as the broadest socioeconomic context for universities, with its own science, technology and innovation (STI) policy tools,
although they have advanced technologies to a very significant extent, and several major inventions have preceded long the proper theories of their underpinning scientific principles,
In other words, the links between science and technology are far from being (uni-)linear. Contrary to the widespread belief that technologies are, in essence, applied sciences,
a number of scientific disciplines evolved from the puzzles why certain technologies work as they do 22.12 This list is far from being exhaustive:
to keep it short, many professionals are mentioned not here, whose activities are also of crucial importance for successfulrtdi activities,
Technologies, Institutions and Organizations, Pinter, London, 1997.12 J. Fagerberg, D c. Mowery, R. R. Nelson (Eds.
and Approaches in Technology and Innovation policy, STI Review, No. 22,1998. 16 OECD, Benchmarking Industry science Relationships, OECD, Paris, 2002.17 W. Polt, C. Rammer, H. Gassler, A. Schibany,
la lettre OST, No. 22,2001. 19 L. Georghiou, Evolving frameworks for European collaboration in research and technology, Res.
of Education and Research, Bonn, 2005.42 G. Dosi, P. Llerena, M. Sylos Labini, The relationships between science, technologies and their industrial exploitation:
which technologies are advancing the new systems, structures and capabilities that will take us forward to 2020,2035 and 2050?
and provoke the traditional complacency of policy makers who tend to treat technology as an externality,
The essence of Cunningham's model is that the application of hierarchical random graphs of technology characteristics to questions as complex as:
enables a probability model to be constructed that anticipates novel combinations of technologies. Using this model he identified a range of technology changes associated with new standards for accessible internet applications within 100days of their emergence and without prior reference to the individual technology morphologies pathways progression.
Imagining the prospects if this technique can be developed more widely conjures up exciting possibilities for the anticipation of future innovation system developments.
and advance technology in ways that are responsive to society's needs and concerns through the definition of problems and boundaries that must be respected.
He holds a Dr. Tech. and a Lic. Tech. in systems analysis from the Helsinki University of Technology and MSC in environmental economics from the University of Helsinki.
Jack E. Smith is Senior Advisor Foresight and Innovation strategy, Defence R&d Canada, and Chair of the Foresight Synergy Network of Canada.
Tech. and M. Sc. degrees are from Helsinki University of Technology. Totti Könnölä1 Institute for Prospective Technological Studies (IPTS), JRC-European commission, Edificio Expo, C/Inca Garcilaso, 3, E-41092 Seville, Spain Corresponding author.
Analysis for radical design Scott W. Cunningham Policy analysis Section, Faculty of technology, Policy and Management, Delft University of Technology, Postbus 5015,2600 GA Delft, The netherlands a r
and analyzing systemic change in technology. Technological changes increasingly stem from the novel recombination of existing technologies. Changes are multitudinous.
A literature review of related work in the field of technology opportunities analysis is presented. We consider a possible, radically decentralized context for the conduct of future design.
An analytical method involving mining weighted graphs from technology archives is presented. The role of this new method in a context of distributed decision-making and design is presented. 2009 Elsevier Inc. All rights reserved.
Hierarchical random graphs Architectural innovation Technology forecasting Design 1. Introduction This paper examines a technique suitable for monitoring
and analyzing systemic change in technology. Technological changes increasingly stem from the novel recombination of existing technologies. Therefore, new techniques are needed for analyzing technology architecture.
because the analysis of a very significant feature of technological change the recombination of existing components is not being supported by most technology opportunity analysis techniques.
A literature review of related work in the field of technology opportunities analysis is presented. A case study of new technology architecture in the information technology domain is presented.
An analytical method involving mining weighted graphs from technology archives is presented. The role of this new method in a context of distributed decision-making and design is presented.
It is the newest and most novel of technologies which presents the greatest challenges for technological forecasting.
Deep uncertainty characterizes many domains of decision-making in science and technology. In particular, under deep uncertainty, there is little agreement or consensus about system structure.
For the decomposition of technologies, morphological analysis has long been practiced as a technique for recognizing component technologies.
Swanson demonstrates integrative capability by demonstrating new links between technologies, inherent in the data, which were not readily apparent to the respective scientific communities.
