2006) have investigated this area for science-based stakeholder dialogues. Their analysis is relevant because the motivation and the challenges of those dialogues tie in with those of transferring foresight results,
2006) contrast science-based stakeholder dialogues with other types of dialogues. In an overview, they cover:
B science-based stakeholder dialogues initiated by scientific institutions with the aim of increasing knowledge
Welp, M.,de la Vega-Leinert, A.,Stoll-Kleemann, S. and Jaeger, C. C. 2006),‘Science-based stakeholder dialogues:
where national governments formulate strategic responses that take into account the existing and anticipated developments in the sciences
Forfa's, the national policy advisory body for enterprise and science in the Republic of ireland, undertook an exercise to assess the implications of global drivers
Although there was understandably a strong focus on‘‘hard''research in science, engineering and technology, within several challenges there was also a clear role for social sciences and humanities.
Biosciences and the genome Cloud computing Privatisation of agricultural science Resources Renewable energy Energy security Water scarcity Food scarcity Peak oil Mineral and resource depletions
and engineering and science skills PAGE 36 jforesight jvol. 15 NO. 1 2013 The project undertaken provided a national view on grand challenges that had been discussed in other settings.
Foresight in science and technology policy co-ordination'',Futures, Vol. 31 No. 6, pp. 527-45.
on the basis of this experience, it is suggested that a widespread national Delphi survey for the identification of science
and technology (S&t priorities should be complemented by the identification of key long-term demand for resources and reshaped management systems.
Keywords Priority-setting, Russia, Natural resources, Long term planning, Foresight project planning, Innovation, Technology led strategy, Sciences Paper type Research paper 1. Introduction In recent years
studies focusing on the identification of science, technology and innovation (S&t&i) priorities have become an integral part of government policy making in almost all developed countries,
The prospects and problems of the natural resources sector constitute a major section in most national science and technology foresight studies.
In the last ten to 15 years, Japan (National Institute of Science and Technology policy, 2010), Finland (University of Joensuu, 2010), the UK (Loveridge et al.
Therefore, identifying S&t and innovation priorities for the natural resources sector has become an extremely important issue
In 2007, the RF Ministry of Education and Science initiated the National S&t Foresight until 2025 to identify S&t priorities (Sokolov, 2008a,2009.
The final objective was a preparation of policy recommendations on the basis of the S&t priorities;
Therefore for this additional investigation the RF Ministry of Education and Science initiated the second cycle of the National S&t Foresight until 2030.
Within the implementation of this foresight study it was realised that S&t priorities should be complemented by innovative priorities for corresponding development of the Russian management system in the field of natural resources,
otherwise the S&t priorities could not be implemented fully. The third foresight study commissioned by the RF Ministry of Natural resources and Ecology was devoted to exactly this task:
i e. to prepare recommendations for shaping Russian national S&t and innovation policy in the sphere of natural resources and environmental protection.
The structure of the project, including analysed S&t areas and levels of analysis, is characterised in the next step.
and interviews were conducted with heads of project teams. 3. Russian FS approaches 3. 1 National S&t Foresight:
B estimation of possible timeframes for major S&t breakthroughs; B evaluation of the position of Russian R&d centres in the international S&t landscape;
and B determination of the most relevant steps to be taken to support the development and commercialisation of science and technology.
PAGE 42 jforesight jvol. 15 NO. 1 2013 This study was based on another foresight study devoted to the identification of national S&t priorities and a corresponding list of critical technologies (Sokolov, 2008b.
The following criteria were used to make the list of critical technologies: B contribution to increasing the GDP growth rate;
and implement the federal goal-oriented programme‘‘S&t priorities for Development of the Russian S&t Sector in 2007-2012''.
''This programme was structured in accordance with the identified S&t priorities, and specific projects were selected on the basis of their relevance to the identified critical technologies.
(which correspond to National S&t priorities), 56 technology areas at the second level (which correspond to critical technologies) and more than 900 topics.
