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ART76.pdf

Introduction Foresight and competitive intelligence (CI) are two fields that seek to address future-oriented environmental scanning (Calof and Smith, 2010.

Also, the rule of foresight has changed from the previous explorative forecasting to more be come more oriented to strategic planning (Martin, 1995.

or create PAGE 54 jforesight j VOL. 15 NO. 1 2013, pp. 54-73, Q Emerald Group Publishing Limited, ISSN 1463-6689 DOI

who contributed significantly to improving the quality of this paper. certain paths of development (Gavigan and Cahill, 1997;

Grupp and Linstone, 1999. Therefore, many countries not only use foresight as a tool to improve anticipatory intelligence but also use it as a priority-setting tool.

foresight results have been used for the implementation of policy measures (Aichholzer, 2001. Competitive intelligence is a systematic way to collect

and emphasizes the importance of a resource-based view of an organization (Powell and Bradford, 2000;

Barney, 1986; Grant, 1991; Markides and Williamson, 1994. According to the resource-based theory, competitive advantage occurs only when there is a situation of resource heterogeneity and resource immobility (Barney, 1991.

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.

Therefore, the ability to access new markets can only be prepared if knowledge about competitor's intention and capabilities can be monitored.

Without such knowledge the capacity to access existing and new markets and to identify and maintain the basis of competitive advantage will be limited (Powell and Bradford, 2000).

In addition to the resource-based theory, the modern emphasis is on network approaches to industrial strategy

and the need for partnering approaches to manage these networks of buyers, suppliers and peer companies, knowing the capabilities and intents of other organization for noncompetitive purposes.

Competitive intelligence is also important to retain a dynamic understanding of the technology trajectories of the surrounding industrial environment (Nelson, 1997.

Therefore, it is not possible generate a viable and appropriate technology strategy without a perception of the changing technical capability of our own industry and that of related industries (Powell and Bradford, 2000.

and popularized (Calof and Smith, 2010). In general, CTI is competitive intelligence within the R&d arena (Herring, 1993;

Ashton et al. 1994). ) It has been defined as:..business sensitive information on external scientific or technological threats, opportunities,

or developments that have the potential to affect a company's competitive situation. Ashton and Klavans (1997) also defined three basic objectives for CTI activities:

1. to provide early warning of external technical developments or company moves that represent potential business, threats or opportunities;

competitor profiling, early warning assessment, scientometrics, science mapping, scenarios, network analysis and so forth (Calof and Smith, 2010).

a combination of CTI and Strategic technology foresight (STF) was proposed recently by Calof and Smith (2010).

where the emphasis VOL. 15 NO. 1 2013 jforesight jpage 55 is not only on the technologies of the future

2006). ) In FISTERA, many national foresight exercise reports were scanned and important ISTS were listed and scouted. In Delphi Austria, an analysis of the Japanese, German, French, British Delphi studies was conducted to separate

and evaluate worldwide technology trends during the preparatory studies (Aichholzer, 2001). In addition, after the Delphi Austria foresight process, the results of the Austria Technology Delphi were reclassified also according to the standard classifications of industry

and policy makers and to propose an explanation of the old structures/high performance paradox (Tichy, 1999;

Orwat, 2003. Another famous example is the foresight activity mapping used by the European foresight monitoring Network (EFMN),

A specially designed taxonomy is used for mapping (Popper, 2009. The mapping dimension of EFMN, especially for the science and technology field

and niches within technology trends where Austria might find opportunities to achieve leadership within the next 15 years (Aichholzer, 2001).

and interactions. 2. Methodological approach 2. 1 Delphi method background Delphi was developed in the 1950s by the US RAND Corporation

Delphi is a subjective-intuitive research method that aims at a consensus PAGE 56 jforesight jvol. 15 NO. 1 2013 on a particular topic among a group of experts,

1970). ) Previous publications have proved that the technique is established an method for foresight activities and that Delphi outperforms other group formats such as statistical groups or standard interacting groups in terms of effectiveness (Rowe and Wright, 1999).

