THE DYNAMICS OF INNOVATION:
FROM NATIONAL SYSTEMS AND "MODE 2" TO A TRIPLE HELIX OF UNIVERSITY‑INDUSTRY‑GOVERNMENT RELATIONS
Henry Etzkowitz* and Loet Leydesdorff**
(rotating first authorship)
Science Policy Institute, Social Science Division,
Department of Science and Technology Dynamics, Nieuwe
Achtergracht 166, 1018 WV
The Triple Helix of University-Industry-Government Relations is compared with alternative models for explaining the current research system in its social contexts. Communications and negotiations between institutional partners generate an overlay that increasingly reorganizes the underlying arrangements. The institutional layer can be considered as the retention mechanism of a developing system. For example, the national organization of the system of innovation has historically been important in determining competition. Reorganizations across industrial sectors and nation states, however, are induced by new technologies (biotechnology, ICT). The consequent transformations can be analyzed in terms of (neo‑)evolutionary mechanisms. University research may function increasingly as a locus in the "laboratory" of such knowledge-intensive network transitions.
1. Introduction: From the Endless Frontier to an Endless Transition
The "Triple Helix" thesis states that the university can play an enhanced role in innovation in increasingly knowledge‑based societies. The underlying model is analytically different from the National Systems of Innovation (NSI) approach (Lundvall 1988 and 1992; Nelson 1993), which considers the firm as having the leading role in innovation, and from the "Triangle" model of Sábato (1975), in which the state is privileged (cf. Sábato and Mackenzie 1982). We focus on the network overlay of communications and expectations that reshape the institutional arrangements among universities, industries, and governmental agencies.
the role of the military has decreased and academia has risen in the
institutional structures of contemporary societies, the network of
relationships among academia, industry, and government have also been transformed,
displacing the Cold‑War "Power Elite" trilateral mode of Wright
Mills (1958) with an overlay of reflexive communcations
that increasingly reshape the infrastructure (Etzkowitz
and Leydesdorff 1997). Not surprisingly, the effects
of these transformations are the subject of an international debate over the
appropriate role of the university in technology and knowledge transfer.
For example, the Swedish Research 2000 Report recommended the withdrawal
of the universities from the envisaged "third m
issues in the Swedish debate are echoed in the critique of academic technology
transfer in the
The institutional innovations aim to promote closer relations between faculties and firms. "The Endless Frontier" of basic research funded as an end in itself, with only long-term practical results expected, is being replaced by an "Endless Transition" model in which basic research is linked to utilization through a series of intermediate processes (Callon 1998), often stimulated by government.
The linear model either expressed in terms of "market pull" or "technology push" was insufficient to induce transfer of knowledge and technology. Publication and patenting assume different systems of reference both from each other and with reference to the transformation of knowledge and technology into marketable products. The rules and regulations had to be reshaped and an interface strategy invented in order to integrate "market pull" and "technology push" through new organizational mechanisms (e.g., OECD 1980; Rothwell & Zegveld 1981).
the U.S.A., these programs include the Small Business Innovation Research
program (SBIR) and the Small Bussiness Technology
Transfer Program (STTR) of the Department of Defense, the Industry/University
Cooperative Research Centers (IUCRC) and Engineering Research Centers (ERC) of
the National Science Foundation, etc. (Etzkowitz
et al., 2000). In
academia encompass a third m
2. Triple Helix Configurations
evolution of innovation systems, and the current confl
Figure 1. An Etatistic Model of University-Industry-Government Relations
Figure 2. A "laissez-faire" Model of University-Industry-Government Relations
second policy model (Figure 2) consi
The Triple Helix Model of University-Industry-Government relations
The overlay of communications and expectations at the network level guides the reconstruction of institutional arrangements
The differences between the latter two versions of the Triple Helix arrangements currently generate normative interest. Triple Helix I is largely viewed as a failed developmental model. With too little room for "bottom up" initiatives, innovation was discouraged rather than encouraged. Triple Helix II entails a laissez-faire policy, nowadays also advocated as shock therapy to reduce the role of the state in Triple Helix I.