Eighty-two topics were formulated for these five thematic areas, in the form of briefly described S&t results, promising technologies or innovation products (e g.‘‘
''The methodology of this study included various expert and analytical techniques being engaged to prepare this S&t foresight (analytical research, bilbliometric and patent analysis, interviews with and polling of experts,
These issues were analysed deeply in the FS2 framework. 3. 2 National S&t Foresight: 2030 (FS2) The aim of this study was an evaluation of required resources
and possible innovation projects for the most important S&t fields. The National S&t Foresight: 2030 was based on the FS1 results and also on a renewed version of the National S&t priorities and Critical technologies.
The study covers three thematic levels, the first of which corresponds to the revised list of National S&t priorities:
B Information and Telecommunication systems; B Living Systems; B Industry of Nanosystems; B Transportation and Aerospace Systems;
B Rational Use of Nature Resources; and B Energy efficiency and Energy Saving.‘‘‘‘Rational Use of Nature Resources''was considered
More than 300 experts from the S&t and business communities, as well as government officials, took part in the exercise.
Topic Importance indexa Expected time of developing S&t solution Possible results (percentage of experts; two top scores) Technology area 1 Technologies for accelerated and efficient recovery of damaged lands, landscapes and biodiversity 97.6 2019 Contributing to dealing with social problems (76.3
including R&d level, contribution to innovative relevant projects, availability of human resources (researchers, engineers and technicians), required level of funding and fixed assets.
and S&t development is almost impossible within the inertial development model for a number of reasons,
‘‘Innovation priorities''in the above study were considered to be major activities in the Russian natural resources sector's management system that would contribute to achieving the RF S&t priorities and solving the main problems in the area.
The innovation priorities until 2025 for the development of the Russian natural resources sector was developed on the basis of identification of the most important problems and challenges regarding the natural resources sector's management system and necessary conditions for S&t development.
and 2. conditions for S&t priority realisation. VOL. 15 NO. 1 2013 jforesight jpage 47 As a result of this study, the innovation priorities and corresponding tasks were formulated for each structural component of the natural resources sector.
In the FS1 framework S&t topics were assessed by different criteria, and in the FS2 framework technology groups were assessed (identified on the basis of the most important and well-developed FS1 topics).
The FS2 criteria for the evaluation of technology groups were identified mostly on the basis of the results of FS1 (see Table I). National S&t Foresight:
and that this was preventing S&t development. FS3 was initiated on the basis of these results and commissioned by the RF Ministry of Natural resources and Ecology (because the focus of FS3 is in the the sphere of responsibility of this Ministry).
and key limitations for S&t development (FS2) created the framework and demands for the identification in FS3 of innovation priorities (see Table III).
in the FS1 framework a large database of promising S&t areas was created; this allowed policy makers to derive a wide range of an information, for example:
B estimates of the level of Russian R&d vis-a vis the world leaders for major S&t areas;
and B measures to support R&d and their commercialisation for all major S&t areas. These FS1 results were used as an information source for many political purposes:
B revision of National S&t priorities and Critical technologies; Figure 3 The general scheme of the structure of projects interrelation VOL. 15 NO. 1 2013 jforesight jpage 49 B design of large-scale innovation projects;
B identification of research projects to be funded within federal and sectoral goal-oriented S&t programmes; B designing sectoral strategies for industries;
and B priorities for international S&t co-operation. However, the real contribution of the Delphi study results to the development of policy documents was mostly indirect
In order to prepare direct recommendations for shaping S&t and innovation policy it is necessary to have more detailed and precise information about resource requirements, the evaluation of emerging markets,
This study provided a more profound knowledge of national competitive advantages the resources required for development of the most important S&t areas,
The project-based recommendations for Russian S&t policy were used to adjust decision-making to future trends, whereas the technology roadmaps for perspective product groups created a background for particular measures aimed at development S&t.
