Science and Public policy February 2010 0302-3427/10/010003-04 US$12. 00 Beech tree Publishing 2010 3 Science and Public policy, 37 (1 february 2010, pages
3 6 DOI: 10.3152/030234210x484766; http://www. ingentaconnect. com/content/beech/spp Introduction to a special section:
Impacts and implications of future-oriented technology analysis for policy and decision-making Karel Haegeman, Jennifer C Harper and Ron Johnston Experiences of recent years place a premium, for governments and individuals,
Professor Ron Johnston Phd, FTSE is the executive directto of the Australian Centre for Innovation Ltd (ACIIC.
and of the new roles for innovation in the global knowledge economy. Table 1. Future-oriented technology analysis methods (Scapolo and Porter, 2008) Families of methods Sample methods Creativity approaches Theory of Inventive Problem solving (TRIZ), future workshops, visioning Monitoring and intelligence
curve modelling, leading indicators, envelope curves, long wave models Expert opinion Survey, Delphi, focus groups, participatory approaches Modelling and simulation Innovations systems descriptions
Dedication to quality, insights, effective communications and innovation are also important. Translate and transfer FTA outputs into policy and decision outcomes.
The methodological framework proposed in this paper is relevant for the development of policies aiming to match technologgica innovations better to societal needs.
reseaarch development and innovation. Identify knowledge gaps (relevant for resolving future problems or for exploiting potential opportunities).
and Innovation that aims to promoot research and innovation of a high international standard for the benefit of Danish society, facilitating development in economic,
which is acknowledged in the research 2015 document (Daniis Ministry of Science, Technology and Innovation, 2008) that sets the stage for research prioritisation in Denmark for the coming four years in a clear relationnshi to the challenges facing
and to prepare the joint reseaarch innovation programmes and common policiie that will be required. Notes 1. See<http://www. eranet-forsociety. net/Forsociety/index. html,
Danish Ministry of Science, Technology and Innovation 2008. RESEARCH2015 A Basis for Prioritisation of strategic Reseaarch Available from<http://en. fi. dk/publications/publications-2008/research2015-a-basis-for-prioritisation-ofstrattegicres/research2015-net. pdf
Those lead to significant changes both in everyday life and business models under the combined influence of technological, organisational and behavioural innovations.
She is currently in charge of the SIMPHS project dealing with market and innovation dynamics around personal health systems.
and heterogeeneou it was necessary from the outset to focus on a sub-set of activities most likely to be impacted by ICT innovation
The first phase of our analysis gave us an understanndin of ways in which ICT innovations challeeng traditional value chain structures and business models,
This was done by reviewing emerging ICT innovations and identifying areas where these will have a significant effect on creative content.
Four future scenarios In developing the four scenarrio the workshop participants considered the impaac of ICT innovation, user behaviours and other factors on the transformation of the creative content industries.
They also include fostering innovation, for instance: supporting R&d for infrastructure; facilitating mobile content development; accelerating broadband penetration;
promoting further innovation-oriented public procureement and adopting further measures to encourage new entrants. Conclusion The methodological setup of the FTA described
and innovation in certain thematic areas was accepted also widely, even if the associated IPRS issues are still controversial.
and Innovation appoiinte following the Hampton Court Summit chaired by Eski Aho. EUR 22005. Luxembourg:
technology and innovation program development. Since founding the Office of Technology foresight at the National research council in 2002, he has led
technology and innovation priorities Creating a language and body of practice for thinking about the future A source of inspiration for policy system actors More comprehensive,
repositioning of old ones Establishment of communications structures between innovation actors Support the empowerment of (innovation and futures) systems actors Contribute towards the development of actor identities Foresight provides many opportunities for enhanced
and experiences Highlighting the need for systemic approaches to both policy making and innovation Stimulation of others to conduct their own foresight exercise after being inspired Accumulation of relevant experience in how to think about the future
innovations implemented and legislation adopted Table 3. Success factors influencing the political role of participatory technology assessment Societal Institutional Process properties Good timing
persistence and innovation, especially in communications; synchronization with the business agenda of the organization Critical success factors for government-led foresight Science and Public policy February 2010 36 Ireland, Japan, Finland and the UK;
In Ireland, Forfas1 sees itself as the national policy advisory board for enterprise, trade, science, technollog and innovation.
and a central innovation and futures committee of the parliameen chaired by the prime minister. Another difference was in the area of participants.