one form or another, most countries and regions are presently trying to attain
some form of Triple Helix III. The common objective is to realize an
innovative environment consisting of university spin‑off firms, tri‑lateral
initiatives for knowledge‑based economic development, and strategic
alliances among firms (large and small, operating in different areas, and with
different levels of technology), government laboratories, and academic research
groups. These arrangements are often encouraged, but not controlled, by
government, whether through new "rules of the game," direct or indirect
financial assistance, or through the Bayh‑Dole
Act in the
3. The Triple Helix of Innovation
Triple Helix as an analytical model adds to the description of the v
In our opinion, typifications in terms of "national systems of innovation" (Lundvall 1988; Nelson 1993); "research systems in transition" (Cozzens et al., 1990; Ziman 1994), "Mode 2" (Gibbons et al., 1994) or "the post modern research system" (Rip and Van der Meulen 1996) are indicative of flux, reorganization, and the enhanced role of knowledge in the economy and society. In order to explain these observable reorganizations in university-industry-government relations, one needs to transform the sociological theories of institutional retention, recombinatorial innovation, and reflexive controls. Each theory can be expected to appreciate a different subdynamic (Leydesdorff 1997).
In contrast to a double helix (or a coevolution between two dynamics), a Triple Helix is not expected to be stable. The biological metaphor cannot work because of the difference between cultural and biological evolutions. Biological evolution theory assumes variation as a driver and selection to be naturally given. Cultural evolution, however, is driven by individuals and groups who make conscious decisions as well as the appearance of unintended consequences. A Triple Helix in which each strand may relate to the other two can be expected to develop an emerging overlay of communications, networks, and organizations among the helices (Figure 4).
sources of innovation in a Triple Helix configuration are no longer
synchronized a priori. They do not fit together in a pregiven order, but they generate puzzles for participants,
Innovation systems, and the relationships among them, are apparent at the organizational, local, regional, national, and multi‑national levels. The interacting subdynamics, that is, specific operations like markets and technological innovations, are continuously reconstructed like commerce on the Internet, yet differently at different levels. The subdynamics and the levels are also reflexively reconstructed through discussions and negotiation in the Triple Helix. What is considered as "industry", what as "market" cannot be taken for granted and should not be reified. Each "system" is defined and can be redefined as the research project is designed.
For example, "national systems of innovation" can be more or less systemic. The extent of systemness remains an empirical question (Leydesdorff and Oomes 1999). The dynamic "system(s) of innovation" may consist of increasingly complex collaborations across national borders and among researchers and users of research from various institutional spheres (Godin and Gingras, this issue). There may be different dynamics among regions. The systems of reference have to be specified analytically, that is, as hypotheses. The Triple Helix hypothesis is that systems can be expected to remain in transition. The observations provide an opportunity to update the analytical expectations.
4. An Endless Transition
The infrastructure of knowledge‑intensive economies implies an Endless Transition. Marx's great vision that "all that is solid, melts into air" (Berman 1982) underestimated the importance of seemingly volatile communications and interactions in recoding the (complex) network system. Particularly, when knowledge is increasingly utilized as a resource for the production and distribution system, reconstruction may come to prevail as a mode of "creative destruction" (Schumpeter 1939 and 1966; Luhmann 1984).
the reconstructing forces be specified? One mode of specification is
provided by evolutionary economics in which the three functional mechanisms
are: technological innovation provides the variation, markets are the
prevailing selectors, and the institutional structures provide the system with
retention and reflexive control (Nelson 1994). In advanced and pluriform societies, the mechanisms of institutional
control are again differentiated into public and pr
can be defined at different levels and from different perspectives within this
complex dynamics. For example, evolutionary economi
In our opinion, these various perspectives open windows of appreciation on the dynamic and complex processes of innovation, but from specific angles. The complex dynamics is composed of subdynamics like market forces, political power, institutional control, social movements, technological trajectories and regimes. The operations can be expected to be nested and interacting. Integration, for example, within a corporation or within a nation state, cannot be taken for granted. Technological innovation may also require the reshaping of an organization or a community (Freeman and Perez 1988). But the system is not deterministic: in some phases intentional actions may be more succesful in shaping the direction of technological change than in others (Hughes 1983).
The dynamics are non‑linear while both the interaction terms and the recursive terms have to be declared. First, there are ongoing transformations within each of the helices. These reconstructions can be considered as a level of continuous innovations under pressure of changing environments. When two helices are increasingly shaping each other mutually, co‑evolution may lead to a stabilization along a trajectory. If more than a single interface is stabilized, the formation of a globalized regime can be expected. At each level, cycles are generated which guide the phasing of the developments. The higher‑order transformations (longer‑term) are induced by the lower‑order ones, but the latter can seriously be disturbed by events at a next‑order system's level (Schumpeter 1939; Kampmann et al. 1994).
