In our model, the knowledge space that analyses these wider socio-technical constellations is the strategy space.
for example, through the application of life cycle analysis. The second aspect was to open the field towards more efficient use of ICTS in the processes, such as solutions for distance-based monitoring, the use of building information models,
The second phase, the SWOT analysis, identified trends in the national ICT business and research environment in the four Nordic countries.
Second, systemic transformation capacities could also be catalysed by integrating novel ICT-based analysis tools. For example
and historical analyses would benefit from the deeper engagement with how the contextual future perspectives are manifested in the past presents'.
Analysis of modular foresight projects at contract research organization. Technological Analysis & Strategic management 21, no 3: 381 405.
Lee, S.,andy. Park. 2005. Customization of technology roadmaps according to roadmapping purposes: Overall process and detailed modules.
These include innovation system modelling, text mining of Science, Technology & Innovation(‘ST&I')information resources, trend analyses, actor analyses,
Such technology opportunitiie analysis (Porter et al. 1994) for NESTS poses notable challenges. FTA increasingly includes science-based technologies
plus patent analyses has contributed to science and technology studies for decades (cf. Van Raan 1988. With the expansion of databases that compile abstract records
NEST analyses often concern economic opportunities, with significant concern to identify and mitigate potential‘unintennded indirect,
To facilitate the analysis of technological change, Hekkert et al. 2007) articulate‘functions of innovation systems'.'Some researchers look into what kind of innovation transfer is most effective (e g.
including bibliometric analyses, social netwoor analyses, and trend analyses. We adapt these to facilitate our study as a function of the state of development of NESTS.
We seek innovation indicators (i e. empirical measures to gauge technological maturation and prospects for successful applications.
Most importantly, we found a willing Phd student (Chen Xu) to collaborate in our analyses. Early formulation of the TDS with pointers towards key institutions can help illuminate needs for special expertise.
Within the context of ongoing empirical analyses of nanotechnology(‘nano')R&d, we focus here on how nanomaterials are being used to enhance the performance of solar cells,
This analysis treats DSSC abstract records through 2010 based on these searches: 4104 documents (including 3134 articles) appearing in the Science Citation Index (SCI) of WOS (fundamental research emphasis;
we focus selectively as such analyses are fairly well known (Porter, Kongthon, and Lu 2002). We begin by showing trends based on the annual activity from each database in Figure 3. It is clear that the research publications drawn from the SCI
and business activity compilations, one can enable social network analyses within and among organisations. 4. 4. Determine potential applications (Step E) We introduced a new technique called‘cross-charting'to explore the links from technological attributes (e g. particular nanomaterials or nanostructures and particular technical advances) to functional
In this paper and in companion analyses of nanobiosensors, we found value in subdividing the technical elements (e g. distinguishing among various nanostructured materials;
The face-tofaac interview with him provided input to allow a first evaluation of our analyses.
With a doctoral student's cooperation, we continued our analyses to FIP. A second round of contacts focused on identifying workshop participants.
Figure 7 raises the desirability of life-cycle Downloaded by University of Bucharest at 05:05 03 december 2014 Text mining of information resources 857 analyses to consider likely life span, maintainability, material transformation
We are investigating DSSC technical component developments through patent analyses that combine text mining, semantic/syntactic analyses,
Figure 7 notes possible impacts and issues worth further analyses. The variability among NEST situations and possible decision needs calls for the FIP approach to be considered very flexibly.
Based on factor analysis, these are grouped into macrodisciipline (the labels shown in Figure 4). For more information,
Towards a combined framework for the analysis of innovation processes. Understanding processes in sustainable innovation journeys, Utrecht. van Merkerk, R. O,
Technology opportunities analysis: Integrating technology monitoring, forecasting & assessment with strategic planning. SRA Journal (Society of Research Administrators) 26, no. 2: 21 31.
