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Three frames for innovation policy: R&D, systems of innovation and transformative change

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Three frames for innovation policy: R&D, systems of innovation and transformative change

Abstract

Science, technology and innovation (STI) policy is shaped by persistent framings that arise from historical context. Two established frames are identified as co-existing and dominant in contemporary innovation policy discussions. The first frame is identified as beginning with a Post-World War II institutionalisation of government support for science and R&D with the presumption that this would contribute to growth and address market failure in private provision of new knowledge. The second frame emerged in the 1980s globalising world and its emphasis on competitiveness which is shaped by the national systems of innovation for knowledge creation and commercialisation. STI policy focuses on building links, clusters and networks, and on stimulating learning between elements in the systems, and enabling entrepreneurship. A third frame linked to contemporary social and environmental challenges such as the Sustainable Development Goals and calling for transformative change is identified and distinguished from the two earlier frames. Transformation refers to socio-technical system change as conceptualised in the sustainability transitions literature. The nature of this third framing is examined with the aim of identifying its key features and its potential for provoking a re-examination of the earlier two frames. One key feature is its focus on experimentation, and the argument that the Global South does not need to play catch-up to follow the transformation model of the Global North. It is argued that all three frames are relevant for policymaking, but exploring options for transformative innovation policy should be a priority.
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Research Policy
journal homepage: www.elsevier.com/locate/respol
Three frames for innovation policy: R&D, systems of innovation and
transformative change
Johan Schot
, W. Edward Steinmueller
Science Policy Research Unit (SPRU), University of Sussex, UK
ARTICLE INFO
Keywords:
Transformation
Sustainable development goals
R&D
National systems of innovation
Innovation policy
ABSTRACT
Science, technology and innovation (STI) policy is shaped by persistent framings that arise from historical
context. Two established frames are identified as co-existing and dominant in contemporary innovation policy
discussions. The first frame is identified as beginning with a Post-World War II institutionalisation of government
support for science and R&D with the presumption that this would contribute to growth and address market
failure in private provision of new knowledge. The second frame emerged in the 1980s globalising world and its
emphasis on competitiveness which is shaped by the national systems of innovation for knowledge creation and
commercialisation. STI policy focuses on building links, clusters and networks, and on stimulating learning
between elements in the systems, and enabling entrepreneurship. A third frame linked to contemporary social
and environmental challenges such as the Sustainable Development Goals and calling for transformative change
is identified and distinguished from the two earlier frames. Transformation refers to socio-technical system
change as conceptualised in the sustainability transitions literature. The nature of this third framing is examined
with the aim of identifying its key features and its potential for provoking a re-examination of the earlier two
frames. One key feature is its focus on experimentation, and the argument that the Global South does not need to
play catch-up to follow the transformation model of the Global North. It is argued that all three frames are
relevant for policymaking, but exploring options for transformative innovation policy should be a priority.
1. Introduction
Public policies, including those directed at science and technology,
arise from understandings of past experience with actions, reflections
on contemporary challenges and perceptions of future potentials for
action. The past, present and future are interpretively connected by
policy scholars and practitioners as well as many others as a guide to
analysis and action. These interpretive connections produce forceful
framings – interpretations of experience, ordering of present circum-
stances and imaginations of future potentialities that create the foun-
dations for policy analysis and action and shape expectations con-
cerning potentials and opportunities (Goffman, 1974;Benford and
Snow, 2000;Taylor, 2003). Framings evolve over time and change
when they are perceived as inadequate to current circumstances. Be-
cause they influence peoples’ imaginations, they also extend beyond the
public policy sphere to influence the mobilisation and activities of non-
governmental organisations as well as the private enterprise sector and
even families and individuals. Some have argued that frame reflection
might hamper action. Following Schön and Reid (1994) we believe the
opposite; it is necessary to engage in frame reflection for designing and
implementing effective policy solutions for complex policy problems.
Modern economic growth is generated by a collection of socio-
technical systems based upon industrial mass production and in-
dividualized mass consumption that extensively employ fossil fuels, is
resource and energy intensive and produces a massive amount of waste.
Despite important improvements in life expectancy and material wel-
fare in many countries, persistent problems of economic crises and
rising inequality coincide with a growing realisation that current socio-
technical systems for meeting our basic needs – whether in food, en-
ergy, mobility, materials, water or resources more generally – are un-
sustainable. While available framings of science and technology policy
that evolved since World II remain relevant, they offer little guidance
for managing the substantial negative consequences of the socio-tech-
nical system of modern economic growth to which they have con-
tributed and of which they are a part.
Our view is that it is time to articulate more forcefully and to ex-
periment in practice with a framing for science, technology and in-
novation policy that emphasises socio-technical system change. Three
framings related to science and technology policy can be delineated,
two of which are available and are systematically employed in policy
https://doi.org/10.1016/j.respol.2018.08.011
Received 18 October 2016; Received in revised form 16 July 2018; Accepted 18 July 2018
Corresponding author.
E-mail address: j.w.schot@sussex.ac.uk (J. Schot).
Research Policy 47 (2018) 1554–1567
Available online 31 August 2018
0048-7333/ © 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
T
discourse and action. Each of these framings involves a model of in-
novation which defines the roles of actors and describes actions that
may be taken to address goals that are also part of the framings we
examine. The third framing, which addresses socio-technical system
change, remains under-developed although it has existed in the back-
ground of policy discussions for many years; recently it has been ac-
knowledged by the OECD (2015; see also (Steward, 2012;Weber and
Rohracher, 2012 and Frenken, 2017).
The first framing focuses on innovation for growth, tapping the
potential of science and technology for prosperity and nurturing socio-
technical systems directed towards mass production and consumption.
It arose as the emphasis on modern economic growth emerged, two
central features of which Kuznets (1973) identified as science-based
industry and sustained improvement in factor productivity.
1
In terms of
science, technology and innovation policy, however, this framing re-
mained tacit or unarticulated until after the Second World War when it
was extended to create a new vision for the role of the State in the
writings of Vannevar Bush (1945) and others.
The second framing – national systems of innovation - emerged
during the 1980s to address some of the consequences for individual
nation states of the experience with modern economic growth – the
intensification of international competition, globalization, the prospects
of being left behind, and the promise of catching up. Similar to the first
framing, some of the features of the second framing were present in an
unarticulated form in earlier years with greater influence on the prac-
tice than on the rationale or theory of science, technology and in-
novation policy. This paper articulates both rationales more clearly and
puts them into historical context.
A third framing – transformative change - is in the making and its
outlines have become clearer in recent years. The aspirations for
transformative change were captured most recently in the UN
Sustainable Development Goals published in 2015. These include
ending poverty and reducing inequality in all its forms everywhere,
promoting inclusive and sustainable consumption and production sys-
tems, and confronting climate change, and many more.
2
This third
framing involves a questioning of how to use science and technology
policy for meeting social needs and addresses the issues of sustainable
and inclusive societies at a more fundamental level than previous
framings or their associated ideologies and practices.
The emergence of a new framing does not necessarily replace ex-
isting framings. However, framings compete with one another for the
imagination of policymakers and, ultimately, citizens. The legitimacy of
rationales and arguments for particular policies and the actions that
follow from them is influenced by the prevalence and understanding of
the framings. Our aim in this paper is to examine the historical devel-
opment of all three framings, illustrating how each arises as a response
to scientific debate, in relation to changing social and economic cir-
cumstances. Ultimately, we contend that research, experimentation,
and reflection on the third framing should be a priority in any con-
sideration of current science, technology and innovation policy, in short
innovation policy, since for us innovation spans the entire process from
scientific discovery to utilisation. Yet we do not argue that the first and
second framing have become superfluous; they have their own ratio-
nale, which is still relevant today and might also be improved. Actual
practice will reflect mixtures of frames. A deeper discussion and
confrontation of frames and a process of critical frame reflection both
by academics as well as policy makers is, however, important, and long
overdue, since framings do have pervasive impacts on practice. This
discussion paper aims to fuel and contribute to the critical reflection
and eventually hopes to inspire new policy practices (Schön and Reid,
1994).
3
2. Framing 1: innovation for growth
Concerns about the future of the industrially developed economies
manifested themselves following World War II. The potential for the re-
emergence of unemployment, inflation, and economic instability was
feared and the roles of the state in mobilising and conducting the war
effort legitimised state intervention that previously had been viewed
sceptically, particularly in the British and American context. Substantial
variation across countries in the state’s support for research and de-
velopment (R&D) prior to the war existed, but with a few exceptions,
such as agricultural research in the US and Europe, these efforts were a
direct consequence of the state’s role in particular activities such as
defence, telecommunications, medical research, geological surveys, and
civil engineering works (Tindemans et al., 2009;Mowery and
Rosenberg, 1989). Following the war, and because of the ensuing Cold
War, there was enthusiasm for an expanded state role in conducting
scientific research which was expected to safeguard the peace and to
bring industrial benefits. Defence research institutes pushed for the
transfer of their research beyond military markets (Galison and Hevly,
1992).
A broad consensus emerged that the state could and should play an
active role in financing scientific research on the premise that new
scientific discoveries would flow into practice through applied R&D by
the private sector. It was also recognised that science was making
substantial contributions to the modernisation of industry – replacing
craft practices and traditions with a continuation and intensification of
scientific management as articulated in Taylorism and Fordism.
Attention to the issues of applied research and technological de-
velopment and their treatment as an investment by firms suggested
shortcomings moving beyond the pre-War focus on invention which
emphasised discovery and discoverers. For these investments to be re-
couped, commercialisation of invention was required.
Commercialisation would only happen if an invention were to be pur-
chased by a significant number of customers. In effect, the framing
describing the origins and nature of invention inherited from the past
was undergoing change. Initially, this involved a focus on R&D as an
investment and led to questions about the rate of adoption (or path of
diffusion) of new products. To capture these processes and to distin-
guish invention from the more complex processes of applied research,
development and commercialisation, the word innovation began to be
employed.
4
The simplest definition of innovation in this context is
commercialised invention.
5
In the late 1950s the popular imagination favouring the economic
1
Kuznets (1973) identified six characteristics defining modern economic
growth. The other four were rapid population growth, structural transformation
(primarily urbanisation and the shift from agriculture to manufacturing and
then to services), changes in ideology (e.g. secularisation), the increased global
reach of developed countries (part of what is now referred to as globalisation),
and the persistence of underdevelopment (at the time of Kuznets article, the
persistence of non-modern growth experience among three quarters of the
world’s population).
2
http://www.un.org/sustainabledevelopment/sustainable-development-
goals/ Accessed 28/11/17.