In all cases these successful functions were housed within a ministry responsible for innovation. In Ireland this was the Industry Ministry
which align with some of the areas where policy will be required,(e g. health technology, agricultural innovation,
Such shifts can result in new technological possibilitiies with potentially revolutionary impacts associated with changing innovation patterns, industry structurres and broader developments in society.
In this paper we reflect on the implications of this new innovation context for traditional product development processes.
there has been an explosion of nondisruuptiv innovations that are not always clearly different from other products on the market (De Marez and Verleye, 2004;
and society and the notion of user-driven innovattion We then explore the implications for traditional innovation and development processes.
) This theory of‘technological determinism'fits into the‘diffusion of innovations'framework (Rogers, 1995), which is dedicated to the adoption and diffusion of new technologies in society.
to the point where the adoptiio rate has become so high that the innovation can be considered successful (this is referred to as the‘critical mass')(Rogers, 1995).
interdisciplinary research on quality of experience (Qoe) and quality of service (Qos) in mobile media environments, evaluation of user-and futureorieente innovation techniques in the ICT domain,
The main contribution of this work involves the development of a‘segmentation forecastting tool for prior-to-launch prediction of adoption potentiial and the development of a blueprint for better introduction strategies for ICT innovations in today's volatile market environment.
User-driven innovation In this new context, the notion of user-led or userdriive innovation has assumed a prominent role.
As a result, userdriive innovation requires an interdisciplinary approach. Several approaches have been put forward for the collection of this type of knowledge.
Living labs are innovation environments that provide full-scale test-bed possibilities for inventing, prototyping, interaactiv testing and marketing of (new) mobile technology applications (Schumacher and Niitamo, 2008;
They can be seen as humancenntri systemic innovation instruments, encouragiin the interaction between all stakeholders in the innovation process and facilitating the involvement of users as co-creators (Ballon et al. 2007).
74), systemmi innovation instruments are intended: to provide platforms for learning and experimeenting facilitate the management of interfacces foster new alignment of elements
Furthermore, as userdriive innovation deals with those user insights (needs, expectations etc. that users cannot always easily articulate,
Microsoft, Concentra and i-City) and the IBBT, founded by the Flemish Government in 2004 to stimulate innovation in the ICT domain.
and companies to gain an insight into the main drivers and constraints in service innovation and into the conditions for meeting social and user requirements (Lievens and Pierson, 2006).
and included an assessment of possible strategies for service innovation. In this paper, we only focus on user
and find it difficult to empathize with other users'lifestyyles e g. a 25-year-old reflects only on his daily Innovation-development process Prior-to-launch Post-launch R&d Opportunity identification Concept design Concept development
and evaluation Innovation development and production Test market and piloting Launch Adoption diffusion User diffusion,
Clusters and single applications were ranked on the basis of the respondennts interest level (Table 4). The overall average interest ranking for all the clusters showed that the most important innovations in these mobile applicatiion are not the most high-tech ones
we reflected on the implications of this new innovation context for traditional development processes. It was mentioned that this predominant focus on the user led to an expannsio of the traditional range of user research instruument with methods and tools from other fields.
Given the implications of the notion of userdriive innovation and the traditional tension betwwee user-and technology-centred strategies,
the mantra that‘innovation should start with the user and end with the user'is pursued not always.
integration and harmonizaatio of these systematic innovation instruments is high on the agenda. But there is always room for improvement.
