Also, the rule of foresight has changed from the previous explorative forecasting to more be come more oriented to strategic planning (Martin, 1995.
The Delphi method is especially useful for long-range forecasting (2030 years), as expert opinions are the only source of information available.
Also, patent documents are used widely as a source for technology forecasting, CTI and for analysis of technology convergence (Kayal, 1999;
while the result from patent analysis for CTI or for forecasting provide a short-term view. Also, survey results of Delphi topics are collective intelligence from the expert interaction of scanned countries
but the forecasting time horizon for the whole foresight activity was set at up to the year 2020, by
. Curran, C. S. and Leker, J. 2011),‘Patent indicators for monitoring convergence examples from NFF and ICT'',Technological forecasting and Social Change, Vol. 78, pp. 256-73.
resurrection and new paradigms'',Technological forecasting and Social Change, Vol. 60 No. 1, pp. 85-94. Hax, A. and Majluf, N. 1996), The Strategy Concept and Process:
implications for technological forecasting'',Technological forecasting and Social Change, Vol. 60 No. 3, pp. 237-45. Markides, C. and Williamson, P. 1994),‘Related diversificaton, core competences and corporate performance'',Strategic management Journal, Vol. 15, pp. 149-57.
Martino, J. P. 1983), Technological forecasting for Decision making, 2nd ed.,North Holland, Amsterdam. Nelson, R. 1997), Why Do Firms Differ
Rowe, G. and Wright, G. 1999),‘The Delphi technique as a forecasting tool: issues and analysis'',International Journal of Forecasting, Vol. 15, pp. 353-75.
Rowe, G.,Wright, G. and Bolger, F. 1991),‘Delphi: a re-evaluation of research and theory'',Technological forecasting and Social Change, Vol. 39, pp. 235-51.
Schmoch, U. 2008),‘Concept of a technology classification for country comparisons'',Final Report to the World Intellectual Property Organization (WIPO), Fraunhofer Institute for Systems and Innovation research, Karlsruhe
Turoff, M. 1970),‘The design of a policy Delphi'',Technological forecasting and Social Change, Vol. 2, pp. 149-71.
Technological forecasting & Social Change 80 (2013) 379 385 Corresponding author at: Center for Strategic Studies andmanagement (CGEE), SCNQD 2, Bl.
Sciencedirect Technological forecasting & Social Change In this context, when analysing the potential of future-oriented technology analysis (FTA) to assist societies, decision-makers and businesses to tackle fundamental, disruptive transformations, in general,
/Technological forecasting & Social Change 80 (2013) 379 385 3. Combining quantitative and qualitative approaches FTA is an umbrella term to denote several decision-preparatory tools (technology foresight,
forecasting and technology assessment and thus it is not a discipline with solid, widely accepted theoretical foundations.
Forecasting e g. demographic or environmental changes is also highly relevant for certain policy needs or to enable technology observers to determine the current life cycle stage of a particular technology of interest
/Technological forecasting & Social Change 80 (2013) 379 385 are by nature complex and largely impervious to top-down rational planning approaches.
whereas Gao et al. 7 propose the development of a new forecasting approach to analysing technology life cycle of a particular technology of interest.
/Technological forecasting & Social Change 80 (2013) 379 385 In more detail, Haegeman et al. 4 depart from the methodological debate that has been a relevant element of the International Seville Conference series on Future-oriented technology analysis (FTA
which is currently the major forecasting approach to analyse technology life cycle (TLC), they propose a model to calculate the TLC for a technology based on multiple patent-related indicators.
/Technological forecasting & Social Change 80 (2013) 379 385 more experimental approaches to creating new solutions
and moving from forecasting activities and expert-driven identification processes towards the inclusion of expertise from a broader range of disciplines, a wider range of stakeholders and sometimes also the knowledge of lay people.
/Technological forecasting & Social Change 80 (2013) 379 385 practice and assist in considering transformations that are going to take us closer to anticipating disruptive innovations and events.