Although this model is abstract, it enables us to specify the various windows of theoretical appreciation in terms of their constitutive subdynamics (e.g., Leydesdorff & Van den Besselaar 1997). The different subdynamics can be expected to select upon each other asymmetrically, as in processes of negotiation, by using their specific codes. For example, the markets and networks select upon technological feasibilities, whereas the options for technological developments can also be specified in terms of market forces. Governments can intervene by helping create a new market or otherwise changing the rules of the game.
When the selections "lock‑in" upon each other, next‑order systems may become relevant. For example, airplane development at the level of firms generates trajectories at the level of the industry in coevolutions between selected technologies and markets (e.g., Nelson 1994, cf. McKelvey 1996). Nowadays, the development of a new technological trajectory invokes the support of national governments and even international levels (like the EU), using increasingly a Triple Helix regime (Frenken and Leydesdorff, forthcoming).
We have organized this theme issue about the Triple Helix of University‑Industry‑Government Relations in terms of three such interlocking dynamics: institutional transformations, evolutionary mechanisms, and the new position of the university. This approach allows us to pursue the analysis at the network level and then to compare among units of analysis. For example, both industries and governments are entrained in institutional transformations, while the institutional transformations themselves change under the pressure of information and communication technologies (ICT) or government policies. Before explaining the organization of the theme issue in detail, however, we wish to turn briefly to the analytical position of the Triple Helix model in relation to other non‑linear models of innovation, like "Mode 2" and "national systems of innovation."
5. Non‑linear models of innovation
As noted, non‑linear models of innovation extend upon linear models by taking interactive and recursive terms into account. These non‑linear terms can be expected to change the causal relations between input and output. The production rules in the systems under study, for example, can be expected to change with the further development of the input/output relations (e.g., because of economies of scale). Thus, the unit of operation may be transformed, as is typical when a pilot plant in the chemical industry is scaled up to a production facility.
changing the unit of analysis or the unit of operation at the reflexive level,
one obtains a different perspective on the system under study. But the
system itself is also evolving. In terms of methodologies, this challenges
our conceptual apparatus, since one has to be able to distinguish whether the
variable has changed or merely the value of the variable. The analysis
contains a snapshot, while the reality provides a moving p
Innovation, in particular, can be defined only in terms of an operation. Both the innovator(s) and the innovated system(s) are expected to be changed by the innovation. Furthermore, one is able to be both a participant and an observer, and one is also able to change perspectives. In the analysis, however, the various roles are distinguished although they can sometimes be fused in "real life" events. Langton (1989) proposed to distinguish between the "phenotypical" level of the observables and the "genotypical" level of analytical theorizing. The "phenotypes" remain to be explained and the various explanations compete in terms of their clarity and usefulness for updating the expectations. Confusion, however, is difficult to avoid given the pressure to jump to normative conclusions, while different perspectives are continuously competing, both normatively and analytically.
us first focus on the p
Lundvall (1988, at p. 357) noted that the interactive terms between demand and supply in user‑producer relations assume a system of reference in addition to the market. The classical dispute in innovation theory had, in his opinion, referred to the role of demand and supply, that is, market forces, in determining the rate and direction of the process of innovation (cf. Mowery and Rosenberg, 1979; Freeman, 1982, p. 211). If, however, the dynamics of innovation (e.g., product competition) are expected to be different from the dynamics of the market (e.g., price competition), an alternative system of reference for the selection should also be specified. For this purpose, Lundvall proposed "to take the national system of production as a starting point when defining a system of innovation" (p. 362).
Lundvall added that the national system of production should not be considered as a closed system: "the specific degree and form of openness determines the dynamics of each national system of production." In our opinion, as a first step, innovation systems should be considered as the dynamics of change in systems of both production and distribution. From this perspective, national systems compete in terms of the adaptability of their knowledge infrastructure. How are competences distributed for solving "the production puzzle" which is generated by uneven technological developments across sectors (Nelson & Winter 1975; Nelson 1982)? The infrastructure conditions the processes of innovation which are possible within and among the sectors. In particular, the distribution of relevant actors contains an heuristic potential which can be made reflexive by a strategic analysis of specific strengths and weaknesses (Pavitt 1984).
solution of the production puzzle typically brings government into the p
et al. (1994) argued that this "new mode of the production of
scientific knowledge" has become manifest. But: how are these
dynamics in the network arrangements between industries, governments, and
academia a consequence of the user‑producer interactions foregrounded by Lundvall
(1988)? Are national systems still a relevant unit of analysis?