In this paper we examine techniques for exploring emergent structures or architectures of technology. Consider a knowledge base of technology where components of technologies are described
and linkages between the technologies are identified. This description of a knowledge base describes many repositories of scientific and technological information,
including: the Internet, science and technology databases, patent databases, newswires, and potentially also newsgroups or other online collaborative environments.
It extends and elaborates upon the procedures described by these authors for discovering new linkages of knowledge through use of a structured representation of science and technology,
which facilitates finding the integrative terms responsible for novel recombination of component technologies. In addition, the paper outlines several important caveat about the use of these models in forecasting new technology:
the nodes are technologies, and the edges are the component relationships that are present between the respective technologies.
The challenge of the technology analyst is to usefully structure this information to anticipate change. The technology designer has a similar challenge in exploring new, heretofore unforeseen, combinations of new technologies.
The network data in the raw is not useful for this purpose. A structured representation of technology is needed for multiple reasons:
interpretation, theory, robustness and also the production of actionable results. An unstructured network contains many parameters,
conforming to theories about the organization of science and technology. Without a theory of the data the technology analyst cannot distinguish between meaningful structure and possibly accidental corruption of the knowledge base.
This knowledge is stored in databases of science and technology. New future-oriented technology analysis techniques, such as the approach suggested here,
and thereby creating a new set of design concepts and a new configuration of components technologies.
but decentralized, knowledge of science and technology is something which can be tested through the use of machine learning techniques.
These concepts are explored further in this paper with a case exploring a software technology known as AJAX.
that many users of technology roadmapping exist in a vertically integrated environment where a few big players have the interests and capabilities to assist in technological coordination.
The description of distributed design in this article is, perhaps, somewhat at odds with the stated premise of technology roadmapping.
D). In this technology analysis application these nodes represent four component technologies of a system. These four nodes may be connected in sixtyfoou possible networks,
representing various combinations of the component technologies. Rather than a full enumeration of links, any observed network of these four component technologies can be represented compactly by introducing three parent nodes, each with their own associated probabilities of linkage.
These parent nodes which cannot be observed directly in the data, represent morphological principles actively at work in structuring the data.
Our previous example of four technologies will be expanded considerably to the analysis of forty-one technologies within an information technology design context.
Ajax is not so much a single technology; rather it is an architecture of technological components.
Recognition of this architecture grew only once the component technologies were given the Ajax name 26.
In this regard of being a novel recombination of source technologies Ajax is not unlike many other modern technologies.
include grid computing, the ipod and iphone, virtualization and LAMPP. 4. 1. Data collection and comparative analysis For the case study we collect data about Ajax and component technologies from the Internet.
At this disambiguation page AJAX the computing technology has been distinguished from other meanings of the word Ajax.
Many of these nodes in this expanded network are now very remote in content from Internet technologies.
Fitting the data The component technologies of Ajax may be represented in hierarchical random graph form. We apply the Monte carlo simulation procedure of Clauset 21 to fit the 41 pages within one hop of Ajax (Programming) into a hierarchical random graph.
along with general purpose technologies such as web servers, Javascript and object-oriented computer science. The hierarchical random graph also productively groups related technologies such as mobile phones and personal digital assistants.
Another example of effective groupings of technology induced by the network structure is the combination of search engines and web crawler.
At the lowest leaves of the tree are functional groupings of technologies including: scripting languages (Activex, Java Applets and Visual basic Script), document models (DOM and XHTML), alternative implementations of Ajax (using JSON and IFRAME),
and web application technologies (including key phrases of rich Internet applications, style sheets, web applications). The Monte carlo simulation procedure evaluated a range of competing solutions to the model.
The consensus diagram makes it clear that there are two sets of technologies technologies which are external
and technologies which may be considered internal to the Ajax paradigm. The internal technologies constitute a hierarchy in Fig. 6,
while external technologies do not reveal much hierarchical structure, at least in this sample of the data. One challenge to classification revealed by Figs. 5 and 6 is the placement of the various web browsers.
Consider that Safari, Internet explorer, Internet explorer 5, and Mozilla all various kinds of Internet browsers are placed in different locations in the hierarchical random graph.
It may be that the various browsers become closely associated with specific innovations in media technology. 4. 3. Interpreting the results Fig. 6 does not label the parent nodes with probabilities because of graphic visibility concerns.