The RF Ministry of Education and Science used the lists of the most important innovation
and research projects as a basis for the selection of projects to be funded. So in terms of our scale, the results of FS2 had a medium direct impact on policy-making
contribution to innovative relevant projects, availability of human resources (researchers, engineers and technicians), required level of funding, fixed assets and others Estimation of resources and risks List
and this is preventing S&t development Innovation priorities for the Russian management system in the natural resources area, which should create conditions for S&t development
and promote solving the key problems identified in the FS2 framework FS3 An identification of innovation priorities for the Russian management system in natural resources until 2030 The innovation priorities
and the large number of players, imply the need to use integrated approaches for identifying S&t and innovation priorities for this sector.
The innovation and S&t priorities for the Russian natural resources sector were identified in the framework of three connected foresight projects.
revision of National S&t priorities and Critical technologies: design of large-scale innovation projects identification of research projects to be funded within federal and sectoral goal-oriented S&t programmes designing sectoral strategies for industries regional priorities for innovation development priorities
for international S&t cooperation However, the real contribution of the Delphi study results to policy documents was mostly indirect
because we could not assess to what extent the project materials were in the development of these documents Indirect FS2 The project-based recommendations for Russian S&t policy were used to adjust decision-making to future trends,
whereas the technology roadmaps for perspective product groups created a background for particular measures aimed at the development of S&t.
The RF Ministry of Education and Science used the lists of the most important innovation
and research projects as a basis for the selection of projects to be funded Direct (medium) FS3 In the framework of this study,
The first of these projects identified major S&t results in the‘‘Rational Use of Natural resources''area,
assessed the current level of Russia's S&t development, and the country's international S&t co-operation potential through the development of a national innovation system.
The study significantly extended the information basis for policy-making, which however could not be used directly in decision-making.
A clear need was highlighted for more detailed analysis of future demand for human, financial and other types of resources for S&t development.
and the potential for further S&t development identified the need to increase appropriate investments significantly. Also, major innovation projects were identified with the promise of high economic and social return.
On the basis of this project recommendations for Russian S&t policy which include the most important research
The RF Ministry of Education and Science used the lists compiled as a basis for selection of the projects to be funded.
widespread national Delphi survey for the identification S&t priorities (which was our FS1) should be complemented by the identification of key long-term demand for resources
updating the Union's approach in the context of the Lisbon strategy'',COM (2003) 112, European commission, Brussels. European commission (2004a),‘Science and technology, the key to Europe's future guidelines for future European union
National Institute of Science and Technology policy (2010),‘The 9th Science and Technology foresight Survey contribution of science and technology to future society.
The 9th Delphi survey'',NISTEP Report No. 140, National Institute of Science and Technology policy, Tokyo. National research council Canada (2005),‘Looking forward:
S&t for the 21st century'',Foresight Consolidation Report, available at www. nrc-cnrc. gc. ca/Nordic Innovation Centre (2007),‘Foresight in Nordic innovation systems'',Nordic Innovation
Sokolov, A. 2008a),‘Science and technology foresight in Russia: results of a national Delphi'',3rd International Seville Conference on Future-oriented technology analysis (FTA), 16-17 october, Seville, Book of Abstracts.
of science and technology: the Delphi study results'',Foresight, Vol. 10 No. 3 (in Russian. United nations Industrial Development Organization (2007), Technology foresight Summit Workbook, United nations Industrial Development Organization, Budapest.
Mapping of future technology themes in sustainable energy Hai-Chen Lin, Te-Yi Chan and Cheng-Hua Ien Abstract Purpose To anticipate science
and technology (S&t) changes and shifts in the competitive environment for the preparation of strategic development in an organization,
or quality and help in identifying the gaps between the probable future changes in S&t and the current capability.
Te-Yi Chan and Cheng-Hua Ien are based in the Trend Analysis Division, Science and Technology policy Research and Information Center (STPI), National Applied research Laboratories (NARL), Taipei
The authors would like to acknowledge support from the National science Council of Taiwan and the efforts of Kang Hsieh in STPI who gave valuable advice on the amendment of this research.
processes or collaborative prospects created by external science and technology (S&t) activities in time to permit appropriate responses;
and 3. to anticipate and understand S&t-related shifts or trends in the competitive environment as a preparation for organizational planning and strategic development.