Since the new mode of knowledge production ("Mode 2") is
characterized as an outcome, it should, in our opinion, be considered as an
emerging system. The emerging system re
has always been organized through networks, and to pursue practical as well as
practical impetus to scientific discovery is
long-standing. Robert K. Merton's (1938)
dissertation reported that between 40-60% of discoveries in the 17th century
could be classified as having their origins in trying to solve p
so-called "Mode 2" is not new; it is the original format of science
before its academic institutionalization in the nineteenth century. Another
question to be answered is why "Mode 1" has arisen after "Mode
2": the original organizational and institutional basis of science,
consisting of networks and invisible colleges (cf. Weingart,
1997; Godin, 1998).Where have these ideas, of the
scientist as the isolated individual and of science separated from the intere
hence, Robert K. Merton posited the normative structure of science
in 1942 and strengthened the ideology of “pure science.” His
emphasis on universalism and skepticism was a
response to a particular historical situation, the need to defend science from
corruption by the Nazi doctrine of a racial basis for science and from Lysenko’s attack on genetics in the
third element in establishing the ideology of pure science was, of course, the
Bush Report of 1945. The huge success of science in supplying practical results
during World War II in one sense supplied its own legitimation
for science. But with the end of the war at hand and wanting to insure that
science was funded in peacetime, a rationale was needed in 1944 when Bush
persuaded President Roosevelt to write a letter comm
the first draft of his report, Bush proposed to
follow the then current British method of funding science at universities. It
would be distributed on a per capita basis according to the number of students
at each school. In the contemporary British system of a small number of
universities, the funds automatically went to an
elite. However, if that model had been followed in the
the time between the draft and the final report, the mechanism for distribution
of government funds to academic research was revised and “peer review” was
introduced. Adapted from Foundation practices in the 1920s and 30s, it could be
expected that "the peers," the leading scienti
This model of “best science” is no longer acceptable to many as the sole basis for distribution of public research funds. Congresspersons who represent regions with universities that are not significant recipients of research funds have disregarded peer review and distributed research funds by direct appropriation, much as roads and bridges are often sited through “log rolling” and “pork barrel” processes. Nevertheless, these politically directed funds support also serious scientific research and instrumentation projects. Even when received by schools with little or no previous research experience, these “one time funds” are typically used to rapidly build up competencies in order to compete within the peer review system.
when a leading school,
Increasing competition for research funds among new and old actors has caused an incipient breakdown of “peer review,” a system that could best adjudicate within a moderate level of competition. As competition for research funds continues to expand, how should the strain be adjusted? Some propose shrinking the research system; others suggest linking science to new sources of legitimation such as regional development.
6. The Future Legitimation of Science
is nowadays apparent that the development of science provides much of the basis
for future industrial development. These connections, however, have been
present from the creation of science as an organized activity in the 17th
century. Marx pointed them out again in the mid-19th century in connection with
the development of chemical industry in
potential of science to contribute to economic development has become a source
of regional and international competition at the turn of the millenium. Until recently, the location of research was of
little concern. The relationship between the site where knowledge is produced
and its eventual utilization was not seen to be tightly linked, even as a first
mover advantage. This view has changed dramatically in recent years, as has the
notion that high-tech conurbations, like Route 128 and
research intensive regions are by now well aware that science, applied to local
resources, is the basis of much of their future potential for economic and
social development. In the
The classic legitimation for scientific research as a contribution to culture still holds and military and health objectives also remain a strong stimulus to research funding. Nevertheless, the future legitimation for scientific research, which will keep funding at a high level, is that it is increasingly the source of new lines of economic development.
created disciplines are often the basis for these heightened expectations. Such
disciplines do not arise only from the subdivision of new disciplines from old
ones, as in the 19th century (Ben David and Collins, 1966). New
disciplines have arisen, more recently, through syntheses of practical and
university can be expected to remain the core institution of the knowledge
sector as long as it retains its original educational m
university may be compared to other recently proposed contenders for knowledge
leadership, such as the consulting firm. A consulting company draws together
widely dispersed personnel for individual projects and then disperses them
again after a project, solving a client’s particular p
course, as firms organize increasingly higher level training programs (e.g.,
7. Implications of the Triple Helix Model
The Triple Helix denotes not only the relationship of university, industry and government, but also internal transformation within each of these spheres. The university has been transformed from a teaching institution into one which combines teaching with research, a revolution that is still ongoing, not only in the U.S.A., but in many other countries. There is a tension between the two activities but nevertheless they co-exist in a more or less compatible relationship with each other because it has been found to be both more productive and cost effective to combine the two functions.