3
Together with others the authors have developed a new initiative entitled
the Transformative Innovation Policy Consortium which aims at stimulating
and facilitating policy experimentation – see www.transformative-innovation-
policy.net.
4
For economists, who were developing the theory of production to reflect the
contributions of technology, the broader terms technical or technological
change were employed in parallel since it allowed discussion of both innova-
tions representing new products and improvements in processes for producing
products. Later, the terms process and product innovations began to be used as
types of technological change.
5
This was a particular concern of Chris Freeman due to his interest in the
social functions of science (Bernal, 1939) and the need to distinguish between
invention and commercialisation of invention. While Freeman was not the first
to make this distinction, he was influential in getting this established due to the
success of Freeman (1974).
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1555
benefits of science provoked a re-examination of the role of scientific
and technological knowledge from both empirical and theoretical per-
spectives. Empirically, the relation between the factors of production
and the growth of economic output was re-examined by Abramovitz
(1956);Solow (1957) and others. Abramovitz and Solow demonstrated
that the contribution of labour and capital growth fell far short of ex-
plaining growth in economic output, leaving a large residual which
Solow attributed to technological change and which Abramovitz re-
ferred to as “some sort of measure of our ignorance about the causes of
growth in the United States”, (p.11). In terms of science and technology
policy, this work seemed to confirm the benefits that science was pro-
viding to the economy. The findings were reinforced by the appearance
of novel artefacts such as mass-market televisions, passenger jet air-
lines, and, more darkly, intercontinental ballistic missiles. The sig-
nificance of the residual provoked an increase in social scientist and
policymaker interest in the processes of technological change. It also
led to a re-examination of the rationale for public intervention in the
research enterprise.
2.1. Rationale/justification for policy intervention
The explicit recognition that investment was required for science,
combined with the empirical insight that technological change was the
single largest factor in economic growth, presented a theoretical
question for economists. It was in this context that Nelson (1959) and
Arrow (1962) asked the question – Are the incentives of market actors
adequate to produce the socially desired level of scientific knowledge?
Their negative answer reflected the nature of scientific knowledge (the
challenges of ‘appropriating’ or owning it) and the logic of the market
(a firm expending costs that will equally benefit rivals is not making a
rational economic decision since the rivals can free ride and obtain a
cost advantage from not making the research expenditure).
6
Thus,
economic theory provided a robust rationale for the public support of
only a component of innovation (discovery or invention). In economics
language, discovery and invention were said to have the features of a
public good, akin to roads or sewers and it was reasonably well-ac-
cepted that public goods suffer from ‘market failure’ – the inadequacy of
market incentives to produce them at the desired level or quality.
The question of whether a similar market failure might apply to the
latter stages of the innovation process – applied research and com-
mercialisation – was not addressed because it was assumed that these in
these later stages, the knowledge would be appropriable – appropriation
of benefits could be protected by trade secrecy, intellectual property, or
simply by maintaining a competitive lead preventing rivals from imi-
tating successful innovations.
7
Policymakers contributed an additional feature to the first framing
by sponsoring mission-oriented research, a continuation and, in some
cases, an extension of the previous role of government research funding
for military activities. Technologies were developed to wage war –
atomic weapons, radar, jet aircraft, ballistic missiles, and computers
were further developed for defence and adapted to civilian application.
The most improbable of these adaptations, the civilian use of ballistic
missiles, was transformed into a space programme and a space race
paralleling the Post-War arms race in nuclear weapons. Maintaining
domestic security by fighting poverty and urban violence and enabling
urban renewal became another area for large scale investments in the
1960s (Light, 2003). The oil crisis of the 1970s led to the formulation of
a new security mission set of policies to reduce reliance on the import of
petroleum which contributed to the early development of renewable
technologies. Policymaker definition and pursuit of missions was mo-
tivated by national prestige and ideological competition between the
state socialism of the then Soviet Union and China and the capitalism of
the West, allied with a promise of economic and social returns on public
investment. A telling feature of the mission framing is physicist Robert
Wilson’s response to a question from US Senator John Pastore about the
defence (mission) value of the new accelerator at Fermilab, at the time,
the largest high energy physics research installation in the world -” …
this new knowledge has all to do with honour and country but it has
nothing to do directly with defending our country except to help make
it worth defending” (US Congress, 1969:113).
Economists and policy makers were not the only contributors to the
first framing of science and technology policy. Awareness of the po-
tentially negative consequences of scientific development was, in the
1950s, limited to a few areas such as the risks of nuclear war and ra-
diation exemplified by the ‘Doomsday Clock’ regularly updated on the
cover of the Bulletin of Atomic Scientists. However, publication of
works like Silent Spring (Carson, 1962) and the Limits to Growth report
by the Club of Rome (Meadows et al., 1972) opened a much wider
agenda of social concern about the potentially negative consequences of
the new products of science. During the 1960s, considerable anxiety
about, and protest against, the possible consequences of science for
public health and safety and, ultimately, environmental quality,
emerged. Policy makers responded to these developments, often re-
luctantly, by developing new regulatory agencies or making important
changes in those agencies that had been established in an earlier era.
For example, the US Food and Drug Administration (FDA), which had
been established in 1906 to set pharmaceutical and food safety stan-
dards, began to regulate the effectiveness of pharmaceuticals after the
worldwide thalidomide disaster.
8
2.2. Framing 1: innovation model and actors
The model of innovation underlying Framing 1 is the commercia-
lisation of scientific discovery with each of the processes that follow
discovery driven by the economic logic of investment and financial
return from the potential market for the innovation. This framing re-
flects a modernist confidence in the inevitability of progress and an
economic rationale of the benefits of choice across a range of compe-
titively mass produced (and hence relatively inexpensive) goods. It is
expected that this science-led process will contribute substantially to
long term economic growth and provide numerous business opportu-
nities. This framing acknowledges that negative consequences do
emerge, but these are attributed to shortcomings in scientific knowl-
edge that can be remedied with further research. Regulation is, for the
most part, applied after the research process is completed and at the
point when problems are experienced in the adoption and use of the
innovation. To identify these problems, governments use risk and
technology assessment exercises and create specific agencies which
inform Parliaments (Vig and Paschen, 2000). Yet these technology as-
sessment activities are not seen as a core part of a science, technology
and innovation policy, but as a useful add-on at best. An example of ex-
post problem solving is CFC (chlorofluorocarbons), an innovation that
improved the safety and quality of refrigeration
9
eventually that was
eventually recognised as a hazard to the ozone layer and its production
was proscribed by international treaty (Montreal Protocol on
6
Both of these assumptions were later questioned. Most dramatically, the
public good nature of science was questioned by Collins (1974) and later by
Callon (1994).Rosenberg (1990) observed that firms did invest in ‘non-ap-
propriable’ science with their own money, perhaps because this was a necessary
condition for employing scientists or integrating their scientists within scientific
communities and networks.
7
Exceptions to this rule included defence where planning most often domi-
nated market competition, medical research which was seen as inherently
public, and agriculture where a considerable share of advance was thought to
stem from more widespread adoption of best practice.
8
This was done with Kefauver Harris Amendment or Drug Efficacy
Amendment, a 1962 amendment to the Federal Food, Drug, and Cosmetic Act.
9
CFCs replaced the refrigerants sulfur dioxide and methyl formate that were,
in the case of leakage, directly hazardous to human health.
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1556
Substances that Deplete the Ozone Layer, 1987).
10
Concerns about the
broader implications for the environment or human health and welfare
of the path of scientific advance were viewed somewhat fatalistically as
the cost of progress. They were mostly marginalised until the late 1970s
and 80 s when incidents such as ozone depletion resulting from CFCs
and the Three Mile Island (1979) and Chernobyl (1986) nuclear acci-
dents occurred.
The actors in this innovation model have a clear division of labour
and responsibility. Scientists are expected to pursue the advance of
scientific understanding with only incidental attention to the potential
commercial value of their discoveries
11
, to publish their work fully
disclosing the methods and findings
12
, and to assume that those taking
up their discoveries will use them in a socially responsible manner. The
public sector is expected to fund scientific research generously and to
regulate science to assure its openness and to encourage self-regulation
of scientific misconduct (e.g. falsifying results or making unjustified
claims) by the scientific community. The public sector is also expected
to offer a means for identifying problems arising from the application of
science and to refer these to experts in the scientific community for
evaluation and solutions, and eventually regulation. The role of the
private sector is to transform scientific discoveries into innovations
which will support sustained long term economic growth. In the 1960s,
it was assumed that the competence to do this would exist primarily in
large incumbent corporations who would be able to build the industrial
research capacities to perform the applied research and development
efforts necessary to commercialise scientific discovery.
2.3. Framing 1: policy practices
The first framing encouraged an expansive view of the benefits of
research but, nonetheless, policy practitioners had to negotiate the
political process through which research funds are allocated. The pol-
icymaker definition of missions and mission led research programmes
discussed above were most apparent in the US where several large
governmental Departments (defense, energy, and health
13
) have con-
tinued to sponsor basic and applied research and in France where
atomic energy and medical research epitomised a dirigiste approach to
scientific advance. The political advantage of mission-led research is
that the funding of basic scientific research can be justified in terms of
its contribution to specific objectives rather than relying solely on the
somewhat vaguer promises about science’s long run benefits.
The stress on the importance of science and technology led to the
creation of many policy instruments aimed at stimulating com-
plementary business R&D including favourable tax treatment, direct
subsidies employed horizontally to specific industries and other fa-
vourable conditions for business investment on the premise that a share
of this investment would flow to innovation activities. The recognition
of the significance of new technology-based firms (NTBFs) in fostering
innovation led to the idea that taxation on capital gains from the ele-
vation of equity values should also receive favourable tax treatment to
encourage further investment in these firms. Comparison of the levels of
R&D investment (public and private) between countries became an
important indicator of commitment and performance. More recently,
the European Union has formalised the aspiration of achieving a 3% of
GDP average research intensity across the EU (European Commission,
2010).
Yet while governments are positive about public funding, almost no
country can afford to do everything in science and technology. Choices
are necessary. This led to the development of mechanisms for making
choices between competing alternatives. A prominent mechanism
which developed during the 1980s and 90 s was technology foresight
(Martin and Irvine, 1989). Foresight activities are one means to bring
societal considerations into the selection process, but in practice per-
ceived technological opportunities often dominate.