) Meta-analysis on foresight methods shows the trends of combination (Popper, 2008: B scenario is used often with literature review, expert panel,
) According to the meta-analysis mentioned above, around 20-39 percent of Delphi exercises are combined with scenario.
and Technology information for analysis is obtained from the Delphi survey and scenario building by group work in the 9th Foresight exercise.
Figure 2 The procedure of analysis VOL. 15 NO. 1 2013 jforesight jpage 11 4. 2 Overall view Relations between the scenarios
Their analysis is relevant because the motivation and the challenges of those dialogues tie in with those of transferring foresight results,
Hence, step 5 of a PAGE 24 jforesight jvol. 15 NO. 1 2013 strategic dialog might be a survey of earlier national funding activities and a gap analysis between those activities and the potential support
and provides knowledge and analysis for a broader, national research prioritisation exercise. The paper analyses the implementation of The irish foresight exercise
which combined analysis of global changes with a participatory process involving national stakeholders. The exercise was designed to assess the implications of global changes for research.
context and methodology 3. 1 Introduction to the case study analysis The presentation and analysis of the case study below is based on my role as part of the research
and implemented that provided the main output required by Forfa's i e. a catalogue of global drivers and trends together with an analysis of their potential impact and opportunities for The irish research and enterprise base.
An iterative methodology, consisting of different stages of analysis of the drivers and trends, and a series of meetings and workshops, served to validate
Global drivers and trends analysis. The first main phase of the exercise consisted of an initial analysis of global drivers and trends across the PESTLE categories (Political, Economic, Social, Technological, Legislative, and Environmental.
This meta-analysis used an assessment framework, which formed the basis of the subsequent project catalogue,
from drivers and trends to grand challenges 4. 1 Catalogue of global drivers and trends from the national context The third level catalogue is a substantial volume that analyses global trends and drivers from a‘‘national
a contextualist analysis and discussion'',Technological forecasting and Social Change, Vol. 74 No. 8, pp. 1374-93.
Originality/value For the first time the paper presents an analysis of Russian foresight projects connected to the natural resources area and an evaluation of their influence on policy decision making.
The analysis of these three Foresight projects is presented below. VOL. 15 NO. 1 2013 jforesight jpage 41 2. Methodology The methodology of the paper includes several steps:
B analysis of the interconnection of the projects'structures and their results; and B an assessment of their impact on policy-making.
and levels of analysis, is characterised in the next step. Then we present the project's methodology (methods used, stages,
number of experts engaged and main criteria for analysis). Finally the main results are described and illustrated.
In the second step of the analysis the interconnection of the structures of the projects is explored.
and 3. questions for further investigation on the basis of the main results and conclusions of the project we identify directions for further analysis in order to increase the impact of the project's results on policy-making.
So, in the framework of this analysis we show how the results of one project are added to the results of the following project,
B socioeconomic objectives analysis; B selection of experts; B identification of thematic areas; B Delphi topics;
A clear need was highlighted for more detailed analysis of future demand for human, financial and other types of resources for S&t development.
So, the analysis showed the synergy of all three projects help to achieve results that had a strong influence on policy decision-making.
and used as sources for future technology themes analysis. A standard mapping taxonomy based on international patent classification system was used to map out the technology concept described in these future technology themes.
Technology interactions can be identified through a causal effect analysis during the mapping, and the results among selected countries are cross-compared
This research may help to solve the practical difficulties faced during the secondary analysis of foresight studies in foresight preparatory studies by providing a consistent classification framework to make comparison and aggregation of future technology options from different countries/regions.
and competitive technology intelligence by utilizing the results deriving from the former as targets for analysis
Keywords Strategic technology foresight, Competitive technology intelligence, Delphi topic analysis, International patent classification system, Sustainable energy, Innovation, Forward planning Paper type Research paper 1
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
With this perception, conventional strength, weaknesses, opportunities and threats (SWOT) analyses are informed by the need to maintain these core competences in the face of the development by competitors of their own core competences and key assets (Hax and Majluf, 1996.
including content analysis, patent analysis, bibliometrics, competitor profiling, early warning assessment, scientometrics, science mapping, scenarios, network analysis and so forth (Calof and Smith, 2010).
