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Vol. 1, No. 1
January-March 2010
InternatIonal Journal of
An official publication of
the Information Resources
Management Association
Social Ecology
and SuStainablE
dEvElopmEnt
Publisher of IT books, journals and cases since 1988
www.igi-global.com
IGI PUBLISHING
Dimitris Assimakopoulos, U. of Grenoble, France
Yannis Bakouros, U. of Western Macedonia, Greece
Ayse Bobeyi, World Bank, USA
Carlos Braga, World Bank, USA
JJ Chanaron, CNRS and U. of Grenoble, France
Denis Ciof, Solar Institute and George Washington
U. School of Business, USA
Phil Cooke, Cardiff U., UK
Raoul de Gouvea, U. of New Mexico, USA
Sylvie Faucheux, Versailles Saint-Quentin-en-
Yvelines U., France
Piero Formica, U. of Bologna, Italy
Jian Gao, Tsinghua U., China
Elie Geisler, Illinois Institute of Technology, USA
Susan Holleran, International Finance Corporation
(IFC) - World Bank, USA
Wu Jisong, U. of Beijing, China
Aris Kaloudis, NIFU STEP, Norway
Sul Kassicieh, U. of New Mexico, USA
Nicos Komninos, URENIO and Aristotle U. of
Thessaloniki, Greece
Mihalis Koratzinos, CERN, Switzerland
Tzong-Ru (Jiun-Shen) Lee, National Chung Hsing
U., Taiwan
Chun Liao, Shanghai U., China
Mathew Manimala, Indian Institute of Information
Technology - Bangalore, India
Thomas Mickiewicz, U. College London, UK
Denisa Popescu, World Bank, USA
Norbert Seel, U. of Freiburg, Germany
Caroline Sipp, Inter-American Development Bank,
USA
Mark Starik, Institute for Corporate Responsibility -
George Washington U., USA
Fred Steward, PSI, UK
Spyros Vliamos, U. of Athens, Greece
Max von Zedtwitz, Tsinghua U. & IMD, Switzerland
Vivienne Wang, United Nations Development
Program, USA
Yilu Zhou, George Washington U. School of
Business, USA
Editor in Chief: Elias G. Carayannis, George Washington U., USA
Chief Associate Editor: David FJ Campbell, U. of Klagenfurt, Austria
Associate Editors: Siau Ching Lenny Koh, U. of Shefeld, UK
Chris Ziemnowicz, The U. of North Carolina, USA
IGI Editorial : Heather Probst, Director of Journal Publications
Chris Hrobak, Journal Publishing Lead
International Editorial Review Board:
IGI Pu b l I s h I n G
w w w .i g i -g l o b a l .c o m
IGIP
IJSESD Editorial Board
January-March 2010, Vol. 1, No. 1
i Elias G. Carayannis, Editor-in-Chief, JSESD
1 21ST Century Democratic Capitalism:
Elias G. Carayannis, GWU, USA
Aris Kaloudis, NIFU STEP, Norway
14
P.P. Nikhil Raj, Sálim Ali Centre for Ornithology and Natural History (SACON), India
P. A. Azeez, Sálim Ali Centre for Ornithology and Natural History (SACON), India
20
China
Huiqiang Cheng, Beijing University of Technology, P. R. China
Xiang-Yun Du, Aalborg University, Denmark
30
Yang Laike, East China Normal University, China
Liao Chun, Shanghai LiXin University of Commerce, China
41
Elias G. Carayannis, George Washington University, USA
David F. J. Campbell, University of Klagenfurt, Austria
In t e r n a t I o n a l Jo u r n a l o f
So c I a l ec o l o g y a n d Su S t a I n a b l e
de v e l o p m e n t
Table of Contents
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 41
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Keywords: Eco-Entrepreneurship, Eco-Innovation, Mode 3, Quadruple Helix, Quintuple Helix, Social
Ecology, Sustainable Development
Triple Helix, Quadruple Helix
and Quintuple Helix and How
Do Knowledge, Innovation
and the Environment
Relate To Each Other?
A Proposed Framework for a
Trans-disciplinary Analysis of Sustainable
Development and Social Ecology
Elias G. Carayannis, George Washington University, USA
David F. J. Campbell, University of Klagenfurt, Austria
ABSTRACT
This article develops an inter-disciplinary and trans-disciplinary framework of analysis that relates knowl-
edge, innovation and the environment (natural environments) to each other. For that purpose the ve-helix
structure model of the Quintuple Helix is being introduced. The Triple Helix model, designed by Etzkowitz
and Leydesdorff (2000), focuses on the relations of universities, industry and governments. The Quadruple
Helix (Carayannis & Campbell, 2009) blends in the perspective of a media-based and culture-based public.
The Quintuple Helix nally frames knowledge and innovation in the context of the environment (natural
environments). Therefore, the Quintuple Helix can be interpreted as an approach in line with sustainable
development and social ecology. “Eco-innovation” and “eco-entrepreneurship” should be processed in such
a broader understanding of knowledge and innovation.
DOI: 10.4018/jsesd.2010010105
42 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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is prohibited.
1. INTRODUCTION: THE
DRAFTING OF A PROPOSED
FRAMEWORK FOR A
TRANSDISCIPLINARY
ANALYSIS OF SUSTAINABLE
DEVELOPMENT AND
SOCIAL ECOLOGY
This article is being guided by the following key
research question: How do knowledge, innova-
tion and the environment (natural environment)
relate to each other? Advanced or advancing
knowledge and innovation systems (across a
multi-level architecture of sub-national, national
and trans-national levels) could be characterized
by a pluralism of knowledge and innovation
modes. In fact, a certain co-evolution or congru-
ence between advanced knowledge (innovation)
systems and advanced (high-quality) democ-
racy may be stated, postulating that advanced
knowledge and innovation take over some of
the structural elements of a democracy, such as
pluralism and diversity.
Referring to the research question as con-
ceptual point of departure, our final objective
is to design and to propose for discussion an
interdisciplinary and transdisciplinary frame-
work of analysis for sustainable development
and social ecology that exactly ties together
knowledge, innovation and the environment.
This model we will call the Quintuple Helix, a
five-helix model that embeds the Triple Helix
and the Quadruple Helix. Triple Helix focuses
on knowledge production and use in context
of “university-industry-government relations”
(Etzkowitz & Leydesdorff, 2000). Quadruple
Helix extends the Triple Helix by adding the
helix of a “media-based and culture-based
public” (Carayannis & Campbell, 2009). The
Quintuple Helix contextualizes the Triple
Helix and Quadruple Helix by further adding
on the helix of the “environment” (“natural
environments”). The Quintuple Helix thus of-
fers an analytical frame or framework where
knowledge and innovation, on the one hand,
are being connected with the environment, on
the other. By this the Quintuple Helix addresses
and incorporates features of “social ecology”.
Furthermore, the Quintuple Helix also can
be seen as a framework for interdisciplinary
analysis and transdisciplinary problem-solving
in relation to sustainable development, because
a comprehensive understanding of the Quintuple
Helix clearly implies that knowledge produc-
tion and use as well as innovation must be set
in context or must be contextualized by the
natural environment of society.
The analytical program of work of this
article will be as follows. In Chapter 2 we pres-
ent an overview of key concepts on knowledge
and innovation, also attempting to trace their
conceptual evolution. Pivotal are innovation and
the national or multi-level innovation systems.
Innovation overlaps or even coincides with the
application, diffusion and use of knowledge.
Chapter 3 summarizes the knowledge and inno-
vation concepts of Mode 1 and Mode 2 (Gibbons
et al., 1994), Triple Helix, and reviews in detail
Mode 3 and Quadruple Helix (Carayannis &
Campbell, 2009). More particularly, we focus in
this article section also on phenomena or trends
of a continuously broader contextualization
of knowledge and on the broadening of some
concepts of democracy. The proposition would
be to state a co-evolution (or certain congruence)
between knowledge and (high-quality) democ-
racy. In the conclusion, Chapter 4, we finally
introduce the Quintuple Helix in reflection of
our principal research question.
2. WHAT ARE KNOWLEDGE
AND INNOVATION? OVERVIEW
OF CONCEPTS AND THE
EVOLUTION OF CONCEPTS
The Wikipedia definition of knowledge, also
cross-referencing to the Oxford English dic-
tionary, lists as a crucial element of knowledge
“the theoretical or practical understanding of a
subject”. The Wikipedia definition furthermore
associates knowledge to “expertise, and skills”
that a person may have gained either by expe-
rience or through education.1 Currently, there
exists a general belief (indicated by numerous
publications) that knowledge becomes increas-
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 43
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ingly important for society, the economy and
also democracy. Advancements and a sustain-
able development of society and the economy
appear unlikely without leveraging and en-
hancing knowledge. This adds plausibility for
using concepts such as the knowledge-based
society, the knowledge-based economy and the
knowledge-based democracy (Carayannis &
Campbell, 2009, p. 224). Perhaps there is even a
shift not only to speak of the knowledge-based
society and economy, but of a knowledge society
and a knowledge economy per se that is being
endogenously driven by knowledge. The con-
cept of a knowledge democracy consequently
complements such propositions.
One could set up two conceptual axes, try-
ing to model knowledge and different types of
knowledge in greater detail (Campbell 2009).
One axis may polarize “codified” (explicit) with
“tacit” knowledge (see, for example, Gibbons
et al., 1994, pp. 167-168). Tacit knowledge
represents an experience-based knowledge,
whereas codified knowledge is written down in
the one or other form. The other axis could po-
larize knowledge that is less dependent or more
dependent on the context: a possible conceptual
wording would juxtapose (compare) knowledge
that is “independent of users and/or appliers”
with a knowledge that is “dependent of users
and/or appliers”. Here differing degrees of con-
textualization of knowledge become manifest
and evident. The closer a knowledge places to
“codified” and “user-independent”, the more
this knowledge is “information”. Contrarily,
the closer a knowledge places to the poles of
tacit and user-dependent, the more various
types of “competencies” are being expressed.
Competencies again stretch from professional
or expert knowledge (know-how) to social
competencies (soft skills, intercultural compe-
tencies) and competences of the personality.2
Higher education teaching, currently, stresses
the notion of “desired learning outcomes” that
become visible as competencies acquired by
students. Kathleen E. Schafer (2008, p. 276)
discusses prospects of a new “era of balanced
leadership” in context of political leadership:
this clearly would require mature social com-
petences on the part of politicians.
Complementary to the above depicted
modeling of knowledge based on the two axes
of codified/tacit and user-independent/user-
dependent, an alternative modeling could focus
more on aggregated features of knowledge,
emphasizing systemic aspects and embedding
knowledge in a larger societal context. Here
several axes (or dimensions) may be discussed
for a broader systemic approach (see also
Carayannis & Campbell, 2009, pp. 214-215):
(1) research, R&D (research and experimental
development): conventionally, research is being
distinguished in basic research, applied research
and experimental development (OECD, 1994, p.
29; 2002, p. 30)3; (2) education: education can
refer to primary education, secondary education
and tertiary education, where tertiary education
is the education being offered by universities
or the higher education system (containing all
HEIs, the higher education institutions) in more
general; (3) innovation; (4) different spatial
axes, which represent geographic, geographic-
spatial or spatial-political concepts, distinguish-
ing between the sub-national (local), national
and trans-national (supranational, global) levels;
(4) perhaps also other non-spatial axes would be
possible, for example “creativity” and attempts
of displaying and measuring creativity.
Focusing on research (R&D), the so-called
“linear model of innovation” was prevailing
for a long time. This linear model leverages
on the fact that the universities (the HEIs)
concentrate on basic research (often or mostly
publicly funded), while firms concentrate on
experimental development (often or mostly
privately financed) (for the U.S., see National
Science Board, 2008, Volume 1, Chapter 4, pp.
14-15). Applied research often is being seen to
position itself “between” basic research and
experimental development. This is carried by the
underlying understanding that ideas, products
or services start as a basic research in context
of universities, and gradually diffuse time-
lagged into society and the economy. Firms
selectively pick up some basic research results
and convert these through applied research and
44 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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experimental development into commercially
profitable products or services for the market.
Challenges obviously are how to design sys-
tematically interfaces and linkages between
publicly funded basic university research and the
privately funded firm-based commercialization
of research for profitable business activities.
Potential risks (or market failures) could be a
private under-investment of research or of basic
research (Tassey, 2001, pp. 42, 61-64). Kline
and Rosenberg (1986) and Miyata (2003, p.