/Technological forecasting & Social Change 80 (2013) 379 385
Quantitative and qualitative approaches in Future-oriented technology analysis (FTA: From combination to integration? Karel Haegeman a,, Elisabetta Marinelli b, Fabiana Scapolo c, Andrea Ricci d, Alexander Sokolov e a European commission, JRC-IPTS, Edificio Expo WTC, C/Inca
and sounds) and a methodology as qualitative when not relying on statistical/Technological forecasting & Social Change 80 (2013) 386 397 The views expressed are purely those of the authors
Sciencedirect Technological forecasting & Social Change mathematical tools. A participatory method, regardless of the qualitative or quantitative data it uses, is one in
(which comprises Foresight, Forecasting and Technology assessment), 1 foresight practitioners have concentrated traditionally on participatory methods based on qualitative data,
Another part of the FTA COMMUNITY, constituted by Forecasting and Technology assessment practitioners, holds an opposite standpoint, considering qualitative and participatory approaches as a second best option, to which we are compelled somehow to refer until adequate quantitative methods arise.
A further point to keep in mind is that numbers may create the impression that the future is less uncertain than it actually is. 3 In this respect Linstone 12,13 points out that the possibilities of forecasting may be limited especially when the dynamic,
Goodwin 11 points to the effect of hindsight bias (the tendency to believe that our forecasts were more accurate than they actually were) on forecasting,
/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.
Remarkably, evidence stemming from the forecasting communities on cases combining qualitative and quantitative methods is limited rather,
/Technological forecasting & Social Change 80 (2013) 386 397 identification of emerging clusters analysing citations and keywords for a particular technology field,
and methods of social scanning and prediction markets could be used to improve professional forecasting and foresight in an era of complex phenomena and disruptive events with high level of uncertainties.
/Technological forecasting & Social Change 80 (2013) 386 397 Other tools and disciplines that can serve as interface to facilitate the use of qualitative and quantitative approaches and data Social network analysis:
/Technological forecasting & Social Change 80 (2013) 386 397 are brought not always together in the analysis 62 and qualitative and quantitative tasks are carried out by different teams,
/Technological forecasting & Social Change 80 (2013) 386 397 Finally, in this debate, there is a tendency to equate qualitative with participatory.
/Technological forecasting & Social Change 80 (2013) 386 397 sciences, Cameron 71 developed the Five Ps Framework, 13 which provides a mixed-methods starter kit,
/Technological forecasting & Social Change 80 (2013) 386 397 reasonable representation of the systems being analysed, and that the intrinsic uncertainties associated with such representation are documented at best. 5. 2. 2. Lack of trust One aspect of trust is that it derives from perceived credibility,
as well as guidance for the 16 If forecasting is used to compare the impact of alternative policy options,
/Technological forecasting & Social Change 80 (2013) 386 397 identification of the features that may help the organisers of FTA projects in the selection of the most appropriate set of tools (characterising
new technology foresight, forecasting & assessment methods, in: JRC Technical Report, EUR 21473 EN, European commission, 2004, Available at:
/Technological forecasting & Social Change 80 (2013) 386 397 32 D. Rossetti di Valdalbero, The Power of Science economic research and European decision-making:
/Technological forecasting & Social Change 80 (2013) 386 397 Fabiana Scapolo holds a Phd on foresight methodologies and practices from the Manchester University (UK).
/Technological forecasting & Social Change 80 (2013) 386 397
Technology life cycle analysis method based on patent documents Lidan Gao a b,, Alan L. Porter c, Jing Wang d, Shu Fang a, Xian Zhang a, Tingting Ma e, Wenping Wang e, Lu Huang e
Within the Future-oriented technology analysis (FTA), technology forecasting traces back to the 1950's 4. One of its half dozen
Another important technology forecasting technique 6 is the use of analogies. Herein, one anticipates growth in an emerging technology based on the pattern of growth observed in a somewhat related technology.
Technological forecasting & Social Change 80 (2013) 398 407 Corresponding author at: Chengdu Library of the Chinese Academy of Sciences, Chengdu 610041, PR China.
0040-1625/$ see front matter 2012 Elsevier Inc. All rights reserved. http://dx. doi. org/10.1016/j. techfore. 2012.10.003 Contents lists available at Sciverse Sciencedirect Technological forecasting
/Technological forecasting & Social Change 80 (2013) 398 407 (test technology) via the nearest neighbour classifier,
/Technological forecasting & Social Change 80 (2013) 398 407 in DII by application year for the Application indicator and count the number of patents in DII by priority year for the Priority indicator
/Technological forecasting & Social Change 80 (2013) 398 407 2. 2. TLC stages of CRT and TFT-LCD It is better to choose a training technology with four TLC stages.