The Triple Helix overlay provides a model at the level of social structure for the explanation of "Mode 2" as an historically emerging structure for the production of scientific knowledge, and its relation to "Mode 1." First, the arrangements between industry and government no longer need to be conceptualized as exclusively between national governments and specific industrial sectors. Strategic alliances cut across traditional sector divides; governments can act at national, regional, or increasingly also at international levels. Corporations adopt "global" postures either within a formal corporate structure or by alliance. Trade blocks like the EU, NAFTA, and Mercosul provide new options for breaking "lock‑ins," without the sacrifice of competitive advantages from previous constellations. For example, the Airbus can be considered as an interactive opportunity for recombination at the supra‑national level (Frenken, this issue).
Second, the driving force of the interactions can be specified as the expectation of profits. "Profit" may mean different things to the various actors involved. A leading edge consumer, for example, provides firms and engineers with opportunities to perceive "reverse salients" in current product lines and software. Thus, opportunities for improvements and puzzle‑solving trajectories can be defined. Note that analytically the drivers are no longer conceptualized as ex ante causes, but in terms of expectations that can be evaluated only ex post. From the evolutionary perspective, selection (ex post) is structure determined, while variation may be random (Arthur 1988; Leydesdorff and Van den Besselaar 1998).
Third, the foundation of the model in terms of expectations leaves room for uncertainties and chance processes. The institutional carriers are expected to be reproduced as far as they have been functional hitherto, but the negotiations can be expected to lead to experiments which may thereafter also be institutionalized. Thus, a stage model of innovation can be specified.
The stages of this model do not need to correspond with product life cycle theory. Barras (1990), for example, noted that in ICT "a reverse product life" cycle seems to be dominant. Bruckner et al. (1994) proposed niche‑creation as the mechanism of potential lock‑out in the case of competing technologies. A successful innovation changes the landscape, that is, the opportunity structure for the institutional actors involved. Structural changes in turn are expected to change the dynamics.
Fourth, the expansion of the higher‑education and academic research sector has provided society with a realm in which different representations can be entertained and recombined in a systematic manner. Kaghan and Barett (1997) have used in this context the term "desktop innovation" as different from the laboratory model (cf. Etzkowitz, 1999). Knowledge‑intensive economies can no longer be based on simple measures of profit maximization: utility functions have to be matched with opportunity structures. Over time, opportunity structures are recursively driven by the contingencies of prevailing and possible technologies. A laboratory of knowledge‑intensive developments is socially available and can be improved upon (Etzkowitz and Leydesdorff 1995). As this helix operates, the human capital factor is further developed along the learning curves and as an antidote to the risk of technological unemployment (Pasinetti, 1981).
Fifth, the model also explains why the tensions need not to be resolved. A resolution would hinder the dynamics of a system which lives from the perturbations and interactions among its subsystems. Thus, the subsystems are expected to be reproduced. When one opens the black‑box one finds "Mode 1" within "Mode 2," and "Mode 2" within "Mode 1." The system is neither integrated nor completely differentiated, but it performs on the edges of fractional differentiations and local integrations. Using this model, one can begin to understand why the global regime exhibits itself in progressive instances, while the local instances inform us about global developments in terms of the exceptions which are replicated and built upon.
materials enable us to specify the negative selection mechanisms
reflexively. Selection mechanisms, however, remain constructs. Over
time, the inference can be cor
Sixth, the crucial question of the exchange media —economic expectations (in terms of profit and growth), theoretical expectations, assessment of what can be realized given institutional and geographic constraints— have to be related and converted into one another. The helices communicate recursively over time in terms of each one's own code. Reflexively, they can also take the role of each other, to a certain extent. While the discourses are able to interact at the interfaces, the frequency of the external interaction is (at least initially) lower than the frequency within each helix. Over time and with the availability of ICT, this relation is changing.