In Delphi Austria, an analysis of the Japanese, German, French, British Delphi studies was conducted to separate
or standard classification system will make it easier to take a cross-foresight comparison and for analysis. Therefore, a structured mapping method that uses a worldwide accepted international classification system i e.
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
Also, patent documents are used widely as a source for technology forecasting, CTI and for analysis of technology convergence (Kayal, 1999;
statistics regarding the code or advanced analysis can be done easily to compare development or the trajectory among different technology domains.
or terms in each Delphi topic through content analysis Step 4 Assign the corresponding IPC codes (main-group level
or social network analysis PAGE 58 jforesight jvol. 15 NO. 1 2013 For converting and aggregating to the 35 WIPO technology classifications in Step 6,
or can be visualized in advance by social network analysis. 2. 3. 3 Examples of Delphi topic mapping.
''The keywords extracted by content analysis are‘‘polymer electrolyte''and‘‘fuel cells''.''By using the IPC subclass code for mapping, the IPC Table III WIPO technology classification No.
for management 8 Semiconductors 9 Optics 10 Measurement 11 Analysis of biological materials 12 Control 13 Medical technology 14 Organic fine chemistry
the source/application technology for the Delphi topics are identified through causal effect analysis, namely the source IPC code and the application IPC code are distinguished by the judgment of a domain expert.
‘‘time of international realization before 2020''for South korea and all Delphi topics from China, are used as the main target for analysis and for comparison.
and the interactions are demonstrated by a directional social network analysis (SNA) with a tool named Nodexl 1 in Figure 3
and the deduced interactions are demonstrated by a directional social network analysis (SNA) in Figure 3. In total,
and the deduced interactions are demonstrated by a directional social network analysis (SNA) in Figure 4. In total 50 linkages are identified from these 46 Delphi topics.
and the deduced linkages for the selected topics are demonstrated also by a directional social network analysis (SNA).
The content of these topics comprises‘‘Circulating fluidized bed flue gas desulfurization'',Coal gasification-based poly-generation technology'',Energy consumption analysis for construction and building environmental systems and energy saving optimization technology,
and the interaction between technologies is identified through a causal effect analysis. Similarities and discrepancies in future technology options among countries are analyzed successfully,
One is to help solving the practical difficulties faced during the secondary analysis of foresight studies in foresight preparatory studies,
Also, the method combines both the advantage of strategic technology foresight and competitive technology intelligence, by utilizing the results derived from the former as a target for analysis
The result of the analysis is based on the foresight activities of three large Northeast Asian countries and some of the technology interactions are prospected differently by these three countries.
Note 1. Nodexl is an online free tool for social network analysis, which can be accessed at http://nodexl. codeplex. com/References Aichholzer, G. 2001),‘Delphi Austria:
Orwat, C. 2003),‘WP 1 Review and analysis of national foresight; D1. 1a Case study: Austria Delphi Austria'',FZK-ITAS Forschungszentrum Karlsruhe Gmbh in der Helmholtz-Gemeinschaft, Institut fu r Technikfolgenabscha tzung und Systemanalyse, available at:
issues and analysis'',International Journal of Forecasting, Vol. 15, pp. 353-75. Rowe, G.,Wright, G. and Bolger, F. 1991),‘Delphi:
The main objective of FTA projects is to assist decision-makers with relevant analyses, observations and new ideas to be prepared better for the future (assuming that it can be predicted)
which require crosscutting analysis and intervention across policy domains 11,12. It is even more so when one tries to tackle the so-called grand challenges.
We need further theoretical analyses and practical work to establish what FTA METHODS would be useful and feasible to facilitate co-ordination of tools/actions used in various policy domains,
and Analysis) and to assess multiple scenarios to support the design of dynamic adaptive policies.