It is assumed commonly that the method makes better use of group interaction (Rowe et al. 1991), whereby the questionnaire is the medium of interaction (Martino, 1983.

The Delphi method is especially useful for long-range forecasting (2030 years), as expert opinions are the only source of information available.

Meanwhile, the communication effect of Delphi studies and the value of the process are acknowledged also. 2. 2 Basic information for the scanned Delphi topics The Delphi topics used for sustainable energy are chosen from foresight reports from Japan, South korea and China.

& future technology of Korea-challenges and opportunities (Korea 2030) China's Report of Technology foresight 2004 Report year 2005 2005 2004 Project promoter/initiator Ministry of Education

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

NO 1 2013 jforesight jpage 57 intellectual property (IP) system that rewards creativity, stimulates innovation

and a new version of the IPC is published regularly by the WIPO (World Intellectual Property Organization, 2011).

and therefore the classification of patents is based on technologies or products that use specific technologies (Schmoch, 2008).

There is long history in economics of the use of patent data to understand the process of invention and innovation (Griliches, 1990;

Also, patent documents are used widely as a source for technology forecasting, CTI and for analysis of technology convergence (Kayal, 1999;

2010; Curran and Leker, 2011. Based on the IPC code given to each patent document, statistics regarding the code or advanced analysis can be done easily to compare development or the trajectory among different technology domains.

Therefore, the IPC code, as a classification system for the state-of-the-art technology, provides a route for linking mid-to long-term technology,

For example, the foresight activity of Japan has up to a 30-year time horizon, and hence the technology trends provided by the scanned Delphi survey will provide a long-term view

while patent analysis provides a more evidence-based view (Popper, 2008. 2. 3. 2 Overall procedures of the mapping.

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,

Schmoch (2008) VOL. 15 NO. 1 2013 jforesight jpage 59 code C08g covering‘‘polymer electrolyte''is identified,

Schmoch (2008) Figure 1 Example for Delphi topic mapping PAGE 60 jforesight jvol. 15 NO. 1 2013 3. Results, impacts and policy options

but the forecasting time horizon for the whole foresight activity was set at up to the year 2020, by

which technology that can be realized before the year 2020 is preselected. Therefore, Delphi topics with a realization time before the year 2020,

which is‘‘time of technological realization before 2020''for Japan, ‘‘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.

Twenty-six Delphi topics in Japan which counts for 74.3 percent of the total Delphi topics,

were regarded as having realization before the year 2020. The remaining six and three Delphi topics are regarded as having realization between the years 2021 and 2030 and after the year 2031, respectively.

In South korea's case, most of the Delphi topics were regarded by experts as having realization before the year 2020;

only one topic regarded as having realization between the years 2021 and 2030. In China, all the topics were regarded as having realization before the year 2020.

Table V summarizes the realization time distribution of Delphi topics in Japan, South korea and China. 3. 1 Mapping technology interactions in Delphi topics 3. 1. 1 Summary result of the mapping in three countries.

The mapping results are demonstrated using the 35 technology fields suggested by WIPO. The summary results of the mapping for technology interaction prospected by Japan,

South korea and China is shown in Figure 2. The y axis denotes the source technology and the x axis denotes the application technology.

energy) is a hot technology application before the year 2020, where the possible source technologies comprise technologies 7 (IT methods for management),

Technology 19 (Basic materials chemistry) is prospected also by these three countries as second hot application technology before the year 2020,

The third hot application technology before the year 2020 is technology 32 (Transport), and the possible Table V Realization time distribution of Delphi topic in Japan, South korea and China Before 2020 2021-2030 After 2031 Time horizon Topics Ratio (percent

) Topics Ratio (percent) Topics Ratio (percent) Japan 26 74.3 6 17.1 3 8. 6 South korea 75 98.7 1 1. 3

0 0 China 83 100 0 0 0 0 VOL. 15 NO. 1 2013 jforesight jpage 61 source technologies are derived from technologies 1