The balance between spatial and virtual relations is contingent upon the availability of the exchange media and their codifications. Codified media provide the system with opportunities to change the meaning of a communication (given another context) while maintaining its substance (Cowan and Foray 1997). Despite the "virtuality" of the overlay, this system is not "on the fly": it is grounded in a culture which it has to reproduce (Giddens 1984). The retention mechanism is no longer given, but "on the move": it is reconstructed as the system is reconstructed, that is, as one of its subdynamics.
the technological culture provides options for recombination, the bound
8. The organization of the theme issue
As noted above, this issue is organized in three main parts, addressing (1) institutional transformation, (2) evolutionary mechanisms, and (3) the second academic revolution. Each part contains five contributions.
In Part One ("Institutional Transformations"), Michael Nowak and Charles Grantham open the discussion with a paper about the impact of the Internet on incubation as an institutional mechanism for technological innovation. The increased complexity of the process induces reflexivity about the choices to be made, and human capital becomes increasingly crucial for carrying the transformations.
The failure of the "opening to the market" as an answer to the state‑dominated economies in the former Soviet Union, because of the neglect of the knowledge‑intensive dimension, is discussed by testing three models against each other in Judith Sedaitis' paper entitled "Technology Transfer in Transitional Economies: Comparing Market, State, and Organizational Frameworks." The author concludes that processes of transfer in these cases can be understood at the intermediate network level.
Morris, in "Vial Bodies: Confl
Thus, not only the institutions themselves are tranformed, but also their mechanisms of transformation. These evolutionary mechanisms are central to the second part of the theme issue. The contribution from the Aveiro team (Eduardo Anselmo de Castro, Carlos José Rodrigues, Carlos Esteves, and Artur da Rosa Pires) returns to the impact of ICT on changing the stage. How can institutional arrangements be shaped to match the options which telematics provide? How can a retention mechanism be organized as a niche or a habitat for knowledge‑intensive developments?
the Portuguese team focuses on the regional level, Susanne Giesecke
takes the analysis to the level of comparing national governments in her
contribution entitled "The Contrasting Roles of Government in the Development
of the Biotechnology Industries in the
Rosalba Casas, Rebeca de Gortari, and Ma. Josefa Santos from
In a contribution entitled "The Triple Helix: An Evolutionary Model of Innovations," Loet Leydesdorff uses simulations to show how a "lock‑in" can be enhanced using a co‑evolution like the one between regions and technologies. A third source of random variation, however, may intervene, reversing the order in a later stage and leading to more complex arrangements of market segmentation (that is, different suboptima). A mechanism for "lock‑out" can also be specified.
In the third part of the issue, we turn to the Second Academic Revolution. In their contribution entitled "The Place of Universities in the System of Knowledge Production," Benoît Godin and Yves Gingras argue against the thesis that the university would have lost its salient position in the university‑industry‑government relations of "Mode 2." Using scientometric data, they show that collaboration with academic teams is central to the operations of the networks which transform this knowledge infrastructure. Although based on Canadian data, the argument is made that this holds true also for other OECD countries.
another world region, Judith Sutz reports about
university‑industry‑government relations in
a contribution entitled "Institutionalizing the Triple Helix: Research
Funding and Norms in the Academic System," Mats Benner and Ulf Sandström take a neo‑institutional approach to the
transformation of the university system in
In a final article, Henry Etzkowitz, Andrew Webster, Christiane Gebhardt, and Branca Terra substantiate their claim that the transformation of the university system is a worldwide phenomenon. In addition to research and higher eduction, the university nowadays has a third role in regional and economic development because of the changing nature of both knowledge production and economic production. While a "hands off" may have been functional to previous configurations, the exigencies of today demand a more intensive interrelationship. As noted, a Triple Helix arrangement that tends to reorganize the knowledge infrastructure in terms of possible overlays, can be expected to be generated endogenously.
acknowledge support from the U.S. National Science Foundation, the European
Alchian, A. A., 1950, Uncertainty, Evolution, and Economic Theory. Journal of Political Economy 58, 211-222.
Esben Slot, 1994, Evolutionary Economics:
Post-Schumpeterian Contributions (Pinter,
W. Brian, 1988, Competing technologies, in: Giovanni Dosi, Chistopher Freeman, Richard
Nelson, Gerald Silverberg, and Luc Soete (Editors), Technical
Change and Economic Theory (Pinter,
Barras, Richard, 1990, Interactive innovation in financial and business services: The vanguard of the service revolution, Research Policy 19, 215-37.