Fostering innovation in networked communications: test and experimentation platfoorm for broadband systems. In Designing for Networked Communications:
Innovation diffusion: The need for more accurate consumer insight. Illustration of the PSAP scale as a segmentation instrument.
A new approach for human centric regional innovation, J Schumacher and V-p Niitamo (eds. pp 1 14.
diffusions of innovations v social shaping of technology. In The Handbooo of New Media, L Lievrouw and S Livingstone (eds.
In The Internatiiona Handbook on Innovation, L V Shavinina (ed.),pp 1094 1100. Oxford, UK:
Diffusion of innovations (4th edn..New york: The Free Press. Rosted, J 2006. User-driven innovation: an introduction.
Journal of Creativity and Innovation Management, 16 (1), 35 45. Soldani, D 2006. Means and methods for collecting
Innovation and Market research. In The Internatioona Handbook on Innovation, L V Shavinina (ed.),pp 835 844.
Oxford, UK: Pergamon/Elsevier. Veryzer, R W and B Borja de Mozota 2005. The impact of userorieente design on new product development:
Democratizing Innovation. Cambridge, MA: MIT Press. Williams, R and D Edge 1996. The social shaping of Technology research Policy, 25 (6), 865 899.
and Innovation (CTI) on the innovation performance of the supported firms based on a matched-pairs analysis of 199 firms supported by the CTI in the period 2000 2002.
HE IMPACT OF THE INNOVATION promottio policy of the‘Commission of Technollog and Innovation'(CTI),
which is the most important government agency for the promotiio of innovation in Switzerland, was investigated in this study.
measurre through six innovation measures (e g. sales, share of innovative products), than‘structurally similar'firms without such activities.
Impact of technology policy on innovation by firms Science and Public policy February 2010 64 avoids the functional form restrictions implicit in running a regression of some type.
We collected innovation data for the promoted firms similla to those already existing for a sample of innovating firms of The swiss Innovation Survey 2002 (Arvanitis et al.
We tested the statistical signifiicanc of the difference of the means of six differeen innovation measures of the subsidized firms and the non-subsidized firms of the matched control group.
and carry out a statistical test on the difference of the differences of the means of the innovation variables of the subsidized firms and the matched nonsubsiidize firms.
For the period 2002 2004 we found that (with one exception), for all six innovation measures and for all four matching methods applied,
the innovation performmanc of CTI-subsidized firms was on average significantly higher than that of the non-subsidized firms in the matched control group.
the use of innovation data for the subsidized firms, collected by means of a survey;
public fiscal policies to support innovation Most OECD countries use large amounts of public funds to support activities that are intended to enhaanc innovation in the business sector.
These funds are used often to provide direct support for private sector research and innovation. A further way of supporting private investment in innovation is through tax incentives for R&d expenditures (see Jaumotte and Pain, 2005 for a survey of the main fiscal policies to support innovation.
The underlyyin justification for public policies to support innovaatio is provided by the economic argument that otherwise the private sector would invest less in innovaativ activities than is socially desirable.
Thus, public fiscal policies to support innovation are designed to alleviate particcula forms of market failure that would lead to under-investment.
and innovation in firms that would otherwise have difficulty funding themselves in the capital market.
He is head of the research section on innovation economics at the KOF. Dr Arvanitis holds a doctorate in economics from the University of Zurich and a doctorate in chemistry from the ETH Zurich.
He has published extensivvel on the economics of innovation, technology diffusion, determinants of the performance of firms,
Impact of technology policy on innovation by firms Science and Public policy February 2010 65 consensus not only among political actors but also among organizations representing business interests.
and innovation at firm level have been launched in recent years. CTI is the government agency through which public funds are poured into the business sector.
To the best of our knowledge, it is unique in Europe as a main promotional policy Impact of technology policy on innovation by firms Science and Public policy February 2010 66 either matching approaches (as in this paper) or selecctio
For one study the target variable is innovation expenditure. The Canadian study uses eight different outputorieente innovation measures as target variables.