/Technological forecasting & Social Change 80 (2013) 398 407 We propose a normalisation method with two steps to pre-process the original data.
/Technological forecasting & Social Change 80 (2013) 398 407 A1 i; j ð Þ A1 i;
/Technological forecasting & Social Change 80 (2013) 398 407 For each test point bk, we compute the distance between bk
/Technological forecasting & Social Change 80 (2013) 398 407 definitive projections. Indeed, explicit analyses of what factors and forces are apt to alter projected developmental trends are worthwhile note Ted Gordon's Trend Impact analysis (TIA) especially 34.
/Technological forecasting & Social Change 80 (2013) 398 407 2 H. X. G. Ming, W. F. Lu, C. F. Zhu, Technology challenges
Technol. 43 (1)( 2008) 157 162.4 J. P. Martino, Technological forecasting for Decision making, 3rd Edition Mcgraw-hill, New york, NY, 1993.5 A t. Roper, S w
J. Banks, Forecasting and Management of Technology, 2nd Edition John Wiley, New york, NY, 2011.6 A l. Porter, M. Rader, Fitting future-oriented technology analysis methods to study
European Management Forum, Davos, 1981.10 H. Ernst, The use of patent data for technological forecasting: the diffusion of CNC-technology in the machine tool industry, Small Bus. Econ. 9 (4)( 1997) 361 381.11 T. H. Lee, N. Nakicenovic, Life cycle of technology
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.
Market Manage. 21 (1)( 1992) 23 31.36 E. Hajime, The suitability of technology forecasting/foresight methods for decision systems and strategy:
Appl. 39 (3)( 2012) 2927 2938.38 E. Hajime, Obstacles for the acceptance of technology foresight to decision makers, lessons from complaint analysis of technology forecasting, Int. J. Foresight Innov.
including Tech Mining (Wiley, 2005) and Forecasting and Management of Technology (Wiley, 2011. Jing Wang is an Associate professor of Huaqiao University.
Her specialty is science and technology management, particularly the study of technology forecasting and assessment. She is focusing on a research on emerging science and technology topics. 407 L. Gao et al./
/Technological forecasting & Social Change 80 (2013) 398 407
Evolutionary theory of technological change: 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;
accepted 6 october 2004 Abstract It is well known the fact that the world of technology is full of biological metaphors,
One of the most powerful technological forecasting tools, the logistic equation, has its origin in the biological realm
Technological forecasting & Social Change 72 (2005) 1137 1152 promising approaches under way. The fourth part with conclusions closes the article,
which would bring a renewed thrust toward new methods in technological forecasting (Fig. 1). The picture suggests that the chaotic phase transition might be behind us
and obstacles to be overcome to transform evolutionary approaches in useful forecasting tools. The present paper intends to present the state-of-the-art on this debate
whether it T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1138 can ever be achieved.
and Fig. 1. Technological forecasting in perspective presented by Linstone in the 30-year anniversary issue of TF and SC (1999).
T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1139 quality control. Peter Corning 5 has pointed out that complexity in nature
and will be seed the and/or the substract for the further development of useful forecasting tools in the technological realm.
the amount of practical work using simulation methods is still a dwarf T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1140 one.
more than an useful metaphor One of the most powerful technological forecasting tools, the logistic equation, has its origin in the biological realm
The mathematical tools that began to be employed in economics (as well as in technological forecasting) starting in the 1970s had been developed by mathematical biologists in the 1920s
T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1141 Yet in 1925 the American biologist and demographer Raymond Pearl 8 in his seminal book
T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1142 3. 2. To point 2:
if we substitute the words dgenetic underpinningst by building blocks T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1143 (following John Holland's 14 original
T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1144 Such a bridge could be offered by a better-developed danthropology of technique,
Social scientists, and particularly economists, have T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1145 never correctly realized that Darwin in his second
beginning with Donald Campbell 23 in the T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1146 1960s (who coined the term Evolutionary Epistemology to characterize Popper
T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1147 the coevolutionary complexity of managing two inheritance systems (the vertical, genetic,
The systems dynamics approach, widely used in technological forecasting since the 1950s, is btop-downq in character
or in other words, for forecasting agents'aggregate behavior. The other approach forms the new sub-field of bartificial Lifeq (AL,
T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1148 Although a consistent ETTC still not exists
which method is suited best for purposes of simulating technological evolution and/or for developing useful tools for technological forecasting.
cellular automata is the poorest for more T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1149 sophisticated simulations due to the simplicity of its basic assumptions and limitations that must be imposed in the rules governing interactions between agents.