Ben David, Joseph, and Randall Collins, 1966, Social Factors in the Origins of New Science: The Case of Psychology, American Sociological Review 3, 45-85.
Benner, Mats, and Ulf Sandström, Institutionalizing the Triple Helix: Research Funding and Norms in the Academic System, Research Policy (this issue).
Marshall, 1982, All That is Solid Melts into Air: The
Experience of Modernity (Simon and
Braczyk, H.-J., P.
Cooke, and M. Heidenreich (Editors), Regional
Innovation Systems (
Bruckner, Eberhard, Werner Ebeling, Miguel A. Jiménez Montaño and
V.,  1980, The Endless Frontier: A Report to
the President (reprinted by Arno Press,
Callon, Michel, 1998, An essay
on framing and overflowing: economic externalities revisited by sociology, in:
Michel Callon (Editor), The Laws of the Market
Cowan, Robin, and Dominique Foray, 1997, The Economics of Codification and the Diffusion of
Cozzens, Susan, Peter Healey, Arie
Rip, and John Ziman (Editors), 1990, The Research System in Transition (Kluwer Academic Publishers,
Dasgupta, P., and P. David, 1994, Towards a new economics of science, Research Policy 23, 487-522.
Paul A., and Dominique Foray, 1994, Dynamics of Competitive Technology
Diffusion Through Local Network Structures: The Case
of EDI Document Standards, in: L. Leydesdorff and P.
Van den Besselaar (Editors), Evolutionary
Economics and Chaos Theory: New Directions in Technology Studies (Pinter,
Etzkowitz, Henry, 1999, Bridging the Gap: The Evolution
of Industry-University Links in the
Henry, (forthcoming), The Second Academic Revolution: MIT and the Rise of
Entrepreneurial Science, Gordon and Breach,
Etzkowitz, Henry, Magnus Gulbrandsen,
and Janet Levitt, 2000, Public Venture Capital:
Government Funding Sources for Technology Entrepreneurs (
Etzkowitz, Henry, and Loet Leydesdorff, 1995, The Triple Helix---University-Industry-Government Relations: A Laboratory for Knowledge-Based Economic Development, EASST Review 14(1), 14-19.
Etzkowitz, Henry, and Loet Leydesdorff (Editors), 1997, Universities in the Global
Economy: A Triple Helix of University-Industry-Government Relations.
Christopher (1982). The Economics of Industrial Innovation
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 (Editors), Technical Change and Economic Theory (Pinter, London), pp. 38-66.
Frenken, Koen, A Complexity Approach to Innovation Networks. The Case of the Aircraft Industry (1909-1997). Research Policy (this issue).
Frenken, Koen, and Loet Leydesdorff, Scaling Trajectories in Civil Aircraft (1913-1997), Research Policy (forthcoming).
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 (Sage, London).
Giddens, Anthony, 1984, The
Constitution of Society (Polity Press,
Godin, Benoît, 1998, Writing Performative History: Is This a New Atlantis? Social Studies of Science 38(3), 465-483.
Godin, Benoît, and Yves Gingras, The Place of Universities in the System of Knowledge Production, Research Policy (this issue).
Government-University-Industry Research Roundtable GUIRR, 1998,
National Science and Technology Strategies in a Global Context. Report
of an International Symposium (
Gustin, B, 1975, The Emergence of the German chemical
profession, 1790-1867. Ph.D. dissertation,
Thomas P., 1983, Networks of Power: Electrification of Western Society
Kaghan, William N., and Gerald B. Barnett, 1997, The Desktop Model of Innovation, in: H. Etzkowitz
and L. Leydesdorff (Editors), Universities in the
Global Economy: A Triple Helix of University-Industry-Government Relations
Kampmann, Christian, Christian Haxholdt, Erik Mosekilde, and John D. Sterman, 1994, Entrainment in a Disaggregated Long-Wave Model, in: L. Leydesdorff and P. Van den Besselaar (Editors), Evolutionary Economics and Chaos Theory: New Directions in Technology Studies (Pinter, London and New York), pp. 109-124.
Christopher G. (Editor), 1989, Artificial Life (Addison Wesley,
Leydesdorff, Loet, 1995, The
Challenge of Scientometrics: the development,
measurement, and self-organization of scientific communications.
