making us believe that the world is a much more predictable place than it really is. 4 With ontological unpredictability Tuomi refers to the theoretical incompatibility between innovation
and predictive models when disruptive and downstream innovation become more frequent, based on the argument that we can only retrospectively know what we are talking about, due to the unpredictability of natural, behavioural and social processes that shape innovation. 387 K. Haegeman et al./
/Technological forecasting & Social Change 80 (2013) 386 397 qualitative) as an imaginative projection of current knowledge in which formal methods and techniques play a subsidiary role (p. 753.
and radical innovations via 5 The European foresight monitoring Network is one of the few attempts to take stock of quantitative and qualitative foresight methods.
and anticipating disruptive innovation, forecasting radical changes and thus limiting the scale of failures (with a focus on market pull vis-à-vis the technology push approach).
is therefore of the essence. 9 8 During the 2011 FTA Conference a lively discussion was devoted to the shift of FTA usage from exploring potential risks to inspiring sustainable innovation.
and addressing different types of innovation. 9 A good example is the contribution that FTA can provide to policy and decision makers in charge of the prioritisation of alternative technological options.
Concepts and Practice, Edward Elgar, Cheltenham, UK, 2008.17 A. Havas, D. Schartinger, M. Weber, The impact of foresight on innovation policy-making:
Change 77 (2010) 466 478.39 K. Haegeman, C. Cagnin, T. Könnölä, D. Collins, Web 2. 0 foresight for innovation policy:
a case of strategic agenda setting in European innovation, innovation: management, Policy Pract. 14 (3)( 2012) 449 469.40 F. K. Jin, W. R. Fah, N d. En, L. M. Wei, L
and has worked previously in innovation policy, regional economic policy, project management and market research. He has been involved in a diversity of European-wide research projects (the most recent one on Visions for the European research area)
and worked in innovation, education and local development policies. She has experience in quantitative and qualitative research methods
and internationally devoted to Foresight and S&t and innovation policies; managed several national S&t foresight exercises in Russia,
In this research, we choose the Derwent Innovation Index (DII) as the data source and Vantagepoint (VP) for data cleaning and extraction.
and the Knowledge Innovation Program of the Chinese Academy of Sciences. We are further sincerely grateful
A l. Porter, Innovation forecasting, Technol. Forecast. Soc. Change 56 (1997) 25 47.15 R. Haupt, M. Kloyer, M. Lange, Patent indicators for the technology life cycle development, Res.
Technol. 34 (4)( 2009) 57 60.21 Y. C. Wu, T. C. Yen, RFID technology innovations:
Policy 29 (2000) 409 434.23 D. Hicks, A. Breitzman, K. Hamilton, F. Narin, Research excellence and patented innovation, Sci.
State-of-the-art and new approaches Tessaleno C. Devezas Technological forecasting and Innovation theory Working group, University of Beira Interior, Covilha, Portugal Received 13 may 2004;
technique, technology and (technological innovation. An evolutionary approach within the framework of danthropology of techniquet is a necessary step to grasp adequately these concepts.
and technology assessment, describing the competition among firms or innovations, or simply among products struggling for a bigger market share.
and Pry 9 demonstrating the validity of the normalized logistic equation in accounting for technological substitution processes or for the diffusion of basic technological innovations.
and diffusion of innovations and pure learning processes (as for instance the growth curve of a child's vocabulary achievement,
what is the common denominator underlying the growth phenomena of populations of multiplying cells, Drosophila, humans, and innovations?
Yet it is the arising of these robust and resilient structures, in other words, the emergence of innovations, that is of profound interest,
that can be subsumed under the following questions are innovations (or novelties) in the biological, cultural,
To begin with it should be stand out that the notion of innovation belongs itself to that collection of fuzzy concepts,
innovation is by far the more transversal of them, bearing probably all possible human spheres of action.
and 11,500, 000 for innovation! But attention please: the true winner in this modern competition is evolution with more than 17,000, 000 hits,
I want to advance the following arguments favoring an evolutionary approach to define innovation and then answering in the positive the question above about the same nature of novelties in the biological, cultural and technological realm:!