715) describe the linear model as a sequence
of the following concepts: basic research; ap-
plied research; development; production; and
marketing. This “simple linear model” Narin
et al. (1997, p. 318) summarize as: “The notion
that technology springs from a scientific base
was originally embedded in the ‘linear model’
of innovation: from basic research through ap-
plied research continuing into technology and
resultant economic benefit.” Lundval (1992,
p. 13) paraphrases this also as a “linear model
of technical change”. Interestingly, this linear
model of innovation often is being closely as-
sociated with Vannevar Bush and his pivotal
report Science The Endless Frontier (Bush,
1945, see the chapter on “The Importance of
Basic Research”). Narin et al. (1997, 317-318)
claim this implicitly and in substance this as-
sociation of the linear innovation model to Bush
appears correct. At the same time, however, it
should be mentioned that Bush himself, in his
famous text, not even mentions the word “in-
novation” (as can easily be verified by an elec-
tronic word search command). Currently, the
linear innovation models are being challenged
by non-linear innovation models that stress the
importance of a simultaneously coupling of
basic (university) research with the commercial
R&D applications of firms in the business sec-
tors. Kline and Rosenberg (1986) propose to
introduce here a so-called “chain-linked model”
(see also Miyata 2003, p. 716). The underlying
concept is to cross-link mutually and directly
basic university research and the applied R&D
commercialization in firms, but also to foster
basic business research and applied research in
universities (Carayannis & Campbell, 2009, p.
209-211). In metaphoric terms, the first-then
(“zuerst-dann”) relationships in the linear
model are being extended by simultaneously-
simultaneously (“gleichzeitig-gleichzeitig”)
relations and network configurations in non-
linear knowledge arrangements (Campbell,
1995, p. 31). Originally “sequenced” processes
are being “parallelized” (Campbell and Güttel,
2005, pp. 167-168; Carayannis & Campbell,
2009, p. 217).
In a systemic (social, societal) under-
standing, knowledge creation and knowledge
production often are associated more closely to
research, basic research and the sciences, thus a
function of universities (HEIs), embedded in a
national or multi-level innovation system, is to
focus exactly on knowledge creation and knowl-
edge production.4 Of course, also other organi-
zations, such as firms, can focus and specialize
on knowledge production. Knowledge creation
and production are being complemented by the
concepts of knowledge application, knowledge
diffusion and knowledge use. This could imply
to think of two sides of knowledge: knowledge
creation and production on the one hand, and
knowledge application and use on the other
(see Figure 1). Knowledge application and
knowledge use already overlap substantially
with the concept of innovation that could be
defined as: innovation leverages knowledge
for knowledge application, diffusion and use,
and thus translates knowledge into application.
This definition of innovation has references to
knowledge and leaves the question open (and un-
resolved), whether there could be an innovation
without knowledge (Carayannis & Campbell,
2009, pp. 213-214). There exists basic research5,
“pure research” or “pure science”6 that is not
interested in issues of application and innova-
tion. Whether an innovation, for example some
forms of management innovations in business
that are not R&D or technology-based, can
qualify as an innovation without linkages to
knowledge, could be debated. But there can
be innovations that are not connected to basic
research (for an overview on innovation, see
Shavinina, 2003). S&T, science and technology,
also spans to both poles of knowledge: science
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 45
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locates more closely to knowledge creation and
production, while technology associates closer
to knowledge application, use and innovation.
Technology may be interpreted as a type of in-
novation (often with a technological hardware
component), interested in converting science
(basic research) into commercial application
and use.
The concept of the “national system of
innovation” (or national innovation system)
was developed by the two scholars Bengt-Åke
Lundvall (1992) and Richard R. Nelson (1993).
This approach contextualizes innovation in
the context of societies at the level of nation
states. Lundvall (1992, p. 2) offers the follow-
ing key definition: “It follows that a system
of innovation is constituted by elements and
relationships which interact in the production,
diffusion, and use of new, and economically
useful, knowledge and that a national system
encompasses elements and relationships, either
located within or rooted inside the borders
of a nation state.” For Lundvall (1992, p. 1)
knowledge constitutes the “most fundamental
resource” and learning the “most important
process” in a modern economy. In that line of
argument we might postulate the following re-
lationship: (1) innovation leverages or translates
knowledge into application and use; (2) applied
or used knowledge always or often or at least
potentially may also be used economically for
economic purposes, for generating financial
revenues and profit; (3) thus innovation also
converts (potentially) knowledge creation and
production into economic activities.
Lundvall (1992, pp. 3-4) acknowledges that
processes of globalization and regionalization
weaken the national systems: “international
specialization was often reflected in a regional
specialization within the countries.”7 Despite
the recognition of such sub-national and
trans-national innovation processes, Lundvall
emphasizes that national patterns still exist and
still play a key role, providing continued plausi-
Figure 1. Conceptualization of (a possible) relationship of knowledge and innovation
46 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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bility for the concept of the national innovation
system: “… we believe that national systems
still play an important role in supporting and
directing processes of innovation and learning.”
The modern nation states acted as “engines of
growth” (Lundvall, 1992).8 Stefan Kuhlmann
(2001, p. 972) also stresses the dominance of
nation-state-structures for the current political
systems: “political systems are still nationally
based, but are, in Europe, spreading increasingly
both to the transnational and to the regional
level”. Lundvall (1992, p. 5) diagnoses that
the concepts of the national innovation systems
“already entered the everyday vocabulary of
policymakers”. This supports opportunities of
and for a cross-country learning. Interestingly,
depending on the level of aggregation or the
level of analysis, as Lundvall (1992, p. 7) says,
innovation systems might differ in their ambi-
tions and goals: the national level emphasizes
“international competitiveness of the national
economy”; at the level of international organiza-
tions the efforts concentrate on “strengthening
economic growth” and “avoiding international
conflicts”; at the global level ambitions focus on
the “long term survival of the global economy”
that depend on “ecological sustainability” and
a “reduction of the extreme social inequality”.
In the conceptual framing of Lundvall, moving
bottom-up upward, the forces of learning gain
in importance.
In further reflection of the concept of the
national innovation system, now the concept of
multi-level systems of innovation has entered the
discourse.9 Multi-level systems of innovation
may be based on a geographic, spatial, geograph-
ic-political or spatial-political understanding,
juxtaposing, for example, sub-national, national
and trans-national levels in one framework.
Kuhlmann (2001, pp. 970-971, 973) speaks
of “multi-level, multi-actor systems” and of
“multi-level innovation policy”. Robert Kaiser
and Heiko Prange (2004, pp. 395, 405-406) use
the terms of a “multi-level governance system”
and discuss perspectives “from national to
multi-level innovation systems”. In addition
to such “spatial axes”, a multi-level system of
innovation also could be based on “non-spatial
axes”, or, to be more precise, on non-spatial axes
of knowledge aggregation (Campbell, 2006, p.
70; Campbell & Carayannis, 2006, pp. 11-14;
Carayannis & Campbell, 2009, pp. 214-216).
For example: innovation may be regarded as the
highest form of knowledge aggregation of re-
search (of the axis of research). Conventionally
understood, technology is broader than research,
and innovation again is broader than technology
(Campbell & Güttel, 2005, p. 154; Carayannis
& Campbell, 2006, pp. 14-15). In that line of
argument, innovation may also qualify as the
broadest aggregation of knowledge of education
(the axis of education). Rephrasing the above
said, a multi-level innovation system could be
based on several spatial and non-spatial axes
that display different levels of (spatial and non-
spatial) knowledge aggregation.
Earlier in this chapter we proposed for
innovation the definition of converting knowl-
edge creation and production to knowledge
application, diffusion and use. From that logic
it follows that, in principle, everything may
qualify as belonging to a national (or multi-
level) system of innovation that supports such
processes and structures of knowledge applica-
tion. How narrowly or how broadly (national)
innovation systems are being defined, therefore,
will differ and is interdependent with a concrete
historical context. Depending on whether we
believe or not believe in that an institution or
structure should be associated to knowledge
and innovation processes, this institution or
structure would play a function for innovation
and thus would be a part (or not) of the (na-
tional) innovation system. In a society, where
knowledge is being associated primarily with
knowledge creation and production in context
of universities and higher education systems,
and only few structural linkages to society and
the economy, the “extension” of a national in-
novation system is more limited. In a society
and economy, emphasizing knowledge applica-
tion, diffusion and use, the national innovation
system obviously “broadens” and becomes
increasingly powerful. Even culture (at least
partially) could belong to the innovation sys-
tem. Kuhlmann (2001, pp. 954, 958, 967), for
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 47
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example, speaks of “innovation cultures”, thus
going clearly beyond a primarily institutional
approach. In the words of Lundvall (1992, pp.
12-23): “In different historical periods differ-
ent parts of the economic system, or different
inter-faces between subsystems, may play a
more or less important role in the process of
innovation”.
The more knowledge application and
knowledge use represent issues of interest,
in a practical sense but also theoretically and
conceptually, the more encompassing the na-
tional or multi-level innovation systems behave.
The ultimate ratio would be that of a society
or an economy that convert to a full and real
knowledge society and knowledge economy,
where almost everyone acts also as a knowl-
edge worker, and with an innovation system
stretching far out and into the peripheries of
society. Kuhlmann (2001, p. 972) accentuates
aspects of a “co-evolution” between the “po-
litical systems” and “innovation systems”. The
innovation system also could be understood as
a system that cross-cuts into other systems of
society, such as the political system, the research
(R&D) system, the education system and the
economic system. The political system may
try to influence the economic system directly
with economic policy-making. Alternatively,
the political system could be inclined to impose
effects on the economic system via innova-
tion policy. Innovation policy, then, would
be an economic policy that cross-references
to knowledge and that leverages knowledge:
“Through innovation policy, however, which
recognizes more specifically the conditions
and ramifications of knowledge, the political
system also projects an indirect and mediated,
knowledge-tailored influence on the economic
system, “This understanding underscores the
interpretation and valuation of the innovation
system as an interface between politics and the
economy” (Carayannis & Campbell, 2006, pp.
18, 16-19).
What results, so the proposition, are forms
of an “indirect coupling” between politics and
the economy. One could even hypothesize that
the more advanced a society and economy
progress, we should expect at least a partial
conversion or transformation from economic
policy to innovation policy. Represents innova-
tion policy a further developed form of economic
policy in context of the knowledge society
and knowledge economy? “For an advanced,
knowledge-based democracy, knowledge and
innovation policies qualify as a superior next-
stage development of ‘old’ economic policies,
and the degree of conversion from economic to
knowledge and innovation policies may serve
as a ‘maturity test’ for governance and policy-
making” (Carayannis & Campbell, 2007, pp.
87-88). However, we also want to stress that
there are manifold opportunities for innovation
policy that are not necessarily associated with
economic activities.
While “innovation” could be modeled
as a top-down process (systemically linking
knowledge production to knowledge applica-
tion), “invention”, on the other hand, may be
modeled as a bottom-up process. “Creativity”
can move top-down as well as a bottom-up
(Carayannis & Campbell, 2007, p. 85). The
Wikipedia definition of creativity emphasizes
the “generation of new ideas or concepts” and
“new associations of the creative mind between
existing ideas or concepts”. 10This implies that
the creation and production of new knowledge
already qualify as examples of and for creativ-
ity. Further propositions are (see again Figure
1): (1) Creativity in knowledge creation and
production is being linked by innovation to
knowledge application and use in the wider
society. (2) Without creativity, the knowledge
input for the innovation process might face
serious constraints. (3) In addition, creativ-
ity can also focus on improving processes of
innovation on the application and use “side
of knowledge”. Creativity management is
interested in developing, controlling, regulat-
ing, and optimizing creativity for organizations
(Dubina, 2005; 2007; 2009). The concept of the
“creative knowledge environments” (CKEs)
focuses on those environments and contexts that
foster creativity in producing new knowledge
and new innovations (Hemlin et al., 2004).11
That line of thinking emphasizes to interpret
48 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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new knowledge as a creative knowledge.12
Or to rephrase: new knowledge qualifies as a
potential candidate for a creative knowledge.
This “construction” of creativity as a new
knowledge or a new production of knowledge
obviously also brings “art” into play. Fiction
or science fiction may serve as stimulators for
creative ideas, with the potential of being later
transformed, at least partially (and of course
not always), into new knowledge creation and
production. We can also call this the creativity
of knowledge creation.
