1991 the EU assigned an advisory
role to the European Committee of Regions. This role was further strengthened
by the Treaty of Amsterdam in 1997, which envisaged direct consultations
between this Committee and the European Parliament. Yet, the question remains:
under what conditions can the political definition of regions as
innovation systems also be made functional to technology transfer
Regions and "regional innovation systems"
From the perspective of innovation theory, regions, sectors, branches, clusters, etc. can all be considered as analytical categories for (non-market) selection environments. These selection environments may provide mechanisms for integration and innovation to a variable extent; they may enhance innovation in one direction, but potentially at the price of blocking innovation into other (e.g., supra-regional) frameworks.
In addition to political definitions, economic organization and knowledge flows determine the innovative potentials of a region as a phenotypical outcome of a complex dynamics. Etzkowitz & Leydesdorff (1995 and 2000) have modeled university-industry-government relations as a "triple helix." While a double helix or a co-evolution (Nelson, 1994) can be expected to stabilize, the social machinery is more complex than a biological one. "Lock-ins" in co-evolutions are entrained in processes of structural reform and adjustment. The triple helix builds on the double helices underlying it.
For example, technologies can "lock-in" into markets without leaving much room for government regulation (as in the famous case of the QWERTY keyboard; David, 1985). Political economies can "lock-in" along other axes, leaving the knowledge-base insufficiently able to disturb these relations in a process of structural adjustment (as in the former Soviet Union). Science-technologies may "lock-in" with state apparatuses as in the energy household, but without sufficient market incentives (McKelvey, 1997). An efficient innovation system requires an overlay that generates variation and selection along the different axes in a distributed mode. This overlay restructures the underlying institutions in an emerging mix of the "new economy" and a pluriform society (OECD, 1996; Freeman and Soete, 1997).
Gibbons et al. (1994) have distinguished a "Mode 2" of the production of scientific knowledge which is "project based" and which tends to remain in transition, as contrasted with the highly institutionalized ("Mode 1") forms of knowledge production of the previous era. In this new mode of knowledge production, hierarchical control by disciplinary structures gives way to heterarchical relations. These can develop their own disciplinary frameworks as in the new (hybrid) sciences of biotechnology, artificial intelligence, new materials, etc. The classification schemes need periodically to be redefined with reference to the time axis. A relevant dimension can be expected to gain or lose momentum with the further development of the overall system.
For example, as universities embark on the third mission of economic development in addition to research and higher education, the further development of incubator facilities in a science park may begin to change the industrial environment of the university itself. New and previously unheard of career opportunities can be offered to alumni; research questions can be fed back from new practice directly, and responsibilities can be expected to be redefined. Offices once generated for technology transfer within a university setting may find themselves part of an emerging infrastructure, located either within a regional development office or perhaps organized increasingly as a separate industry (e.g., http://www.zernikegroup.com/ ). The fluidities of a network system defy the reification of an innovation system in terms of strong definitions.
Innovation can only be defined in terms of operations at an interface,
and a system of innovations remains a theoretical reconstruction from a
given perspective. The reconstruction of this selection mechanism has the
status of a (theoretically informed?) hypothesis. When a system of innovations
can no longer be defined as a stable unity, its definition becomes a challenge
to research and further theorizing. While the "triple helix" is driven
by rearrangements among the helices that fuse the knowledge infrastructure
with the industrial structure, the study of "triple helix"-like systems
is driven by this need to enlighten and orient the policy arena.
One observes only the innovations, but selection mechanisms can be hypothesized, and these hypotheses can be elaborated into specifications that can sometimes be tested. One expects a variety of selection mechanisms (in addition to markets) to operate upon one another and upon the innovations under study. "Innovation organizers" deliver an "up-hill" battle in more than a single dimension (Gebhardt, 1997; Etzkowitz et al., 2000).
While at each moment in time markets set constraints, political assessments and managerial priorities guide the process of making strategic choices. When academia is involved, reputations and the conditions for scientific achievement set criteria other than short-term market forces for the processes of formulating heuristics and of problem solving. Thus, a layer of codes with different functions operates interactively on the agencies carrying the innovation process, while the institutions set historical contingencies and contraints.
In our opinion, three functional imperatives can be distinguished: economic viability, scientific and technological challenge, and the political or managerial organization of the innovation process. The result of these interactions has then to be legitimated at the level of the general system, e.g., in terms of "social accountability." Furthermore, the functional imperatives are involved in a complex and pluriform process with institutional imperatives, since the one-to-one relations between the functions and institutions of a previous period (Merton, 1942) can no longer be legitimated. Universities may assume functions in the market place, for example, by organizing science parks and incubators; government may take the lead in organizing venture capital; while industries increasingly outsource and control knowledge production in public arenas.