From the source technology side, technology 27 (Engines, pumps, turbines) is the hottest source technology for application to other technologies before 2020,

technology 15 (Biotechnology) to technology 1 Figure 2 Summary result of the mapping in three countries PAGE 62 jforesight jvol. 15 NO. 1 2013 (Electrical machinery

hybrid power system/vehicle use China Hybrid power system VOL. 15 NO. 1 2013 jforesight jpage 63 As shown in Figure 3, technology 1 (Electrical machinery, apparatus,

energy) is targeted the main application technology by other technologies before the year 2020. The source technologies comprise technologies 12 (Control), 15 (Biotechnology), 17 (Macromolecular chemistry, polymers), 19 (Basic materials chemistry), 20 (Materials, metallurgy), 24 (Environmental

the technology interactions of the Delphi topics before the year 2020 are much more divergent.

interactions across WIPO technologies for Delphi topics from Japan PAGE 64 jforesight jvol. 15 NO. 1 2013 (Civil engineering).

Figure 4 Technology interactions across WIPO technologies for Delphi topics from South korea VOL. 15 NO. 1 2013 jforesight jpage 65 engineering;

Therefore, the top 25 percent important Delphi topics before 2020 are selected according to the foresight result in each country,

jforesight jvol. 15 NO. 1 2013 energy. The important source technologies comprise technologies 15 (Biotechnology), 17 (Macromolecular chemistry, polymers), 19 (Basic materials chemistry), 24 (Environmental technology) and 35 (Civil engineering.

VOL. 15 NO. 1 2013 jforesight jpage 67 cells'',Solar and fuel cell power system in practical use,

and Figure 7 Technology interactions across WIPO technologies in top 25 percent important Delphi topics from South korea PAGE 68 jforesight jvol. 15 NO. 1 2013

technologies in top 25 percent important Delphi topics from China VOL. 15 NO. 1 2013 jforesight jpage 69 technology of solar cells,

this PAGE 70 jforesight jvol. 15 NO. 1 2013 kind of capability gap identification becomes easier.

in order to assign IPC codes to relevant records since January 2010 (Vivavip, 2010). In addition, since the IPC code provides a hierarchical framework for mapping future technology themes,

which can be accessed at http://nodexl. codeplex. com/References Aichholzer, G. 2001),‘Delphi Austria: an example of tailoring foresight to the needs of a small country'',available at:

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a survey'',Journal of Economic Literature, Vol. 28 No. 4, pp. 1661-707. Grupp, H. and Linstone, H. A. 1999),‘National technology foresight activities around the globe:

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Vivavip (2010),‘Inspec IPC codes have been added back to 1969'',Free Pint Limited, available at: http://web. vivavip. com/forum/Wire/read. php?

i 87550 World Intellectual Property Organization (2011),‘Preface to the International Patent Classification (IPC)''World Intellectual Property Organization, available at:

www. wipo. int/classifications/ipc/en/general/preface. html (accessed February 10, 2010. 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),

which is under the National Applied research Laboratories (NARL). Her research interests include foresight, technology roadmap, and patent analysis.

Hai-Chen Lin is the corresponding author and can be contacted at: hclin@stpi. narl. org. tw Dr Te-Yi Chan received BS, MS and Phd degrees in Computer Engineering from Chung Yuan Christian University

in 2000,2002 and 2007, respectively. He is now an Associate Researcher at Science and Technology policy Research and Information Center (STPI),

which is under the National Applied research Laboratories (NARL). He works on data processing and text mining, and adopts these mechanisms to conduct research into science and technology development trends.

Cheng-Hua Ien received A MS degree in Food Science and Technology from Taiwan University in 1983.

VOL. 15 NO. 1 2013 jforesight jpage 73 To purchase reprints of this article please e-mail:

ART77.pdf

Received 14 may 2011 Accepted 18 september 2012 Available online 28 november 2012 This paper reflects on the potential of future-oriented analysis (FTA) to address major change

and in tackling the so-called grand challenges. 2012 Elsevier Inc. All rights reserved. Keywords: FTA practices Fundamental change and transformations Grand challenges 1. Introduction Drawing upon a critical reflection on the selected papers for this special issue as well as on the discussions that took place at the fourth Seville International Conference on Future-oriented technology analysis,

Technological forecasting & Social Change 80 (2013) 379 385 Corresponding author at: Center for Strategic Studies andmanagement (CGEE), SCNQD 2, Bl.