This scientific meeting could be planned following the format of A t. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1150 recent proposal of this author with George Modelski for a seminar on Globalization as Evolutionary Process 40 to be held in the spring of 2005 in Paris,
T. C. Devezas/Technological forecasting & Social Change 72 (2005) 1137 1152 1151 34 J. Goldenberg, B. Libai, Y. Louzoun, D. Mazursky
Modeling, Simulating and Forecasting Social Change, a Proposal of a Seminar to the Calouste Gulbenkian Foundation,
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
Adaptive Robust Design under deep uncertainty Caner Hamarat, Jan H. Kwakkel, Erik Pruyt Delft University of Technology policy Analysis Department, PO BOX 5015,2600 GA Delft
Characteristic for these techniques is that they aim at charting the Technological forecasting & Social Change 80 (2013) 408 418 Corresponding author.
0040-1625/$ see front matter 2012 Elsevier Inc. All rights reserved. http://dx. doi. org/10.1016/j. techfore. 2012.10.004 Contents lists available at Sciverse Sciencedirect Technological forecasting
Goodwin and Wright 12, p. 355 argue that all the extant forecasting methods including the use of expert judgment, statistical forecasting,
/Technological forecasting & Social Change 80 (2013) 408 418 Fig. 1 shows a framework that operationalizes the high level outline of adaptive policy-making.
In a recent special issue of Technological forecasting and Social Change on adaptivity in decision-making, the guest editors conclude that Adaptive policy-making is a way of dealing with deep uncertainty that falls between too much precaution and acting too late.
/Technological forecasting & Social Change 80 (2013) 408 418 operationalizing the Adaptive Policy-making Framework is structured through workshops 35.
/Technological forecasting & Social Change 80 (2013) 408 418 explicitly considers the opportunities that uncertainties can present.
/Technological forecasting & Social Change 80 (2013) 408 418 In order to explore the problem and the uncertainties of energy transitions,
/Technological forecasting & Social Change 80 (2013) 408 418 fraction of new technologies for the no policy ensemble (in blue) and the basic policy ensemble (in green) as well as the KDES of the end states of all
/Technological forecasting & Social Change 80 (2013) 408 418 this signpost. Using this trigger, the corrective action would be to stop investing in Technology 2
/Technological forecasting & Social Change 80 (2013) 408 418 4. Discussion and implications for Future-oriented technology analysis (FTA) In this paper we proposed an iterative computational approach for designing adaptive policies that are robust
In addition, all the extant forecasting methods contain fundamentalweaknesses and struggle deeply in grapplingwith the long-term'smultiplicity of plausible futures.
/Technological forecasting & Social Change 80 (2013) 408 418 3 E. Pruyt, J. H. Kwakkel, G. Yucel, C. Hamarat, Energy transitions towards sustainability:
(2011) 292 312.12 P. Goodwin, G. Wright, The limits of forecasting methods in anticipating rare events, Technol.
/Technological forecasting & Social Change 80 (2013) 408 418 Caner Hamarat is a Phd researcher at the Faculty of technology, Policy and Management of Delft University of Technology.
/Technological forecasting & Social Change 80 (2013) 408 418
Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty Jan H. Kwakkel, Erik Pruyt Faculty of technology, Policy,
including technology forecasting, technology intelligence, future studies, foresight, and technology assessment 1. In their own ways each of these approaches is used for analyzing technological developments and their potential consequences.
Similarly, if the Technological forecasting & Social Change 80 (2013) 419 431 Corresponding author. Tel.:++31 15 27 88487.
0040-1625/$ see front matter 2012 Elsevier Inc. All rights reserved. http://dx. doi. org/10.1016/j. techfore. 2012.10.005 Contents lists available at Sciverse Sciencedirect Technological forecasting
E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 that policy or planning debates can often be served even by the discovery of thresholds, boundaries,
E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 This small and simplistic System Dynamics model was developed in about one day in close collaboration with a mineral/metal expert
Start, end, slope Fig. 1. Causal loop diagram of the scarcity model 18.422 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013
E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 otherwise. Next, we tried to identify subspaces in the overall uncertainty space that show a high concentration of crises runs using the Patient Rule Induction Method 31 33.