Strategic alliances across sectors, across nations, and across levels of society may crisscross existing institutional barriers. A virtual reality of communication operates as part of the social reality of existing relations. The Internet, or more generally the ICT revolution, reinforces these cross-connections. What may have been functional at one moment in time can be expected to lose its functionality at another. An innovation system can be expected to generate more options than can be pursued. Thus, there is continuous selection pressure generated endogenously.
Nevertheless, social structures are also remarkably stable, particularly
when culture is involved. The challenge, in our opinion, is to open traditional
cultures to the transitions of a so-called "new economy" at the Internet
without generating a sense of alienation. How can traditional values be
made functional to the (sometimes disruptive) process of science-based
innovation, and how can the process of innovation be made functional to
the celebration of community values? Can the new network mode of knowledge
production be provided with an interpretation that enables us to answer
The human resource base
In metropolitan areas like New York City, the new ICT facilities have enabled corporations to hire people in neighbourhoods that they would never wish to visit directly (Leydesdorff & Etzkowitz, 1998). New technologies enable us to redefine the boundaries of the relevant social systems and markets. The abstraction of local contingences enhanced by "virtual" dimensions potentially constitutes a cross-cultural community relating through the new media of communication. The options are open and this operation again can become self-reinforcing. Can the new technology be used to break down isolation, to promote active orientation to the forces of the market, and to provide access to new cultural traits and carriers?
The network mode tends to distinguish operationally in terms of "inclusion" and "exclusion": who is connected. and who is given the right to access which parts, and on what grounds? Does regionalization mean a traditional closure as we may witness nowadays in some of the conservative regions in Europe or does it mean a new definition of the region as only one among the various sub-dynamics which enable people to participate in technological developments? Is the definition of a region political and/or functional? Can the region function as a resource, that is, a means to an end or is it defensively defined as an end to be secured against outside influences? Is it a base for misguided "nationalistic" sentiment or can it be a source of re-engagement in local affinity despite other cultural differences, a system of wealth generation, and of the retention of cultural renewal?
As in the case of the other selection mechanism, the analytical issue
here is whether the dimension under study is reified or entertained reflexively.
From the perspective of innovation theory, the region has no status other
than that of another possible frame of reference for the selection. However,
the coordination mechanism may be less abstract and alienated than at the
level of an industrial cluster or a technology. The accountability can
be provided with a social dimension that can counterbalance inequalities
produced by otherwise prevailing mechanisms. The reflexive entertainment
of the region as a category provides us with a means to investigate the
functionality of the concept, explore the question of whether a regional
system can also be innovative, and enjoy the cultural richness of reaching
beyond the traditional closure. The question of whether the concept of
"region" is functional to the concept of "technology transfer" can thus
be made an empirical one, because the hypothesis of a positive feedback
of geographical proximity on technological development merits further investigation.
A comparison of the regions of Catalonia and the Basque Country can help to illustrate our point. Both these regions have (sub-)national aspirations within a European and Spanish context. While the Basque region emerged from the Franco period with no single fully fledged university, the Barcelona region has been an important center of cultural and S&T activities—second to Madrid—over a long period of time. When both these regions suffered from the economic downswings in the early 1990s—while entertaining openings to an emerging European policy arena—regional innovation policies came high on their respective agendas.
In the Basque Country (further elaborated in a paper by Moso and Olazaran, this issue) the urgent need to modernize the industrial infrastructure made this economic problem the system of reference for a restructuring of the region during the 1980s and 1990s. As these authors conclude, regional technology policies were defined in relation to the demands of this process. Thus, the focus was not primarily on radically new technologies, but on the restructuring of existing ones. In the Catalonia region, on the other hand, competition in terms of newly emerging technologies like biotechnology, provided a major input to the restructuring of the region. Technology transfer is enhanced in this region at places where the knowledge infrastructure can be brought to bear on regional development issues.
In a paper about the region of Baden-Württemberg, one of the other "motors" of Europe mentioned above, Krauss and Wolf (this issue) note that the momentum of innovation may be declining in relation to the Munich region (in Bavaria). Emerging ICT and multimedia technology seems to favour metropolitan areas because of their rich environment in terms of cultural capacities. Thus, regions are positioned very differently with reference to newly emerging technologies, existing industrial capacities, the knowledge and human resource base, etc. Radosevic (this issue), for example, discusses the regions in central and eastern Europe in terms mainly of their differences, and he points at the importance of relating these regions to EU innovation networks.