"In biological systems an innovation can be achieved without necessarily changing the genetic underpinnings of a feature,
dgenotypest by any sequence of building blocks, ddifferential reproductive successt by differential adoption in a market and dphenotypet by technical expression. $ My final argument favoring an evolutionary definition of innovation regards the aspect mentioned above of how strongly evolutionary
4. My proposal of definition is then simply 4. 1. Innovation is the emergence of a new adaptive design This definition has sufficiently broad meaning
when we focus the evolutionary analysis on technological innovations we are not necessarily simplifying the field of discussion,
3 Are technological innovations indeed teleological or Lamarckian in nature or not? Looking at the history of inventions and basic innovations we can find some evident cases of intended
and/or planed novelties as well as it appears to be common to find a wide range of dramatic early random experimentation with radically different designs,
In a very recent book edited by John Ziman 15 (Technological innovation as an Evolutionary Process) we have different authors theorizing about these questions,
which otherwise open the way to the revival of Joseph Schumpeter's ideas of a evolutionary global economy driven by the clustering of basic innovations
this set of processes is driven fundamentally innovation (each in its own scale), exhibits power-law behavior and it is poised in the critical boundary between order
Stephen Wolfram 32, has been applied to the evolutionary simulation of the innovation diffusion process by a group of the Hebrew University led by Jacob Goldenberg and Sorin Salomon 33,
as Gerald Silverberg and Bart Verspagen 35, for the study of the distribution of innovations;
David Goldberg 37, for instance, for studying the connection between the two basic processes of innovation, continual improvement and discontinuous change.
and selection+recombination as expressing the basic mechanisms of continual improvement and innovation, respectively. In the present stage of our knowledge no one can be sure
and more energetic among a broad innovation-driven and co-evolutionary set of processes, composing the whole of the world system.
discovery, invention and innovation cycles revisited, Technol. Forecast. Soc. Change 18 (1980) 257 282.11 T. Modis, Predictions:
From Chaos To order, Perseus Books, Cambridge, Ma, 1998.15 J. Ziman (Ed.),Technological innovation as an Evolutionary Process, Cambridge university Press, 2003.16 R. R. Nelson, S g. Winter
, S. Efroni, Using cellular automata modeling of the emergence of innovations, Technol. Forecast. Soc. Change 68 (2001) 293 308.
the reawakening of extinct innovations, Technol. Forecast. Soc. Change 71 (2004) 881 896.35 G. Silverberg, B. Verspagen, A percolation model of innovation in complex technology spaces, J. Econ.
Dyn. Control 29 (2005) 225 244.36 Z. Michalewicz, D. B. Vogel, How to Solve it:
Modern Heuristics, Springer, Berlin, 2002.37 D. Goldberg, The design of innovations: lessons from the genetics, lessons from the real world, Technol.
and Head of the Technological forecasting and Innovation theory Working group (TFIT-WG). T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1152
Policy learning is also a major issue in evolutionary economics of innovation 27 29. Early applications of adaptive policies are also found in the field of environmental management 30,31,
Innovation strategies in Interdependent States, Edward Elgar Publishing Ltd. Gloucestershire, 2006.28 A. Faber, K. Frenken, Models in evolutionary economics and environmental policy:
Change 76 (2009) 462 470.29 L. K. Mytelka, K. Smith, Policy learning and innovation theory: an interactive and co-evolving process, Res.
Change 77 (2010) 1195 1202.48 W. J. Abernathy, K. B. Clark, Innovation: mapping the winds of creative destruction, Res.
Future scenarios to inspire innovation Peter De Smedt a,, Kristian Borch b, Ted Fuller c a SVR, Research centre of the Flemish Government, Boudewijnlaan 30, B-1000 Brussels, Belgium b Department of Management Engineering
Due to the social dynamics of innovation, new socio-technical subsystems are emerging, however there is lack of exploitation of novel ideas
elements of good practices and principles on how to strengthen innovation systems through future scenarios are identified. This is needed because innovation itself needs to be oriented along more sustainable pathways enabling transformations of socio-technical systems. 2012 Elsevier Inc. All rights reserved.
Keywords: Reflexive inquiry Innovation Scenario practice Grand challenges 1. Introduction In the context of this paper, future scenarios can be seen as narratives set in the future to explore how the society would change
if certain trends were to strengthen or diminish, or various events were to occur. Future scenarios substantially differ from predictions, i e.,
and using scenarios and orienting innovation systems and research priorities 6. Technological forecasting & Social Change 80 (2013) 432 443 Corresponding author.
and using scenarios lead to the expected direct and indirect inputs for orienting innovation systems? These concerns are legitimate
and to disclose some principles by which scenario processes can inspire innovation. Today's grand challenges from climate change to unemployment and poverty go beyond economic
whose distinctive feature is disagreement among experts and stakeholders about the long-term consequences of present-day innovations 11.
and systems of innovation are shaped by social, cultural and political power as well as by technological rationalism and such indeterminism makes systemic approaches to innovation policy far from linear or predictable.