To ensure that the division of labour between scientific research as a
public good and the private appropriability of applied research, de-
velopment and commercialisation, policy actions to strengthen and
extend intellectual property protection were undertaken. The US has
been particularly aggressive in this area with the establishment of the
Court of Appeals for the Federal Circuit (1982) with a principal remit to
review patent litigation, extensions to the patent life for pharmaceutical
products (1984) and taking a leading role in the Trade Related Aspect
of Intellectual Property (TRIPS) agreement incorporated in the 1994
Uruguay Round of the General Agreement on Tariffs and Trade (GATT).
Finally, education for research careers was a common policy aim
throughout the first framing period and has continued more recently
with an emphasis on STEM (science, technology, engineering and
mathematics) subjects. Assuring the supply of researchers is seen as
critically important to fostering science-based growth.
2.4. Framing 1: alternative or counter framings
The first framing’s depiction of large scale scientific enterprise
joined with large enterprise or complex eco-systems of NTBFs was very
dominant in the US and Europe, but it posed a major challenge for less
developed countries which lacked the resources to invest in the level of
R&D that was required. Sagasti (1980) argued that this was producing
two civilisations, one that generates the knowledge and derives the
principal benefits from it and the other (i.e. the developing world)
passively receiving a part of this knowledge and thereby a diminished
capacity for sovereignty and self-determination. In addition, the tech-
nologies developed by this ‘first civilisation’ were themselves seen as
disadvantaging others as they required capabilities, infrastructures and
a broader context which does not exist in the developing world
(Stewart, 2008). These counter-framings of the beneficial nature of
scientific progress and innovation in the developed country context led
to responses by scholars and policymakers in the less developed coun-
tries.
Following the earlier work of Prebisch (1950) and Singer (1950), a
doctrine of import substitution led a number of countries, particularly
in Latin America, to withdraw from the general trend toward more
liberal international trade tariffs in order to build their own innovation
capacity and infant industries. The same types of policies were em-
ployed in East Asia, perhaps with a greater degree of targeting of spe-
cific industries and with a clear intent to build export capacity rather
than import substitution. Although largely abandoned by the 1990s,
many concluded that these policies had positive effects in the East Asian
context and some argued that these policies had positive impacts in the
Latin American context, e.g. Colistete (2010).
14
The success of these
10
The Montreal Protocol is an example of incomplete regulation since it did
not provide measures for sequestering and destroying existing stocks of CFCs.
So one line of investigation in Framing 1 is regulatory effectiveness from which
ideas about the ‘precautionary principle’ follow.
11
An interesting revision of this part of the model was suggested by Stokes
(1997) who suggested it might be possible to distinguish between lines of sci-
entific research which might be ‘use-inspired’ (e.g. Pasteur’s investigations into
the mechanisms of fermentation) from those that are ‘pure’ (e.g. Bohr’s in-
vestigation of energy states in atoms)
12
See Dasgupta and David (1994) for an interpretation of scientific dis-
closure as an alternative to appropriability for generating social welfare.
13
The unusual structure of the US government (compared to centralised
parliamentary democracies) severs the usual relationship between higher edu-
cation and science policy. In the US, the majority of universities are established
and financed by individual states of the union. The very substantial increase in
Federal funding for research greatly benefitted several of these (e.g. University
of California and the universities established by the Morrill Act of 1862, which
provided a one-off grant of substantial land from the Federal government) as
well as several leading private universities (MIT, Stanford, Harvard, Chicago
and Columbia). See Geiger (1993).
14
In both areas, international pressures were important reasons for the
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1557
policies also contributed to the emergence of a second frame for sci-
ence, technology and innovation policy with an emphasis on national
systems of innovation.
Developments related to Schumacher (1974) and Stewart (1973)
argument calling for an appropriate technology movement attempted to
harness research processes to produce technologies that would be more
suitable in the developing country context (Kaplinsky, 2011). For the
most part, innovations coming out of this movement addressed features
of poverty (e.g. better ovens for using local fuels) rather than meeting
expectations that they would provide significant additions to the in-
come of developing country people. Nonetheless, ideas from this social
movement have recently re-appeared in writings about frugal innova-
tion (Radjou et al., 2012), innovation from the bottom of the pyramid
(London and Hart, 2004), and inclusive innovation (Chataway et al.,
2014). These ideas are becoming integrated in a third frame for science,
technology and innovation policy aiming at enlarging participation in
the innovation process.
3. Framing 2 – national systems of innovation
The emergence of Framing 2 was a response to the perceived in-
completeness of the first framing and to the some of the consequences
of pursuing this model. The post-World War II growth experience that
continued with relatively minor interruptions until the oil shocks of the
1970s and the serious recession of 1981 (often referred to in Europe as
an economic crisis) intensified competition between countries and
highlighted differences in national industry innovative and productive
performance. It also became more apparent during the 1980s that the
convergence between higher and lower income countries was occurring
at a much slower rate than could be explained using the first frame’s
premise that scientific and technological knowledge was a global public
good – in principle, available to everyone in the world. The assumed
global catching up as a result of technology transfer did not happen,
except for the tigers in East-Asia. An explanation of this state of affairs,
consistent with the first framing, was that the richer countries were
protecting and thus holding back scientific or technological knowledge,
thereby excluding other countries from utilising this knowledge to en-
gage in a catching-up process. This idea was contested by Soete (1985)
who observed that the industrial structure of technology-based com-
panies often contained smaller or medium sized firms that were able
and willing to sell technologies (e.g. license patents, sell advanced ca-
pital goods, or be acquired at prices lower than the implicit costs of
reproducing their technologies).
These conundrums in the application of Framing 1 led scholars to
re-examine the linear model of innovation that underlay this framing.
Four important modifications were indicated. First, rather than a global
public good, it was recognised that scientific and technological
knowledge often contained important tacit elements. Knowledge did
not freely travel over geographical and cultural distances, but instead
was ‘sticky’ (Von Hippel, 1994). Second, the ability to absorb knowl-
edge from the worldwide network of research and researchers depends
on absorptive capabilities (Cohen and Levinthal, 1989) which require
prior experience in related research and application. Third, ‘absorptive
capacities’ were found to be social capabilities that stemmed not only
from the level of education but also its qualities and the social cap-
ability of entrepreneurship.
15
Fourth, the character of technological
change was recognised as being cumulative and path-dependent
(David, 1975;Arthur, 1983). A balance existed between major dis-
ruptive innovations that alter the trajectories of search and improve-
ment (path-disrupting), and cumulative innovations that reinforce and
strengthen existing strengths and centres (path-reinforcing), often in
ways that raise important barriers to new entrants.
These modifications of the underlying model of innovation sug-
gested that important international differences might exist in the ca-
pacity to innovate and focussed attention on the processes of learning
and the relation between different organisations in a society. Freeman
et al. (1988) and Lundvall (1992) employed the term national systems
of innovation to identify differing configurations of organisations con-
cerned with the generation and utilisation of scientific and technolo-
gical knowledge. Central to this idea was that some configurations
might be much more effective than others, contributing substantially to
the explanation of the very uneven rates of productive and innovative
performance throughout the world. In particular, Freeman et al. (1988)
suggested that Japan had made important organisational innovations in
the generation and utilisation of technological knowledge which ex-
plained its ability to catch up and overtake companies in advanced
manufacturing sectors such as automobiles and televisions. Linsu Kim
also made major contributions indicating that it is not just R&D in-
vestment but localised learning that generated development and al-
lowed South Korea to catch-up (Kim, 1999). These insights com-
plemented by the growing empirical recognition that innovation is
often initiated by users (von Hippel, 1988) or through feedbacks among
applied research, development and commercialisation activities in what
Kline and Rosenberg termed a chain link model of innovation (Kline
and Rosenberg, 1986).
In the version of national systems of innovation offered by Freeman
(1987,1988), these systems had a national character, reflecting dif-
ferences in institutions and policies. In Lundvall (1985,1988), the
centrality of capabilities for learning was additionally emphasised as a
national characteristic that applied to country-based organisations. The
justification for a geographic-political bounding of these systems was
twofold: institutions and policies are largely established at a national
level and knowledge does not travel easily outside the socio-cultural
milieu in which it is created. Further differentiation of systems of in-
novation thinking involved an emphasis on the ‘stickiness’ of knowl-
edge across geographic spaces suggesting regional systems of innova-
tion or, alternatively, cognitive alignment created by common
participation in an industry and its technological problems regardless of
nationality, leading to sectoral systems of innovation (for an informed
discussion of these varieties see Edquist (1997)).
3.1. Rationale/justification for policy intervention
The socio-historical context of the systems of innovation literature is
important. It arose in an attempt to explain the insurgence of East Asian
economies, first Japan, then the four ‘tigers’ (Taiwan, Korea, Singapore,
and Hong Kong) and, most recently, China. The explanation is that
these countries had become competitive thanks to their national sys-
tems of innovations, which made it possible to participate in a positive
way in the globalisation of trade and finance. The stress on competi-
tiveness is aligned with neoliberal thinking, yet Frame 2 clearly departs
from such thinking by emphasizing the ability of the state to shape a
competitive nation.
From a neoliberal economic perspective, globalisation is seen as the
spread of an international system of liberal trade and investment
creating the basis for international competition and, hence, efficiency in
production and distribution.
16
However, there are important qualifi-
cations to the positive interpretations of this perspective – the processes
of globalisation simultaneously have allowed millions of people to
improve their material wellbeing and impoverished millions of others.
(footnote continued)
abandonment of the policies.
15
The promotion of entrepreneurship is often a stand in for pro-business and
anti-government political sentiments (i.e. the favouring of private rather than
public collective action). However, it also reflects social norms regarding taking
initiative and departing from existing practices often involving the building of
new businesses.
16
The neoliberal perspective is exemplified by Friedman (2005).
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1558
While many of the less developed economies have made major strides
in total national income, the distribution of this income within coun-
tries has, in many cases worsened, and the gap between the income of
the richer nations and the poorest nations has widened (Keeley, 2015;
van Zanden et al., 2014). From the perspective shared by Frames 1 and
2, growth of output and employment is also of central importance in the
future economic welfare of countries and their citizens. Falling behind
in growth raises the spectre of decline and a downward spiral in which
a country becomes less able to compete in international markets and,
because of increasing imports, to maintain domestic firm production of
traded goods. It also threatens the State’s ability to distribute income
from higher tax income. A central aim for science, technology and in-
novation policy is therefore the maintenance of competitiveness – a
goal often stated in mercantilist terms as becoming ever more compe-
titive in order to stimulate continuous growth through exports while
preserving a dominant share in domestic production for domestic
consumption.