Cooke (1998) suggested the following scheme for the classification of
regional innovation systems:
Governance of enterprise innovation support
Nine ideal types of regional innovation systems. (Source: Cooke 1998, at p. 22.)
In developing this schema Cooke (1998) showed the great diversity that characterzie regional innovation systems. Of singular importance to innovation policies has been the European awareness of the regional and national failure to generate as many innovations as competing blocs like North America or South-East Asia. Since 1998, the latter has fallen away somewhat as a zone of "disruptive" innovation (Schumpeter, 1943), but the USA has further strengthened its lead in innovation, particularly in the so-called ‘new economy’ sectors of biotechnology, information technology, and the new media.
With hindsight, the above schema can be considered as prescient with reference to the specification of California and Ontario as globalized yet grassroots innovation systems. Although California always outstripped Ontario in scale, Nortel is, with Lucent, the leading ‘backbone’ hardware supplier for telecommunications, and until its recent acquisition by Alcatel, Newbridge Networks, developed indigenously in Ontario, was a leading multiplexer switch firm.
The Cisco Systems of Silicon Valley, Intel and Oracle among them, have
an armlock on vast segments of the Internet hardware and software portion
of the new economy. For the European Union, the lesson is crystal-clear.
These firms developed from the start-up phase very rapidly by virtue of
California’s and, to a lesser extent Ontario’s, benign regulatory climate
for innovative business growth. The elements of the ‘New Economy Innovation
System’ in California include well-funded public investment in the science
base, comparatively little public start-up financing, and aggressive venture
capitalist investment to bring forth multitudes of technology businesses,
many of which are then taken to the market as publicly-quoted firms, and
then develop the interaction further.
Policy implications and the organization of the issue
The latest thing in the economy is the formation of ‘EcoNets’ or intra-cluster clans of start-ups. Networks of networks (Biggiero, this issue) change the relevant environments of the agencies which they embed. These networks partially and temporarily shield developments against market forces, while market signals can continuously be appreciated. They provide negotiating power at the meso-level with macro-actors like governments.
The Silicon Valley venture capitalists Kleiner Perkins have retained investments in over two hundred start-up firms among whom they encourage inter-trading. Intel and other corporate venturing arms have created technology keiretsus while Cisco have internalized their version through a recent wave of acquisitions. Cooke’s contribution (this issue), gives a sense of the relationship between the large public funding of university research and the rapid commercialization made possible by venture capital in biotechnology. Some evidence is offered that a version of venture capital-driven innovation in ‘new economy’ sectors may have taken root in the U.K. and, it might be added, also in Germany, one of the larger European economies.
The localized, university-focused commercialization of applied science is illustrated in Rip’s account (this issue) of the processes operating in the Netherlands’ much-admired case of the University of Twente. Krauss and Wolf show how German venture capital has been stimulated by large public-venture subsidies through the BioRegio contest. The new realization that regions form platforms for clustered innovative activity with links to national and global centers of excellence is demonstrated in Koschatzky’s careful study of weakly-developing ties in a fragmented national ‘system’ in Slovenia. Biggiero (this issue) discusses the formation of "networks of networks" or "hypernetworks" as the next-order frame of integration for innovative development and explores the potential of these concepts for understanding technological development at the regional level.
In more traditional industries the importance of localized linkage and ‘stickiness’ towards the national centre of finance and the public-science base in weak regional settings like Norway (Isaksen and Asheim this issue) is instructive. We see evidence in the European cases of a continuation of the belief that innovation has to be supported actively and subsidized regularly by public funding. This is undoubtedly a case of market failure that has resulted in a mindset in Europe to the effect that public intervention is imperative, especially through the regional delivery instruments already noted.
The focus on small firms, and the relative success where the public sector can concentrate on a few faster-growers, is discussed in the case of Upper Austria by Tödtling and Kaufmann (this issue). Of greatest concern, however, is the evidence that such smaller firms have strong regional orientations but poor or non-existent inter-firm networking and interactions with university researchers, something that must be considered by policies to promote stronger private innovation support infrastructures in such regions.