2.1 Summary of Chapter 2
Analyses of knowledge originally focused
more on the knowledge creation and produc-
tion. Universities and other HEIs were at the
core, delivering basic research and educational
functions. Innovation as a concept was either
not mentioned literally (for example, Bush,
1945) or had a conservative connotation. Joseph
Schumpeter, for example, does not make a
strong connection to knowledge in his definition
of innovation, as is being expressed by the fol-
lowing quote about innovation (taken from Mi-
yata, 2003, p. 715): “(1) an introduction of new
products (or products with improved quality);
(2) new method of production; (3) new markets
and distributing channels; (4) new sources of
supply and inputs; (5) new organizations of an
industry” (Schumpeter, 1934, p. 66).
Later approaches emphasize the connection
of innovation to knowledge by interpreting in-
novation as a knowledge application, diffusion
and use. Now, innovation is being regarded as
essential for the leveraging and “fuelling” of
knowledge into the society and economy of a
knowledge society and a knowledge economy.
Innovation carries knowledge far into society,
fills all of society with knowledge. Often (not
always) this applied knowledge has roots in
processes of knowledge creation and production
in types and arrangements of basic research.
This inclusion of innovation into the concep-
tualization of knowledge has the effect that the
concept of knowledge is being “broadened” and
contextualized by society. Knowledge is also a
social process. Without references to society
and social applications and the problem-solving
potentials of knowledge, knowledge cannot be
understood sufficiently anymore. Knowledge
application and use feed back directly into
knowledge creation and production (non-linear
innovation models). Concepts such as the na-
tional systems of innovation (Lundvall, 1992;
Nelson, 1993) or the multi-level innovation sys-
tems (Kuhlmann, 2001; Kaiser & Prange, 2004;
Carayannis & Campbell, 2006) emphasize these
aspects of a society-wide stretch of knowledge.
Economic policy is being partially replaced by
innovation policy (Carayannis & Campbell,
2006; 2007). Carrying such ideas consistently
further, this also implies that knowledge pro-
duction and knowledge application, from a
systemic perspective, should not only reflect
the context of society, but, in addition, also the
environmental context of society. Knowledge
is being contextualized by society, but also by
the (natural) environments of society.
3. MODE 1, MODE 2 AND
MODE 3: TRIPLE HELIX
AND QUADRUPLE HELIX
The author team of Gibbons, Limoges, No-
wotny, Schwartzman, Scott, and Trow (Gib-
bons et al., 1994)13 distinguishes between two
different modes of knowledge production.
“Mode 1” focuses on the traditional role of
university research in an elderly “linear model
of innovation” understanding. This reflects a
basic university research, interested in “first/
basic principles” and “discoveries”, with a
disciplinary research structure, where quality is
being controlled primarily by disciplinary peers
or a disciplinary peer review process. These
disciplinary peers exercise a strong quality gate
keeper function and represent also a university
(higher education) system with powerful hi-
erarchies, built into the institutions (Gibbons
et al., 1994). Success in Mode 1 (of Mode 1
university research) is defined as a quality or
excellence that is approved by hierarchically
established peers: “Success in Mode 1 might
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 49
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perhaps be summarily described as excellence
by disciplinary peers” (Gibbons et al., 1994).
Mode 1 is not concerned with the application,
diffusion and use of knowledge, and Mode
1 does not focus on features in relation to
problem-solving for the society or the economy.
Non-linear innovation models are of no major
concern for Mode 1.
Mode 2 knowledge production, on the
contrary, can be characterized by the follow-
ing five principles: (1) “knowledge produced
in the context of application”; (2) “transdis-
ciplinarity”; (3) “heterogeneity and organi-
zational diversity”; (4) “social accountability
and reflexivity”; (5) and “quality control”.
Mode 2 represents a “problem solving which
is organized around a particular application”
and where: “Knowledge production becomes
diffused throughout society. This is why we
also speak of a socially distributed knowledge”
(Gibbons et al., pp. 3-4). In Mode 2 the terms
“discovery”, “application” and “fabrication”
(also fabrication of knowledge) overlap. Exploi-
tation of Mode 2 knowledge demands, at least
to a certain extent, actual participation in the
knowledge production process. Prerequisites of
Mode 2 were (are) the massification of tertiary
higher education, followed by a considerable
spill-over of higher education graduates and
higher education knowledge (competencies)
into society. Advancing IT technologies al-
lowed an effective communicative link-up
of those different knowledge-competent sites
outside of the universities and the higher edu-
cation sector. Continuous communication and
negotiations between knowledge producers
are crucial. Manifold network arrangements
are necessary features for linking together
knowledge producing sites “through function-
ing networks of communication” (Gibbons et
al., 1994, p. 6).
The principle of transdisciplinarity under-
scores the primacy of problem-solving in Mode
2, for which different disciplinary knowledge
may be combined or recombined in conventional
or unconventional formats. The purity of disci-
plinary knowledge does not define a criterion
of concern. Transdisciplinarity, according to
Mode 2, should develop “a distinct but evolving
framework to guide problem solving efforts”,
is not interested in establishing new academic
disciplines, and represents a “problem solving
capability on the move” (Gibbons et al., 1994,
p. 5). Tacit knowledge (embedded in individual
persons or organizations) is as valid or relevant
as codified knowledge (written down or stored).
In epistemic terms, researchers, in Mode 2, “do
not concern themselves with the basic prin-
ciples of the world but with specific ordered
structures within it” (Gibbons et al., 1994, p.
24). Therefore, one may postulate that Mode 2
resembles a transdisciplinary problem-solving
knowledge, where: “knowledge production in
Mode 2 occurs within transient contexts of
application” and with “knowledge producers
with many different institutional affiliations,
either simultaneously or sequentially” (Gibbons
et al., 1994, p. 33). Success in Mode 2 means
that knowledge was useful or that a knowledge
production contributed effectively to a problem-
solving in society or the economy: “In Mode 2
success would have to include the additional
criteria such as efficiency or usefulness, defined
in terms of the contribution the work has made
to the overall solution of transdisciplinary prob-
lems”, and the quality control is being exercised
by the “community of practitioners” that do not
follow the structure of an institutional logic of
academic disciplines (Gibbons et al., 1994, p.
33). Mode 2 demands more social account-
ability and reflexivity, and a greater sensitivity
for the impact of knowledge on society and the
economy. Values of individuals and of groups
must be reflected, to allow social acceptance
for a particular problem-solving approach.
The authors of Mode 2 (Gibbons et al., 1994)
postulate that Mode 2 developed out of Mode
1. Furthermore, there is a parallel existence
of Mode 2 and Mode 1 with co-evolutionary
effects (see generally Gibbons et al., 1994;
see furthermore Nowotny et al., 2001; 2003;
Campbell & Güttel, 2005, p. 154; Campbell,
2006, pp. 71-73, 91-92).
The “Triple Helix” (three-helix) model
focuses on the interaction of the state, academia
and industry. In accordance with the OECD
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classification of sectors the state represents the
government sector, academia the higher educa-
tion sector, and industry the business enterprise
sector. For Etzkowitz and Leydesdorff (2000,
p. 115) the “university-industry-government
relations” are of a crucial importance, with
universities representing a core institution in
the knowledge society: “The university can be
expected to remain the core institution of the
knowledge sector” (Etzkowitz & Leydesdorff,
2000, pp. 117-118). Furthermore: “The Triple
Helix thesis states that the university can play
an enhanced role in innovation in increas-
ingly knowledge-based societies” (Etzkowitz
& Leydesdorff, 2000, p. 109). Research and
teaching are central functions of universities.
In context of a “second academic revolution”
now a “third mission” gains in importance for
universities, which assigns to universities also
the function of supporting “economic devel-
opment” (Etzkowitz & Leydesdorff, 2000, p.
110). The U.S. university system after 1945
was guided by the principles of a “peer review”
system that allocated funds to a “scientific
elite”. But the third mission, finally, caused a
“breakdown” of this pure peer review system
or of the “best science” model, since it linked
science to “new sources of legitimating such
as regional development”, where “science
provides much of the basis for future industrial
development”. The advancing of economic
development is being added to the agenda of
universities, extending complementarily the
original mission of research excellence and
teaching. “Less 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”
(Etzkowitz & Leydesdorff, 2000, pp. 116-117).
In that context Etzkowitz (2003) also speaks
of the “entrepreneurial university”. It appears
evident that the so-called third mission displays
in substance a series of features similar to the
above discussed concept of Mode 2.
Empirically, different Triple Helix con-
figurations can exist. In the “etatistic model”
(a strong state model) the state dominates the
other sectors. This may serve as a description
for the former communist regimes in the Soviet
Union and Eastern Europe. In the “laissez-faire
model” the different sectors and institutions are
considerably separated. Earlier national systems
of innovation in the West, which operated under
the premises of linear models of innovation,
could represent empirical examples. The “Triple
Helix III” model of “tri-lateral networks and
hybrid organizations” of “university-industry-
government relations” may be described in the
following way: “… is generating a knowledge
infrastructure in terms of overlapping institu-
tional spheres, with each taking the role of the
other and with hybrid organizations emerging
at the interfaces” (Etzkowitz & Leydesdorff,
2000, pp. 111-112). According to Etzkowitz and
Leydesdorff (2000, p. 112), the Triple Helix III
model represents currently for most countries
the dominant frame of reference, the crucial
benchmark for knowledge and innovation. Key
here is the overlap and cross-communication
between the different helices or sectors in a
knowledge society and economy. In such a
context also “non-linear models of innovation”
can be embedded more easily. Some conclusions
of Triple Helix are (Etzkowitz & Leydesdorff,
2000, pp. 118-119): (1) the nation-state no
longer defines the only level for arrangements
between government and industrial sectors; (2)
profit represents an important driving force; (3)
successful innovations change the “landscape”,
meaning the “opportunity structure” for institu-
tions; (4) the “human capital factor” gains in
importance; (5) tensions create a “dynamics for
the system”, so they do not necessarily have to be
resolved; (6) the communication density within
each helix is higher than across the helices,
however, in connection to the advancement of
systems the cross-helix communication flow
should increase substantially.
Triple Helix, as a model, references explic-
itly to the models of Mode 1 and Mode 2, by
claiming that Mode 2 describes the underlying
change in the knowledge production, whereas
Triple Helix could be interpreted as an “overlay”
at the level of social structures: “The Triple Helix
overlay provides a model at the level of social
structure for the explanation of Mode 2 as an
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historically emerging structure for the produc-
tion of scientific knowledge, and its relation to
Mode 1” (Etzkowitz & Leydesdorff, 2000, p.
118; for a summary of Triple Helix see Campbell
& Güttel, 2005, p. 154; Campbell, 2006).
The “Quadruple Helix” (four-helix) model
adds to government, universities (higher educa-
tion) and the economy as further fourth helix the
“public”, more precisely being defined as the
“media-based and culture-based public”: “This
fourth helix associates with ‘media’, ‘creative
industries’, ‘culture’, ‘values’, ‘life styles’, and
perhaps also the notion of the ‘creative class’
(a term, coined by Richard Florida, 2004).
Plausibility for the explanatory potential of
such a fourth helix are that culture and values,
on the one hand, and the way how ‘public real-
ity’ is being constructed and communicated by
the media, on the other hand, influence every
national innovation system” (Carayannis &
Campbell, 2009, p. 206). This fourth helix also
could be titled or described as the media-based,
culture-based and values-based public. The
Quadruple Helix is analytically broader than
the Triple Helix, thus can be used for research
questions outside the core focus of Triple Helix.
The Quadrupe Helix reflects on phenomena such
as the “media-based democracy” or a “multi-
media information society” (Plasser & Plasser,
2002). Strategies and policies of knowledge and
innovation may be supported by communica-
tion strategies in or through the media (mass
media). Art can be seen as something to foster
creativity, implying new forms of knowledge
and innovation. Visions in the arts perhaps trig-
ger, in the long run, the development of a new
technology or the launch of a next technology
cycle. Kuhlmann (2001) speaks of “innovation
cultures”, asserting that a knowledge society
and knowledge economy also are being driven
by cultures and values. Multi-cultural settings
feed into creativity. The principle of social
accountability and reflexivity of Mode 2 has
the consequence that the underlying values of
individuals, groups and of society as a whole
must be recognized and taken into account, so
that a knowledge, produced in the context of
application and tailored for a problem-solving,
is being socially accepted and thus can be
successfully applied. Social processes of a
knowledge production must be sensitive for
culture and the values that influence a society.
Here the Mode 2 approach and the Quadruple
Helix model interplay.
