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2012 | OriginalPaper | Buchkapitel

Mode 3 Knowledge Production in Quadruple Helix Innovation Systems

Twenty-first-Century Democracy, Innovation, and Entrepreneurship for Development

verfasst von : Elias G. Carayannis, David F. J. Campbell

Erschienen in: Mode 3 Knowledge Production in Quadruple Helix Innovation Systems

Verlag: Springer New York

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Abstract

Developed and developing economies alike face increased resource scarcity and competitive rivalry. In this context, science and technology appear as an essential source of competitive and sustainable advantage at national and regional levels. However, the key determinant of their efficacy is the quality and quantity of entrepreneurship-enabled innovation that unlocks and captures the benefits of the science enterprise in the form of private, public, or hybrid goods. Linking basic and applied research with the market, via technology transfer and commercialization mechanisms, including government–university–industry partnerships and capital investments, constitutes the essential trigger mechanism and driving force of sustainable competitive advantage and prosperity. In this volume, the authors define the terms and principles of knowledge creation, diffusion, and use, and establish a theoretical framework for their study. In particular, they focus on the “Quadruple Helix” model, through which government, academia, industry, and civil society are seen as key actors promoting a democratic approach to innovation through which strategy development and decision-making are exposed to feedback from key stakeholders, resulting in socially accountable policies and practices.

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See Carayannis, BILAT, March 2011, SAIS TRC, June 2011 and Springer JKEC, Fall 2011.

See Carayannis and Campbell, IJTM, 2009.

See Carayannis, BILAT, March 2011, SAIS TRC, June 2011 and Springer JKEC, Fall 2011.

See also Carayannis and Campbell 2011.

Furthermore, see Milbergs (2005).

See discussion on democracy in the conclusion of this article.

“Culture is the invisible force behind the tangibles and observables in any organization, a social energy that moves people to act. Culture is to the organization what personality is to the individual—a hidden, yet unifying theme that provides meaning, direction, and mobilization.” (Killman 1985).

Technology is defined as that “which allows one to engage in a certain activity …with consistent quality of output,” the “art of science and the science of art” (Carayannis 2001) or “the science of crafts” (Braun 1997).

We consider the following quote useful for elucidating the meaning and role of a “knowledge nugget” as a building block of the “Mode 3 Innovation Ecosystem”: “People, culture, and technology serve as the institutional, market, and socio-economic ‘glue’ that binds, catalyzes, and accelerates interactions and manifestations between creativity and innovation as shown in Fig., along with public-private partnerships, international Research & Development (R&D) consortia, technical / business / legal standards such as intellectual property rights as well as human nature and the ‘creative demon’. The relationship is highly nonlinear, complex and dynamic, evolving over time and driven by both external and internal stimuli and factors such as firm strategy, structure, and performance as well as top-down policies and bottom-up initiatives that act as enablers, catalysts, and accelerators for creativity and innovation that leads to competitiveness” (Carayannis and Gonzalez 2003, p. 593).

Of course there may also be systems of clusters and networks or clusters and networks of systems.

For an example of an interesting analysis of the applicability of systems or networks for the field of research policy, see Sylvia Kritzinger et al. (2006).

Carayannis and Zedwitz (2005).

Networking is important for understanding the dynamics of advanced and knowledge-based societies. Networking links together different modes of knowledge production and knowledge use, and also connects (subnationally, nationally, and transnationally) different sectors or systems of society. Systems theory, as presented here, is flexible enough for integrating and reconciling systems and networks, thus creating conceptual synergies.

Carayannis and Alexander (2004).

Carayannis and Alexander (1999a).

Carayannis (2001, pp. 169–170) discusses chaos theory and fractals in connection to technological learning and knowledge and innovation system architectures: “Chaos theory is a close relative of catastrophe theory, but has shown more potential in both explaining and predicting unstable non-linearities, thanks to the concept of self-similarity or fractals [patterns within patterns] and the chaotic behavior of attractors (Mandelbrot) as well as the significance assigned to the role that initial conditions play as determinants of the future evolution of a non-linear system (Gleick 1987). There is a strong affinity with strategic incrementalism, viewed as a third-order (triple-layered), feedback-driven system that can exhibit instability in any given state as a result of the operational, tactical, and strategic technological learning … that takes place within the organization in question.”