The recent economic crisis reminds us of the importance of mobilizing science, technology and innovation not solely for generating economic benefits,
but also for anticipating and responding to the grand challenges 15. At a strategic level, the European union took up this challenge via the Innovation Union Flagship Initiative as part of the Europe 2020 strategy launched in 2010.
This initiative is an example of a strategic approach integrating research and innovation instruments and actors to tackle the innovation emergency related to the grand challenges the European union is facing 16, p1.
Futures thinking is an essential element of developing such a strategy. For example, Hamel and Prahalad 17 emphasize that strategy should draw up consistent visions of the future.
The traditional concepts and models of innovation are not always adequate to embrace the complexity for addressing the grand challenges 10,15.
It has been documented well that the innovation process is interactive including a multitude of short-term and long-term feedback loops between the different stages of the innovation process 15,24.
innovations are not only contributing to the solutions. Innovations in the past have been also part of the current unsustainable trends.
Therefore innovation research needs increasingly be oriented towards the challenges presented by environmental complexity and socioeconomic turbulence 25.
In order to investigate how scenario analysis can help better cope with the grand challenges and inspire innovation, we analyze several scenario exercises to better understand the role future scenarios can play as a tool for orienting innovation systems.
The remaining sections of this paper are organized as follows: Section 2 sets out the methodology of how we use reflexive inquiry to analyze the scenario case studies.
Section 3 describes how we conceptualize inspiring issues and paradigms from different scientific disciplines such as business and innovation research, futures studies, sociology and policy analysis.
These concepts and paradigms are used then to analyze the selected scenario case studies. For example, we look how the applied
In Section 5, we further discuss our findings addressing how scenario practice can orientate innovation systems in the view of the grand challenges.
/Technological forecasting & Social Change 80 (2013) 432 443 2. Material and methods How can we learn about orienting innovation systems from future scenario practice?
and adapting our underlying theoretical premises. 3. Concepts of innovation, futures thinking and scenarios 3. 1. Innovation systems Innovation involves the application of new ideas
or the reapplication of old ideas in new ways to develop better solutions to our needs 31.
Innovation is invariably a cumulative, collaborative activity in which ideas are shared, tested, refined, developed and applied 32.
The concept of national innovation systems is rooted in evolutionary economic theorizing on socio-technical change 33 35.
The development of innovation theory over the past decades has involved a major reformulation, with innovation no longer seen primarily as a process of discovery,
i e. new scientific or technological principles, but rather as a nonlinear process of learning 36.
An innovation system is never static; it evolves with alterations in the content of technologies and products as well as in the relationships among various other innovation systems.
Due to the socially dynamic characteristic of innovation 37, new socio-technical (sub systems will emerge over time 22.
By consequence, innovation systems are described as networks of actors and institutions that develop, diffuse and use innovations 38.
Hence, innovation leads to change only to the extent that agents are successful in taking advantage of the opportunities,
i e. agents need to develop capabilities 39. Innovation in the 21st century differs from the model embraced in the last century
(i e. profit-oriented and nationally targeted) with a linear, technological and deterministic characteristic 15. Although the innovation process is now much more open and receptive to social influences,
further progress calls for a greater involvement of stakeholders who can introduce the necessary capabilities
and interests in research and innovation to address the grand challenges. For instance, Hekkert et al. 40 highlight that stimulating knowledge flows (alone) is not sufficient to induce technological change and economic performance.
There is a need for stakeholders to exploit this knowledge in order to create new business opportunities. This stresses the importance of stakeholders as sources of innovation.
The required characteristics of the new mode of public involvement are challenging: long-term forward-looking intervention, inter-ministerial, demand-side instruments combined and coordinated with supply-side instruments, based on foresight,
Hence, the social dimension in innovation should be acknowledged as a legitimate research area and linkages with social systems of innovation and social innovation stakeholders should be strengthened
so that innovation experiments include the inherent social dimension within the research community 15.3.2. Futures thinking Futures thinking is used for medium to long-term strategic analysis and planning.
According to Jørgensen 41, citing Dreborg 42, there are three modes of thinking about the future, each with their own methodologies the predictive, the eventualities and the visionary mode of thinking, see Table 1 for a more elaborate description.