The concept of “Mode 3” (Carayannis &
Campbell, 2006) is being carried by several
considerations. For advanced knowledge societ-
ies and economies it is crucial to accept and to
foster a pluralism of different knowledge and
innovation modes (paradigms). In advanced
knowledge societies and economies this plu-
ralism is being “integrated” on the basis of a
co-existence and co-evolution of a diversity of
knowledge and innovation modes (paradigms),
enabling a mutual cross-learning of different
“knowledges”. (Over time, some knowledge
and innovation modes may become replaced by
others.) This makes knowledge more similar to
democracy, allowing to speak of a “democracy
of knowledge” (Carayannis & Campbell, 2009,
pp. 207-208). Key features of Mode 3 are:
“Crucial for the suggested ‘Mode 3’ approach
is the idea that an advanced knowledge system
may integrate different knowledge modes. Some
knowledge (innovation) modes certainly will
phase out and stop existing. However, what is
important for the broader picture is that in fact
a co-evolution, co-development and co-special-
ization of different knowledge modes emerges.
This pluralism of knowledge modes should be
regarded as essential for advanced knowledge-
based societies and economies. This may point
to similar features of advanced knowledge and
advanced democracy” (Carayannis & Campbell,
2009, p. 206). “‘Mode 3’ allows and emphasizes
the co-existence and co-evolution of different
knowledge and innovation paradigms. In fact,
a key hypothesis is: The competitiveness and
superiority of a knowledge system is highly de-
termined by its adaptive capacity to combine and
integrate different knowledge and innovation
modes via co-evolution, co-specialization and
co-opetition knowledge stock and flow dynam-
ics (for example, Mode 1, Mode 2, Triple Helix,
linear and non-linear innovation)” (Carayannis
& Campbell, 2009, p. 223).14
52 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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For a multi-level advanced Mode 3 knowl-
edge system the existence and co-evolution of
a pluralism and diversity of knowledge and
innovation modes is pivotal. This pluralism in
fact promises advantages, flexibility and appears
necessary for prospects and opportunities in
direction of a further development of knowledge
societies and knowledge economies. Just as
democracy must balance different and opposite
viewpoints and is being driven by a pluralistic
political spectrum of a variety of political par-
ties, politicians and voters, also a Mode 3 knowl-
edge society and a Mode 3 knowledge economy
require and excel a diversity in knowledge and
innovation. This does not rule out that some
knowledge or innovation modes can phase out
(historically) and are being replaced by other
(new) knowledge and innovation modes. The
notion of a co-evolution of knowledge (and
innovation) modes rather emphasizes that
despite phenomena of a “paradigm shift”15 the
general picture of a co-existence of a pluralism
of modes is not being questioned (on the “struc-
ture of scientific revolutions” see also Kuhn,
1962; Umpleby, 2005).16Mode 3 encourages
interdisciplinary thinking and transdisciplinary
application of interdisciplinary knowledge.
Hybrid thinking, parallel and simultaneously
in different systems or on the basis of “trans-
systemic” conceptual approaches, appears to
be key. One could argue that concepts such as
“sustainability”, “sustainable development” or
“ social ecology” are already per se interdisci-
plinary and transdisciplinary, should analysis
be followed by application. Research questions
and problem-solving in relation to ecology, the
environment, environmental changes and en-
vironmental protection increasingly depend in
interdisciplinary and transdisciplinary network
configurations of different knowledge and in-
novation modes. Hybridization in Mode 3 also
refers to how Mode 1 could be combined with
Mode 2 or how Triple Helix may be embedded
and contextualized within a wider Quadruple
Helix architecture. Hybridization furthermore
applies to opportunities of combining differ-
ent technologies, at least for specific periods:
examples for hybrid technologies may be the
co-existence of physical paper books in print and
electronic (online) books17 or the co-existence
of different drive motors of the coming hybrid
and plug-in hybrid cars that most likely will
mark a major change for land transportation
with hopefully environmentally positive ef-
fects such as considerable reductions in CO2
emissions18 (see Figure 2).
Mode 3 claims a certain congruence of
structures and processes of advanced knowledge
and advanced democracy. In the following two
chapters (3.1 and 3.2) we want to add some
plausibility to these propositions.
3.1 The Broader Contextualization
of Knowledge and the Creation
of a Knowledge Democracy
There are clear indications that the conceptu-
alization and contextualization of knowledge
have become increasingly broader. Knowledge
creation and production was and still is being
extended to knowledge application, diffusion
and use, incorporating ideas of innovation.
Knowledge users out in the practical fields
are just as important as knowledge producers
(knowledge creators), and, depending on the
specific constellation or network configuration
(for example, in a non-linear innovation ar-
rangement), the same person or institution can
act as a knowledge producer and/or knowledge
user. The combination of Mode 1 and Mode 2 is
more extensive than a pure Mode 1 system, and
this also holds true for the following combina-
tions: Triple Helix and Quadruple Helix over
Triple Helix, and linear and non-linear models
of innovation over one-way linear innovation
models. National systems of innovation are be-
ing reframed in context of multi-level systems of
innovation. In principle, knowledge for a practi-
cal problem-solving of society or the economy
has the same relevance as knowledge involved
in basic research activities on the fundamental
“principles of the world”. Transdisciplinarity,
here, means the application of interdisciplinary
(or also disciplinary) knowledge. This emphasis
of the application context of knowledge and the
problem-solving interest of innovation imply
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 53
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that “knowledge production becomes diffused
throughout society” (Gibbons et al., 1994, p.4).
Therefore, in this particular understanding, this
form of knowledge represents also a social
knowledge.
Empowering citizens as knowledge pro-
ducers and knowledge users can contribute
to a process of “democratizing innovation”
(Von Hippel, 2005). Eric von Hippel distin-
guishes between a “user-centered innovation”
and a “manufacturer-centric innovation”. The
user-centered approach implies that “users of
products and services” are “increasingly able
to innovate for themselves”. “Lead users” are
the “innovating users”, who can be individuals
or firms. Users innovate so that they have what
they cannot find on the market. Lead users
often “freely reveal their innovations” to oth-
ers, as being exemplified by the “open source”
software movement. “Innovation communi-
ties” help to diffuse innovations more quickly.
User innovations contribute in general to the
social welfare of a society. Manufacturers, in
fact, should search for “lead user innovations”
and then should consider how these could be
re-translated into new products or services,
offered by commercial firms. Manufacturers
may consider providing “toolkits” with their
products or services, so that users can design
their own customized solution or application
(Von Hippel, 2005).19
This society-wide stretch of knowledge
production and knowledge use implies that
knowledge and innovation “flow through” all
(at least the major sections) of society: society
and the economy are “filled” with knowledge
(see Figure 3). When society in general becomes
knowledge-based, then this contributes to the
establishment of a knowledge-based democracy
or even a knowledge democracy. The Mode
3 architecture of knowledge emphasizes that
Mode 2-based knowledge for problem-solving
often (but of course not always) has hybridized
cross-linkages to a Mode 1-based knowledge
of basic research in the sciences (in context of
universities), partly in a linear, partly in a non-
linear framework of innovation models. It is
evident that wide-spread knowledge can support
Figure 2. Key features and propositions of Mode 3
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democracy and the formation of high-quality
democracy. Electoral studies clearly indicate
that the higher the level of educational attain-
ment, the more likely a person will vote (for
the U.S. see U.S. Census Bureau, 2008, Table
5). Education thus drives electoral participation
rates. Higher education benefits people also in
economic and socio-economic terms (for the
U.S. see Baum and Payea, 2005, and Baum et
al., 2006). Several analyses indicate positive
interactions and feedback loops between educa-
tion, democracy and the economy (Carmines
and Stimson, 1980; Saint-Paul and Verdier,
1993). Values are sometimes being typologized
and contrasted in the two groups of “materialist”
and “postmaterialist” values. Postmaterialism
is more sensitive for environmental issues.
There is a hope that economic progress finally
gives rise to postmaterialist values in the long
run: “The scarcity hypothesis implies short-
term changes, or period effects: Periods of
prosperity lead to increased Postmaterialism,
and periods of scarcity lead to Materialism.
The socialization hypothesis implies that long-
term cohort effects also exist: the values of a
given generation tend to reflect the conditions
prevailing during its preadult years” (Inglehart,
1990, pp. 75, 79). Should values diffuse and
become more dominant in favor of a greater
protection of the environment, then a problem-
solving in Mode 2, which demands more social
accountability and reflexivity, would have to
recognize such a value shift. This would in-
crease opportunities for “eco-innovation” and
“eco-entrepreneurship”.
3.2 The Broadening of the
Concept of Democracy and
of the Quality of Democracy:
Democracy and the Environment
In congruence to a tendency that knowledge
has been conceptualized more broadly over
time, by extending knowledge from knowledge
creation and production to knowledge applica-
tion, diffusion and use (furthermore emphasiz-
ing a pluralism of knowledge modes, thus the
metaphor of a “democracy of knowledge”),
one can formulate the proposition that there is
also a tendency that the concepts of democracy
increased their complexity. Minimum defini-
tions of democracy are being challenged by
maximum definitions. Originally, democracies
were described in terms of an “electoral democ-
racy”, focusing on political rights and on issues
of elections. Robert A. Dahl (1971, pp. 2-9)
explains democracy as the interplay of the two
dimensions of “public contestation” (“political
competition”) and “participation”. The “liberal
democracy” already is more demanding than a
pure electoral democracy, adding to the political
rights the civil liberties. The country-based free-
dom measures, in a global comparative format,
produced by Freedom House (2008, 2009a,
2009b), refer to such a liberal-democracy-
understanding, since their measures focus on
and combine political rights and civil liberties.
In modern democratic theory the originally two
dimensions of democracy of Dahl have been
substantially complemented. In a review about
the quality of democracy, Larry Diamond and
Leonardo Morlino (2004, pp. 22-23) identify the
following eight dimensions that appear crucial
for a democracy and the quality of democracy:
rule of law; participation; competition; verti-
cal accountability; horizontal accountability;
freedom; equality; and responsiveness.
Another question is, whether democracy
represents a concept only of the political sys-
tem or, alternatively, a concept that extends to
society and thus also focuses on the interfaces
of the political system with society and the
economy? For Guillermo O’Donnell (2004,
p. 13) the human beings (as “agents”) are
endowed with the following characteristics:
they have (in principle) the autonomy to make
decisions; they have the cognitive ability to
reason; and they have a responsibility for their
own actions. Already at this point it appears to
be evident why people (human beings), in a
society enriched with knowledge and never-
ending knowledge flows, are better prepared
to act as conscious “agents” who reflect their
democracy politically and who are engaged in
a political decision-making. O’Donnell (2004)
defines the following two key dimensions for de-
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 55
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mocracy and the quality of democracy: “human
rights” (for example political rights, civil rights
and social rights) and “human development”.
O’Donnell (2004, p. 55) uses the metaphor
of a “nexus of these three currents”, where
democracy, human rights and human develop-
ment are intertwined. The conceptual formula
of O’Donnell for the quality of democracy thus
may be paraphrased as (Campbell, 2008, p. 41):
“quality of democracy = (human rights) + (hu-
man development)”. By incorporating human
development, O’Donnell (2004, pp. 11-12)
carries his understanding of democracy and
the quality of democracy already far out into
society, because he draws a direct intellectual
line to the Human Development Reports and
the Human Development Index (HDI), which
is being regularly and annually released by the
United Nations Development Program (UNDP).
Interpreting O’Donnell freely and referring to
his approach as a theoretical point of departure,
one could set up the hypothesis that, at least in
principle, the HDI qualifies as a measure for
human development in a comparative global
format (see, for example, UNDP, 2009, pp.
171-175). O’Donnell emphasizes that human
development actually transforms the human
rights from rights into real freedoms.20
The “Democracy Ranking of the Qual-
ity Ranking” applies, as underlying model of
democracy, a broad conceptualization of de-
mocracy and the quality of democracy, which
is even more encompassing than the approach
of O’Donnell.21 The conceptual formula of
the “Democracy Ranking” is: “quality of de-
mocracy = (freedom & other characteristics
of the political system) + (performance of the
non-political dimensions)”. In addition to the
Figure 3. Trends in the broadening of concepts
56 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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political system, the performance of the non-
political dimensions also is being factored in.
With this focus on performance, the “Democ-
racy Ranking” attempts to be “neutral” with
regard to a left/right or liberal/conservative
axis, not favoring either left or right values,
ideologies or policies, but looks more closely
on the output of performance that should be
empirically accessible and indicator-based for
reasons of measurment. In Western political
thought, traditionally, freedom often is more
closely associated with the right or conserva-
tism, and equality with the left (Harding et al.,
1986, p. 87). The non-political dimensions,
in context of the “Democracy Ranking”, are:
gender, economy, knowledge, health, and the
environment (Campbell, 2008, pp. 30-41;
Campbell & Barth, 2009, pp. 216-218; Camp-
bell & Pölzlbauer, 2009, pp. 3-8; Campbell &
Sükösd, 2002).