17
The national innovation system approach is thus complementary to
a competitiveness agenda, based upon trade advantage rather than
national prestige or military power. Advocates of this agenda (which
remains influential today) argue that states need to assist in building up
a national system of innovation either to preserve or to expand the
competitive advantage of domestic firms. The rationale of the compe-
titiveness agenda retains a Frame 1 perspective to the extent that in-
terventions are limited to pre-competitive research, i.e. the creation of
knowledge upstream of product design. This limitation is largely due to
concerns about state support or quasi-mercantilist policies which were
proscribed in order to create a level playing field in international trade
competition. Scholars have argued for (Graham, 1994) and against
(Cohen and Noll, 1991) this extension of state action. A Frame 2 per-
spective would focus less on funding pre-competitive R&D and more on
learning between the actors in the system. Recently Mazzucato (2013)
focusses on the important role of the state as high-level risk-taker in
developing new technologies, an activity that is both downstream and
more purposeful than science investment. More generally, she draws
attention to the important role of finance plays in national systems of
innovation, a role which has been ignored in many national system of
innovation policies and approaches. She argues that long term patient
finance is needed, provided by the state, to make commercialisation
and diffusion happen.
In terms of the governance of policy interventions, Frame 2 suggests
the desirability of alliances and coordination among the actors within
the innovation system to avoid system failure – the lack of cooperation
and coordination. Other system failures are possible including capture
by vested interests of government policies aimed at facilitating research
and innovation and the creation of cartels under the banner of im-
proved research cooperation and coordination. In this framing, these
should be dealt with by the, often separate, regulatory ministries or
agencies of national governments which, due to the competitiveness
agenda, often have been unwilling to act against domestic concentra-
tions of economic power due to fears of loss of competitiveness in re-
lation to other large multinational companies.
18
3.2. Framing 2: innovation model and actors
Despite its inclusion of a wide range of actors who are seen as
having agency to improve innovation systems, Framing 2 sustains the
technology push perspective of Framing 1. Although users are specifi-
cally identified as a possible source of innovation in the model of in-
novation underlying Framing 2, and user-producer relations are seen as
key, the agency of users is limited to providing input into the knowl-
edge production process by firms and other knowledge providers such
as universities.
The underlying model of innovation in Framing 2, however, was
fundamentally revised with important implications for policy practice.
It moved away from a linear understanding of innovation towards a
more interactive model as is exemplified by the chain-linked model. A
key relevant work distinguished a Mode 1 and Mode 2 structure of
knowledge production similar to our two framings (Gibbons et al.,
1994). This work distinguished five features of Mode 2 knowledge
production: 1) knowledge is increasingly produced in the context of
application,
19
2) transdisciplinarity, the merging or ‘inter-penetration’
of disciplinary frameworks to produce new common frameworks for
research in the context of application (p.29), 3) heterogeneity and or-
ganisational diversity, reflecting the increasing diversity of actors in-
volved in knowledge production, 4) social accountability and reflex-
ivity, involving a wider range of experts in the research process to
accommodate ethical and environmental concerns
20
, and 5) quality
control, the observation that traditional disciplinary peer review of
what constitutes good science becomes more complex as knowledge is
produced in the context of application rather than within established
disciplines and their self-referential norms. Gibbons et al. (1994) sug-
gested the need for institutional reform with particular attention to the
relationships between direct government research efforts (e.g. in public
research laboratories), industrial research and university research to
stimulate the creation of networks to facilitate coordination and co-
operation. This focus on institutional links and interactions resonates
very well with Framing 2, the national system of innovation approach.
A related line of research and policy advocacy within Framing 2 has
been presented using the term Triple Helix (Etzkowitz and Leydesdorff,
1997;Etzkowitz, 1998,2008) – the label refers to the increasingly inter-
twined nature of government, industry, and university research efforts.
Similar to Gibbons et al. (1994), scholars participating in triple-helix
studies have sought to map and analyse the new forms of cooperation
emerging between institutions, to consider processes of governance that
align the interests of these different institutions and to provide guidance
to each type of institution as to how they might enact reforms that
would make national systems of innovation function more effectively.
An important element of triple-helix research has been the premise that
universities should become more entrepreneurial, fostering new com-
pany formation through spin-offs and licensing technology produced
through university research.
The difficulties in transferring knowledge between locations pro-
voked a re-examination of geographical localisation effects (Gertler,
2001). Initial studies highlighted the existence of industrial clusters
(Castells and Hall, 1994) suggesting policies aiming to concentrate
activities of a particular type, e.g. the Malaysian multimedia corridor
(Bunnell, 2002). However, later studies found that governance issues
17
Of course, this raises the same problems with economic sustainability that
Smith (1960 [1776]) observed with regard to earlier mercantilist practices and
that led then and in more recent history to periodic episodes of tariff increases
and breakdowns in international trade.
18
For example, in 1999, the US repealed the Glass Steagall Act (1933) which
had regulated concentration of banks due to the perceived competitive threat of
large foreign banks.
19
According to Gibbons et al. (1994) knowledge production was becoming
more ‘socially distributed’ and had ‘transcended the market’ (p.4) although
their work continues to focus on distinctions between university and industry
producers of knowledge with only an oblique reference (p.37) to von Hippel
(1976,1988) that ‘the presence of potential buyers and users directly in the
contexts of development influence the direction that innovative lines of re-
search will take.’ In fact, von Hippel documents in these two works that it was
users who were directly responsible for many major innovations in the scientific
instrument and other fields.
20
This foreshadows our discussion of these issues in Framing 3. The dis-
cussion of this in Gibbons et al. (1994) (pp. 7-8 and in brief reference
throughout the work) suggests that mechanisms of accountability and institu-
tions for reflexivity were already in place. However, almost no evidence is of-
fered for this conclusion
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1559
were of critical importance and difficult to reproduce (Cooke, 2001)
and that proximity in several different senses had the potential for
detrimental as well as positive effects (Boschma, 2005), further devel-
oping the ‘stickiness’ of knowledge.
In terms of actors and innovation, Framing 2 reflects perceived
changes in the processes by which applicable knowledge is generated
and exchanged. Rather than being a linear flow from science to applied
R&D to commercialisation, knowledge is generated through interaction
among the (more diverse) actors in national, sectoral and regional in-
formation systems. These interactions involve a process of interactive
learning and the building of capabilities to absorb and adapt knowl-
edge, often influenced by physical and cognitive proximity. For these
processes to be effective, alignment of these actors’ objectives and ca-
pacities for interaction is necessary. Within this model, considerable
attention is paid to exemplars such as Silicon Valley (Kenney, 2000) or
Route 128 (Saxenian, 1996) in the US or the Cambridgeshire area of
England (Garnsey and Heffernan, 2005). There is, however, little con-
sensus as to how this model might be influenced by policy.
3.3. Framing 2: policy practices
The lack of academic consensus regarding the relative effectiveness
of different types of interventions based on a Framing 2 perspective has
led to considerable variety in actual policy practices (Steinmueller,
2010). Central governments have undertaken substantial efforts to
build technopoles (e.g. Sophia Antipolis in France (Longhi, 1999)) and
science hubs (e.g. Tsukubu science city in Japan (Tatsuno, 1986). Re-
gional authorities have attempted to re-vitalise areas by making in-
vestments in new technology-based firms, e.g. the Research Triangle in
the US state of North Carolina (Link and Scott, 2003). These efforts
have had mixed success and the time horizon for successful national or
regional development appears to be very long relative to the tenure of
political decision makers who initiate such plans.
Policies that aim to improve the coordination and alignment among
different actors in innovation systems have been undertaken in many
countries. These often involve funding conditionality, e.g. research
funding on the condition of participation with other organisations in a
network. Such conditional funding has been applied to university,
corporate, and public research laboratory funding. Exemptions from
competition policy guidelines limiting meetings and collaborations
among firms in specific industries have also been proposed and enacted
in order to encourage research network formation (Jorde and Teece,
1990). Foresight has also been used and advocated as a tool for better
communication, more effective coordination, development of con-
sensus and generation of commitment (Martin and Johnston, 1999).
One of the distinguishing features of Framing 2 is the greater role
ascribed to agency as compared to Framing 1 and, accompanying, this
is a greater interest in entrepreneurship. The nature of the entrepreneur
was a central issue in the writings of Schumpeter (Schumpeter, 1947,
1949). However, it was not until the 1980s that a specific focus on
policies cultivating entrepreneurship involving the formation and
growth of new firms, particularly those involving the use of new
technologies started to be a central concern of policy. Promotion of new
technology-based firms (NTBFs)
21
sits uneasily with neoliberal views of
the efficacy of markets and which suggests firm size is irrelevant to the
degree or nature of innovativeness (Kulicke and Krupp, 1987). How-
ever, when issues of agency are considered explicitly, the focus and
drive of such firms, along with the personalities of their entrepreneurial
founders, suggests a reason for special consideration of these types of
firms in government promotion policies. Such policies also reflect the
growing concern for employment and the associated observation that
small and medium sized firms (SMEs) provide the majority of
employment in most economies. In many contexts, this is more of a
problem than an advantage (compared with their larger rivals, SMEs
generally do not have the resources or market presence to engage in R&
D or the large-scale promotion of new technologies, often have lower
levels of productivity and experience higher rates of bankruptcy). The
identifying feature of NTBFs, however, is their pioneering of new
technologies, some of which produce rapid growth in employment and
output. NTBFs also contribute to the larger national system of innova-
tion by creating a greater degree of diversification and specialisation,
enabling larger firms to select from a population of firms with many
more new ideas than might be produced solely through internal R&D
processes.
Framing 2 also suggests a renewed policy focus on the issues of
technological diffusion or take up. The systems approach emphasises
the connection between supply and demand which is taken to be
mediated by non-market as well as market processes. Many modern
technologies involve coordination between firms in sectors such as
aerospace, electronics, COPS (complex products and systems, such as
flight simulators) and zero net carbon emission buildings involving not
only substantial scientific and technological knowledge; but knowledge
that is distributed across many specialised firms. In order for these
sectors to develop and flourish the relationship with their customers
need to be sufficiently stable to support investment while the networks
of firms comprising these sectors need to be adequately coordinated.
Issues of demand and coordination were often addressed historically
through government procurement. While government procurement re-
mains important, private sector demand for the products and services of
these sectors has increased dramatically (in part due to the privatisation
of previous government enterprises in telecommunications and trans-
port). Privatisation not only introduces markets, it also restructures the
non-market relations within these sectors. Governments have a choice
whether these restructurings are conducted in a laissez faire fashion or
involve a role for government regulation, promotion, and interven-
tions.