Nonetheless, the principal virtue of this hierarchical graph approach is the ability to use this probability model to anticipate novel combinations of technologies.
but not yet observed in the Wikipedia knowledge base are shown below in Table 2. Fig. 6. Consensus diagram for Ajax Technologies. 1145 S w. Cunningham/Technological forecasting
These technology linkages are associated with a 70%likelihood. Some additional research into the first item reveals that there are indeed developments here:
and manipulate these web components through a range of alternative assistive technologies. An example of an assistive technology is screen readers;
screen readers convert plain text HTML messages to audible speech or Braille output. This new standard for rich Internet applications was incorporated in a recent beta version of Internet explorer 8. 5. Policy impacts These developments in ARIA are less than a year old at the time this paper was written the W3c posted a working draft
It recognized these new changes without explicit linkages in the knowledge base of technologies. Thus, the hierarchical random graph approach may provide a new forecasting, analysis and design technique for architectural innovation.
We have argued in this paper that many previous technology forecasting techniques have focused only on incremental and dominant designs.
which they struggle to encode within the network of scientific progress Polanyi 35 Changes in technology in this case are manifested in changes in network structure Knowledge is built upon the configuration of knowledge claims,
and not associated with single individuals Table 2 The most likely new combinations of technology predicted by the graph.
This technological network clearly demonstrated technologies internal and external to the core technology network. The disassortative character of this network means that architectural innovation is much likely to occur from external technologies.
Other technological architectures may be very different: these might be assortative networks which favor the use of technologies which are internal,
and therefore already present within the system. The author suggests that the original conception of architectural change,
and case studies. 6. Interpretations from the philosophy and sociology of science The hierarchical random graph is one possible model of science, technology and innovation data.
Derrida's ideas informed Callon and others who developed actor network theory as a vehicle for research in science and technology 33.
Knowledge about science and technology may come in two forms. Explicit knowledge entails knowledge about specific claims.
the existence of the claim can be verified through recourse to knowledge bases of science and technology.
Polanyi's account of science and technology has technologists laboring at the interface of claims,
The alternative approach would be to expressly encode the configuration within the database of science and technology.
a hierarchical random graph, is a useful way for structuring diffuse knowledge bases of science and technology.
as well as presaging a significant reorganization of the science and technology database to better match technological progress.
Nonetheless revealing undocumented links still provides a useful stimulus for technology monitoring efforts. The procedure proposed in this paper provides an objective method of predicting new technological linkages.
For instance, the nodes used in this study ranged from specific technologies, to people (Jesse James Garrett), to institutions (W3c.
While a mix of node types might be desirable (for instance technology as well as process), it may be difficult to establish a uniform definition of the technological components of the network.
The case study recognized impending change in nodes related to W3c standard setting, rich Internet technologies, and Internet explorer.
Paper Presented at the Portland International Conference on Management of Engineering and Technology, Portland, 2007.2 A. De Haan, K. Mulder, Sustainable air transport:
Q. 35 (1990) 6045 6633.4 A l. Porter, A t. Roper, T. W. Mason, F. A. Rossini, J. Banks, Forecasting and Management of Technology
Policy 14 (1985) 235 251.17 J. P. Dismukes, Technologies of thinking'seen key to accelerated radical innovation, Res.
Tech mining to accelerate radical innovation, PICMET 2007 Proceedings, 2007.19 Y. Yasunaga, M. Watanabe, M. Korenaga, Outline of the strategic technology roadmap of METI (Ministry of Trade and Industry
of Japan) and trial approaches for technology convergence with the methodology of technology roadmapping, PICMET 2007 Proceedings, Portland, Oregon:
the reconfiguration of existing product technologies and the failure of established firms, Adm. Sci. Q. 35 (1990) 9 30.30 S g. Green, M. B. Gavin, L. Aiman-Smith, Assessing a multidimensional measure of radical technological innovation, IEEE Trans.