3. Evolution of market price for a 1000 runs. 424 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 3. 2
-1%+4%425 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 could serve as a starting point for slightly modifying the outlined dynamic adaptive plan,
E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 can be decommissioned. Generation companies'expansion decisions are driven mainly by profit expectations,
E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 irreducible uncertainties inherent in the forces driving toward an unknown future beyond the short term
E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 some structural uncertainties were taken into account.
Future research avenues include elaborating on the use of EMA for designing dynamic adaptive policies and the use of EMA for 429 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80
E. N. Zalta (Ed.),The Stanford Encyclopedia of Philosophy, 2008.4 W. Ascher, Forecasting: An Appraisal for Policy makers and Planners, Johns hopkins university Press, Baltimore, 1978.5 J. D. Sterman, All models are wrong:
dynamic scenario discovery under deep uncertainty, Technological forecasting and Social Change,(under review. 23 R. U. Ayres, On the practical limits to substitution, Ecol.
)( 2008) 201 214.430 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431 Jan Kwakkel is a postdoctoral researcher at Delft
from short-term crises to long-term transitions. 431 J. H. Kwakkel, E. Pruyt/Technological forecasting & Social Change 80 (2013) 419 431
and using scenarios and orienting innovation systems and research priorities 6. Technological forecasting & Social Change 80 (2013) 432 443 Corresponding author.
0040-1625/$ see front matter 2012 Elsevier Inc. All rights reserved. http://dx. doi. org/10.1016/j. techfore. 2012.10.006 Contents lists available at Sciverse Sciencedirect Technological forecasting
/Technological forecasting & Social Change 80 (2013) 432 443 2. Material and methods How can we learn about orienting innovation systems from future scenario practice?
/Technological forecasting & Social Change 80 (2013) 432 443 experiments in the policy process, new concepts and sustainable solutions can be found to grand challenges.
/Technological forecasting & Social Change 80 (2013) 432 443 The concept of the multiple-axes method is based on one of the approaches used by Pierre Wack 52.
The Delphi method is developed as a systematic, interactive forecasting method, which relies on a panel of experts.
/Technological forecasting & Social Change 80 (2013) 432 443 our analysis a better understanding of the linkages between scenario design, methods used and related outcomes.
/Technological forecasting & Social Change 80 (2013) 432 443 The images of the future are focused on key internal developments
/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.
/Technological forecasting & Social Change 80 (2013) 432 443 The solutions developed should be socially reflexive
/Technological forecasting & Social Change 80 (2013) 432 443 acknowledge the limits of our analysis: i e. using a policy perspective for doing an ex-post analysis of future scenario practice.
/Technological forecasting & Social Change 80 (2013) 432 443 References 1 C. Harries, Correspondence to what?
/Technological forecasting & Social Change 80 (2013) 432 443 58 J. P. Gavigan, F. Scapolo, A comparison of national foresight exercises, Foresight 1 (1999) 495
/Technological forecasting & Social Change 80 (2013) 432 443
The role of future-oriented technology analysis in the governance of emerging technologies: The example of nanotechnology Petra Schaper-Rinkel AIT Austrian Institute of technology, Donau-City-Straße 1, A-1220 Vienna, Austria a r t i c l e
from the first monitoring and forecasting studies on nanotechnology to the establishment of national nanotechnology programs
and then recognizing that the Technological forecasting & Social Change 80 (2013) 444 452 E-mail address:
. 2012.10.007 Contents lists available at Sciverse Sciencedirect Technological forecasting & Social Change emergence of nanotechnology is adjudicated not just in labs,
but rather also in processes such as technology forecasting, technology assessment and participatory future-oriented studies, involving scientists, policymakers, media,
whereas in the field of converging technologies broad futuristic discourses took place that were followed not by funding strategies dedicated explicitly to converging technologies. 445 P. Schaper-Rinkel/Technological forecasting
In this paper, FTA is used as the umbrella term covering subfields such as technology foresight, technology forecasting, technology roadmapping and technology assessment cf. the list in 29 and combining tools, ranging fromquantitative methods
446 P. Schaper-Rinkel/Technological forecasting & Social Change 80 (2013) 444 452 support nanotechnology education, research and development the fastest will thrive in the new millennium 1. These statements illustrate that the report
The funding is provided through the NNI member agencies. 6 The Center for Nanotechnology in Society at Arizona State (CNS-ASU) is funded by the NSF. 447 P. Schaper-Rinkel/Technological forecasting
The BMBF commissioned several forecasting studies on nanotechnology-related fields starting in the early 1990s.