22
Government policy practices in the Framing 2 involve education
and training of the workforce with the aim of supporting the absorptive
capacities of firms and other organisations. Absorptive capacity is one
of several types of non-market capabilities that become visible when the
analysis of knowledge generation and distribution is deepened beyond
the linear model embodied in Framing 1.
23
In developing economies,
the appropriate direction of educational and skills training policies
often involves the achievement of particular instrumental skills in sci-
ence and technology. In the industrialised economies, there is a con-
tinuing tension between laissez faire education policies and skills and
labour force development policies that provide greater resources for
particular types of education (Machin and Vignoles, 2015).
3.4. Framing 2: alternative or counter framings
The national systems of innovation and related (sectoral and re-
gional) frameworks are structured around knowledge sharing and col-
laboration among organisations employing professional researchers. A
consequence of this is that the broader societal discussion of techno-
logical options and directions is not integrated into the operation of
networks, even when these networks are established as the result of
government intervention. In effect, the national system of innovation
21
As a descriptive category, NTBFs already existed in reviews of industrial
performance.
22
A pure laissez faire approach is rare since governments typically remain
involved in issues such as standardisation and regulation as well as being major
customers in the restructured sectors.
23
Capabilities for networking including supplier and value chain manage-
ment, market development and knowledge management are other examples of
such non-market capabilities. Although some parts of these capabilities can be
acquired through market transactions, the choices involved in these transac-
tions themselves require capabilities within the firm or organisation.
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1560
framing continues the technocratic politics of the innovation for growth
framing (Framing 1). Both framings, as commonly employed in policy
discussion, share an understanding that investment in R&D and in-
novation is positive. This investment might be criticised and thus
stopped for ethical or environmental constraints, but there is not a
multiplicity of pathways or alternatives which need to be discussed by
all stakeholders including users and the wider public. The alternative or
counter framing is one that explicitly introduces participatory and in-
clusive processes that are empowered to identify alternatives and to
influence or take decisions regarding all possible options. This is not a
process which should be left entirely to the scientific community.
This alternative framing suggests thus the need to open up process
of choice to all stakeholders including marginalised actors, to provide
them a voice and influence over what paths are followed in research
and its funding. This issue has been taken up more recently by Dutrénit
and Sutz (2014);Lundvall et al. (2009) and others who draw on a na-
tional system of innovation approach. They ask why this approach gives
little attention to the problems of developing countries. Their central
concern is that the national system of innovation approach is leading to
social exclusion, and they stress, the need for participatory approaches
so as to democratise knowledge production (Dutrénit and Sutz, 2014).
The call for more and wider participation has been present in criticisms
and debates in Europe and the US since the 1970s. It has often led to
one-way public understanding of science type of initiatives which aim
at making the public understand why investment in science deserves
support (Miller, 2001). However, it also led to suggestion for more
radical new policy practices such as Constructive Technology Assess-
ment, Interactive Technology Assessment and Participatory Technology
Design to help in the identification of options and consequences to
existing trajectories of development and change (Rip et al., 1995;Irwin,
2006).
3.5. Summary
As noted earlier, frames are persistent. The first framing of science
and technology policy, based on the premises that science is the basis
for long term economic growth, and that innovation largely involves
the commercialisation of scientific discovery, is present in con-
temporary discussions. Many of the policy practices developed within
this framing of the issues are still practiced although some have been
subject to modification as competing framings of economic policy such
as neoliberalism have sought to limit state aid and to favour markets
over government policies more generally, including innovation policy.
Representatives of the scientific community commonly argue that the
independence of members of this community to pursue curiosity-driven
research is a prime value and is responsible for profoundly important
innovations, a perspective that is consistent with the first and second
framing.
Reflections on policy practice stemming from the first framing have
led to questions about the focus on R&D. It was argued that it is im-
portant to look at how the results of research efforts are used and ab-
sorbed in the economy. The second framing emerged aimed at boosting
the absorptive capacity by entrepreneurs and through institutional
linkages.
Over time it has become clear that the processes of technological
change are uneven in both time and space. Clusters of innovations that
restructure particular sectors have been characterised as disruptive or
major innovations because of their effects on incumbent firms and jobs.
Although the general optimism suggested by the first and second
framings regarding the social welfare impacts of these changes pre-
vailed throughout the 20th century, the extent of income inequality in
high income countries has increased. A number of middle income
countries appear to be trapped into reliance on natural resource-based
growth and trade, and although the BRIC group (Brazil, Russia, India
and China) is a partial exception, many lower income countries have
made little progress in catching up. It is unclear whether more
investment in R&D and building national systems of innovation will
lead to development and catching up. Questions are also asked whether
these investments will reduce inequality and help solve social problems.
They may even deepen these, because only a small segment of the
population will receive the primary benefits from these investments. In
addition, the climate change effects of greenhouse gas emissions, the
environmental effects of the volume of household and industrial waste,
and other externalities produced by the pattern of growth pursued
within the first and second framing have suggested that the regulatory
model bolted on to the basic innovation model is unable to address
these externalities. What is needed to address social (inequality, pov-
erty) and environmental problems is a focus on the directionality of
socio-technical systems, and a more participatory and inclusive ap-
proach. These features are not easily encompassed in the first and
second framings.
4. Framing 3: transformative change
For a decade now governments have recognized they may need to
align social and environmental challenges better with innovation ob-
jectives. Climate change, reduction of equality, poverty and pollution
have been transformed into challenges and opportunities for science,
technology and innovation policy. Through initiatives such as Horizon
2020, the EU expects innovation to address a number of well-chosen
societal challenges and for example contribute to a transition to low-
carbon and inclusive economy.
24
The 2015 Lund Declaration explicitly
prioritises training a new generation of researchers who will have the
skills to address grand societal challenges underpinned by an excellent
research base.
25
Also, the newly signed universal Paris climate change
agreement has set the ambitious goal to reach zero net carbon emissions
in the second half of the century, and the United Nations (2015) has
formulated 17 Sustainable Development Goals (SDGs), calling for
greener production, increased social justice, a fairer distribution of
welfare, sustainable consumption patterns and new ways of producing
economic growth.
Can we expect innovation to deliver on these challenges? Science,
technology and innovation policies are based on the assumption that
innovation is a force for creating a better world.
26
The idea is that
developing new technologies will lead to higher labour productivity
and economic growth, and a better competitive position. It is expected
that remaining externalities can be managed through regulation. In-
novation policy focuses subsequently on stimulating R&D and building
national systems of innovation. The assumption is that such a policy can
lead to green growth in which governments are able to invest in clean
technology missions, reducing pollution and cleaning up the environ-
ment. It is also assumed that inequality will be reduced through new job
opportunities generated from growth and income redistribution. How-
ever, this is of course only so when we assume nation-states, despite
globalisation, have the ability to invest in clean technologies in a per-
sistent way for a longer time period, are in the position to organize the
distribution function in an adequate way, confront tax avoidance, and
are not captured and/or corrupted by other interests which favour in-
vestment and distribution in other directions. A main challenge is
whether the State is indeed in the position to deliver on this.
The potential erosion of the power of nation-states, however, is not
the main challenge. A more fundamental challenge is whether the ex-
ternalities that are generated by growth such as such as climate change
can indeed be managed ex-post through clean technology and dis-
tributional measures, even with a strong state in place. Our core
24
European Commission, KI-31-12-921-EN-C
25
https://www.ukro.ac.uk/authoring/researcher/Documents/
151215_lund_declaration.pdf
26
Exceptions include military security where the operative goal is better
stated as avoiding worse states of the world.
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1561
proposition is that the existing R&D and national systems of innovation
frames for science, technology and innovation policy are unfit for ad-
dressing the environmental and social challenges. An important reason
is that both Frames 1 and 2 assume that stimulating innovation is po-
sitive, there is no deep engagement with the fact that innovation always
represents a certain directionality. Of course, both framings recognize
that technology development might lead to some bad outcomes in the
short term, but it is claimed that the overall benefit compensates for
this. For example, innovation may lead to unemployment in sectors
experiencing rapid technical change; however, in the long term, ev-
eryone will benefit since new high quality jobs will be generated. It was
for this reason that Schumpeter regarded technical change as a process
of creative destruction. As Soete (2013), however, reminds us, in-
novation may also lead to destructive creation, benefiting the few at the
expense of the many, leading to low quality jobs, and creating more
problems than it solves. We think it is time to recognize in our framings
for innovation policy that many technologies are deeply implicated in
persistent environmental and social problems. Innovation contributes
massively to the current resource-intensive, wasteful and fossil fuel-
based paradigm of mass production and mass consumption (Meadows
et al., 2004;Bardi, 2011;Steffen et al., 2015). It also contributes di-
rectly to inequality because current innovation trajectories favour high
tech solutions which assume high quality and pervasive infrastructure,
and produces mass-produced products aimed mainly for consumers
with substantial purchasing power (Kaplinsky, 2011). Innovation po-
licies in their current formats may lead to economic growth but often
exacerbate inequalities. Even fast growth, such as China’s, is accom-
panied by growing inequality (Dutrénit and Sutz, 2014). The starting
point of a new third frame for science, technology and innovation
policy should be that innovation cannot be equated with social pro-
gress, even when corrective social policies are in place. After all, in-
novation itself may be causing a growing set of externalities. How then
can science, technology and innovation policy address the double social
and environmental challenge?
We argue that to meet the ambitious challenges expressed for ex-
ample in the SDGs, we need a new framing for innovation policy. This is
what we call Framing 3 aimed at transformative change. This raises the
question – what needs to be transformed? Based on the research in
sustainability transitions studies we argue that transformation of socio-
technical systems is needed in energy, mobility, food, water, healthcare,
communication, backbone systems of modern societies (Grin et al.,
2010;Markard et al., 2012;Steward, 2012;OECD, 2015). Socio-tech-
nical system transformation is very different from just developing new
radical technological solutions. For example, science, technology and
innovation policy can focus on the introduction of electric vehicles and
its weak spot: overcoming the limited range through battery develop-
ment. However, if the electric vehicle only is a substitute for the current
car and we continue with a car dominated mobility system, the low
carbon and inclusive economy will still be far away. Industry structures
may be transformed but ambitious SDGs are not met. Therefore, we
argue, it would be better to focus innovation policies supporting the
emergence of new mobility systems in which for example private car
ownership is less important, other mobility modalities such as small taxi
vans, public transportation, walking and bicycling are more used in
combination with for example electric vehicles provided by types of
companies dedicated to the provision of mobility services using ICT
capabilities. In this new system, mobility planning and thus also re-
duction of mobility has become an objective of all actors, and even a
symbol of modern behaviour. This is what we call a socio-technical
system transition, it implicates co-production of social, behavioural and
technological change in an interrelated way. Socio-technical system
transformation (or transition) is about changing skills, infrastructures,
industry structures, products, regulations, user preferences and cultural
predilections. It is about radical change in all elements of the config-
uration. This also makes system transitions difficult, because elements
tend to be aligned and reinforce each other. It involves social
innovation, since the focus is on many social elements and their rela-
tions with technological opportunities. It can include high tech solu-
tions as well as innovation in old technologies (bicycles in the example
above). System innovation always involves multiple actors, including
civil society and users who can play a crucial innovative role – not just
one of articulating a demand to be supplied by firm innovation
(Oudshoorn and Pinch, 2003;Schot et al., 2016).