Scott Cunningham received a Ph d. in Science, Technology and Innovation policy from the Science policy Research Unit.
developed patents in the fields of pricing and promotion algorithms, been a research fellow at the Technology policy Assessment Center of Georgia Tech,
He currently works for the Faculty of technology, Policy and Management, of the Delft University of Technology,
His book on Tech Mining co-authored with Alan Porter, was published in 2001 with Wiley. 1149 S w. Cunningham/Technological forecasting & Social Change 76 (2009) 1138 1149
, A. Klinke A j. Markard A m. Maurer b, A. Ruef a a Department Innovation research in Utility Sectors at The swiss Federal Institute of Aquatic Science and Technology (Eawag), Switzerland
at the German Fraunhofer Institute for Systems and Innovation research ISI, Germany e Technology and Society Unit of The swiss Federal Institute of Materials Science and Technology (Empa
technology and innovation policy 6. Foresight is however much less well developed in strategic planning contexts as it often misses the link between analyzing uncertainties to assessing options
technologies and skills that determine a stable context in which highly complex system configurations can develop 12.
Due to ICT, miniaturization of components, new technological solutions like membrane technology or new measuring and control devices, radically different system configurations might become available with grossly enhanced performance characteristics.
and prioritize science, technology and innovation policy measures. While the earlier approaches tended to be techno-deterministic,
the later applications more explicitly address the co-evolution of technology and society 19. In line with this shift of attention, foresight was conceived mainly as an informing policy task until the 1970s,
or transport technology scenarios without explicitly assessing adequate strategies 39 43. Others include the assessment of options
Weaknesses incorporate the uncertainty about system reliability of the technology and uncertainties associated with service reliability,
and incorporated early on in a robust decision procedure able to respond to emerging information (e g. concerning decentralized technologies),
Human choice and climate change resources and technology, Battelle Press, Columbus, 1998.13 M. S. Jørgensen, U. Jørgensen, C. Clausen, The social shaping approach to technology foresight
An Investigation into the Long-term challenges and Opportunities for the UK's Strategic Highway Network, Highway Agency for England, London, 2003.42 Office of Science and Technology, Intelligent Infrastructure Futures, Foresight Directorate
/Technological forecasting & Social Change 76 (2009) 1150 1162 49 K. M. Hillman, B. A. Sandén, Exploring technology paths:
A comparison of alternative technologies to decarbonize Canada's passenger transportation sector, Technol. Forecast. Soc.
Eckhard Störmer is a project leader at the Social science Research Department Cirus (innovation research in utility sectors) at The swiss Federal Institute of Aquatic Science and Technology (Eawag.
Hans Kastenholz is a senior researcher at the Technology and Society unit of The swiss Federal Institute of Materials Science and Technology (Empa.
technology forecasting and technology assessment 1. As noted in Könnölä et al. 2, the gradual paradigm shift in the innovation research
and technology oriented forecasstin practices and called for new participatory and systemic foresight approaches 3. Also the R&d functions are moving from the basic science
and technology push driven innovation processes to the systemic innovations that emerge close to the market 4. Consequently,
and both technology-driven and problem-driven approaches are taken 1. It is stressed also that it is important to see technology as part of a whole technological and societal system 11.
The scope and context of the analysis, as well as the examination of the technology, its impacts and related policy,
are all important in this respect. This means, for instance, studying whether the assessed technology does the job better than the previous methods,
whether it fits into the company and/or the society, and whether it has impacts or side-effects.
will the technology be needed usable and also in the future. Consideration of opinions, attitudes, fears, interests and hopes may then be as important as consideration of clear facts.
and space technology in the 1960s 13. These fields are renowned for their complicated systems, where possible accidents may have far-reaching consequences.
A systematic and Fig. 2. A systemic framework for methods 10.1 For instance, the TA studies carried out by the US Office of Technology (OTA) in 1974 1995 primarily served to inform Congress
when technology-related legislative policy options were considered. 1166 R. Koivisto et al.//Technological forecasting & Social Change 76 (2009) 1163 1176 analytic way to assess
It is emphasised also that new market developments, technologies, threats and vulnerabilities are emerging and that they require proactive anticipation of the future worlds.
economics and technology, applying big amount of creative brainstorming approaches ending to two potential scenarios.
the process, the technology, people, the environment and so on should be known as fully as possible. The project states that a good modelling tool would help to model the future interdependencies supported by an integration of the scenario work and the systematic risk assessment. 3. 2. Managing opportunities,
a medium-size company offering control systems for high-tech companies, a medium-size technology company and a large-size technology company. 2 The back-pocket roadmap starts
In the medium-size technology company a roadmap of the offering of the company in the future was done
In both technology and risk assessment this is made by changing mindsets, building trust among actors and developing better preparedness for the change,
Foresight for Europe, Final Report of the High level Expert Group for the European commission, April 24, 2002, European commission, Brussels, 2002.6 A. Eerola, E. Väyrynen, Developing technology forecasting and technology assessment
10 O.,Saritas, Systems thinking for Foresight, Ph d. Thesis, PREST, Manchester Business school, University of Manchester, 2006.11 E. Braun, Technology in context.