the aim of these forecasting exercises was to identify new and promising fields for research funding, to deliver a sound and broad information basis for funding decisions in these research fields
The results of the forecasting exercises were published in technology analyses, summarizing the process and results of the forecasting exercises for nanotechnology in general and for various subfields of nanotechnology,
including fullerenes, synthetic supramolecular systems, nanotubes, and nanobiology. These reports provided information on the technology field
these early monitoring and forecasting activities were followed by an initiative of the BMBF to establish the first six national nanotechnology competence centers with annual funding.
448 P. Schaper-Rinkel/Technological forecasting & Social Change 80 (2013) 444 452 Nanolux (optics industry, nanotechnology for energy efficient lighting.
Through the action plan, other federal ministries8 finally joined the German nanotechnology initiative more than fifteen years after the firstmonitoring and forecasting activitieswere conducted.
FTA in the governance of nanotechnology started with forecasting activities and expert-driven identification processes in which expertise was limited by involving actors exclusively from government,
449 P. Schaper-Rinkel/Technological forecasting & Social Change 80 (2013) 444 452 In this later stage, heterogeneous stakeholders beyond the actors of the early established nano-policy networks
In the late 1980s and early 1990s, several industrial countries established their first programs in 450 P. Schaper-Rinkel/Technological forecasting & Social Change 80 (2013) 444 452
Making it in Miniature Nanotechnology Report Summery, POST, Parliamentary Office of Science and Technology policy, London, 1996, p. 4. 451 P. Schaper-Rinkel/Technological forecasting & Social Change
Concepts and Practice, 2008, pp. 154 169.33 K. Cuhls, From forecasting to foresight processes new participative foresight activities in Germany, J. Forecast. 22 (2003) 93 111.34
from forecasting to technological assessment to sustainability studies, J. Clean. Prod. 16 (2008) 977 987.49 TAB, in:
and methods and practices of futuring. 452 P. Schaper-Rinkel/Technological forecasting & Social Change 80 (2013) 444 452
Technological forecasting & Social Change 80 (2013) 453 466 Corresponding author. E-mail address: Elna. Schirrmeister@isi. fraunhofer. de (E. Schirrmeister.
0040-1625/$ see front matter 2012 Published by Elsevier Inc. http://dx. doi. org/10.1016/j. techfore. 2012.10.008 Contents lists available at Sciverse Sciencedirect Technological forecasting
Both these 1 www. innovation-futures. org. 454 E. Schirrmeister, P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 approaches can be termed inductive
but also in the weak signal collection available on the internet. 2 The movie is available at www. innovation-futures. org. 455 E. Schirrmeister, P. Warnke/Technological forecasting & Social Change
web-extracted innovation. 456 E. Schirrmeister, P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 Fig. 3. Screenshot from the INFU web-based
survey. 457 E. Schirrmeister, P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 Fig. 4. Visualisation of all INFU visions. 458 E. Schirrmeister,
P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 2. 2. Visual inspiration The INFU amplifications were illustrated in a visual,
P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 without any rootwithin phenomena that can be observed today 25,26.
P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 the scenario building activity is looking for a consensus building process among the participants
Dimensionof change Modified specificationextreme A Modification specificationextreme B Today's dominantspecification Fig. 7. Assessment of coverage of dimensions of change. 461 E. Schirrmeister, P. Warnke/Technological forecasting
and use phases. 462 E. Schirrmeister, P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 (2) Participation:
Fig. 9. Element from INFU mini panel Participatory Innovation. 463 E. Schirrmeister, P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466
P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 dominance of the macro-level and the influence of today's perception of consistency were reduced to give room for creative assessment of structural transformation.
465 E. Schirrmeister, P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466 References 1 O. Da Costa, P. Warnke, C
Her research focuses on Foresight methodology and the mutual shaping of technology and society. 466 E. Schirrmeister, P. Warnke/Technological forecasting & Social Change 80 (2013) 453 466
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