Some years ago, the paradigm example of efficient and effective regional innovation service-delivery was the well-networked region of Baden-Württemberg in which an enterprising public bureaucracy substituted for an active and entrepreneurial investor class. This was a model for regions with economies needing to develop trajectories away from a declining ‘old’ to a thriving ‘new’ profile. There are additional problems in implementing this model when regional and national governments are the main suppliers of direct services. They are reluctant to ‘let go’ of their support projects, their functionaries may be fearful of their career consequences if they lose control of a glamorous new governmental function to support regional innovation, and they may feel moral repugnance at the intra-regional disparities that may grow if California-style private enterprise support models are ‘allowed’ to prosper.
The lesson for the public sector is that firms listen and respond most to other firms. Nowadays they have highly varied and specialist needs that markets alone can meet, and they will benefit substantively from efforts (as with Germany’s BioRegio) to use public funding intelligently to build up private innovation support infrastructures at the regional level. The role of government at different levels is increasingly catalytic instead of orchestrating (Leydesdorff, 2000): how can different incentives be provided and resources be made available at the right moment in order to generate a mixture of university-industry-government relations fruitful for high-tech niche-formation? How can a retention mechanism be added to the selection by the market? (e.g., Molina and Michilli, this issue).
The challenge to local, regional, national, and supra-national governments is to learn from places where this has happened naturally, to learn a second time from policies that have set up such systems successfully in still (relative to California) highly-regulated European settings, and to evolve a model reflexively of an appropriately adapted kind also in less favoured regional settings. This may be less difficult than it sounds, given the widespread view that venture capital and even seed-corn or business-angel capital is less scarce than hitherto assumed, that it has spread to most cities even in less-favoured regions, and that risk-aversity, as practised by multinational venture houses like 3i, is less pronounced than it used to be, since the real scarcity is often one of ideas.
To help overcome this, the one knowledge-creating asset that is present
in or near most regions, the university, may have a crucial new role to
play (Rosa Pires et al. 1997; Etzkowitz and Leydesdorff, 1997).
Here, learning from cases like MIT, Cambridge or Twente can be of the greatest
importance. Accordingly, the public sector has a duty to absorb and disseminate
these lessons to the market as well as to other important parts of the
regional innovation system if all are to reap the benefits of the massive
historical investment that has, practically everywhere, been committed
to the science and technology base. The issue of "technology transfer"
is thus brought back home.
The authors are grateful for the support to the workshop provided by the Department of Education and the Department of Industry of the Basque Government, the Spanish Ministry of Education, the Kutxa Bank Foundation, and the Research Institute for Logic, Cognition, Language and Information (ILCLI) of the University of the Basque Country.
return to home page
Bruckner, Eberhard, Werner Ebeling, Miguel A. Jiménez Montaño and Andrea Scharnhorst, 1994, ‘Hyperselection and Innovation Described by a Stochastic Model of Technological Evolution’, in: Loet Leydesdorff and Peter Van den Besselaar (eds.), Evolutionary Economics and Chaos Theory: New Directions in Technology Studies, London and New York: Pinter, pp. 79-90.
Rosa Pires, Artur da, and Eduardo Anselmo de Castro, 1997, ‘Can a strategic project for a university be strategic to regional development?’, Science and Public Policy 24, 15-20.
Cooke, Philip, 1998, ‘Introduction. The origins of the concept’, in: Braczyk, H.-J., P. Cooke, and M. Heidenreich (eds.), Regional Innovation Systems, London/ Bristol PA: University College London Press, pp. 2-25.
David, Paul A., 1985, ‘Clio and the Economics of QWERTY’, American Economic Review 75, 332-7.
Etzkowitz, Henry, Magnus Gulbrandsen, and Janet Levitt (2000). Public Venture Capital: Government Funding Sources for Technology Entrepreneurs, New York: Harcourt Brace.
Etzkowitz, Henry, and Loet Leydesdorff, 1995. ‘The Triple Helix of University-Industry-Government Relations: A Laboratory for Knowledge Based Economic Development,’ EASST Review 14 (1), 11-19.
Etzkowitz, Henry, and Loet Leydesdorff (eds.), 1997, Universities and the Global Knowledge Economy: A Triple Helix of University-Industry-Government Relations, London: Cassell Academic.
Etkzowitz, Henry, and Loet Leydesdorff, 2000, ‘The Dynamics of Innovation: From National Systems and "Mode 2" to a Triple Helix of University-Industry-Government Relations’, Research Policy 29 (2), 109-123.
Freeman, Christopher, 1988, ‘Japan, a New System of Innovation’, in: Giovanni Dosi, Chistopher Freeman, Richard Nelson, Gerald Silverberg, and Luc Soete (eds.), Technical Change and Economic Theory, London: Pinter.