Shaper-Rinkel 13 analyses future-oriented governance of emerging technologies in the USA and in Germany,
and QT approaches does lead not only to a richer analysis of possible futures, but also to a wider view on possible directions of future developments.
and Analysis (EMA) is a methodology for analysing dynamic and complex systems and supporting long-term decision-making under uncertainty through computational experiments.
Shaper-Rinkel 13 analyses future-oriented governance of emerging technologies. She explores the role that different types of FTA played in the development of nanotechnology governance in the USA and in Germany.
7 L. Gao, A l. Porter, J. Wang, S. Fang, X. Zhang, T. Ma, W. Wang, L. Huang, Technology life cycle analysis method
12 J. H. Kwakkel, E. Pruyt, Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty, Technol.
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;
and analysis on the consequences and outcomes of applying specific techniques in the course of FTA. 5 Scapolo
and Porter 27 argue that this absence of stocktaking analysis is mirrored also in the lack of guidance on how to evaluate FTA projects that combine different methodologies.
In some cases, the interactions between the two approaches are limited to cross-checking of assumptions and findings of the same analysis
For instance, quantitative analysis of this kind offers valuable information for the development of S&t Delphi survey topics,
or for the quantitative analysis of qualitative data (such as statistical analysis of stakeholder opinions or networking behaviour. Such exercises push experts in quantitative and qualitative techniques closer to each other,
Online analysis of data and creation of knowledge repositories: Cooke and Buckley 7 believe that web 2. 0 tools can be used to make data of all sorts accessible to respondents and researchers:
/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:
Social network analysis has attracted attention in the past years allowing quantitative analysis on relationships and links that make up various social processes.
network analysis can be used to enable robust analysis of foresight data, which are often complex to present
/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,
where the future is the object of analysis, as there are different ways of exploring the future, based on e g. differences in beliefs or educational backgrounds.
Cost Benefit Analysis or similar tools that require the valuation (or at least some form of quali-quantitative estimation) of a variety of factors including the social costs
(and in fact are adopted in the framework of quantitative analyses as well. On the other hand, qualitative approaches have been adopted for many decades (e g. scenarios) with no other involvement than that of the FTA EXPERTS.
methods research and data analyses, J. Mixed Methods Res. 4 (4)( 2010) 342 360.60 R. B. Johnson, A j. Onwuegbuzie, Mixed methods research:
)( 2012) 56 68.75 H. White, Combining quantitative and qualitative approaches in poverty analysis, World Dev. 30 (3)( 2002) 511 522.76 C. Ansell, A. Gash
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
is trend analysis. This includes both historical time series analyses and fitting of growth models to project possible future trends 5. Most trend projection is naïve i e.,
Usually, patent application activity is tracked as a TLC indicator for the S-curve analysis 10,12, 13.
Framework of TLC analysis. 400 L Gao et al.//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
we employ a cross-correlation analysis to measure the similarity among the 13 indicators in the four stages.
Table 4 provides the results of the cross-correlation analysis (r=0. 9). Emerging stage:
vuutð13þ Table 4 Cross-correlation analysis for 13 indicators (r=0. 9). TLC stage Emerging Growth Maturity Decline Group 1 1, 2
it is a good time to invest in NBS to pursue potentialmarkets. 4. Conclusions How might technology life cycle analysis based on patents contribute to FTA?
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.
trend analyses (where it best fits), but also monitoring and intelligence, matrices (analogies), modelling, and a hint of roadmapping.
Yuan Christian University, Taiwan, 2005.13 C. M. Chu, Using technology life cycle to analysis the developing trend of thin-film photovoltaic industry, Ph d. dissertation, National Central
Inf. 9 (2006) 160 166.18 C. M. Chu, Using technology life cycle to analysis the developing trend of thin-film photovoltaic industry, Ph d. dissertation, National Central
Serv. 11 (2009) 59 63.20 H. L. Yu, Analysis of the particleboard technology based on TRIZ and S-Curve technique evolution law, Forest.
an empirical analysis, Rand J. Econ. 25 (1994) 319 333.26 T. H. Chang, A study on the Technique Development of RFID-Base on life-cycle theory, Ph d
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.