4.1. Rationale/justification for policy intervention
Weber and Rohracher (2012) have explored various rationales
which legitimize science, technology and innovation policy. They argue
that the market failure and system failure rationales that underpin
current innovation policies should be complemented by policies aimed
at transformation. We agree that the framing of transformative needs a
strong narrative and analysing the characteristics of failures could be a
good starting point. Weber and Rohracher propose that policies for
transformative change begin with the recognition of four type of fail-
ures: directionality, policy coordination, demand-articulation and re-
flexivity. This is a very useful framework we would like to draw upon
and add to.
Directionality failure refers to the lack of means for making social
choices over alternative pathways of development. The transformative
change frame takes the question of direction as a starting point and
requires a process for setting collective priorities. It assumes delibera-
tion, a diversity of opinions and thus conflict. Eventually it aims to
establish what Weber and Rohracher call corridors of acceptable de-
velopment pathways.
27
Stirling (2008;2009) argues convincingly that
working with a greater diversity of options without turning too easily
and quickly to “for” or “against” arguments regarding specific ones is
crucially important. Addressing directionality failures requires taking
into account options beyond the narrow boundaries set by incumbents.
It nurtures opportunities for various groups to challenge dominant
views embedded in the current socio-technical systems.
28
Yet at some
point in the process, there will be a need to close down exploration and
focus on certain options. This is not only because solutions need con-
centration of resources and build-up of capabilities, but also to prevent
continuing investment in less promising options (from a transforma-
tional point of view) which will block the upscaling of sustainable
trajectories. Addressing directionality failure is thus not only about the
lack of consideration for a large set of diverse options, but also refers to
the lack of attention to the connections between options and SDGs or
other social challenges. Transformative innovation policy therefore
faces difficult ex-ante and continuing trade-offs among the interests and
visions of different groups. The governance of transformative innova-
tion should be recognized for what it is: a political process which should
provide room for appraising and negotiating the development of a di-
verse set of pathways as well as making choices for specific ones. In this
negotiation process, visions of various groups do not have to be fully
congruent, stakeholders need to recognize sufficient commonly attrac-
tive elements they can relate to in order to move forward (Grin et al.,
2010: 335).
Policy coordination failure refers to lack of ability to coordinate
horizontally policies from various domains. This is different from Frame
2 coordination failure which refers to coordination among the actors in
the science, technology and innovation domain. The coordination
failure addressed by innovation policy for transformative change is
about coordination with specific sectoral policies for healthcare,
transport, energy, food and agriculture, which are obviously crucially
27
This definition of directionality is broader than the one advanced by
Stirling (2008;2009). Who focuses more on one end of the process; the need for
innovation policies which open up a variety of different pathways.
28
Stirling et al developed a very useful multi-criteria mapping tool to sup-
port this process, see http://www.sussex.ac.uk/mcm
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1562
important when socio-technical system change in these areas is at stake.
However, since transformative change is about transforming many
systems, and in the end also the structure of the economy and society,
coordination with other cross-cutting policies, including tax policy,
economic policy, social policy, is vital. Finally, there are multi-level
policy coordination failures to overcome between local, regional, na-
tional and international policy. Transformative change thus needs a
whole of government approach; yet such an approach is prone to red
tape issues, huge transaction costs and capture by incumbents who are
thriving on the dominant socio-technical systems. Therefore, it is
questionable whether the usual approach of creating committees tasked
with coordination, and other coordination structures such as national
research and innovation councils will overcome this policy failure.
We argue that transformative change requires addressing co-
ordination failure by integrating coordination improvements during the
construction of transformative change pathways. The focus should be on
emerging and open-ended coordination in a process of working to-
gether towards transformative change. The notion of tentative gov-
ernance advanced by Kuhlmann and Rip (2014) captures this spirit. It is
defined as an approach which is provisional, revisable, dynamic and
open and includes experimentation, learning, reflexivity, and reversi-
bility. Experimentation is promoted in the sustainability transitions
literature, for example through the concept of Strategic Niche Man-
agement (Kemp et al., 1998;Schot and Geels, 2008), one means of
implementing coordination within innovation policy. Here experiments
are seen as temporary spaces for actors working together on a variety of
concrete pathways, including policy actors as well as other business,
civil society, users and private funders. Strategic niche management
should be seen as a novel form of policy and action and even a new
form of transformative governance, not just a means of piloting or de-
monstrating novel solutions (Turnheim et al., 2018). It is often very
difficult to assure that such spaces go beyond classical technically-or-
iented demonstration and pilot projects. Experiments demand that ac-
tors embrace uncertainty and accept failure as part of the learning
process, focus on articulation of new shared expectations and visions,
the building of new networks, and the shaping of new markets (called
niches) which eventually will challenge dominant practices in main-
stream markets and institutions.
Finally, reflexivity failure must be addressed. For Weber and
Rohracher this is about the capacity to monitor, anticipate and involve
all actors in the self-governance process of transformative change. This
is indeed important, but in terms of failure we would like to stress a
particular form of reflexivity which is connected to deep learning (or
second-order learning) which happens when actors question their un-
derlying assumptions for example about mobility and energy con-
sumption (Schot and Geels, 2008). In policy-making, technology op-
tions are often tested against assumed stable preference such as the
need for mobility and provision of long trips by cars as in the electric
vehicle example above. Hence the emphasis on batteries and not on
new mobility services because the electric vehicles is seen as a sub-
stitute for the current gasoline car not as a stepping stone towards a
new mobility system. Deep learning assumes that actors critically assess
their own preferences and experiment with alternatives. This is what
addressing the reflexivity failure should be about: stimulating the
ability to look from a distance (this could be an imagined future; or a set
of social and environmental challenges) at one’s own deeply embedded
routines which drive collective behaviours and socio-technical change
towards optimisation instead of transformative change.
4.2. Framing 3: innovation model and actors
In the innovation model underlying Frame 3, there is no single best
pathway to sustainability, equality or any other socially desirable goal.
Instead the process of system innovation (embodying invention, in-
novation and diffusion) involves multiple actors in negotiating alter-
native pathways that have the potential to achieve system change. In
this framing the model of innovation must be experimental because, at
the outset, no pathway is known to be fit for purpose in meeting
challenges or feasible in large scale application. It is only through the
accumulation of experience by a variety of actors with different moti-
vations and priorities that an acceptable pathway or pathways can be
discovered and pursued. The aim of experimentation is systemic and
disruptive change informed by scepticism that marginal changes in
existing systems are likely to be ineffective. Yet it is true that it is, as
yet, unclear how experimentation can generate transformative change,
beyond the pilot and/or the niche development which may follow from
it. The question of anchoring and scaling up of experiments is not
sufficiently addressed in the literature or in practice (Kivimaa et al.,
2017).
The sustainability transitions literature does suggest that although
having policies in place for experiments building alternative niches is
crucially important, it is not sufficient. The policy mix should also
contribute to a process of destabilisation of existing locked-in socio-
technical systems (Turnheim and Geels, 2012;Kivimaa and Kern, 2016;
Rogge and Reichardt, 2016;Kern et al., 2017). The resistance to change
from incumbent networks benefitting from the current systems can be
very strong. Such networks often include industries, parts of the gov-
ernments as well as users and civil society. These actors do not perceive
a need to change their behaviour and also believe that they can cope
with challenges ahead within existing frameworks. Incumbency is not
only about vested interests and organisational commitments but also
about cognitive lock-in and values, and thus in the end about prevailing
regulatory, cognitive and normative collective rules embedded in pre-
vailing socio-technical systems. Obviously, any new policy attempt
must navigate pre-existing policies and find ways to create a productive
layering of existing and new policies.
It is important to stress that Framing 3 is not principally a model of
science and technology regulation. Instead, it focuses on innovation as a
search process on the system level, guided by social and environmental
objectives, informed by experience and the learning that accompanies
that experience, and a willingness to revisit existing arrangements to
de-routinize them in order to address societal challenges. A claim un-
derlying Framing 3 is that the innovation process is likely to be effective
in achieving these goals if it is inclusive, experimental and aimed at
changing the direction of socio-technical systems in all its dimensions.
Since socio-technical systems will be defended by policy-makers, users,
industry and civil society groups who benefit from their current shape
and hold worldviews and values which would not require systematic
change, transformative innovation policy necessitate engagement in
science and technology politics not just policy. The type of politics
promoted is one which opens up spaces for experimentation, societal
learning, public debate, deliberation and negotiation, as advanced in
the earlier concept of constructive technology assessment (Rip, T.J.
Misa and Schot, 1995; Schot et al., 2003).
Framing 3 departs from the innovation model of Framing 1 which
focuses on R&D investment, and the enlargement of flows of useful
knowledge in which interactions between government and the scientific
community are central, with some additional attention to issues of
diffusion. It also departs from the Framing 2 system focus on boosting
the absorptive and learning capacity of the system of innovation by
building networks of knowledge among producer and user organisa-
tions, stimulating the alignment and coordination of these organisations
with the aim of producing technological change, and facilitating en-
trepreneurship in the service of the goals of growth, employment and
international competitiveness. The innovation model of both Framings
1 and 2 views social and environmental goals as being achieved through
economic growth and the possibility of re-distribution of surpluses
generated by productivity improvements and by a capacity for tech-
nocratic elites to regulate externalities in the service of social and en-
vironmental goals. By contrast Framing 3 involves deliberating and
exploring these social and environmental goals and underlying values
and embedding them in processes of systemic change. It is built on the
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1563
belief that inclusive deliberation processes give rise to more common
commitments to a search for effective solutions to social and environ-
mental challenges and to recognition that these solutions necessitate
experimentation and learning about underlying assumptions and va-
lues. Framing 3 gives recognition to the fact that assumptions and va-
lues are co-produced in these processes, they are emergent in character
and are further shaped and consolidated in the process of system
change. Framing 3 does not assume consensus, instead the underlying
innovation thrives on the need to identify and work with diversity,
dissension and conflicting worldviews, recognizing the contributions
which can be made by a large variety of actors, and bringing out into
the open the politics involved in any innovation process.