“A fractal is a geometric object which is rough or irregular on all scales of length, and so which appears to be ‘broken up’ in a radical way. Some of the best examples can be divided into parts, each of which is similar to the original object. Fractals are said to possess infinite detail, and some of them have a self-similar structure that occurs at different levels of magnification. In many cases, a fractal can be generated by a repeating pattern, in a typically recursive or iterative process. The term fractal was coined in 1975 by Benoît Mandelbrot, from the Latin fractus or ‘broken’. Before Mandelbrot coined his term, the common name for such structures (the Koch snowflake, for example) was monster curve. Fractals of many kinds were originally studied as mathematical objects. Fractal geometry is the branch of mathematics which studies the properties and behavior of fractals. It describes many situations which cannot be explained easily by classical geometry, and has often been applied in science, technology, and computer-generated art. The conceptual roots of fractals can be traced to attempts to measure the size of objects for which traditional definitions based on Euclidean geometry or calculus fail.” (http://en.wikipedia.org/wiki/Fractal).

On “innovation culture,” see also: Kuhlmann 2001, pp. 954, 958 and 962.

Figure 4 should be seen here as a suggestion, as an input for discussion. The conceptual feasibility of Fig. 4 still would have to be tested.

On interdisciplinarity (“Interdisziplinarität”), see Markus Arnold (2009, pp. 65–97).

For interesting examples of integrating and analytically combining research in the fields and disciplines of the social sciences and natural sciences, see: Gottweis 1998; Hindmarsh and Prainsack 2010; Prainsack and Wolinsky 2010.

On potential epistemic (epistemological) implications of the Quintuple Helix model for society-nature interactions and social ecology, see Campbell and Campbell (2011, pp. 15–16, 23–27).

Loet Leydesdorff (2012) launched the interesting intellectual experiment of engaging in theorizing on “N-Tuple of Helices” of innovation systems, introducing a multi-dimensional view perspective. In abstract terms, one may always refer to a structure (matrix structure) of N-Tuple Helices. However, in the models of innovation, being presented here, we propose concrete characteristics and properties of the Quadruple and Quintuple Helix so to transform these into meaningful tools for empirical analysis and application. There are also epistemic (epistemological) qualities of the Quadruple and Quintuple Helixes innovations systems.

This, of course, also challenges our external and internal governance models of higher education. For an overview on governance approaches in higher education, see Ferlie et al. (2008, 2009). See also Biegelbauer (2010). On structures and changes of universities, see also Krücken (2003a, 2003b), and Krücken et al. (2007).

In the German language, “university-related” would qualify as “außeruniversitär” (Campbell 2003, p. 99).

Hans Pechar and Lesley Andres (2011, p. 25) carried out an analysis that compared “welfare regimes and higher education”. While all OECD “…countries have experienced an unprecedented expansion in higher education during the second half of the twentieth century,” they “…differ, however, with respect to the significance of education, and more specifically, higher-education policies within their overall framework of welfare policies”. So Pechar and Andres (2011, p. 25) “employ the concept of the ‘welfare regime’ and a ‘trade-off’ hypothesis to understand the different national approaches to higher-education”. Concerning “welfare-state regimes,” Pechar and Andres refer to a typology of Gøsta Esping-Andersen. Esping-Andersen (1990, pp. 50–54) identifies three types of welfare regimes (see also Pechar and Andres 2011): liberal welfare regimes (for example Canada and the U.S., Australia and New Zealand, the UK); conservative welfare regimes (for example Austria, France, Germany, the Netherlands and Belgium, Switzerland, Italy); and social-democratic (universal) welfare regimes (for example Norway, Sweden, Denmark, and Finland).

“Fortgesetzt, bezogen auf Modelle über oder von ‘Kausalität’, ließe sich andenken, die Wenn-dann-Beziehungen (‘if-then relations’) mit systematischen Wenn-wenn-Beziehungen (‘if-if relations’) zu ergänzen” (Campbell 2009, p. 123).

For a short discussion on whether or not the IFF Faculty for Interdisciplinary Studies (iff Fakultät für Interdisziplinäre Forschung und Fortbildung), at the Alpen-Adria-University Klagenfurt, qualifies to represent a Mode 3 type of organization in higher education, see Campbell (2009, pp. 122, 127).

On evaluation, quality management and quality enhancement in higher education in more general, see also: Blimlinger et al. 2010; Campbell 2003; Jacob 2007; Teichler 2006.