One of the often-overlooked elements in the innovation process that hinders smooth communication and interaction within emergent networks is time 44.
as well as to innovation objectives and milestones 55. The Delphi method is developed as a systematic, interactive forecasting method,
This technique is used often in national foresights to guide innovation and national research policies 58 60. All the above describe approaches to futures thinking during which (potential) inputs for scenarios can be produced.
missing the opportunity to explore the potential for innovation in conflicting views. Although legitimate for several reasons,
In addition, our analysis indicates that scenarios with a strong focus on consensus during the development are often too vague and too broad for defining tangible innovation opportunities.
We found that crystallizing concrete policy initiatives for innovation from long-term future images, i e. beyond twenty years, can be difficult.
In that sense the potential for innovation within the system (i e. inward reflection) is acknowledged less. When considered from the perspective of creating legitimacy for action we also suggest that the scenarios in this group could benefit fromcomplementary techniques connecting the long-term future images to the present via stepping stones.
Using roadmaps is an example of such a complementary technique for linking scenarios with internal innovation capabilities (i e. inward reflection.
and establishing a common vision among the innovation stakeholders as a boundary framework before moving into technology roadmapping 70.4.2.2.
Clearly innovation is an essential feature of the scenarios. 2 PRELUDE: PROSPECTIVE Environmental analysis of Land use Development in Europe. 437 P. De Smedt et al./
The innovation potential of the scenarios can be strengthened through broadening the system boundaries and enriching the future images.
In addition, including perspectives from the different stakeholders can reveal new areas for innovation 73.4.2.3. Backcasting from principles A third group of practice is characterized by a focus on backcasting from principles.
This will provide essential information about the robustness of the innovation potential. The 3rd SCAR foresight exercise (see Appendix 1) also falls into this group with its focus on research priorities
and innovation to meet necessary change and uncertainties in the agri-food sector facing resource constrains and environmental limits.
and using future scenarios to inspire innovation do not only deal with the collection of data and models;
and how future scenarios can inspire innovation. 3 http://www. naturalstep. org/./438 P. De Smedt et al./
/Technological forecasting & Social Change 80 (2013) 432 443 5. Discussion Due to the social dynamic characteristic of innovation, new socio-technical subsystems are emerging 24.
however, there is lack of exploitation of innovative solutions for orienting innovation in itself along more sustainable pathways 15.
At the same time innovation has become one of the main engines of growth. However, these two overarching trends have not yet been reconciled 15.
Hence, it is important to recognize that representing scientific and technological diversity offers an important means to help foster more effective forms of innovation
This complexity challenges the capacity of innovation systems to acknowledge the social dimension of innovation and to learn from experience.
The question that emerges is how we can learn from using and developing future scenarios to assist in the orientation of innovation systems?
we can then attribute the most characteristic mode of thinking. 4 Innovation is not only about invention, creation,
or discovery, it is also about adaptation and emergence of new innovation systems 31. Principles on how to orient innovation systems through future scenarios will require conditions for collaboration.
Table 2 Linking groups of future scenario practice from a policy perspective with modes of future thinking.
or contributions to the enablers for orientating innovation systems through future scenarios (i e. pros and cons). Our analysis of the case studies listed in Appendix 1 suggests that a variety of modes of futures thinking,
To strengthen the enablers for innovation within the scenario process, the link between practice and theory,
and implications) cross-fertilizations between the techniques of the different groups can enhance the innovation potential.
the success of innovation is to a great extent dependent upon the activities and abilities of individuals who enthusiastically support it. 6. Conclusions In this paper we analyzed
and using future scenarios as a tool for orienting innovation systems. Our analyses of the scenario case studies from Appendix 1 revealed elements of good practice and implications on how to better address innovation through future scenarios.
For instance different modes of futures thinking have been identified through the process of deconstruction. In this paper, we argue that these modes of futures thinking are shown to contribute in different ways to orientating innovation systems.
Hence, by using a reflexive methodology we were able to create a heuristic to learn from the process of developing
In addition, we also identified some points of departure for further refinement of current scenario practices with respect to innovation.
We also want to Table 3 Different modes of futures thinking for orienting innovation systems via future scenarios.
and cons with respect to orient innovation systems Intuitive Surprise and confrontation Think the unthinkable and conceptualize future situations where uncertainties are high Allows strong imagination including alternative futures that are competing Weak on acceptance,
but often too vague, too broad to inspire innovation Eventuality Possibility Explore contrasting futures and conceptualize future situations for the long-term where uncertainties are expressed differently Allows rigorously exploring boundaries and complexity.