The development and implementation of transformative innovation
policy requires a new knowledge base. Not one dominated by eco-
nomics and innovation studies, but a more interdisciplinary one in
which sustainability transitions studies, STS and more broadly gov-
ernance studies, history of technology, and other fields contribute.
Since transformation is a global process, it also requires a deep in-
volvement of development studies. There are signs interactions between
these fields is emerging, but overviews of innovation policies are often
still far too limited in their scope (Smits et al., 2010;Fagerberg et al.,
2013;Fagerberg, 2016). There is still a long way to go.
4.3. Framing 3: policy practices
The policy actions needed for transformative can be translated in
new public missions, yet this will not be sufficient and if done in the
wrong way may lead to problematic outcomes. Public investment on its
own will not bring about the necessary system transformation
(Kuhlmann and Rip, 2014;Foray et al., 2012). Mission oriented policies
could be productive if the missions are formulated in an open-ended
way that encourages experimentation and diversity. New forms of en-
gagement and networks are required between public, private and third
sector actors.
Transformative change requires change of life-style, and thus daily
mobility, water, energy, food and other resource use practices, not only
of individual users (or consumers) but also of industrial and profes-
sional users. In the end, change is not only about the construction of
new production structures, but also of user environments and markets
in which new type of demands and use preferences will be dominant
(Ornetzeder and Rohracher, 2006). Mazzucato (2015;2016) stresses
the need for actively shaping and creating. Such a process cannot be left
to the producers, it needs to involve the users in a wide range of ca-
pacities: as user-producers (users-entrepreneurs) actively coming up
with new solutions, users-legitimators providing new visions and ex-
pectations which help shape investment decisions and policy changes,
user intermediaries who broker contacts between producers and larger
groups of users, user-citizens who lobby for wider system reform and
user-consumers who develop new life-styles, preferences and practices
(Ornetzeder and Rohracher, 2006;Schot et al., 2016). This involvement
of users goes far beyond raising awareness and/or measures to articu-
late existing demand. Instead transformative innovation policy prac-
tices should seek active contributions and find ways to assist users in
constructing new demands, user environments and markets.
In this framing it is essential to reflect on social and environmental
needs and the search process has to be guided by improvements in
anticipation of collateral effects and consequences. Developing processes
through which anticipation might be feasible is a priority for bringing
Framing 3 into practice. Some guidance on the processes that facilitate
anticipation is available in the practices developed in connection with
foresight activities and those of technology assessment groups. The
focus of their efforts is often directed at large scale commercial appli-
cation aimed at catching the next wave of technological opportunity
which may open new possibilities, as in technology assessment of na-
notechnology or biotechnology. In Frame 3, the aim of anticipation is to
identify areas for experimentation and, in doing so, to examine the
consequences that may follow in terms of energy and materials use, the
jobs likely to be created, and the effects on the environment of the
introduction and use of new physical artefacts or information processes.
Anticipatory deliberation aims not at producing blueprints, but at
generating multiple possibilities and diverse pathways. It aims to sus-
tain a process of collective search and learning rather than a short-term
assessment based on narrow criteria and yes/no type decision making.
Anticipation is by nature speculative. While it can provide broad
outlines of possibilities it cannot foresee the details that come to light
only through experimentation and learning. Thus, while essential, an-
ticipation must be joined with experimentation within a range of pos-
sibilities suggested by anticipation exercises. Is it better to recycle than
to repair and upgrade? What agricultural practices will prove viable as
alternatives to current reliance of fossil fuels for energy, fertilisers,
transport and processing? What practices will be most effective in
achieving carbon neutral buildings and infrastructures? Here we come
back to our argument that these questions can only be answered
through experimentation at a scale well beyond that of the R&D la-
boratory. It calls for societal experimentation. It is only through actual
practice that experience and deep learning are generated and that the
advantages and disadvantages of a particular innovation pathway can
be identified and remedied by revision or by choosing a different de-
velopment pathway. Deep learning occurs collectively and enables
changes in cognitive frames and assumptions and is akin to second-
order learning (Schot and Geels, 2008). Societal experimentation must
include grassroots innovation with communities and civil society
(Smith and Seyfang, 2013). Framing 3 envisages that experimentation
grows and nurtures new pathways and, in the process, challenges in-
cumbent firms and government agencies that are aligned with them
(regime actors) in preserving the existing trajectory. As argued above,
this entails political struggles around the new goal of sustainability and
it requires incumbent networks including firms to go through process of
strategic reorientation (Geels and Penna, 2015). In this process the role
of intermediary actors in advocating competitive niches, new visions
and policies is crucial (Kivimaa, 2014), as is the construction of net-
works embracing both niche and dominant regime actors (Diaz et al.,
2013)
The need for anticipation, experimentation, learning, and the for-
mation of bridging networks and alliances suggests new institutional
arrangements and governance structures that cut across governments,
markets, and civil society. It also suggests involving public and private
finance and new ways to share and appropriate the gains in knowledge
from these activities. In addition to these new institutional arrange-
ments, ways to better connect existing institutions to achieve co-
ordination and to record and learn from processes of anticipation and
learning are needed. This will require new sets of skills for bridging the
social sciences and the science, technology engineering and mathematic
(STEM) fields which have recently been a priority in many countries
seeking to respond to the imperatives of international competition and
economic growth through productivity increase. Such bridging skills
can be developed through the emerging practice of responsible research
and innovation (Stilgoe et al., 2013;Rip, 2014). When the goals set for
of socio-technical systems reflect a range of social and environmental
needs and more inclusive ideas about social welfare, bridging between
what is possible and what is desirable will also require individuals with
capabilities for bridging social and scientific and technological do-
mains. This implies a re-orientation of education policy and, ultimately,
a pedagogy that is consistent with the desired transition to more sus-
tainable outcomes.
5. Final discussion
Framing 3 raises questions about the shortcomings of science,
technology and innovation in addressing issues of sustainability and
poverty or inequitable income distribution. These shortcomings are
seen as largely external to innovation policy in Framings 1 and 2. This
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1564
makes these framings partly incompatible. Yet our articulation of
Framing 3 does not imply we believe governments should completely
abandon Framings 1 and 2. Investment in knowledge infrastructure and
R&D is an important component of any science, technology and in-
novation policy as well as building up of a set of linkages between main
actors and the encouragement of productive interactions and learning
processes among them in the context of national, sectoral, regional and
in fact transnational systems of innovation. Real world policy contexts
will also always involve a wide range of policy instruments drawing on
several rationales. The policy evolution may take three forms: adding
new goals and instruments (layering), added new rationales and goals
without changing instruments (drift), and adding instruments without
altering rationales (conversion) (see Kivimaa and Kern, 2016). What we
have seen in our work with the Transformative Innovation Policy
Consortium is mainly forms of drift and conversion, less so a process of
layering (Chataway et al., 2017). Layering can also lead to incon-
sistencies, and that is where our thinking about combining three frames
should begin: what would be productive forms of layering?
We would argue the inconsistencies between Framings and instru-
ments can be prevented by thinking about the layering through the lens
of one particular frame. If we were to look at Framings 1 and 2 from the
point of view of Framing 3, we would see that R&D investments pro-
moted in Framing 1 need to become aligned with ongoing process of
anticipation and experimentation and the process of establishing sus-
tainable pathways. Assessing whether regulation delivers barriers for
socio-technical systems change as well as how it could be used to
contribute to the transformative process, for example through a process
technology forcing standard setting, is also necessary. Framing 2 pro-
cesses of building up systems of innovation and promoting en-
trepreneurship need to be opened up too. Questions need to be asked
whether the current systems and entrepreneurial activity only lead to
related variety, reinforcing unsustainable pathways, or whether there is
scope for unrelated variety, too, which would allow a diversification
process in new, more sustainable directions (Frenken, 2017). In addi-
tion, it is not just learning by using, production and interacting which
would be encouraged in Framing 2 (these are all examples for first order
learning), but deep learning too, and this can only happen when the
systems of innovation accept conflict, diversity and dissension. In the
long term, Frame 3 initiatives should be allowed to shape the compo-
sition and directionality of systems of innovation and of R&D invest-
ments.
However, even when policy actors would be able to coordinate
across the framings and thus achieve productive layering from a Frame
3 perspective, there remains an incompatibility between the framings
which policy actors will have to navigate. This is because Framing 3
encourages a deeper set of questions concerning the fit of current socio-
technical systems of provision with societal goals and, ultimately, about
the governance of innovation processes. It argues that eventually we
will need transformative change in many socio-technical systems for
sustainable food, energy, mobility, healthcare, water, and commu-
nication provision. Such systems change is not only about change of
production, but also of distribution and consumption, so it involves all
actors in the economy and society, and is thus pervasive across the
entire economy and wider society. The required systems-wide trans-
formation might be called a Second Deep Transition (Schot, 2016;Schot
and Kanger, 2018;Kanger and Schot, 2018). The transition is deep
because it involves changing a set of deeply embedded directions such
as mass production, individualised mass consumption, productivity,
resource-intensity, carbon-intensity, and global production, shared
among several socio-technical systems. These directions have led to
high levels of wealth and welfare in a number of countries, but also
have left many people in the developing world behind and currently are
contributing towards increased inequality within the rich and highly
innovative countries as well. They also lead to increasing resource in-
tensity, carbon lock-in, and severe ecological degradation. These di-
rections were created during the First Deep Transition to industrial
modernity. The magnitude of social and technical changes required for
a Second Deep Transition implies entering a new phase in the history of
industrialization, industrial capitalism and perhaps even modernity.
The framing implies constructing a new relationship between the state,
the market, and civil society, and most likely, new forms of pro-active
and entrepreneurial state action on national and as well as city levels,
new networks between the state, business, civil society, and new su-
pranational structures ensuring global coordination.
Eventually these new relationships will delegitimize the market
failure argument on which Frame 1 is premised. They will question the
contribution of R&D investment to social goals and purposes, and argue
for government involvement and investment in situations where this
contribution is lacking. It may lead to a much more intensive partner-
ship with investments of governments interfering in what is considered
a free market and thus be viewed as anathema to Frame 1 thinking.