Freeman, Christopher and Luc Soete, 31997 , The Economics of Industrial Innovation London: Pinter.
Freeman, Chris, and Carlota Perez, 1988, ‘Structural crises of adjustment, business cycles and investment behaviour’, in: Giovanni Dosi, Chistopher Freeman, Richard Nelson, Gerald Silverberg, and Luc Soete (eds.), Technical Change and Economic Theory. London: Pinter, pp. 38-66.
Fujigaki, Yuko, and Akiya Nagata, 1998, ‘Concept Evolution in Science and Technology Policy: The process of change in relationship among university, industry, and government’, Science and Public Policy 25 (6), 387-395.
Gebhardt, Christiane, 1997, Die Regionalisierung von Innovationsprozessen in der Informationstechnologie. Staatliche Forschungsfoerderung im Zeitalter der Globalisierung, Wiesbaden: Deutscher Universitäts Verlag.
Gibbons, Michael, Camille Limoges, Helga Nowotny, Simon Schwartzman, Peter Scott, and Martin Trow, 1994, The new production of knowledge: the dynamics of science and research in contemporary societies, London: Sage.
Kline, S. J., and N. Rosenberg, 1986, ‘An overview of innovation’, in: R. Landau and N. Rosenberg (eds.), The Positive Sum Strategy: Harnessing Technology for Economic Growth, Washington, D.C.: National Academy Press.
Leydesdorff, Loet, 2000, ‘Are EU Networks Anticipatory Systems? An empirical and analytical approach’, in: Daniel M. Dubois (ed.), Computing Anticipatory Systems – CASYS'99. Woodbury, NY: American Physics Institute.
Leydesdorff, Loet and Henry Etzkowitz, 1998, ‘The Triple Helix as a model for innovation studies’, Science and Public Policy 25 (3), 195-203.
Lundvall, Bengt-Åke, 1988, ‘Innovation as an interactive process: from user-producer interaction to the national system of innovation’, in: Giovanni Dosi, Chistopher Freeman, Richard Nelson, Gerald Silverberg, and Luc Soete (eds.), Technical Change and Economic Theory, London: Pinter, pp. 349-369.
Lundvall, Bengt-Åke (ed.), 1992, National Systems of Innovation, London: Pinter.
McKelvey, Maureen D., 1997, ‘Emerging Environments in Biotechnology’, in: Henry Etzkowitz and Loet Leydesdorff (eds.), Universities and the Global Knowledge Economy: A Triple Helix of University-Industry-Government Relations, London: Cassell Academic, pp. 60-70.
Merton, Robert K. (1942). ‘Science and Technology in a Democratic Order’, Journal of Legal and Political Sociology, 1, 115-26.
Mowery, David C., and Nathan Rosenberg, 1979, ‘The influence of market demand upon innovation: a critical review of some empirical studies’, Research Policy 8, 102-153.
Nelson, Richard R. (ed.), 1982, Government and Technical Progress: a cross-industry analysis New York: Pergamon.
Nelson, Richard R. (ed.), 1993, National Innovation Systems: A comparative analysis. New York: Oxford University Press.
Nelson, Richard R., 1994, ‘Economic Growth via the Coevolution of Technology and Institutions’, in: Loet Leydesdorff and Peter Van den Besselaar (eds.), Evolutionary Economics and Chaos Theory: New directions in technology studies, London: Pinter, pp. 21-32.
Nelson, Richard, and Sydney Winter, 1975, ‘Growth Theory from an Evolutionary Perspective: The Differential Productivity Growth Puzzle’, American Economic Review 65, 338-44.
Nelson, Richard R., and Sidney G. Winter, 1977, ‘In search of useful theory of innovation’, Research Policy 6, 36-76.
OECD, 1964, The Residual Factor and Economic Growth, Paris: OECD.
OECD, 1980, Technical Change and Economic Policy, Paris: OECD.
OECD, 1996, The Knowledge Economy, Paris: OECD.
Rothwell, Roy, and Walter Zegveld, 1981, Industrial Innovation and Public Policy, London: Pinter.
Saxenian, Anne, 1994, Regional Advantage: Culture and Competition in Silicon Valley and Route 128. Cambridge, MA/London: Harvard University Press.
Schumpeter, Joseph (1943). Socialism, Capitalism and Democracy. London: Allen & Unwin.
Yamuachu, Ichizo, 1986, ‘Long Range Strategic Planning in Japanese R&D’, in: Chirstopher Freeman (ed.), Design, Innovation and Long Cycles in Economic Development, London: Pinter.
return to home page