For the “Democracy Ranking” the concept
of democracy goes beyond the boundaries of
the political system and includes the intersec-
tions between politics and society, but also
the performance of society, which is being
interpreted as a responsibility of politics. The
“Democracy Ranking” reflects also explicitly
on the embeddedness of society in the context
of the natural environment (environments),
more directly of course the impact of society
on nature. Environmentally sensitive behav-
ior of people and society would factor into
the “Democracy Ranking” as a good quality
environment. O’Donnell (see again 2004, p.
55) refers to the three-current understanding of
democracy, human rights and human develop-
ment. The “Democracy Ranking” applies a
four-current understanding that links together
democracy, human rights, human development,
and the (natural) environment of society. Here
an interplay is being constructed between the
quality of democracy and the quality of the en-
vironment. Those cross-references between the
political system, society, the economic system,
and the environment indicate that the “Democ-
racy Ranking” model reveals socio-ecological
features of sustainable development. While the
industrialized nations or the advanced OECD
countries often rank high with regard to the
quality of their human rights or their economic
and socio-economic performance, they often
also pollute the environment considerably more
than many of the so-called less or least devel-
oped countries (LDCs, LLDCs). In an age of a
growing importance of global interwovenness
and global responsibility, this for a large part
negative impact of the industrialized countries
on the environment should be taken more strictly
into account. In the “Human Development
Report 2007/2008” (UNDP, 2007, pp. 21-47),
devoted most importantly to the issue of fighting
climate change, clearly a link is being drawn
between increased CO2 emissions (and other
greenhouse gases) and rising temperatures. The
“world is warming” because of “human-induced
climate change”. Above all the industrialized
countries and regions cause most of the global
CO2 emissions, thus they express a negative
balance of “deep carbon footprints” (on the
concept of the “Ecological Footprint” see also
Monfreda et al., 2004).
There are different initiatives, interested in
measuring the quality of the environment. For
example, the “Environmental Sustainability
Index” (ESI) focuses on the “ability of na-
tions to protect the environment over the next
several decades”. For that purpose 76 different
data sets were aggregated into 21 “indicators
of environmental sustainability”, referring to
the following features: “natural resource en-
dowments, past and present pollution levels,
environmental management efforts, and the
capacity of a society to improve its environ-
mental performance” (Esty et al., 2005, p. 1).
The Environmental Sustainability Index was
published for the last time for 2005. The follow-
up product is the Environmental Performance
Index (EPI), which, so far, was released for
2006 and 2008. The EPI framework focuses on
offering a “composite index of current national
environmental protection efforts”. There are two
key core objectives: “reducing environmental
stresses to human health (the Environmental
Health objective)” and “protecting ecosystems
and natural resources (the Ecosystem Vitality
objective)”. For that purpose the EPI applies
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 57
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25 indicators that are being aggregated to three
distinct levels (policy categories, objectives, and
the final index) (Esty et al., 2008).22
3.3 Summary of Chapter 3
Schumpeter’s concept of the built-in “creative
destruction” mechanism of a capitalist economy
can be explained, in a modern knowledge-based
language, with the need of managing simultane-
ously different technology life cycles and the
conversion from “old” to “new” technology life
cycles (on technology life cycles, see Tassey,
2001; Campbell, 2006). Technology life cycles
link “knowledge waves” to the growth (growth
and decline) cycles and long-term performance
and competitiveness of an economy. Technology
life cycles drive an economy and demand per-
manent change. Every technology life cycle has
an “expiration date”, but always new technology
cycles are being created. Several technology life
cycles, at different stages of market maturity,
operate in parallel. Therefore, innovation and
innovativeness represent crucial characteristics
of firms in a market economy. Economic perfor-
mance depends on entrepreneurs, who leverage
the momentum and dynamics of technology
life cycles.23
Schumpeter (1976, pp. 82-83) provides
the following famous quote on the creative
destruction: “Capitalism, then, is by nature a
form or method of economic change and not only
never is but never can be stationary. And this
evolutionary character of the capitalist process
is not merely due to the fact that economic life
goes on in a social and natural environment
which changes and by its change alters the data
of economic action; this fact is important and
these changes (wars, revolutions and so on)
often condition industrial change, but they are
not its prime movers. Nor is the evolutionary
character due to a quasi-automatic increase
in population and capital or to the vagaries of
monetary systems of which exactly the same
thing holds true. The fundamental impulse that
sets and keeps the capitalist engine in motion
comes from the new consumers’ goods, the
new methods of production or transportation,
the new markets, the new forms of industrial
organization that capitalist enterprise creates.
…This process of Creative Destruction is the
essential fact about capitalism”.
The concept of Mode 3 is more inclined
to emphasize the co-existence and co-evolution
of different knowledge and innovation modes.
Mode 3 even accentuates such a pluralism and
diversity of knowledge and innovation modes
as being necessary for advancing societies and
economies. This pluralism supports processes
of a mutual cross-learning from the differ-
ent knowledge modes. Between Mode 1 and
Mode 2 manifold creative arrangements and
configurations are possible, linking together
basic research and problem-solving. Indi-
vidual knowledge and innovation modes may
phase out and become replaced in context of a
“paradigm shift” (see again Kuhn, 1962). There
also may be some cyclical patterns, indicating
how dominant or non-dominant certain modes
are during certain periods, captured by the
phrase of “knowledge swings” (Carayannis &
Campbell, 2009, p. 225). This, however, does
not alter the general pattern of a co-existence
and co-evolution of a continuous and continu-
ing diversity of knowledge and innovation
modes. The Quadruple Helix model adds to the
“university-industry-government relations” the
fourth helix of a “media-based and culture-based
public” that also includes values and different
value systems.
For the advanced knowledge societies
and knowledge economies we can set up for
discussion the following propositions about
possible “evolutionary” effects (described by
the concepts of Mode 3 and Quadruple He-
lix): (1) the pluralism of the knowledge and
innovation modes suggests features similar to
and in congruence with the political pluralism
and diversity of democracy. The notion of a
“democracy of knowledge” (Carayannis &
Campbell, 2009, pp. 207-208) describes these
phenomena. (2) The hybrid coupling of Mode
1 basic research and Mode 2 problem-solving
leads to a society-wide diffusion of good-
quality knowledge. Knowledge is being broadly
contextualized by society. Innovation carries
58 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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is prohibited.
knowledge application, diffusion and use far
out into society and the economy. Knowledge
producers and knowledge users are cross-linked
in heterogeneous networks, with shifting func-
tions and continuous reconfigurations. The same
persons and institutions can act simultaneously
as knowledge producers and knowledge users.
This society-wide flow of knowledge (claimed
by Mode 3 and Quadruple Helix) also supports
citizenry and political citizenship for a high
quality democracy. Here knowledge society,
knowledge economy and knowledge democracy
meet and overlap. (3) Over time, concepts of
democracy have become more complex and
demanding. Broader conceptualizations of
democracy transcend the boundaries of the
political system and integrate the interplay of
politics, society and the economy. In such a
wider understanding the co-evolution of hu-
man rights and human development is crucial
(for example, see O’Donnell, 2004). A next
step in broadening the concept of democracy
would be to blend together the co-evolution
of human rights, human development and of
the environment. Cross-linking human rights,
human development and the environment
already bridges analytically into sustainable
development, clearly including features of
social ecology.
It is not easy to balance Schumpeter’s con-
cept of “creative destruction”, contextualized
in a modern interpretation in the framework of
the technology life cycles, with the pluralism
and co-evolution approach of Mode 3 and the
Quadruple Helix. Of course one could attempt
to juxtapose the two spheres of (1) pluralistic
knowledge and innovation modes and (2) the
dynamics of the technology life cycles, where
technology life cycles departure from specific
knowledge and innovation modes. But some
conceptual tensions between these two differ-
ent understandings still remain. Schumpeter’s
model emphasizes more the aspects of com-
petition or of a radically competitive capitalist
economic system. Mode 3 and Quadruple Helix
are more in favour of stressing the opportuni-
ties of co-evolutionary learning. In that sense
Mode 3 and Quadruple Helix indicate a path of
sustainable development for an economic sys-
tem, interested in advancing a market economy
that is socially and environmentally sensitive,
thus recognizing and implementing criteria of
“social ecology”. Here is sufficient space and
are sufficient opportunities for “eco-innovation”
and “eco-entrepreneurship”. Mode 3 and Qua-
druple Helix may help converting the “creative
destruction” (at least partially) into a “creative
learning” and a “creative co-evolution”.
4. CONCLUSION:
SUSTAINABLE DEVELOPMENT,
SOCIAL ECOLOGY AND
THE QUINTUPLE HELIX
Society could be designed or understood to
consist of different subsystems (or systems).24
The political system or the economic system
are such examples. Politics and the economy
are being embedded by society, thus society, in
this understanding, is more comprehensive than
politics and the economy. For every societal
subsystem the other subsystems of society or
society as a whole represent “social environ-
ments” (societal environments). In a spatial
(spatial-political) multi-level architecture,
societies could be located at different levels
of aggregation, ranging from sub-national
(local, regional) to national and trans-national
(supranational, global). Society again is being
contextualized by the “natural environment”
(the natural environments).
In everyday language, when not further
specified, the term environment normally is
being associated with the natural environment.
The planet earth has a natural environment. The
concept of a natural environment may also be
applied to other planets (or moons). “Ecol-
ogy” refers to the interdisciplinary analysis of
either interactions between living organisms
or interactions between living organisms and
their environments. Based on those interaction
patterns, the sum of living organisms and of
the non-living environment define an “ecosys-
tem”.25 “Sustainability” can focus either on the
relationship of society to the economy (e.g.,
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 59
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is prohibited.
socio-economic regimes or configurations) and/
or the relationship of society with the natural
environments (Winiwarter & Knoll, 2007, pp.
306-307; Adams, 2006, pp. 1-3). Concerning
biological systems, “biodiversity” represents an
indicator for sustainability (see Vadrot, 2008,
pp. 62-79). The Human Development Index
of the Human Development Reports (UNDP,
2007; 2009) can be interpreted as a measure of
“sustainable development” of societies or of
countries in global comparison. A key quote on
sustainable development pinpoints on a defini-
tion of the so-called Brundtland Commission
that states that sustainable development “meets
the needs of the present without compromising
the ability of future generations to meet their
own needs” (United Nations, 1987a, 1987b; see
also Winiwarter & Knoll, 2007, p. 305).
Referring to our analysis in the previous
sections of the article, we could also define
sustainable development as a co-evolution of the
different systems of society, based on knowledge
and a mutual cross-learning that is socially and
environmentally sensitive and that is receptive
for concepts of a quality of democracy. “Social
ecology” looks at the “society-nature interac-
tions” between “human society” (“culture”,
the “cultural (symbolic) sphere of causation”)
and the “material world” (“nature”, the “natural
(biophysical) sphere of causation”). The “bio-
physical structures” or “biophysical structures
of society” mark an area of overlap between
culture (the cultural) and nature (the natural),
and between these “biophysical structures” and
nature a metabolism (or a “social metabolism”,
with potential of a “socio-metabolic transition”),
in context of specific “metabolic profiles”,
occurs (see Fischer-Kowalski, 1998; Fischer-
Kowalski & Hüttler, 1999; Fischer-Kowalski
& Haberl, 2007; Haberl et al., 2004, 2009; see
also Hopwood et al., 2005; Kates et al., 2001).26
“Sociometabolic regimes represent dynamic
equilibria of society-nature interactions and are
characterized by typical patterns of material and
energy flows (metabolic profiles)” (Krausmann
et al., 2008, p. 1). Sustainable development and
social ecology represent areas and fields for
interdisciplinary analysis and transdisciplinary
problem-solving. “Sustainability science is
emerging as a transdisciplinary effort to come to
grips with the much-needed symbiosis between
human activity and the environment” (Rapport,
2007, p. 77).