, T. Luoma, S. Toivonen, Managing uncertainty in the front end of radical innovation development, Proc. of IAMOT 2007 16th International Conference on Management of Technology, May 13 17,2007, Florida
, USA, International Association for the Management of Technology, 2007, pp. 1306 1324.36 T. Luoma, J. Paasi, H. Nordlund.
and gives courses in Lappeenranta University of Technology. Dr. Nina Wessberg is Senior Research scientist at VTT.
She graduated in Helsinki University of Technology and holds a Phd from Helsinki Swedish School of economics and Business administration
Besides technological development decision-makers need all-inclusive knowledge of future developments of society, economy and impacts of science and technology.
Technology barometerwas developed in order tomeasure the scientific technological and socioeconomic state and development level of the nation and formaking related comparative analysis to other nations.
and the crucial element in production, with information and communication technologies comprehensively supporting interaction, the dissemination and exploitation of knowledge between individuals, businesses and other communities, plus the provision and accessibility of services.
In technology barometer, the indicators of knowledge society assess the gearing of the human and intellectual capital investments towards science and technology
the applications of information and communications technologies, and the outcomes of these investments as R&d productivity.
In conclusion, an indicator study of the technology barometer comprises 12 sub-indicators providing an index-type key value indicating the state of technology at a given time.
The exact questions and formulations used can be found in the full barometer report 7. The purpose of the survey is to cast light onto the respondents'valuations regarding technology, perception about current state of affairs,
and technology will be followed increasingly through means of interactive, instantly updated electronic media. The positive news here is that these areas continue to attract young people.
in basic technologies and business thinking alike, so as to generate product concepts with increasing initiative and courage.
science and technology will be followed increasingly by means of interactive, instantly updated media such as the Internet and popular TV programmes of science and technology. 4. Conclusions Despite the inevitable methodological challenges,
the technology barometer has proven to be capable of casting additional light on bottlenecks and problem areas within the national innovation environment in Finland.
and its results can be utilized as an aid and support for long-term decisions concerning science, technology, innovation and education.
and Section 4. 2 discusses further development perspectives of the barometer in the future. 4. 1. Results of barometer support innovation policy-making One of the strategic aims of technology barometer exercise is to provide guidance on technologies and actions
Moreover, the process of developing Finnish national strategic centres for science, technology and innovation is underway in the technology fields with future importance for businesses and the society.
) Employment Index (Storrie and Bjurek) Innovation/technology Summary Innovation Index (EC) Networked Readiness Index (CID) National Innovation Capacity Index (Porter and Stern) Investment
in Knowledge-based Economy (EC) Performance in Knowledge-based Economy (EC) Technology Achievement Index (UN) General Indicator of Science and Technology (NISTEP) Information and Communications technologies
/Technological forecasting & Social Change 76 (2009) 1177 1186 Appendix B. Technology barometer 2007 Technology instrument for measuring citizens'attitudes and the nation's orientation towards a knowledge-based
3. 2. Knowledge society development 3. 2. 1. Investment in research and product development 3. 2. 2. Information and communication technologies ICT expenditure The use of information
and communication technologies ecommerce 3. 2. 3. Application of new knowledge 3. 3. Innovative society 3. 3. 1. Understanding of knowledge
. Views concerning scientific-and-technical institutions and organizations 4. 3. 3. Views regarding the roles of knowledge and technology in Finnish society
4. 4. Innovative society 4. 4. 1. Investments and entrepreneurial activeness 4. 4. 2. Potential effects of the development of technology on the quality of life 4. 5
His recent research work is related to the rationales of innovation policy, foresight of technologies (e g. transition towards sustainable energy systems), intellectual property rights,
The future fields are all crosscutting issues based on science and technology. All of them are specifically knowledge dynamic fields. 2009 Elsevier Inc. All rights reserved.