Finallly in three studies some technology diffusion measure is chosen as the goal variable. Most studies Table 1. Summary of selected empirical studies Study/country Policy instrument being evaluated Number of firms Approach Impact on target variable Sakakibara (1997),
+for small firms no effect for large firms Czarnitzki and Fier (2002), Germany Public innovation subsidies in German service sector 210 Matched-pairs analysis (nearest
neighbour matching) Innovation expenditure: innovation expenditure/sales:++Almus and Czarnitzki (2003), Germany R&d subsidies to East german firms (1994,1996, 1999) 622 Matched-pairs analysis (calliper matching) R&d intensity:+
+Pointner and Rammer (2005), Austria Programme of promoting use of CIMT (Flexcim Programme, 1991 1996) 301 (a) Selection correction:
+-positive (negative) and statistically significant effect at 10%test level Impact of technology policy on innovation by firms Science and Public policy February 2010 67 find a positive policy effect but in some cases
additional information on the firms whose projeect were subsidized that was collected through a survey of the subsidized firms based on a shortenne version of the questionnaire used in The swiss Innovation Survey 2002;
and the data for firms that reported the introduction of innovations in the period 2000 2002 in The swiss Innovation Survey 2002.
A further 14 subsidized firms were identiffie among the participants of The swiss Innovation Survey 2002.
and reported the introduction of innovations in the period 2000 2002 built the pool of non-subsidized firms from
-and-a-half years until the end of the reference period to realize some impact of these projects on their innovation performmanc (e g. introduce new products);
one-and-ahaal years is an adequate time lag between R&d and realization of R&d outcomes for most industries and for incremental innovations.
whether or not they would have had enough time until the end of 2002 to realize any additional innovation gains. 53%of projects were finished by the middle of 2001,78%by the end of 2001.
%Impact of technology policy on innovation by firms Science and Public policy February 2010 68 significantly lower than the respective share of projeect of these scientific fields.
as measured by output innovation measures (e g. sales share of innovative products), than‘structural similaar firms without such activities.
In order to measure appropriately the influence of CTI subsidies on a firm's innovation performannc(‘treatment effect')4 we should be able to measure the performance difference of the two‘states'of a firm (subsidized by the CTI(‘treated')/non-subsidized by the CTI
CTI database, authors'calculations Impact of technology policy on innovation by firms Science and Public policy February 2010 69 firms which are subsidized not out
G g a-=0 N a Impact of technology policy on innovation by firms Science and Public policy February 2010 70 (6) where and is the kernel7 at the point In a fifth step,
We used six innovation variabble covering the output side of the innovation process: an ordinal measure of the technical importance of the introduced product and process innovations;
8 an ordinal measure of the economic importance of the introduced product and process innovations;
9 percentage reduction of average variable productiio costs due to process innovation; sales of new products new to the firm or to the market as a percentage of total sales;
sales of significantly improved or modified (alreead existing) products as a percentage of total sales;
in order to test the robustness of our results given that innovation is a latent phenomenon and every single indicator measures only partly aspects of this complex phenomenon.
Results of the matched-pairs analysis Comparison of the innovation performance of subsidized firms depending on the subsidy quotient Table 4 provides a qualitative summary of the resuult of the comparison of the innovation performannce as measured by six different
We calculated the differrenc of the means of the two categories of firms (subsidized, non-subsidized) for six innovation variables and four matching methods,
With one exception(‘importance of introduced innovations from an economic point of view';‘'‘nearest neighbour'method) we found that the subsidized firms showed a significantly higher 0 1(,)N N A b W i j C D)}
introduced innovations from a technical point of view*Yes Yes Yes Yes Importance of introduced innovations from an economic point of view*No Yes Yes Yes Percentage reduction of average variable production costs due to process innovation Yes Yes Yes Yes Sales of significantly improved
*Originally ordinal variable measured separately for product and process innovations on a five-point Likert scale (1=very small, 5=very high.