To date, studies on CTI have used a full range of analytical techniques, including content analysis, patent analysis, bibliometrics,
competitor profiling, early warning assessment, scientometrics, science mapping, scenarios, network analysis and so forth (Calof and Smith, 2010).
The mapping dimension of EFMN, especially for the science and technology field and socioeconomic sectors which the collected foresight activity explicitly address, are fingerprinted based on the Frascati Manual classification and the NACE code classification,
I Basic information for scanned foresight reports from Japan, South korea and China Japan South korea China Report Title The 8th Science and Technology foresight Survey Delphi Analysis Prospect of future society
, Culture, Sports, Science and Technology, Japan The Ministry of Science and Technology of the Republic of korea Ministry of Science and Technology agency or organization responsible for the foresight activity Science and Technology foresight Center, National Institute
of Science and Technology policy (NISTEP) Foresight and Strategy Planning Team, Korean Institute of S&t Evaluation and Planning (KISTEP), The Science
and Technology policy Research institute (STEPI) Technology foresight Research team, National research Center for Science and Technology for Development Time horizon 2035 2030 2020 Original category Energy and resources Energy
Therefore, not only policy makers at the national level but also researchers who are conducting a research agenda can use such a structured analysis result to see the future trends in their proper scope
Ashton, B. W. and Klavans, R. A. 1997), Keeping Abreast of Science and Technology: Technical intelligence for Business, Batelle Press, Columbus, OH.
Ashton, B. W.,Johnson, A. H. and Stacey, G. S. 1994),‘Monitoring science and technology for competitive advantage'',Competitive intelligence Review, Vol. 5 No. 1, pp. 5-16.
and business strategy'',Management Science, Vol. 32 No. 10, pp. 1231-41. Barney, J. B. 1991),‘Firm resources and sustained competitive advantage'',Journal of Management, Vol. 17 No. 1, pp. 99-120.
''Science & Technology trends Quarterly Review, No. 18, available at: www. nistep. go. jp/achiev/ftx/eng/stfc/stt018e/qr18pdf/STTQR1802. pdf (accessed March 8, 2011.
Martin, B. R. 1995),‘Foresight in science and technology'',Technology analysis & Strategic management, Vol. 7 No. 2, pp. 139-68.
PAGE 72 jforesight jvol. 15 NO. 1 2013 About the authors Hai-Chen Lin is now an Associate Researcher at Science and Technology policy Research and Information Center (STPI),
He is now an Associate Researcher at Science and Technology policy Research and Information Center (STPI),
and adopts these mechanisms to conduct research into science and technology development trends. His research interests include foresight, data mining,
Cheng-Hua Ien received A MS degree in Food Science and Technology from Taiwan University in 1983.
She is now an Associate Researcher at Science and Technology policy Research and Information Center (STPI),
A, Ed. Corporate Financial center, Sl. 1112,70712-900, Brasília-DF, Brazil c Institute of Economics, Research centre for Economic and Regional Studies, Hungarian Academy of Sciences, H
and also use scientific methods when analysing the past and the present in order to consider future options
Besides scientific methods, various other techniques are used also. The main objective of FTA projects is to assist decision-makers with relevant analyses,
This means that they cut across scientific disciplines policy domains, and governance levels 10. They typically involve complex and systemic relationships within and between social, technological, economic, environmental, and value systems.
Clearly, different types of technologies may have different developing patterns, especially for those technologies close to basic science, such as biotechnology,
and governance network-building coupled with avoiding centralised S&t planning. In Germany, FTA is used mainly for addressing the future of existing areas of strength
focused largely on science-industry relations, 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.
The notion of FTA addressing research and innovation policy through priority-setting and articulation of demand has shifted to the search of breakthrough science
and is now a senior advisor of STI (Science, Technology and Innovation policy and strategy at CGEE.