Framing 3 may also well lead to a complete rethinking of the relevance
of the notion of systems of innovation and who is involved and can
speak on whose behalf. Instead of the recommendation to build systems
of innovation of various kinds, it may lead to the conclusion that the
role of the government is precisely the opposite: to experiment and
transform the existing set of relationships, and for example focus on
local and transnational instead of national linkages.
Framings 1 and 2 emerged and were developed mainly in the US
and Europe, and they have been criticised from a development per-
spective. Both frames assume that developing countries need to catch-
up, build their own systems of innovation process in order to absorb
what comes from the developed world and build their own capability.
Frame 3 does not assume that innovations and socio-technical system
change will necessarily come from the Global North or that other
countries need to play catch-up with those innovations. On the con-
trary, the assumption is that both the Global North and Global South
are in a position to experiment with and contribute to transformative
change and that mutual deep learning can be beneficial. In this framing,
diverse pathways are promoted and local generation, experimentation
and adaptation within a complex process of system transformation
should be embraced.
A final question is whether transformative change is an over-
ambitious goal for the scholarly and practitioner community presently
engaged with science, technology and innovation policy
29
. On the one
hand, the answer is clearly yes: such a change cannot be achieved solely
by STI policies; other policies need to contribute too. One should even
go further and recognize that transformative change will not come
about because of new policies; it is a much broader historical process, in
which many actors actively participate already. Transformative in-
novation policy should thus be seen as a response to what is happening
in and to the contemporary world in transition. We would like to add
that the challenges as defined and expressed in the SDGs are very real. If
inequalities become more severe, consequences of climate change and
pollution begin to hit harder, leading for example to more migration
and perhaps even contribute to more conflicts, popular unrest and
threat of armed conflict will ultimately force governments and other
actors to respond. Science, technology and innovation will have to be
part of this response, since they are hugely implicated in the generation
of all these so-called externalities. Therefore, it is urgent and timely for
policy-makers and researchers in this area not to wait, but to develop
not only a new framing but also begin to experiment with new policy
practices. These should address the double social and environmental
challenges head on and contribute to peaceful and low-cost transitions
to new socio-technical systems.
29
The scale of challenge to this community has been outlined in Nelson
(2013).
J. Schot, W.E. Steinmueller Research Policy 47 (2018) 1554–1567
1565
Acknowledgements
This research was partially funded by the Transformative
Innovation Policy Consortium, a multi-partner collaborative pro-
gramme of capability building and policy experimentation (see http://
tipconsortium.net/).
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... This study contributes to research on AI policy debates by looking on how they articulate the purpose of AI development and use. To do that, it draws on the studies of the two major frames of technology policy, namely its contribution to economic competitiveness and societal challenges (Diercks et al., 2019;Mazzucato, 2021;Schot & Steinmueller, 2018;Ulnicane, 2016). According to the first frame, technology is expected to contribute to economic growth and competitiveness. ...
... Technology policy globally is undergoing major changes in framing (Diercks et al., 2019;Mazzucato, 2021;Schot & Steinmueller, 2018;Ulnicane, 2016). Traditionally, technology policy largely focussed on economic growth, productivity and competitiveness and was justified by market failures and system failures requiring government intervention in times when market did not provide sufficient support, investment and networks for the development and use of new technologies. ...
... Traditionally, technology policy largely focussed on economic growth, productivity and competitiveness and was justified by market failures and system failures requiring government intervention in times when market did not provide sufficient support, investment and networks for the development and use of new technologies. Recently, the key assumptions of this frame have increasingly been challenged arguing that technology development should be directed towards societal objectives known as Grand societal challenges and the United Nations Sustainable Development Goals in the areas such as climate change, health and poverty reduction (Diercks et al., 2019;Mazzucato, 2021;Schot & Steinmueller, 2018;Ulnicane, 2016). Rather than fully replacing previous economically oriented technology policy frame, new focus on societal challenges can be seen as layering process when old and new technology paradigms co-exist and in practice sometimes overlap. ...
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... Les friches sont un objet de recherche idéal pour explorer ces questions (Evans, 2003 ;Jones et Evans, 2006 ;Lokman, 2017), elles représentent un « artefact » des sociétés humaines, qui permet de faire l'archéologie des activités anthropiques, à l'instar du passé industriel d'un territoire (archéologie industrielle 1 , voir par ex., Woronoff, 1989), et, leur transformation offre une opportunité pour étudier la transformation socio-écologique, par les initiatives potentiellement transformatrices développées sur ces sites et la manière dont celles-ci sont construites et mises en oeuvre. La transformation et/ou la régénération des friches représente alors une situation/cas permettant l'étude du changement transformateur (Burch et al., 2014 ;De Haan et Rotmans, 2018 ;Grin et al., 2010 ;Schot et Steinmueller, 2018) nécessaire, à l'initiation de la transition écologique en France. Nous nous proposons d'explorer ce sujet à travers la question centrale de cette recherche, à savoir « est-ce que les acteurs mobilisent la Notre problématique se décline en deux questions de recherche: i) quelle est la prise en compte des enjeux de l'adaptation aux changements climatiques par les acteurs des friches; et ii) quelle intégration des dynamiques socio-économiques et écologiques dans la conception et la mise en oeuvre des initiatives de transformation de friches, dans un contexte de changement global. ...
Thesis
L’objectif de la thèse est d’explorer les actions et les perceptions des acteurs intervenants dans la transformation de ces espaces délaissés, au niveau d’un territoire (sur la base du cas de l’Aire Métropolitaine de Lyon-Saint-Etienne, LySEM), dans le contexte des changements globaux. Il s’agit en particulier de savoir si les acteurs mobilisent la transformation et/ou régénération des friches pour développer des trajectoires socio-économiques et écologiques soutenables, à l’échelle locale ? Et si oui, comment procèdent-ils ?Dans le chapitre 1, nous avons cherché à identifier les parties-prenantes à considérer lors de la mise en œuvre d’initiatives de transformation de friches, quelle qu’elle soit leur nature, et les logiques qui sous-tendent ces projets de transformation, en fonction des contextes et des enjeux au sein des territoires. Nous avons pu montrer dans le chapitre 2, sur la base d’exemples tirés de la littérature, les possibilités qui s’offrent aux acteurs pour redévelopper des friches sous une perspective socio-écologique, en soutenant les capacités adaptatives des systèmes écologiques et les capacités adaptatives des systèmes sociaux. Ainsi, nous avons proposé un cadre heuristique pour analyser la transformation des friches, avec un volet écosystémique, permettant de limiter les approches économico-centrée de ces initiatives.Dans le chapitre 3, nous avons d’abord, exploré la prise en compte des changements climatiques, dans la mise en œuvre de stratégies et d’actions pour l’adaptation et la préservation de la biodiversité. Cette analyse a montré que les acteurs, bien qu’ils soient conscient des impacts des changements climatiques au niveau local, les actions en faveur de l’atténuation et/ou l’adaptation climatique restent subordonnées aux intérêts limités du court-terme, notamment de nature socio-économique et aux approches de planification qui favorisent des réponses isolées, réactives. Nous avons pu constater aussi un fort intérêt pour la transformation des délaissés vers des espaces verts en les promouvant et en les concevant pour leurs avantages esthétiques, d'infrastructure verte et de loisirs, et dans une moindre mesure pour la biodiversité. Dans le chapitre 4, nous nous sommes focalisés sur les acteurs de l’aménagement du territoire intervenants de manière directe ou indirecte dans la transformation des friches, afin d’explorer leurs points de vue (world views) à propos de la mise en œuvre d’un changement qui permet une reconfiguration du système d’aménagement en vue de développer des trajectoires socio-économiques et écologiques soutenables, au niveau du terrain d’étude, LySEM. Nous nous sommes appuyés sur l’approche par la construction de récits de changement (ou narrative of change), pour analyser les dires des acteurs. Cette analyse a montré que les narratives produites remettent en question le modèle capitaliste de développement économique, sans pour autant proposer d’imaginaires alternatifs transformateurs. Les territoires tentent de remobiliser les sites en friches dans des logiques marchandes et répondre à des enjeux de compétitivité, d’optimisation du développement socio-économique, tout en intégrant des objectifs environnementaux comme outil d’aménagement. Dans le chapitre 5, nous avons réalisé une revue de littérature à propos de la transformabilité des systèmes socio-écologiques complexes afin de mettre l’accent sur les risques d’apparition de problèmes pernicieux qui peuvent entraver ces processus de transformations délibérées. La compréhension des processus sous-jacents aux transformations socio-écologiques apporte des éléments pour anticiper la mise en œuvre en identifiant les facteurs conduisant à l'émergence de problèmes pernicieux lors de la conception de transformations socio-écologiques.
... One relevant question is how knowledge systems and social institutions such as law enforcement and higher education institutions have sustained systemic marginalization of Blacks, as the racialized "Other," inferior, and worth less (Apata 2020;James 2012;James and Turner 2017). Higher educational institutions occupy a privileged position in the business of knowledge production and innovation towards social development (Schot and Steinmueller 2018;Etzkowitz and Zhou 2017). In the last four decades, Canadian universities, like those in other countries, have been reeling from dramatic changes due to or in response to neoliberal globalization of higher education (Majhanovich 2020;Connell 2013). ...
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... In the case of cooperatives, it should be noted many authors view renewable energy cooperatives as a tool for sustainable economic development without paying attention to the barriers that need to be overcome before such cooperatives are established [14]. ...
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The triple helixof university-industry-government interactions is a universal model for the development of the knowledge-based society, through innovation and entrepreneurship. It draws from the innovative practice of Massachusetts Institute of Technology (MIT) with industry and government in inventing a regional renewal strategy in early 20th-century New England. Parallel experiences were identified in “Silicon Valley,” where Stanford University works together with industry and government. Triple helix is identified as the secret of such innovative regions. It may also be found in statist or laissez-faire societies, globally. The triple helix focuses on “innovation in innovation” and the dynamic to foster an innovation ecosystem, through various hybrid organizations, such as technology transfer offices, venture capital firms, incubators, accelerators, and science parks. This second edition develops the practical and policy implications of the triple helix model with case studies exemplifying the meta-theory, including: • how to make an innovative region through the triple helix approach; • balancing development and sustainability by “triple helix twins”; • triple helix matrix to analyze regional innovation globally; and • case studies on the Stanford’s StartX accelerator; the Ashland, Oregon Theater Arts Clusters; and Linyi regional innovation in China. The Triple Helix as a universal innovation model can assist students, researchers, managers, entrepreneurs, and policymakers to understand the roles of university, industry, and government in forming and developing “an innovative region,” which has self-renewal and sustainable innovative capacity.