Mean values are used for product and process innovations. Statistical significance: 5%test level Impact of technology policy on innovation by firms Science and Public policy February 2010 71 innovation performance than non-subsidized firms (at the 5%test level.
Hence, these results seem to be quite robust across various methods and innovatiio indicators. Having controlled for the size and age of the firms, sector affiliation, region, export propensity,
The detailed results in terms of figures for each innovation measure and each method are found in Tables A3 A6 in the Appendix.
and non-subsidized firms (after matching) for subsidized firms with a subsidy quote>median than for subsidized firms with subsidy quotient<median‘Nearest neighbour'‘Calliper'‘Kernel'‘Local linear regression'Importance of introduced innovations
from a technical point of view*Yes Yes Yes Yes Importance of introduced innovations from an economic point of view*No No No No Percentage reduction of average variable production costs due to process innovation Yes Yes Yes Yes Sales of significantly improved
*Originally ordinal variable measured separately for product and process innovations on a five-point Likert scale (1=very small, 5=very high.
Mean values are used for product and process innovations. Statistical significance: 5%test level Impact of technology policy on innovation by firms Science and Public policy February 2010 72‘low-subsidy'firms from that of the respective groups of non-subsidized firms.
For five innovation indicators we found that the difference of the means of the‘high-subsidy
The larger the amount of the subsidy relative to a firm's own R&d investment, the stronger is the impulse for the innovation performannc of a firm.
For one innovation variable(‘importtanc of introduced innovations from an economic point of view')we could not find any significant effect,
meaning that relatively larger subsidies do not necessarily result in a stronger tendeenc by subsidized as compared to non-subsidized firms to introduce innovations that are economicaall important.
It appears that larger subsidies resuul in more technologically important innovations in subsidized firms than in non-subsidized firms.
according to our results the larger the subsidy (in relative terms), the larger the impact effect for a series of indicators that measure the economic success of innovation (sales shares of products with different grades of innovativeeness reduction
More detailed results in terms for figures for each innovation measure and each method can be found in Tables A7 A10 in the Appendix.
This could be shown by four different matching methods (with the exception of the nearest neighbour method for the indicator‘importance of introduced innovations from an economic point of view'.
Impact of technology policy on innovation by firms Science and Public policy February 2010 73 Appendix Table A1.
Italian (continued) Impact of technology policy on innovation by firms Science and Public policy February 2010 74appendix (continued) Table A3.
firms Difference in means of active firms/non-active firms (column 3 column 2) Means Statistical significance (test level 5%)Importance of introduced innovations from a technical
point of view*3. 34 (0. 03) 3. 44 (0. 05) 3. 75 (0. 06) 0. 31 (0. 08) Yes Importance of introduced innovations from an economic
variable production costs due to process innovation 4. 98 (0. 29) 3. 59 (0. 43) 8. 61 (1. 24) 5. 02 (1
*Originally ordinal variable measured separately for product and process innovations on a five-point Likert scale (1=very small,
5=very high) Mean values are used for product and process innovations Number of non-subsidized firms=996;
firms Difference of means of active firms/non-active firms (column 3 column 2) Means Statistical significance (test level 5%)Importance of introduced innovations from a technical
point of view*3. 34 (0. 03) 3. 36 (0. 02) 3. 75 (0. 06) 0. 39 (0. 06) Yes Importance of introduced innovations from an economic
variable production costs due to process innovation 33.73 (0. 84) 36.32 (0. 43) 48.36 (2. 39) 12.04 (2. 47) Yes Sales of significantly improved or
*See footnotes to Table A3 for key (continued) Impact of technology policy on innovation by firms Science and Public policy February 2010 75 Appendix (continued) Table A5.