Leydesdorff, Loet, 1997, The Non-linear Dynamics of Sociological Reflections, International Sociology 12, 25-45.
Leydesdorff, Loet, and Henry Etzkowitz, 1996, Emergence of a Triple Helix of University-Industry-Government Relations, Science and Public Policy 23, 279-286.
Leydesdorff, Loet, and Henry Etzkowitz, 1998, The Triple Helix as a model for innovation studies, Science and Public Policy 25(3), 195-203.
Leydesdorff, Loet, and Nienke Oomes, 1999, Is the European Monetary System Converging to Integration? Social Science Information 38(1), 57-86.
Leydesdorff, Loet, and Peter Van den Besselaar, 1997, Scientometrics and Communication Theory: Towards Theoretically Informed Indicators Scientometrics 38, 155-74.
Leydesdorff, Loet, and Peter van den Besselaar, 1998, Competing Technologies: Lock-ins and Lock-outs, in: Daniel M. Dubois (Editor), Computing Anticipatory Systems, Proceedings of the American Institute of Physics 437 (American Institute of Physics, Woodbury, NY) pp. 309-323.
Luhmann, Niklas, 1984, Soziale Systeme. Grundriß
einer allgemeinen Theorie (Suhrkamp, Frankfurt a. M.) [Social
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 (Editors), Technical Change and Economic Theory (Pinter, London), pp. 349-369.
Lundvall, Bengt-Åke (Editor), 1992, National Systems of Innovation. (Pinter,
MacLane, Saunders, 1996, Should Universities Imitate Industry? American Scientist 84(6), 520-521.
Maturana, Humberto R., 1978, Biology
of Language: The Epistemology of Reality, in: G. A. Miller and
McKelvey, Maureen D., 1996, Evolutionary Innovations:
The Business of Biotechnology (
Merton, Robert K., 1938, Science, Technology and Society
in Seventeenth Century
Merton, Robert K., 1942, Science and Technology in a Democratic Order, Journal of Legal and Political Sociology 1, 115-26.
C. Wright, 1958, The Power Elite (
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.
Richard R. (Editor), 1982, Government and Technical Progress: a
cross-industry analysis (
Richard R. (Editor), 1993, National Innovation Systems: A comparative study
(Oxford University Press,
Richard R., 1994, Economic Growth via the Coevolution
of Technology and Institutions, in: L. Leydesdorff
and P. Van den Besselaar (Editors), Evolutionary
Economics and Chaos Theory: New Directions in Technology Studies (Pinter,
Nelson, Richard, and Sydney Winter, 1975, Growth Theory from an Evolutionary Perspective: The Differential Productivity Growth Puzzle, American Economic Review 65, 338.
Richard R., and Sidney G. Winter, 1982, An
Evolutionary Theory of Economic Change (Belknap Press,
Neurath, Otto, Rudolf Carnap, and Hans Hahn, 1929, Wissenschaftliche Weltauffassung — Der Wiener Kreis (Veröffentlichungen des Vereins Ernst Mach, Vienna).
OECD, 1980, Technical Change and Economic Policy (OECD, Paris).
1981, Structural Change and Economic Growth (
Pavitt, K., 1984, Sectoral patterns of technical change: towards a theory and a taxonomy, Research Policy 13, 343-73.
Rip, Arie, and Barend Van der Meulen, 1996, The Post-modern Research System, Science and Public Policy 23(6), 343‑352.
Nathan, and Richard R. Nelson, 1994,
and Walter Zegveld, 1981, Industrial Innovation
and Public Policy (Pinter,
Sábato, Jorge, 1975, El pensamiento
latinoamericano en la p
Jorge, and M. Mackenzi, 1982, La producción de technología. Autónoma o transnacional (
Joseph , 1964, Business Cycles: A Theoretical, Historical and Statistical
Analysis of Capitalist Process (
Schumpeter, Joseph, 1966, Invention and Economic Growth
Sobel, D., 1995, Longitude (Penguin, Harmondsworth).
Storr, Richard, 1953, The Beginnings
of Graduate Education in
Weingart, Peter, 1997, From "Finalization" to "Mode 2": old wine in new bottles? Social Science Information 36(4), 591-613.
Ziman, John (1994). Prometheus Bound: Science in a Dynamic
Steady State (