/Technological forecasting & Social Change 80 (2013) 379 385 3. Combining quantitative and qualitative approaches FTA is an umbrella term to denote several decision-preparatory tools (technology foresight,

/Technological forecasting & Social Change 80 (2013) 379 385 are by nature complex and largely impervious to top-down rational planning approaches.

/Technological forecasting & Social Change 80 (2013) 379 385 In more detail, Haegeman et al. 4 depart from the methodological debate that has been a relevant element of the International Seville Conference series on Future-oriented technology analysis (FTA

) since its launch in 2004. They claim that current trends in FTA and the increasing policy demand for robust evidence for decision-making indicate that there may be a momentum for pushing FTA towards integrating qualitative (QL) and quantitative (QT) approaches,

/Technological forecasting & Social Change 80 (2013) 379 385 more experimental approaches to creating new solutions

/Technological forecasting & Social Change 80 (2013) 379 385 practice and assist in considering transformations that are going to take us closer to anticipating disruptive innovations and events.

Defending Against the Unknown, the Uncertain & the Unexpected, Presidents & Prime ministers, vol. 11, Issue 2, 2002, pp. 33 36,(Mar/Apr 2 D. Loveridge, O. Saritas

Manag. 24 (8)( 2012) 753 767.3 L. Georghiou, J. C. Harper, Rising to the challenges Reflections on Future-oriented technology analysis, Technol.

Chang. 80 (3)( 2013) 467 470 (this issue. 4 K. Haegeman, E. Marinelli, F. Scapolo, A. Ricci, A. Sokolov, Quantitative and qualitative approaches in Future-oriented technology analysis (FTA:

Chang. 80 (3)( 2013) 386 397 (this issue. 5 P. De Smedt, K. Borch, T. Fuller, Future scenarios to inspire innovation, Technol.

Chang. 80 (3)( 2013) 432 443 (this issue. 6 M. Weber, A. Havas, D. Schartinger, Exploring the Potential impact of FLA on National Innovation systems.

Chang. 80 (3)( 2013) 398 407 (this issue. 8 H. Ritteland, M. Weber, Dilemmas in a general theory of planning, Policy Sci. 4 (1973) 155 169.9 C. Cagnin, E. Amanatidou, M

Public policy 39 (2012) 140 152.10 M. Boden, C. Cagnin, V. Carabias, K. Haegeman, T. Konnola, Facing the Future:

Time for the EU to Meet Global Challenges, EUR 24364 EN, Publications Office of the European union, Luxembourg, 2010.

bhttp://ftp. jrc. es/EURDOC/JRC55981. pdf>,accessed Oct 2011. 11 C. Hamarat, J. H. Kwakkel, E. Pruyt, Adaptive Robust Design under deep uncertainty, Technol.

Chang. 80 (3)( 2013) 408 418 (this issue. 12 J. H. Kwakkel, E. Pruyt, Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty, Technol.

Chang. 80 (3)( 2013) 419 431 (this issue. 13 P. Shaper-Rinkel, The role of future-oriented technology analysis in the governance of emerging technologies:

Chang. 80 (3)( 2013) 444 452 (this issue. 14 E. Schirrmeister, P. Warnke, Envisioning structural transformation lessons from a foresight project on the future of innovation, Technol.