The originally natural sciences-based
biological concept of the “ecosystem” may
also be reinterpreted by the social sciences
and redesigned to fit the purpose of a “social
or societal ecosystem”. A societal ecosystem
would embed the crucial “elements” (for
example actors, institutions, structures and
processes) as well as their complex interaction
patterns that characterize an ecosystem, but
would also stretch into the contextualization by
the social (societal) environments of the other
systems (subsystems) of society, and is finally
contextualized by the natural environment of
the whole society. A societal ecosystem also
(at least potentially) interacts with its social
and natural environments. An example for a
societal ecosystem would be the “innovation
ecosystem” that focuses on the complexity of
innovation and innovation systems, framed by
societal and natural environments (Carayannis
& Campbell, 2009; see, furthermore, Milbergs,
2004, 2005a, 2005b). For the “innovation eco-
system” the non-linear models of innovation
are of a key importance. The concepts of “bio-
logical ecosystems” and of “social ecosystems”
(societal ecosystems) demonstrate the whole
interdisciplinary stretch of “ecology”, underpin-
ning the intellectual and academic challenge of
cross-referring and cross-relating ideas between
the social sciences and natural sciences, but
also highlights the benefit of interdisciplinary
inquiry for transdisciplinary application. Social
ecosystems and biological ecosystems could be
covered and integrated by a transdisciplinary
framework based on “social ecology”.
When the relationship and interplay of
society and the economy are being regarded as
a (possible) criterion for sustainable develop-
ment, then it appears plausible that Guillermo
O’Donnell’s (2004) conceptualization of the
quality of democracy, tying together and inte-
grating human rights and human development,
also qualifies as a sustainable-development-
60 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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approach. We could claim here an overlap (at
least partial overlap) between the concepts of
the quality of democracy and of sustainable
development. Is sustainable development a
route to high-quality democracy? Or does
the quality of a democracy manifest itself in
patterns of sustainable development? Broader
conceptualizations or definitions of democracy
that do not limit democracy to the political
system but are interested in integrating the
political system, society and the economy in
the one or other configuration and under the
“umbrella” of democracy, potentially reflect
aspects of sustainable development. Between
so-called maximum definitions of democracy
and sustainable development manifold theoreti-
cal windows of congruence open up. Should a
conceptualization of a democracy or the quality
of a democracy be designed so broadly as to
reflect also the (natural) environmental context
of society, then such a framing would not only
be compatible with a sustainable development
framework in general, but would also incorpo-
rate features of “social ecology”. Therefore, a
concept of knowledge democracy (quality of
democracy) that links together the political
system, society, the economy and environ-
ment allows the application of concepts of
social ecology in a framework of sustainable
development.
The earlier chapters of this article arrived
at the following conclusions or suggested the
following propositions for discussion:
1. The broadening and “societal contextual-
ization” of the concept of knowledge and
of knowledge by incorporating innova-
tion: Traditional concepts of knowledge
focused more on knowledge creation and
production, for example basic university
research in the context of higher educa-
tion systems. Later concepts also included
knowledge application, diffusion and use,
emphasizing that innovation could be re-
garded as using knowledge for application
and problem-solving. Innovation-oriented
knowledge diffused and still diffuses far
out into society, and is being characterized
as a “social” (“societal”) knowledge, con-
textualized by society. Key in that context
is also the concept of the “national system
of innovation” (Lundvall, 1992; Nelson,
1993). The whole spectrum of knowledge
stretches from the creation and production
of new knowledge, to innovation, the appli-
cation and use of knowledge, frequently in
non-linear models of innovation. Creativity
refers either to new knowledge or to new in-
novation. Interestingly, for the global level
of innovation systems, Lundvall (1992, p.
7) claims that non-economic aspects, such
as “ecological sustainability” and a reduc-
tion of “extreme social inequality”, gain
importance. In context of this broadening
and society-wide stretch of knowledge,
two theories (models) on knowledge and
innovation are pivotal: Triple Helix (Etz-
kowitz & Leydesdorff, 2000) looks at the
dynamic interaction of the “helices” of
“university-industry-government rela-
tions”. In the Mode 1 and Mode 2 approach
(Gibbons et al., 1994) the basic university
research (Mode 1) is being supplemented
by a knowledge (Mode 2) that focuses
on a problem-solving for society and the
economy.
2. A possible (partial) congruence and co-
evolution of knowledge and democracy:
Here, two developments run in parallel
that have features of a congruence and
co-evolution.
2.1. The pluralization of knowledge:
Advanced and further advancing
(multi-level) knowledge and innova-
tion systems can be characterized by a
pluralism and diversity of knowledge
and innovation modes. This pluralism
is in fact necessary for promoting the
continued development of knowledge
societies and knowledge economies.
Based on such a dynamics, a “democ-
racy of knowledge” emerges, with
pluralistic knowledge and innovation
modes, with possible co-evolutionary
effects of a cross-learning. Advanced
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 61
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knowledge takes over structural ele-
ments of a democracy, i.e. behaves
like a pluralistic democracy. “Mode
3” (Carayannis & Campbell, 2006;
2009) emphasizes this pluralism and
co-evolution of different and diverse
knowledge and innovation modes.27
Cross-learning between knowledge
modes in Mode 3 potentially softens
the sharp edges of the “creative de-
struction” in the economic-techno-
logical vision of Schumpeter (1976),
and moves the systems in favor of a
“creative learning” and a “creative
co-evolution”. Mode 3 stresses hy-
brid combinations and possibilities
of combination between Mode 1 and
Mode 2 or between basic research,
on the one hand, and applied research
and experimental, on the other.28 For
Mode 3 it is crucial that Mode 2
problem-solving in the twentieth and
twenty-first centuries (and most likely
also beyond) is cross-connected with
types of a Mode 1 basic research.29
“Quadruple Helix” (Carayannis and
Campbell, 2009) adds to the “univer-
sity-industry-government relations” of
the Triple Helix model the fourth helix
of a “media-based and culture-based
public” that also includes culture and
values. This spreading of knowledge
also helps building a knowledge
democracy with political citizens
that have the knowledge of making
informed decisions.
2.2. The broadening of democracy:
Theories of democracy have become
increasingly complex over time.
Concepts on liberal democracy are
more demanding than the simpler
versions of an electoral democracy.
Some approaches emphasize that de-
mocracy is not just a description of the
political system, but also cross-refers
to society, the economy and other
subsystems of society. O’Donnell
(e.g., 2004) defines the quality of
democracy out of an interplay of
“human rights” and “human develop-
ment”. The “Democracy Ranking”
model of quality of democracy (e.g.,
Campbell, 2008) goes even further,
adding also the (natural) environment
or the support of the natural environ-
ment to its conceptualization. Where
a model of democracy cross-cuts hu-
man rights, human development and
environmental development, there are
clearly references to “social ecology”.
A high-quality democracy is more
complex than a medium-quality liberal
democracy. High-quality democracies
depend on a pluralized and advanced
knowledge and innovation to perform.
The diversity of a democracy obviously
supports the diversity of knowledge.
Here the new complexity of knowledge
and of democracy meet and come
together. High-quality democracy
is a knowledge-based democracy, a
knowledge democracy.
How do knowledge, innovation and the
environment (natural environment) relate to
each other? Societies or democracies (high-
quality democracies), based on a co-evolution
of the subsystems of society or of the subsys-
tems in interaction with the whole of society,
where mutual learning and a “positive” learning
interaction take place, follow the rationale of
sustainable development. Advanced and plural-
ized knowledge, with a co-evolution and mutual
learning processes between different knowledge
and innovation modes, also adopts the rationale
of sustainable development. For the purpose of
further discussion and analysis we lastly want to
propose and introduce the five-helix model of
the “Quintuple Helix”, where the environment
or the natural environments represent the fifth
helix (see Figure 4). The Triple Helix focuses
on “university-industry-government relations”.
The Quadruple Helix frames the Triple Helix
in context of a “media-based and culture-based
public”. The Quintuple Helix finally embeds
62 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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the Quadruple Helix (and the Triple Helix)
in context of the environment or the natural
environments.30 Depending on the analytical
point of departure or on the practical interest
of application and decision-making, either a
Triple Helix, Quadruple Helix or a Quintuple
Helix model could be more appropriate.
The Quintuple Helix model is interdisci-
plinary and transdisciplinary at the same time:
the complexity of the five-helix structure implies
that a full analytical understanding of all helices
requires the continuous involvement of the
whole disciplinary spectrum, ranging from the
natural sciences (because of the natural environ-
ment) to the social sciences and humanities (be-
cause of society, democracy and the economy).
The Quintuple Helix also is transdisciplinary,
since it can be used as a frame of reference for
decision-making in connection to knowledge,
innovation and the (natural) environment. The
Quintuple Helix can be proposed as a framework
for transdisciplinary (and interdisciplinary)
analysis of sustainable development and social
ecology. With the adding of the “fifth helix of
the (natural) environment/environments” to
knowledge creation, production, application,
diffusion and use, knowledge and innovation
(advanced and pluralized Mode 3 knowledge
and innovation systems) are transformed to a
knowledge and innovation that is sensitive or at
least potentially sensitive for “social ecology”:
knowledge and innovation, contextualized by
society, meets the context of society, the envi-
ronment. Therefore, the Quintuple Helix has the
potential to serve as an analytical framework for
sustainable development and social ecology, by
conceptually relating knowledge and innovation
to the environment. Sustainable knowledge is
a knowledge that reflects on the performance
and quality of the environment, the natural
environment. The Quintuple Helix furthermore
outlines what sustainable development might
Figure 4. The five-helix model of the Quintuple Helix
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is prohibited.
mean and imply for “eco-innovation” and “eco-
entrepreneurship” in the current situation and
for our future.
ACKNOWLEDGMENT
We want to thank the following persons for
literature search or critical review of selected
sections of the article: Robert R. Fragnito, Presi-
dent, Webmaster and Founder of the Middle East
Monitoring Group (http://www.mideastmoni-
toring.com) and Eugenio Guelbenzu, Deputy
Director & Hydrogen Program Manager of
Acciona Biocombustibles, Spain (http://www.
acciona.es). For possible errors in the article
only we, the authors, are responsible.
REFERENCES
Adams, W. M. (2006, January 29-21). The Future of
Sustainability: Re-thinking Environment and Devel-
opment in the Twenty-first Century. In Proceedings
of the IUCN Renowned Thinkers Meeting. Madrid:
The World Conservation Union (IUCN). Retrieved
from http://cmsdata.iucn.org/downloads/iucn_fu-
ture_of_sustainability.pdf
Baum, S., & Payea, K. (2005). Education Pays 2005
Update. Washington, DC: College Board. Retrieved
from http://www.collegeboard.com/prod_down-
loads/press/cost05/education_pays_05.pdf
Baum, S., Payea, K., & Steele, P. (2006). Edu-
cation Pays 2006 Second Update. Washington,
DC: College Board. Retrieved from http://www.
collegeboard.com/prod_downloads/press/cost06/
education_pays_06.pdf
Bomberg, E., & Stubb, A. (2003). Introduction .
In Bomberg, E., & Stubb, A. (Eds.), The European
Union: How Does it Work? (pp. 3–18). Oxford, UK:
Oxford University Press.
Brandenburger, A. M., & Nalebuff, B. (1997). Co-
Opetition. New York: Doubleday.
Bush, V. (1945). Science the Endless Frontier. Wash-
ington, DC: National Science Foundation.
Campbell, D. F. J. (2006). The University/Business
Research Networks in Science and Technology:
Knowledge Production Trends in the United States,
European Union and Japan . In Carayannis, E. G.,
& Campbell, D. F. J. (Eds.), Knowledge Creation,
Diffusion, and Use in Innovation Networks and
Knowledge Clusters. A Comparative Systems Ap-
proach across the United States, Europe and Asia
(pp. 67–100). Westport, CT: Praeger.
Campbell, D. F. J. (2008). The Basic Concept for the
Democracy Ranking of the Quality of Democracy.
Vienna, Austria: Democracy Ranking.
Campbell, D. F. J. (2009). “Externe Umwelten”.
Außensichten auf das iff . In Arnold, M. (Ed.),
iff. Interdisziplinäre Wissenschaft im Wandel (pp.
101–134). Vienna, Austria: LIT.
Campbell, D. F. J., & Barth, T. D. (2009). Wie kön-
nen Demokratie und Demokratiequalität gemessen
werden? Modelle, Demokratie-Indices und Länder-
beispiele im globalen Vergleich. SWS-Rundschau,
49(2), 208–233.
Campbell, D. F. J., & Güttel, W. H. (2005). Knowl-
edge Production of Firms: Research Networks and
the “Scientification” of Business R&D. Interna-
tional Journal of Technology Management, 31(1/2),
152–175. doi:10.1504/IJTM.2005.006629
Campbell, D. F. J., & Pölzlbauer, G. (2009). The
Democracy Ranking 2008/2009 of the Quality of
Democracy: Method and Ranking Outcome. Vienna,
Austria: Democracy Ranking.