Research centre for Economic and Regional Studies, Hungarian Academy of Sciences (http://econ. core. hu/english/inst/havas. html),
at the same time, the improved availability of S&t and innovation indicators and the advances in quantitative methods provide more input for quantitative analysis;
For instance, quantitative analysis of this kind offers valuable information for the development of S&t Delphi survey topics,
Järvanpää et al. 34 analyse the use of bibliometric data for distinguishing between science-based and conventional technologies,
or to identify Emerging s&t areas 38. Comparison of outcomes of qualitative and quantitative approaches Participants at the 2011 International Seville Conference on FTA raised the potential of the use of qualitative and quantitative methods for identifying
Cooke and Buckley 7 believe that web 2. 0 tools can be used to make data of all sorts accessible to respondents and researchers:
irrespective of whether the others are researchers, clients or respondents (p. 289). However, to date no concrete examples of this approach could be identified,
or issues at the interplay between science and society, to keep track of the content of one's intellectual portfolio of knowledge
Scientists (particularly natural scientists and technologists) often tend to consider subjectivity, e g. experts opinions as a disturbance to be avoided,
and reinforced by, the lack of researchers, practitioners and evaluators skilled in both quantitative and qualitative FTA APPROACHES. 10 It is for instance neither common, nor easy,
perceptions on the expectations of different audiences, methodological preferences of the (mixed methods) researcher, structure of the research project, different timelines for different method types, skill specialisms, the nature of the data, ontological differences,
/Technological forecasting & Social Change 80 (2013) 386 397 sciences, Cameron 71 developed the Five Ps Framework, 13 which provides a mixed-methods starter kit,
Integrating Quantitative and Qualitative approaches in the Social and Behavioral Sciences, Sage Publications, 2009.6 M. Wood,
www. foresight-platform. eu/community/foresightguide/2010accessed August 2012.24 J. E. Smith, O. Saritas, Science and technology foresight baker's dozen:
/Technological forecasting & Social Change 80 (2013) 386 397 32 D. Rossetti di Valdalbero, The Power of Science economic research and European decision-making:
EUR 24041 EN, European commission, Directorate-General for Research, Socioeconomic Sciences and Humanities, 2009, Available at:
He contributed to several ex-ante and ex-post Impact assessment studies of FP programmes and activities in the fields of Environment, Bio-based economy and Socioeconomic sciences and humanities.
and internationally devoted to Foresight and S&t and innovation policies; managed several national S&t foresight exercises in Russia,
participated in dozens of international projects. Alexander Sokolov is a member of a number of high-level expert groups at the OECD and other international organisations. 397 K. Haegeman et al./
a Chengdu Library of the Chinese Academy of Sciences, Chengdu 610041, PR China b School of economics and Management, Southwest Jiaotong University, Chengdu 610031, PR China c
Chengdu Library of the Chinese Academy of Sciences, Chengdu 610041, PR China. Tel.:++86 13811903239.
we count the number of patents Table 1 Technology life cycle indicators by former researchers. Author Indicator Robert J Watts, Alan L Porter 14 Number of items in databases such as Science Citation Index number of items in databases such as Engineering
Index number of items in databases such as U s. patents Number of items in databases such as Newspaper Abstracts Daily Issues raised in the Business
science literature 22,23 and other patents 24. Backward citations to science literature indicate a linkage between science and the patented technology.
Backward citations to other patents may indicate a linkage between other technologies and the patented technology.
Different types of technologies may have different developing patterns, especially for those technologies close to basic science, such as biotechnology.