Policy 1 (3 4)( 2004) 1740 2816.39 C. Lee, Y. Cho, H. Seol, Y. Park, A stochastic patent citation analysis approach
and we are witnessing today an intense debate on duniversal Darwinismt as a broad theoretical framework for the analysis of the evolution of all open,
and we are witnessing today an intense debate on duniversal Darwinismt as a broad theoretical framework for the analysis of the evolution of all open,
if we restrict our analysis to dtechnological innovationt (our present context). I want to advance the following arguments favoring an evolutionary approach to define innovation
when we focus the evolutionary analysis on technological innovations we are not necessarily simplifying the field of discussion,
1 What should be the suitable unity of analysis in technological evolution? Or in other words, what then actually evolves?
At this point it is worth to point out that I agree with Joel Mokyr 19 that the unity of analysis that makes sense for the study of technological evolution is the dtechnique.
Such top-down analyses are very suitable for describing the system's regularities and for identifying dominant feedback loops,
technique is the most suitable basic unity of analysis and must be viewed as the enduring search for bypasses (shortcuts) obeying the general physical principle of the least action;
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
Model-based decision support Deep uncertainty Adaptive policy-making Exploratory Modeling and Analysis 1. Introduction Conceptual, formal, and computational models are used commonly to support decision-making
and the analysis of wild cards and weak signals 11. Characteristic for these techniques is that they aim at charting the Technological forecasting & Social Change 80 (2013) 408 418 Corresponding author.
when the analysis and assumptions critical to the policy's success have lost validity. 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.
A possible quantitative approach for operationalizing the Adaptive Policy-making Framework is by using Exploratory Modeling and Analysis 36 38.
4) the generation of a large ensemble of scenarios,(5) the exploration and analysis of the ensemble of scenarios obtained in Step 4
as well as the main causes of these troublesome and promising regions,(6) the design informed by the analysis in Step 5 of policies for turning troublesome regions into unproblematic regions,(7) the implementation of the candidate policies
(9) the exploration and analysis of the ensemble of scenarios obtained in Step 8 in order to identify troublesome and/or promising regions across the outcomes of interest,
A modified classification in combination with PRIM could be utilized for such an analysis. This study also has implications for Future-oriented technology analysis (FTA.
Our analysis shows that ARD can be used to develop long-term adaptive and robust policies for grand societal transformations.
and Analysis can be utilized successfully in the context of adaptive policy-making. The iterative approach for designing robust adaptive policies helps to identify
Exploratory Modeling, Real Options analysis and Policy design which is supported by The next Generation Infrastructures (NGI) Foundation.
a strategic analysis under conditions of deep uncertainty, in: Technical Reports, RAND, Santa monica, California, 2009.14 D. H. Meadows, J. Richardson, G. Bruckmann, Groping in the dark:
Exploratory modeling and analysis: a promising method to deal with deep uncertainty, in: Technology policy and Management, Delft University of Technology, Delft, 2008, p. 285.37 E. Pruyt, J. Kwakkel, A bright future for system dynamics:
. Kastenholz, A. Klinke, J. Markard, M. Maurer, A. Ruef, The exploratory analysis of trade-offs in strategic planning:
. J. Conover, A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics 21 (1979) 239 245.56 Eric Jones, Travis Oliphant
His research interests are exploration and analysis of dynamically complex systems under deep uncertainty. In his Phd research, he focuses on long term decision-making under deep uncertainty using the Exploratory Modeling and Analysis method.
His applied interests include climate change/energy issues, public health and health policies, financial crisis and energy systems. His current research interests are adaptive policy making and the use of optimization in policy-making.
Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty Jan H. Kwakkel, Erik Pruyt Faculty of technology, Policy,
and Analysis (EMA) is an approach that uses computational experiments to analyze complex and uncertain issues.
Future-oriented technology analysis Exploratory Modeling and Analysis Deep uncertainty System dynamics Adaptive policymaking Agent-based modeling 1. Introduction Future-oriented technology analysis (FTA) is understood as an umbrella label for various approaches
and Analysis (EMA) tailored to this. EMA aims at offering decision support even in the face of many irreducible uncertainties, by systematically exploring the consequences of a plethora of uncertainties ranging fromparametric uncertainties (e g. parameters ranges), over structural uncertainties (e g. different
and analysis Various scientific fields including the environmental sciences, transportation research, economics, and the political sciences, are involved in providing model-based decision support.
Exploratory Modeling and Analysis (EMA) is a research methodology that uses computational experiments to analyze complex and uncertain systems 12,13.
and the analysis of the results of these experiments 12,13. EMA is focused not narrowly on optimizing a (complex system to accomplish a particular goal or answer a specific question,
run the model and extract the results. 3. 1. 3. Analysis of results Fig. 2 shows the dynamics for 5 different outcomes of interest.
This display however also shows the need for further analysis: the individual runs are difficult to trace in this plot.
A more detailed analysis was performed in order to assess whether the cyclical behavior arises out of a particular combination of uncertainties.
More thorough analysis of the results is needed still for even roughly 6000 behaviors in case of 50,000 runs are still unwieldy for supporting decision-making.
which one can sample. 3. 2. 3. Analysis of results One key challenge for airport planners is to design a plan for guiding the future developments of the airport that is robust with respect to the future 36.
The column‘static plan'in Table 5 shows the results of this analysis. Looking at the various outcome indicators,
This figure Table 3 Tools integrated in the fast and simple model for airport performance analysis. Airport performance aspect Tool Capacity FAA Airfield Capacity Model (FCM
Emissions Emission Dispersion Modeling System (EDMS) the FAA required tool for emission analysis 41. Third party risk Methodology developed by the National Air Traffic Services (NATS) for third-party risk 42,43 the NATS methodology has been extended to apply to multiple runways 49,50.
which the option evolves during the time horizon of the simulation. 3. 3. 3. Analysis of results Fig. 5 shows a performance envelope for five outcome indicators.
else it is coded as 1. Fig. 6 shows a classification tree that results from this analysis. The tree was generated using the open source data mining package Orange 47.
a further analysis was presented. These results could be used for further improving the adaptive plan. The third case illustrated how EMA can be combined with agent-based models.
Theoretically, the potential of EMA to FTA is its ability to cope with a multiplicity of deep and irreducible uncertainties in the analysis of decision-making problems
The effective analysis, visualization, and communication of EMA insights are thus of crucial importance for its successful real world application.
Res. 4 (1993) 435 449.13 D. B. Agusdinata, Exploratory Modeling and Analysis: A Promising Method to Deal with Deep uncertainty, in:
analysis of trade-offs in strategic planning: lessons from regional infrastructure foresight, Technol. Forecast. Soc. Chang. 76 (2009) 1150 1162.17 J. Kooroshy, C. Meindersma, R. Podkolinski, M. Rademaker, T. Sweijs, A. Diederen, M. Beerthuizen, S. de
and Hubbert peak analysis for predicting mineral resources depletion, Resour. Conserv. Recycl. 54 (2010) 1074 1083.21 W. Auping, The uncertain future of copper, in:
An Exploratory System Dynamics Model and Analysis of the Global Copper System in The next 40 Years, Delft University of Technology, Delft, 2011.22 J. H. Kwakkel, W
Vensim DSS Reference Supplement, Ventana Systems, Inc, 2010.30 D. N. Ford, A behavioral approach to feedback loop dominance analysis, Syst.
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