1) Identification of new focuses in research and technology 2) Designation of areas for crosscutting activities 3) Exploration of fields for strategic partnerships 4) Derivation of priority activity lines
and technology and was broadened to look into the future of the next 10 to 15 years and even further.
For the monitoring process, an international panel of well-known and acknowledged experts who have an overview in their fields were asked about the current state and new developments in research and technology.
and interviewed in order to find the most promising topics in research and technology for the next 10 to 15 years or even further in the future.
these fields were selected as starting points to search for new topics in science and technology, at first at the national level, later on internationally.
1. Life sciences and biotechnology 2. Information and communication technology 3. Materials and their production processes 4. Nanotechnology 5. Optics/photonics/optoelectronics 6. Industrial production processes
7. Health research and medicine 8. Infrastructure technology, urbanisation and environmental development 9. Environmental protection technology and sustainable development 10.
transport and traffic technology, mobility, logistics (land, water, air, space) 12. Cognitive sciences and neuroscience 13.
and new developments in science and technology or long-term research questions were described at these crossroads. These crosscutting areas were additional starting points for searches.
but with science and technology push topics. Therefore, the criteria to be matched incorporated some of the demand aspects
and technology landscape are really relevant and if theymeet the criteria of the process. In order to keep it simple and user-friendly,
and technology are already receiving sufficient support, and solutions are on the way or better: the topics are not new,
and use of new living beings with new properties by integrating artificial systems 29 Hydrogen technology systems 28 Research on illnesses caused by lifestyle 27 Affective Computing 26
and in science and technology with a longer-term view and codifying this knowledge in reports for BMBF contributes directly to the first two objectives of the process (objectives no. 1 and 2). It is expected that policy implementation will be facilitated by this information, by defining strategic partnerships and recommendations,
because experts in the broader sense were the persons who knew about the details in science and technology.
The current BMBF Foresight process is about science and technology it needs experts who are able to understand
and were focused on results that are within the limits of BMBF reach and responsibility (science and technology).
but stress science and technology because other topics may not be implemented directly by a BMBF. Therefore, those topics which are not directly BMBF topics are handed over to others by raising their awareness.
, Science and Technology (MEXT), in: National Institute of Science and Technology policy (NISTEP (Ed.),Kagakugijutsu no chûchôki hatten ni kakawaru fukanteki yosoku chôsa (The 8th Science and Technology foresight Survey Future science and Technology
in Japan, Delphi Report) Report no. 97, NISTEP, Tôkyô, 2005.5 Science and Technology foresight Center, Ministry of Education, Culture, Sports, Science and Technology (MEXT), in:
National Institute of Science and Technology policy (NISTEP (Ed.),Kyûsoku ni hattenshitsutsu aru kenkyû ryûiki chôsa (The 8th Science and Technology foresight Survey Study on Rapidlydevellopin Research area
) Report no. 95, NISTEP, Tôkyô, 2005.6 Science and Technology foresight Center, Ministry of Education, Culture, Sports, Science and Technology (MEXT), in:
new foresight on science and technology, Technology, Innovation and Policy, Series of the Fraunhofer Institute for Systems and Innovation research ISI no. 13, Physica, Heidelberg, 2002.17 Bundesministerium für Forschung und
Technologie (Federal Ministry for Research and Technology, BMFT (Ed.),Deutscher Delphi-Bericht zur Entwicklung von Wissenschaft und Technik (German Delphi Report on the Development
of Science and Technology), Bonn, 1993.18 O. Da Costa, P. Warnke, Chr. Cagnin, F. Scapolo, The impact of foresight on policy-making:
new foresight on science and technology, Technology, Innovation and Policy, Series of the Fraunhofer Institute for Systems and Innovation research ISI no. 13, Physica, Heidelberg, 2002.30 Science and Technology foresight Center, Ministry
of Education, Culture, Sports, Science and Technology (MEXT), in: National Institute of Science and Technology policy (NISTEP (Ed.),Comprehensive analysis of Science and Technology Benchmarking and Foresight report no. 99, Tôkyô:
NISTEP (English short version), 2005.31 L. Georghiou, et al. The Handbook of Technology foresight, Concepts and Practice, PRIME Series on Research and Innovation policy, 2008.32 S. Kuhlmann, et al.
Overtext Web Module V3.0 Alpha
Copyright Semantic-Knowledge, 1994-2011