Often an imbalance between outward/inward reflection limiting the recognition of its internal innovation capacity Predictive Probability Better contextualize
what we know to be prepared for upcoming situations Allows defining (a sequence of) clear steps for innovation Weak on surprise
and external change Visionary Preference Envision how society can be designed in a better (e g. more sustainable) way Allows creating authentic alternative visions to guide innovation Weak on clear targets,
and defining areas for innovation Weak on complexity of socio-technological systems Evolutionary Interaction Engage in sustainable pathways enabling transformations of innovation systems Allows a systemized negotiation process linking a variety of social actors
innovation Risk of not reaching out to key (technological) actors 440 P. De Smedt et al.//Technological forecasting & Social Change 80 (2013) 432 443 acknowledge the limits of our analysis:
Innovation systems are complex and dynamic and scenario practice is applied more widely than our sample. Therefore, when using reflexivity in research or in scenario practice,
diffuse, and use innovations. Learning of participants is not always an objective as such, but the process of exchanging knowledge is recognized to overcome some limits of conventional research,
i e. integrating different modes of futures thinking, is needed for orienting innovation along more sustainable pathways enabling transformations of socio-technical systems.
Thirdly, we want to emphasize that the social dimension in innovation systems should be acknowledged as a legitimate research area
and linkages with social innovators and other social innovation stakeholders should be strengthened so that social innovation experiments inform the research community.
Acknowledgments The authors are grateful to the COST Action A22 network, IPTS and different past and present foresight network initiatives such as the European foresight Platform and Forlearn for organizing creative discussion platforms on foresight and scenario initiatives.
, E. A. Eriksson, T. Malmér, B. A. Mölleryd, Foresight in Nordic innovation systems, Nordic Innovation Centre, Oslo, 2007.7 T. J. Chermack, Studying scenario planning:
http://ftp. jrc. es/EURDOC/JRC55981. pdf). 10 C. Cagnin, E. Amanatidou, M. Keenan, Orienting innovation systems towards grand challenges and the roles that FTA can play, in:
Integrating Insights, Transforming Institutions and Shaping Innovation systems, Seville, 12 13,may 2011, 2011.11 A. Webster, Technologies in transition, policies in transition:
Pract. 3 (2001) 311 337.15 OECD, Fostering innovation to address social challenges, in: Workshop Proceedings, OECD, Paris, 2011.16 EC, Innovation Union Competitiveness Report 2011.
Executive Summary) European commission, DG Research and Innovation, Brussels, 2011.17 G. Hamel, C. K. Prahalad, Competing for the Future, Harvard Business school Press, Boston, 1994.18
R. Bradfield, G. Wright, G. Burt, G. Cairns, K. Van der Heijden, The origins and evolution of scenario techniques in long range business planning, Futures
Chang. 65 (2000) 23 29.24 B. Carlsson, S. Jacobsson, M. Holmén, A. Rickne, Innovation systems: analytical and methodological issues, Res.
Policy 31 (2002) 233 245.25 T. Rickards, The future of innovation research, in: L. V. Shavinina (Ed.),The International Handbook on Innovation, Pergamon, London, UK, 2003.26 L. Gunderson, C. Folke, M. A. Janssen, Reflective practice, Ecol.
Soc. 12 (2007) 40 (online URL: http://www. ecologyandsociety. org/vol12/iss2/art40/./27 A l. Cunliffe, Reflexive inquiry in organizational research:
L. V. Shavinina (Ed.),The International Handbook on Innovation, Pergamon, London, 2003.32 C. Leadbeater, We-Think:
The Power of Mass Creativity, Profile Books, London, 2008.33 C. Freeman, The national system of innovation in historical perspective, Camb.
B. A. Lundvall (Ed.),National systems of Innovation: Towards a Theory of innovation and Interactive learning, Pinter, London, 1992.35 R. Nelson, S. Winter, In search of a useful theory of innovation, Res.
Policy 6 (1977) 36 76.36 L. K. Mytelka, K. Smith, Policy learning and innovation theory: an interactive and co-evolving process, Res.