The tenure-track model represents a well-established standard model for academic careers in higher education, particularly for the core faculty at universities and other higher education institutions. Already earlier in our analysis we introduced the idea of “cross-employment” or “multi-employment,” where a faculty member or knowledge worker would have employment relations with different organizations or institutions (within the same sector or cross-cutting alternative sectors) at the same time. Cross-employment, therefore, allows individuals to opt for “parallel careers” within and/or outside academia. It remains to be seen, whether cross-employment has the capability to establish itself as an additional and positively-defined role model for academic careers in higher education, in parallel to the already existing role mode of tenure-track (tenure).

The “academic firm,” as a notion and concept, was first developed by Campbell and Güttel (2005).

In many contexts, this second option appears to be more realistic, particularly when we analyze multinational companies or corporations (MNCs) that operate in global context.

Another branch of knowledge can be based on education and its diversified manifestations.

As an example for a reviewing of innovation policy in context of a national innovation system, see the analysis of Guy Ben-Ari (2006) on Israel.

A possible acronym here may be: MLIS or MLISs.

In that context also the mutual overlapping between R&D, S&T and ICT (information and communication technology) should be stressed.

On sectoral systems of innovation, see also in greater detail in later sections of our analysis.

Should we add a further comment to the concepts of Mode 1 and Mode 2, it would be interesting to consider, how Mode 1 and Mode 2 relate to the notions of “Science One” and “Science Two,” which were developed by Umpleby (2002).

Concerning a further-going discussion of the Technology Life Cycles, see: Cardullo 1999; Tassey 2001.

A political mode could be seen as a particular political approach (clustering political parties, politicians, ideologies, values, and policies) to society, democracy, and the economy. Conservative politics, liberal politics or social democratic politics could be captured by the notion of a “political mode”.

For a short review on “embedded systems research” in Austria, see the analysis by Prem (2005).

Here again aspects and criteria such as the advertisement or “attention economy” (Davenport and Beck 2001) could be mentioned.

This may create opportunities for the Academic Firm. We introduced the academic firm as a concept already earlier.

Perhaps, only when the whole world is being defined as one global knowledge cluster and innovation network, then, for the moment, we cannot aggregate and escalate further to a mega-cluster or mega-network.

For example, Joseph A. Schumpeter (1942, Chaps. XX–III) emphasized this method-based criterion for democracy.

For more information on Freedom House, see on the internet: http://www.freedomhouse.org/template.cfm?page=1.

On the web, the Democracy Ranking can be visited under: http://www.democracyranking.org/en/.

For attempts, trying to analyze the quality of a democracy, see for example Campbell and Schaller (2002).

On “democratic innovation,” see, furthermore, Saward (2006).

The disjointed incrementalism approach to decision making (also known as partisan mutual adjustment) was developed by Lindblom (1959, 1965) and Linblom and Cohen (1979) and found several fields of application and use: “The Incrementalist approach was one response to the challenge of the 1960s. This is the theory of Charles Lindblom, which he described as ‘partisan mutual adjustment’ or disjointed incrementalism. Developed as an alternative to RCP, this theory claims that public policy is actually accomplished through decentralized bargaining in a free market and a democratic political economy” (http://www3.sympatico.ca/david.macleod/PTHRY.HTM).

“Studies have shown that the early period of a new area of technology is often characterized by technological ferment but that the pace of change slows after the emergence of a dominant design” (http://www.findarticles.com/p/articles/mi_m4035/is_1_45/ai_63018122/print).

The term constitutes the brainchild or conceptual branding of the authors as part of this journey of discovery and ideation.

View again “Democratic Innovation,” edited by Michael Saward (2006). There is always a need to evaluate different policy fields of politics in reference to the values of democracy and the quality of democracy, for example asylum policy (Rosenberger 2010).

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Titel: Mode 3 Knowledge Production in Quadruple Helix Innovation Systems
verfasst von: Elias G. Carayannis
David F. J. Campbell
Verlag: Springer New York
Buch: Mode 3 Knowledge Production in Quadruple Helix Innovation Systems
Print ISBN: 978-1-4614-2061-3

Electronic ISBN: 978-1-4614-2062-0

Copyright-Jahr: 2012
DOI: https://doi.org/10.1007/978-1-4614-2062-0_1