Campbell, D. F. J., & Sükösd, M. (Eds.). (2002). Fea-
sibility Study for a Quality Ranking of Democracies.
Vienna, Austria: Global Democracy Award.
Carayannis, E. G., & Campbell, D. F. J. (2006).
“Mode 3”: Meaning and Implications from a Knowl-
edge Systems Perspective . In Carayannis, E. G.,
& Campbell, D. F. J. (Eds.), Knowledge Creation,
Diffusion, and Use in Innovation Networks and
Knowledge Clusters. A Comparative Systems Ap-
proach across the United States, Europe and Asia
(pp. 1–25). Westport, CT: Praeger.
Carayannis, E. G., & Campbell, D. F. J. (2007).
A “Mode 3” Systems Approach for Knowledge
Creation, Diffusion, and Use: Towards a Twenty-
First-Century Fractal Innovation Ecosystem . In
Carayannis, E. G., & Ziemnowicz, C. (Eds.), Redis-
covering Schumpeter. Creative Destruction Evolving
into “Mode 3” (pp. 717–111). Houndmills, UK:
Palgrave Macmillan.
64 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global
is prohibited.
Carayannis, E. G., & Campbell, D. F. J. (2009). “Mode
3” and “Quadruple Helix”: Toward a 21st Century
Fractal Innovation Ecosystem. International Jour-
nal of Technology Management, 46(3/4), 201–234.
doi:10.1504/IJTM.2009.023374
Carayannis, E. G., & Ziemnowicz, C. (Eds.). (2007).
Re-Discovering Schumpeter: Creative Destruc-
tion Evolving into “Mode 3”. London: Palgrave
Macmillan.
Carmines, E. G., & Stimson, J. A. (1980). The Two
Faces of Issue Voting. The American Political Science
Review, 74(1), 78–91. doi:10.2307/1955648
Cullell, J. V. (2004). Democracy and the Quality of
Democracy. Empirical Findings and Methodologi-
cal and Theoretical Issues Drawn from the Citizen
Audit of the Quality of Democracy in Costa Rica .
In O’Donnell, G., Cullell, J. V., & Iazzetta, O. M.
(Eds.), The Quality of Democracy. Theory and Ap-
plications (pp. 93–162). South Bend, IN: University
of Notre Dame Press.
Dahl, R. A. (1971). Polyarchy. Participation and Op-
position. New Haven, CT: Yale University Press.
Diamond, L., & Morlino, L. (2004). The Quality of
Democracy. An Overview. Journal of Democracy,
15(4), 20–31. doi:10.1353/jod.2004.0060
Dubina, I. N. (2005). Managing Creativity: Theo-
retical Approaches to Employees’ Creativity De-
velopment and Regulation. International Journal
of Management Concepts and Philosophy, 1(4),
334–349. doi:10.1504/IJMCP.2005.008532
Dubina, I. N. (2007). Optimally Managing Creativ-
ity in Organisations . In Carayannis, E. G. (Ed.),
Managing Creative and Innovative People: The Art,
Science and Craft of Fostering Creativity, Triggering
Invention and Catalyzing Innovation (pp. 143–170).
Westport, CT: Praeger.
Dubina, I. N. (2009). Yпpaвлeниe твopчecтвoм
пepcoнaлa в ycлoвияx иннoвaциoннoй экoнo [Cre-
ativity Management in the Innovation Economy].
Moscow, Russia: Academia.
Esty, D. C., Levy, M., Kim, C. H., de Sherbinin, A.,
Srebotnjak, T., & Mara, V. (2008). 2008 Environ-
mental Performance Index. New Haven, CT: Yale
Center for Environmental Law and Policy.
Esty, D. C., Levy, M., Srebotnjak, T., & de Sherbinin,
A. (2005). 2005 Environmental Sustainability Index:
Benchmarking National Environmental Stewardship.
New Haven, CT: Yale Center for Environmental
Law & Policy.
Etzkowitz, H. (2003). Research Groups as “Quasi-
Firms”: The Invention of the Entrepreneurial Uni-
versity. Research Policy, 32, 109–121. doi:10.1016/
S0048-7333(02)00009-4
Etzkowitz, H., & Leydesdorff, L. (2000). The Dynam-
ics of Innovation: from National Systems and “Mode
2” to a Triple Helix of University-Industry-Gov-
ernment Relations. Research Policy, 29, 109–123.
doi:10.1016/S0048-7333(99)00055-4
Fischer-Kowalski, M. (1998). Society’s Metabolism.
The Intellectual History of Materials Flow Analysis,
Part I, 1860-1970. Journal of Industrial Ecology,
2(1), 61–78. doi:10.1162/jiec.1998.2.1.61
Fischer-Kowalski, M., & Haberl, H. (Eds.). (2007).
Socioecological Transitions and Global Change.
Trajectories of Social Metabolism and Land Use.
Cheltenham, UK: Edward Elgar.
Fischer-Kowalski, M., & Hüttler, W. (1999). Soci-
ety’s Metabolism. The Intellectual History of Ma-
terials Flow Analysis, Part II, 1970-1998. Journal
of Industrial Ecology, 2(4), 107–136. doi:10.1162/
jiec.1998.2.4.107
Florida, R. (2004). The Rise of the Creative Class: And
How It’s Transforming Work, Leisure, Community,
and Everyday Life. Cambridge, MA: Basic Books.
Freedom House. (2008). Methodology. Washington,
DC: Author.
Freedom House. (2009a). Freedom in the World
Comparative and Historical Data. Country Ratings
and Status, FIW (Freedom in the World) 1973-2009.
Washington, DC: Author.
Freedom House. (2009b). Map of Freedom in the
World. 2009 Edition. Washington, DC: Author.
Gibbons, M., Limoge, C., Nowotny, H., Schwartz-
man, S., Scott, P., & Trow, M. (1994). The New
Production of Knowledge. The Dynamics of Science
and Research in Contemporary Societies. London:
Sage.
Haberl, H., Fischer-Kowalski, M., Krausmann,
F., Martinez-Alier, J., & Winiwarter, V. (2009). A
Socio-metabolic Transition towards Sustainability?
Challenges for Another Great Transformation. Sus-
tainable Development, 17.
Haberl, H., Fischer-Kowalski, M., Krausmann, F.,
Weisz, H., & Winiwarter, V. (2004). Progress towards
Sustainability? What the Conceptual Framework
of Material and Energy Flow Accounting (MEFA)
Can Offer. Land Use Policy, 21(3), 199–213.
doi:10.1016/j.landusepol.2003.10.013
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 65
Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global
is prohibited.
Harding, S., Phillips, D., & Fogarty, M. (1986). Con-
trasting Values in Western Europe. Unity, Diversity
and Change. Studies in the Contemporary Values of
Modern Society. Houndmills, UK: MacMillan.
Hemlin, S., Allwood, C. M., & Martin, B. R. (Eds.).
(2004). Creative Knowledge Environments: The
Influences on Creativity in Research and Innovation.
Camberley, UK: Edward Elgar.
Hooghe, L., & Marks, G. (2001). Multi-Level Gov-
ernance and European Integration. Lanham, MD:
Rowman & Littlefield Publishers.
Hopwood, B., Mellor, M., & O’Brien, G. (2005).
Sustainable Development: Mapping Different Ap-
proaches. Sustainable Development, 13, 38–52.
doi:10.1002/sd.244
Inglehart, R. (1990). Culture Shift in Advanced
Industrial Society. Princeton, NJ: Princeton Uni-
versity Press.
Kaiser, R., & Prange, H. (2004). The Reconfigura-
tion of National Innovation Systems – The Example
of German Biotechnology. Research Policy, 33,
395–408. doi:10.1016/j.respol.2003.09.001
Kates, R. W. (2001). Environment and Development:
Sustainability Science. Science, 292(5517), 641–642.
doi:10.1126/science.1059386
Kline, S. J., & Rosenberg, N. (1986). An Overview
of Innovation . In Landau, R., & Rosenburg, N.
(Eds.), The Positive Sum Strategy. Washington, DC:
National Academy Press.
Krausmann, F., Fischer-Kowalski, M., Schandl, H.,
& Eisenmenger, N. (2008). The Global Sociometa-
bolic Transition: Past and Present Metabolic Profiles
and Their Future Trajectories. Journal of Indus-
trial Ecology, 12(5), 637–656. doi:10.1111/j.1530-
9290.2008.00065.x
Kuhlmann, S. (2001). Future Governance of In-
novation Policy in Europe – Three Scenarios.
Research Policy, 30, 953–976. doi:10.1016/S0048-
7333(00)00167-0
Kuhn, T. S. (1962). The Structure of Scientific Revolu-
tions. Chicago: The University of Chicago Press.
Lundvall, B.-A. (Ed.). (1992). National Systems of
Innovation. Towards a Theory of Innovation and
Interactive Learning. London: Pinter Publishers.
Meglic, J., Kern, T., Urh, B., Balkovec, J., & Roblek,
M. (2009). Influence of Polyvalence Professionals
on Product Development Process Efficiency. Stro-
jarstvo, 51(2), 105–121.
Milbergs, E. (2004). Measuring Innovation for
National Prosperity. Washington, DC: Center for
Accelerating Innovation.
Milbergs, E. (2005a). Innovation Ecosystems and
Prosperity. Washington, DC: Center for Accelerat-
ing Innovation.
Milbergs, E. (2005b). Setting the Stage for Innovation.
Accelerating Innovation 2005 Conference. Washing-
ton, DC: Center for Accelerating Innovation.
Miyata, Y. (2003). An Analysis of Research and
Innovative Activities of Universities in the United
States . In Shavinina, L. V. (Ed.), The International
Handbook on Innovation (pp. 715–738). Amsterdam,
The Netherlands: Pergamon. doi:10.1016/B978-
008044198-6/50049-8
Monfreda, C., Wackernagel, M., & Deumling,
D. (2004). Establishing National Natural Capital
Accounts Based on Detailed Ecological Footprint
and Biological Capacity Assessments. Land Use
Policy, 21(3), 231–246. doi:10.1016/j.landuse-
pol.2003.10.009
Narin, F., Hamilton, K. S., & Olivastro, D. (1997).
The Increasing Linkage between U.S. Technology
and Public Science. Research Policy, 26, 317–330.
doi:10.1016/S0048-7333(97)00013-9
National Science Board. (2008). Science and Engi-
neering Indicators 2008. Volumes 1 and 2. Arlington,
VA: National Science Foundation.
Nelson, R. R. (1990). Capitalism as an Engine
of Progress. Research Policy, 19, 193–214.
doi:10.1016/0048-7333(90)90036-6
Nelson, R. R. (Ed.). (1993). National Innovation
Systems. A Comparative Analysis. Oxford, UK:
Oxford University Press.
Nowotny, H., Scott, P., & Gibbons, M. (2001). Re-
thinking science. Knowledge and the public in an age
of uncertainty. Cambridge, UK: Polity Press.
Nowotny, H., Scott, P., & Gibbons, M. (2003). Mode
2 Revisited: The New Production of Knowledge. Min-
erva, 41, 179–194. doi:10.1023/A:1025505528250
O’Donnell, G. (2004). Human Development, Human
Rights, and Democracy . In O’Donnell, G., Cullell,
J. V., & Iazzetta, O. M. (Eds.), The Quality of De-
mocracy. Theory and Applications (pp. 9–92). South
Bend, IN: University of Notre Dame Press.
66 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global
is prohibited.
OECD. (1994). The Measurement of Scientific and
Technological Activities. Proposed Standard Practice
for Surveys of Research and Experimental Develop-
ment. Frascati Manual 1993. Paris: OECD.
OECD. (2002). The Measurement of Scientific and
Technological Activities. Proposed Standard Practice
for Surveys on Research and Experimental Develop-
ment. Frascati Manual 2002. Paris: OECD.
Palmberg, C., & Luukkonen, Y. (2006). The Different
Dynamics of the Biotechnology and ICT Sectors in
Finland . In Carayannis, E. G., & Campbell, D. F. J.
(Eds.), Knowledge Creation, Diffusion and Use in
Innovation Networks and Knowledge Clusters (pp.
158–182). Westport, CT: Praeger.
Plasser, F., & Plasser, G. (2002). Global Political
Campaigning. A Worldwide Analysis of Campaign
Professionals and Their Practices. Westport, CT:
Praeger.