Policy 14 (2002) 1 13.37 R. Sternberg, J. Pretz, J. Kaufman, Types of innovation, in:
L. V. Shavinina (Ed.),The International Handbook on Innovation, Pergamon, London, UK, 2003.38 In: C. Edguist (Ed.),System of Innovation:
Technologies, Institutions and Organizations, Pinter publishers, London, 1997.39 B. Carlsson, R. Stankiewicz, On the nature, function,
. Smits, Functions of innovation systems: a new approach for analyzing technological change, Technol. Forecast. Soc. Chang. 74 (2007) 413 432.41 M. S. Jørgensen, Visions and visioning in foresight activities, in:
Guiding Exploratory Innovation and Strategy, the 4th International Seville Conference on Future-oriented technology analysis (FTA: 12 & 13,may 2011, May 13 2011.71 O. Saritas, J. Aylen, Using scenarios for roadmapping:
Paper Presented at the Future seminar of the Centre for Technology, Innovation and Culture, University of Oslo, 7th of June, 2007, in:
social innovation in a complex world, in: OECD (Ed.),Fostering Innovation to Address Social challenges, Workshop Proceedings, OECD, Paris, 2011, pp. 59 64.80 M. Godet, The art of scenarios and strategic planning:
tools and pitfalls, Technol. Forecast. Soc. Chang. 65 (2000) 3 22.81 T. J. B. M. Postma, F. Liebl, How to improve scenario analysis as a strategic management tool, Technol.
Chang. 72 (2005) 161 173.82 J. Hauschildt, Promoters and champions in innovations: development of a research paradigm, in:
L. V. Shavinina (Ed.),The International Handbook on Innovation, Pergamon, London, UK, 2003. Peter De Smedt has a background in ecological system analyses.
and define research and innovation agendas of established science industry networks. The aim of the paper is to show what problems/challenges with regard to the innovation system have been addressed and
what main actors have been involved, from the first monitoring and forecasting studies on nanotechnology to the establishment of national nanotechnology programs
Governance Emerging technologies Key enabling technologies Nanotechnology Public engagement Foresight Technology assessment Responsible research and innovation 1. Introduction As science and technology become more central to economic development,
A decade ago, the question addressed how to maximize the contribution of such technologies to economic innovation with the intention of enhancing competitiveness 1, 2. Today,
and to address national innovation systems. In the case of nanotechnology, a variety of FTA ACTIVITIES have been in use over the last quarter of a century to structure the field itself
and define research and innovation agendas. In both countries, the public policy activities to foster nanotechnology were accompanied by efforts to establish governance structures to coordinate interactions between actors of the innovation system.
The paper considers the following questions: How is embedded FTA in the national innovation policy? How are specific governance measures related to FTA and to the establishment of focal organizations?
What are the contributions of the distinct future-oriented approaches to the development of nanotechnology governance?
and vision building which impact the complex interplay of factors governing innovation trajectories 27.1 http://www. iso. org/iso/iso technical committee. html?
especially in science, technology and innovation policy-making, 28 the above mentioned activities can all be considered as FTA.
and no experts represented the social sciences, humanities, innovation studies, environmental studies or science and technology studies. At this stage, the FTA ACTIVITIES did not involve a broad range of stakeholders.
which can be characterized as a model of linear and science-driven innovation. In this model, technology results from research whereas society has to adapt to technology to make its applications successful.
The goals defined in the latest NNI strategic plan of 2011 address this user-centric ecosystem by covering the whole ecosystem of innovation:
they address R&d (Advance a world-class nanotechnology research and development program), innovation (Foster the transfer of new technologies into products for commercial and public benefit),
The strategy focused on so-called lead innovations, value chain-oriented collaborative projects with partners from science and industry.
and this institutional fragmentation can also be observed with regard to the governance of science, technology and innovation in the field of nanotechnology. 4. Comparing the US and Germany 4. 1. Timing and intervention Between the late 1980s and the late 1990s,
Participatory processes as well as different concepts of responsible research and innovation in nanotechnology were triggered by global debates on the risks of nanotechnology. 4. 2. International screening
such as the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) focus on regulation issues relevant for their domain without being involved fully in the ecosystem of nano-related Innovation policy definition
and preparation of funding programs) and to influence the national innovation systems by implementing nanotechnology programs and nanotechnology regulatory structures in later stages.
either for future innovative governance or for using nanotechnology for disruptive innovation to address grand societal challenges.
The US nanotechnology governance is oriented conceptually toward responsible research and innovation and broad participation. It has established broad networks with a focal organization as the basis for implementing its strategic vision.
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