firms Difference of means of active firms/non-active firms (column 3 column 2) Means Statistical significance (test level 5%)Importance of introduced innovations from a technical
point of view*3. 34 (0. 03) 3. 39 (0. 02) 3. 75 (0. 06) 0. 36 (0. 06) Yes Importance of introduced innovations from an economic
variable production costs due to process innovation 4. 98 (0. 29) 5. 85 (0. 11) 8. 61 (1. 24) 2. 76 (1
) Active firms Difference of means of active firms/non-active firms (column 3 column 2) Means Statistical significance (test level 5%)Importance of introduced innovations
from a technical point of view*3. 34 (0. 03) 3. 39 (0. 02) 3. 75 (0. 06) 0. 36 (0. 06) Yes Importance of introduced innovations
of average variable production costs due to process innovation 4 98 (0. 29) 5. 85 (0. 11) 8. 61 (1. 24) 2. 76
*See footnotes to Table A3 for key (continued) Impact of technology policy on innovation by firms Science and Public policy February 2010 76 Appendix (continued) Table A7.
test level 10%)Difference of the difference of the means (column 3-column 2) Importance of introduced innovations from a technical point of view*0. 42 Yes 0. 18 Yes Yes Importance of introduced innovations from an economic
point of view*0. 05 No 0. 03 No No Percentage reduction of average variable production costs due to process innovation 6. 80 Yes 3. 80 Yes Yes Sales of significantly improved
test level 10%)Difference of difference of means (column 3-column 2) Importance of introduced innovations from a technical point of view*0. 46 Yes 0. 33 Yes Yes Importance of introduced innovations from an economic
point of view*0. 13 No 0. 26 Yes No Percentage reduction of average variable production costs due to process innovation 4. 10 Yes 1. 90 Yes Yes Sales of significantly improved
*See footnotes to Table A3 for key (continued) Impact of technology policy on innovation by firms Science
test level 10%)Difference of the difference of means (column 3-column 2) Importance of introduced innovations from a technical point of view*0. 39 Yes 0. 30 Yes Yes Importance of introduced innovations from an economic
point of view*0. 08 No 0. 24 No No Percentage reduction of average variable production costs due to process innovation 3. 60 Yes 1. 70 Yes Yes Sales of significantly improved
test level 10%)Difference of difference of means (column 3-column 2) Importance of introduced innovations from a technical point of view*0. 40 Yes 0. 31 Yes Yes Importance of introduced innovations from an economic
point of view*0. 09 No 0. 24 No No Percentage reduction of average variable production costs due to process innovation 3. 80 Yes 1. 90 Yes Yes Sales of significantly improved
*See footnotes to Table A3 for key Impact of technology policy on innovation by firms Science
The ordinal variable was measured originally separately for product and process innovations on a five-point Likert scale (1=very small, 5=very high;
and process innovations. 9. See Note 8. 10. There is some measurement error in this calculation due to the time incongruence between subsidies granted before the beginning of 2000
Economics of Innovation and New technology, 9 (2), 111 148. Caliendo, M and R Huber 2005.
Do innovation subsidies crowd out private investment? Evidence from the German service sector, ZEW Discussion paper No. 02-04, Mannheim, Germany:
Switzerland 2007 2008 European trend chart on innovation. Brussels: European commission. Feller, I 2007. Mapping the frontiers of evaluation of public-sector R&d programmes.
An overview of public policies to support innovation, OECD Economics department Working papers No. 456. Paris: OECD. Klette, T J, J Moen,
In Policy Evaluation in Innovation and Technology Towards Best Practices, pp 225 253. OECD: Paris. Silverman, R 1986.
*Ron Johnston2 and Fabiana Scapolo3 1mark Boden, European commission Joint research Centre, Institute for Prospective Technological Studies, Seville, Spain 2professor Ron Johnston, Australian Centre for Innovation
and the issues it brings to prominence need to catalyse major innovation in organisations and governance.
what is the possibility and role of innovation, and what are the key policy messages.
and a planning approach that attempts to identify innovation application points. These features impact directly on the client's perceived ability and engagement.
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