Chang. 80 (3)( 2013) 453 466 (this issue. Cristiano Cagnin (Phd) used to work as a scientific officer at JRC-IPTS

Attila Havas (Phd, 1997) is a Senior Research fellow at the Institute of Economics Research centre for Economic and Regional Studies, Hungarian Academy of Sciences (http://econ. core. hu/english/inst/havas. html),

In 1997 2000 he was the Programme Director of TEP, the Hungarian technology foresight programme. He has contributed to international research projects on STI policies, innovation,

/Technological forecasting & Social Change 80 (2013) 379 385

ART78.pdf

Quantitative and qualitative approaches in Future-oriented technology analysis (FTA: From combination to integration? Karel Haegeman a,, Elisabetta Marinelli b, Fabiana Scapolo c, Andrea Ricci d, Alexander Sokolov e a European commission, JRC-IPTS, Edificio Expo WTC, C/Inca

Received 14 may 2011 Received in revised form 9 july 2012 Accepted 3 september 2012 Available online 8 november 2012 The FTA COMMUNITY relies on a set of disciplines and methods,

and this paper summarises and furthers the discussion developed during the 2011 edition, building on the debates at the conference and between members of the conference Scientific Committee, to which the authors of this paper belong.

combining research and practice, to overcome such barriers. 2012 Elsevier Inc. All rights reserved. Keywords: Qualitative Quantitative Barriers Combination Integration FTA Epistemological divide 1. Introduction The methodological debate has been a relevant element of the International Seville Conference series on Future-oriented technology analysis (FTA

) since its first edition in 2004. For the 2011 edition, the Scientific Committee decided to focus specifically on the combination of quantitative and qualitative methodologies.

This article, drawing on a position paper written for the conference, reports and expands on the lessons learnt during the event.

& Social Change 80 (2013) 386 397 The views expressed are purely those of the authors

Nevertheless in the discussions at the 2011 FTA Conference some trends were identified suggesting that methodological combination may potentially become more common amongst FTA scholars and practitioners.

the 2011 FTA Scientific Committee argued that the exclusive use of qualitative methods can lead to partial views on possible futures,

/Technological forecasting & Social Change 80 (2013) 386 397 qualitative) as an imaginative projection of current knowledge in which formal methods and techniques play a subsidiary role (p. 753.

or for the identification of potential disruptive technologies 5 10 years ahead. Shibata et al. 33 distinguish between incremental

/Technological forecasting & Social Change 80 (2013) 386 397 identification of emerging clusters analysing citations and keywords for a particular technology field,

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

/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.

During the 2011 International Seville Conference on FTA, the use of images and visualisation techniques was suggested as a tool,

and sustainability 43 (See http://www. sitra. fi/en/articles/2012/strategic-design-finlandsneewapproach-problem-solving).

/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,

is therefore of the essence. 9 8 During the 2011 FTA Conference a lively discussion was devoted to the shift of FTA usage from exploring potential risks to inspiring sustainable innovation.

/Technological forecasting & Social Change 80 (2013) 386 397 Finally, in this debate, there is a tendency to equate qualitative with participatory.

/Technological forecasting & Social Change 80 (2013) 386 397 sciences, Cameron 71 developed the Five Ps Framework, 13 which provides a mixed-methods starter kit,

/Technological forecasting & Social Change 80 (2013) 386 397 reasonable representation of the systems being analysed, and that the intrinsic uncertainties associated with such representation are documented at best. 5. 2. 2. Lack of trust One aspect of trust is that it derives from perceived credibility,

The different and highly heterogeneous contributions to the 2011 International Seville Conference on Future-oriented technology analysis in this area share a common bottom line:

/Technological forecasting & Social Change 80 (2013) 386 397 identification of the features that may help the organisers of FTA projects in the selection of the most appropriate set of tools (characterising

and both the Scientific Committee and the participants of the 2011 Seville Conference on Future-oriented technology analysis for the fruitful discussions that helped shaping and refining it.

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Karel Haegeman is a scientific officer at JRC-IPTS (European commission. He has masters in business economics and in marketing,

/Technological forecasting & Social Change 80 (2013) 386 397 Fabiana Scapolo holds a Phd on foresight methodologies and practices from the Manchester University (UK).

and Innovative Approaches) and EFONET (Energy Foresight Network) and is rapporteur of the EC Working group Global Europe 2030 2050.

/Technological forecasting & Social Change 80 (2013) 386 397

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