Acknowledgement This research was undertaken at Georgia Tech, drawing on support from the National science Foundation (NSF) through the Center for Nanotechnology in Society (Arizona State university;
Award no. 0531194) and the Science of Science policy Program Measuring and Tracking Research Knowledge Integration (Georgia Tech;
and do not necessarily reflect the views of the National science Foundation. We deeply appreciate the financial support to this research from the West Light Foundation of the Chinese Academy of Sciences,
and the Knowledge Innovation Program of the Chinese Academy of Sciences. We are further sincerely grateful
and dedicate our acknowledgement to the experts in TFT-LCD, CRT and NBS: Prof. Shouqian Ding, Prof.
use of patent data, IEEE in Beijing, 2008.22 M. Meyer, Does science push technology? Patents citing scientific literature, Res.
Lidan Gao is an Associate professor of Chengdu Library of The Chinese Academy of Sciences. She focuses on patent analysis.
Shu Fang is a Professor and the Director of Chengdu Library of Chinese Academy of Sciences.
Xian Zhang is an Associate professor of Chengdu Library of The Chinese Academy of Sciences. Her major is informetrics
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;
Recognition of this fact in last decades is leading firmly to a new scientific paradigm, a complex bio-socioeconomics, with the convergence of different fields of science toward
what makes Darwinism a so controversial and long-lived scientific discipline, still open to further developments and applications. Theorizing about the evolutionary (Darwinian) aspects of technological change is then not merely a question of using metaphors and making analogies,
and artificial life are still emerging sciences, some important modeling attempts were undertaken along with the last decades and
with the convergence of different fields of science toward what may be the clue to understand the modus operandi of devolutiont per se the development of evolutionary algorithms for many different problem-solving and/or theoretical applications.
epitomizes one of the greatest mysteries of evolution still challenging scientists the emergence of novelty.
This terminus was proposed first in 1777 by the German economist Johannes Beckman (in his opus beinleitung zur Technologie oder zur Kenntnis der Handwerke, Fabriken und Manufakturenq) as science
are still emerging sciences. There are two possible approaches to simulating technological and/or socioeconomic systems. The systems dynamics approach, widely used in technological forecasting
NK technology landscapes, initially proposed by Stuart Kauffman 26 and further pursued by other researchers of the Santa fe Institute, like Jose'Lobo 27 and Walter Fontana 28;
also conducted in close collaboration with other researchers at the Santa fe Institute. Cellular automata, initially developed for gaming simulation
It has been used for instance by some researchers of the Maastricht evolutionary school of economics (MERIT), as Gerald Silverberg and Bart Verspagen 35, for the study of the distribution of innovations;
In technology and science GAS have been used as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems,
Altogether the application of these methods within the limits imposed by their own characteristics has helped researchers in unraveling some until now hidden properties of technological systems.
I see the new science of Digital Darwinism based on further improvements of genetic algorithms and genetic programming as the most promising candidate for establishing the knowledge basis of a working Evolutionary theory of technological change,
The Roles of Metaphors in Science, University of Illinois Press, 2003.5 P. Corning, Nature's Magic:
and emergence in complex networks, SFI-Working Paper 02-07-029,2002. 32 S. Wolfram, A New Kind of Science, Wolfram Media, Inc.,2002.33 J. Goldenberg
Integrating Science and Politics for the Environment, Island Press, Washington, 1993.33 D. Collingridge, The Social control of Technology, Frances Pinter Publisher, London, UK, 1980.34 J. P. Brans
from art to computational science and more, in: The 30th International Conference of the System Dynamics Society, St gallen, Switzerland, 2012.38 S. Bankes, Exploratory modeling for policy analysis, Oper.
/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.
There have been scientists who have realized this. Some claim the forecast is always wrong 4, others say all models are wrong 5,
Science, Decision making, and the Future of Nature, Island Press, WASHINGTON DC, 2000.3 G. Smith, Newton's philosophiae naturalis principia mathematica, in:
reflections on becoming a systems scientist, Syst. Dyn. Rev. 18 (2002) 501 531.6 O. H. Pilkey, L. Pilkey-Jarvis, Useless Arithmetic:
Why Environmental Scientists Can't Predict the Future, Columbia University Press, New york, USA, 2007.7 R. J. Lempert, S. Popper, S. Bankes, Shaping The next One hundred Years:
)( 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
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