Rapport, D. J. (2006). Sustainability Science: An
Ecohealth Perspective. Sustainability Science, 2,
77–84. doi:10.1007/s11625-006-0016-3
Saint-Paul, G., & Verdier, T. (1993). Education,
Democracy and Growth. Journal of Development
Economics, 42, 399–407. doi:10.1016/0304-
3878(93)90027-K
Schafer, K. E. (2008). Have We Succeeded? Politi-
cal Leadership Lessons from the United States . In
Zimmer, A., & Jankowitsch, R. M. (Eds.), Political
Leadership. Annäherungen aus Wissenschaft und
Praxis (pp. 263–278). Berlin: Polisphere.
Schumpeter, J. A. (1934). The Theory of Economic
Development. Cambridge, MA: Harvard University
Press.
Schumpeter, J. A. (1976). Capitalism, Socialism and
Democracy. New York: Harper Perennial.
Shavinina, L. V. (Ed.). (2003). The International
Handbook on Innovation. Amsterdam, The Nether-
lands: Pergamon Elsevier Science.
Tassey, G. (2001). R&D Policy Models and Data
Needs . In Feldman, M. P., & Link, A. N. (Eds.), Inno-
vation Policy in the Knowledge-Based Economy (pp.
37–71). Boston: Kluwer Academic Publishers.
Umpleby, S. A. (2005). What I Learned from
Heinz von Foerster About the Construction
of Science. Kybernetes, 34(1/2), 278–294.
doi:10.1108/03684920510575843
UNDP. (2007). Human Development Report
2007/2008. Fighting Climate Change: Human
Solidarity in a Divided World. New York: United
Nations Development Program.
UNDP. (2009). Human Development Report 2009.
Overcoming Barriers: Human Mobility and Devel-
opment. New York: United Nations Development
Program.
United Nations. (1987a). Report of the World Com-
mission on Environment and Development (42/187).
New York: United Nations.
United Nations. (1987b). Report of the World Com-
mission on Environment and Development: “Our
Common Future. New York: United Nations.
U.S. Census Bureau. (2008). Voting and Registra-
tion in the Election of November 2008. Washington,
DC: Author.
Vadrot, A. (2008). “Der Wille zur Wahrheit als der
Wille zur Macht”. Die theoretischen Implikationen
der Schnittstelle zwischen Politik und Wissenschaft in
der Biodiversitätspolitik. (Magisterarbeit.). Vienna:
University of Vienna.
Von Hippel, E. (1988). The Sources of Innovation.
Oxford, UK: Oxford University Press.
Von Hippel, E. (2005). Democratizing Innovation.
Cambridge, MA: MIT Press Winiwarter, V., & Knoll,
M. (2007). Umweltgeschichte. Köln, Germany:
Böhlau.
ENDNOTES
1 See: http://en.wikipedia.org/wiki/Knowledge
(retrieved: October 18, 2009)
2 In that understanding, emotional competence
may cross-cut social competences and person-
ality.
3 The OECD is the “Organization for Economic
Co-operation and Development”.
4 In the context of this article, we use “knowl-
edge creation” and “knowledge production” as
interchangeable terms. A possible distinction
may emphasize that knowledge creation is
more fundamental and basic (more overlap-
ping with basic research) than the knowledge
production.
5 We want to quote, how the OECD (1994, p.
29) defines basic research: “Basic research is
experimental or theoretical work undertaken
primarily to acquire new knowledge of the
underlying foundation of phenomena and
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 67
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is prohibited.
observable facts, without any particular ap-
plication or use in view.” This definition the
OECD repeats unchanged in 2002 (OECD,
2002, p. 30).
6 Etzkowitz and Leydesdorff (2000, p. 116) use
the term of “pure science” for describing the
post-1945 university system in the U.S., which
largely behaved according to the principles
that were formulated and postulated by Van-
nevar Bush (1945). Etzkowitz and Leydesdorff
(2000, p. 116) speak in this context also of an
“ideology of pure research”.
7 In a different book section, Lundvall (1992, p.
15) says: “As pointed out, we do not assume the
process of innovation to be exclusively local-
ized inside national borders. On the contrary,
we recognize that the process of innovation
has increasingly become multinational and
transnational reflecting, for example, R&D
cooperation between big firms based in dif-
ferent nations.”
8 Nelson (1990) describes or paraphrases
capitalism as an engine of growth. As Nelson
(1990, p. 193) states at the beginning of his
article: “Economists, from Marx, to Schum-
peter, have touted capitalism as an engine
of technical progress. But what kind of an
engine is it? How does it work? What are the
strengths and weaknesses?”
9 We can speculate, to which extent research
about the European Union (EU) and con-
cepts such as a multi-level governance of
the EU (Hooghe and Marks, 2001; Bomberg
and Stubb, 2003, p. 9) helped inducing and
creating the concept of multi-level systems of
innovation (Carayannis and Campbell, 2006,
p. 11).
10 See: http://en.wikipedia.org/wiki/Creativity
(retrieved: October 29, 2009)
11 Hemlin et al. provide the following defini-
tion for CKEs (quoted from the slide page
number 3 of a power point presentation:
http://www.spp.gatech.edu/conference2006/
PPTs/Hemlin_7E.pdf, retrieved November
16, 2009): Creative knowledge environments
= “… those environments, contexts and sur-
roundings, the characteristics of which are
such that they exert a positive influence on
human beings engaged in creative work aim-
ing to produce new knowledge or innovations,
whether they work individually or in teams,
within a single organization or in collaboration
with others”.
12 Consequently, the influential book The New
Production of Knowledge (Gibbons et al.,
1994) also could have been titled as The
Creative Production of Knowledge.
13 The full names of the whole research team are:
Michael Gibbons, Camille Limoges, Helga
Nowotny, Simon Schwartzman, Peter Scott,
and Martin Trow.
14 On the concept of “co-opetition” (forms or
network configurations of a simultaneous
cooperation and competition) see Branden-
burger and Nalebuff (1997).
15 Modes of knowledge and innovation may
be reinterpreted as “paradigms” or as being
paradigm-based.
16 According to Wikipedia (http://en.wikipedia.
org/wiki/Thomas_Kuhn, retrieved: November
12, 2009) the concept of a “paradigm shift”
is being referred to Kuhn, however, was not
literally created by Kuhn.
17 At least one potential quality of print books will
be to serve as a different backup medium (in
paper) for the electronic e-books. University
libraries again often are challenged of not
exactly knowing, where to store the masses
of print publications in the long run.
18 Current hybrid cars combine a combustion
engine with an electric motor. Next generation
automobiles might be hybrid plug-in hydrogen
cars that link an electric motor with a fuel cell.
Such cars could either be externally charged
directly with electricity or could convert, in the
fuel cell, hydrogen and oxygen to electricity
(and heat) for the electric motor. Hydrogen cars
powered by fuel cells emit only water (water
vapour). Is the electricity for the plug-in device
or the hydrogen for the fuel cell generated in
a clean way, this next generation technology
might contribute to a substantial reduction of
carbon dioxide emissions of the land-bound
traffic and would help balancing the current
effects of a global warming of the world cli-
mate. Several analysts believe that some of
the Japanese and German car companies are
(at least for the moment) the global leaders
in hydrogen technology.
19 Two key books of Eric von Hippel, “The
Sources of Innovation” (1988) and “Democ-
ratizing Innovation” (2005), are electronically
available as a free download (http://web.mit.
edu/evhippel/www/books.htm). Print versions
must be purchased. This illustrates how a print
medium and an electronic medium of the same
publication can be combined in an innovative,
creative and effective way, and furthermore
might indicate a promising hybrid strategy
for publishers in the future.
20 As an interesting example for a citizen audit
on the quality of democracy, which was car-
ried out in recent years, see Cullell (2004) on
Costa Rica.
68 International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010
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is prohibited.
21 The general website address of the “Democ-
racy Ranking” is: http://www.democracyrank-
ing.org/en
22 See also: http://epi.yale.edu/Home
23 For an analysis of the different dynamics
in the biotechnology and ICT sectors in
Finland, Christopher Palmberg and Terttu
Luukkonen (2006, pp. 160-161, 167-169)
apply the concept of the “competence block”.
Here the “entrepreneur” is crucial. Palmberg
and Luukkonen define the entrepreneur as:
“Entrepreneurs, or innovators, who identify
profitable inventions and introduce them in
the market. … The task of the entrepreneur is
to identify those ideas that have the greatest
potential commercial value and therefore to
contribute to turning inventions into innova-
tions in the market.”
24 A system could be defined as consisting of “ele-
ments/parts” and the “rationale/self-rationale”
of these system elements (Carayannis and
Campbell, 2009, p. 204). Of course, alternative
definitions for a system also are possible.
25 See also: http://en.wikipedia.org/wiki/Ecol-
ogy (retrieved: November 06, 2009).
26 See also: http://www.uni-klu.ac.at/socec/
inhalt/1860.htm
27 Government/opposition cycles of the political
system find a partial equivalent in the so-called
concept of “knowledge swings”, referring to
the possibility of a sequential patterning of
which modes of knowledge or innovation are
dominant in which periods of time (Carayannis
& Campbell, 2009, p. 225).
28 This also leads to the question whether Mode
3 encourages that professionals carry hybrid
competences, and thus qualify as “polyvalence
professionals” (see, for example, Meglic et
al., 2009).
29 In earlier historical periods also variations of a
Mode 2 problem-solving existed, but with less
or no cross-connections to a sciences-based
Mode 1 knowledge. In that line of thinking,
Mode 2 might be “older” than Mode 1 (see also
Etzkowitz & Leydesdorff, 2000, p. 116).
30 At this point we leave it open, what in the
logical continuation of such a conceptual
sequence a Sextuple Helix (six-helix model)
or a Septuple Helix (seven-helix model) pos-
sibly may or could be.
Dr. Elias G. Carayannis (http://business.gwu.edu/faculty/elias_carayannis.cfm) is Full Professor
of Science, Technology, Innovation and Entrepreneurship, as well as co-Founder and co-Director
of the Global and Entrepreneurial Finance Research Institute (GEFRI) and Director of Research
on Science, Technology, Innovation and Entrepreneurship, European Union Research Center,
(EURC) at the School of Business of the George WashingtonUniversity in Washington, DC.
Dr. Carayannis' teaching and research activities focus on the areas of strategic Government-
University-Industry R&D partnerships, technology road-mapping, technology transfer and
commercialization, international science and technology policy, technological entrepreneurship
and regional economic development. Dr. Carayannis has several publications in both academic
and practitioner journals, including IEEE Transactions in Engineering Management, Research
Policy, Journal of R&D Management, Journal of Engineering and Technology Management,
International Journal of Technology Management, Technovation, Journal of Technology Transfer,
Engineering Management Journal, Journal of Growth and Change, Review of Regional Stud-
ies, International Journal of Global Energy Issues, International Journal of Environment and
Pollution, Le Progres Technique, and Focus on Change Management. He has also published
thirteen books to date on science, technology, innovation and entrepreneurship with CRC Press,
Praeger/Greenwood, Palgrave/MacMillan and Edward Elgar, and has several more projects
under contract. He is Editor-in-Chief of the Edward Elgar Book Series on Science, Technology,
Innovation and Entrepreneurship; the Springer Book Series on Innovation, Technology, and
Knowledge Management; the Springer Journal of the Knowledge Economy; and the IGI Inter-
national Journal of Social Ecology and Sustainable Development; and Associate Editor of the
International Journal of Innovation and Regional Development. Email: caraye@gwu.edu
International Journal of Social Ecology and Sustainable Development, 1(1), 41-69, January-March 2010 69
Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global
is prohibited.
David F. J. Campbell is a Research Fellow at the Institute of Science Communication and Higher
Education Research (WIHO), Faculty for Interdisciplinary Studies (iff), University of Klagen-
furt [http://uni-klu.ac.at/wiho]; Lecturer in Political Science at the University of Vienna; and
Quality Manager and Quality Researcher at the University of Applied Arts in Vienna. Campbell
co-edited Demokratiequalität in Österreich: Zustand und Entwicklungsperspektiven (Leske +
Budrich, 2002) (“Democracy Quality in Austria”) and Knowledge Creation, Diffusion, and Use
in Innovation Networks and Knowledge Clusters (Praeger, 2006), and his articles on innovation
and society have been published in several international journals. Campbell teaches (taught) at
the University of Klagenfurt, University of Vienna, and George Washington University in Wash-
ington D.C. (Elliott School of International Affairs). His two research focuses concentrate on
research about knowledge and research about democracy and the quality of democracy. Email:
david.campbell@univie.ac.at