and became the subject of global discussion among NGOS 54 and reinsurance companies 55. These interventions can be characterized as uninvited participation 56
For decades the dominant definition of innovation as new products and processes that are introduced to the market combined with the common understanding of companies as the main actors in this process was questioned hardly ever.
At the same time more and more companies look into diverse databases and use crowd sourcing to foster their innovation, to get inspiration and to benchmark creative dynamic in their sectors.
Denmark Visioning session among CIVISTIA consortium in Copenhagen 2. Automatising innovation Patrick Corsi Consultant, Belgium Four interviews with key companies (IBM, EPFL, INSEAT, ISTIA
Innovation Leadership Forum, UK (Russia) Three seminars in the framework of international conferences with researchers and company representatives in Nürnberg, London and Exeter) 4. City-driven systemic
and companies involved with city level innovation in Paris 5. Innocamp Society Dominik Wind Until we see new land (Innovation camp Start-up),
Company profit as the main driver of innovation activity is being complemented. Solving social problems become an important driving force to innovate for both companies and individuals.
In addition, individual persons are motivated to contribute to innovation activities (such as crowdsourcing initiatives or idea competitions) for their pleasure.
Participants heard about the evolving technology strategy of one of Europe's leading companies. Since the 1990s Nokia would have been on any list of European industrial success stories as it rose to global leadership in themobile telephony sector.
the company now best illustrates the fragility of success when fast moving technological and social changes can expose wrong bets made both on platform technologies
what companies should do. The result of this has been a portfolio which has consisted of three main elements.
the former largely restricted to collaborative grants under the argument that firms needed an incentive to work together on pre-competitive activities,
The third strand, focused almost exclusively on small and medium-sized firms, seeking to build their capabilities and offering some limited resources.
For example, one LME aspect is that major Danish firms finance a large part of their research and development themselves.
An even more important LME aspect is that Danish firms and public institutions have substantial freedom to hire
often shift employment from one company to another or from a public institution to a private firm.
and individuals across company levels and private/public sectors. However, Denmark retains also many features of the CME-type.
and companies in Denmark support the initiation of participatory consensus approaches 2. 4. National styles in foresight and foresight methods In a recent paper,
and private companies. Furthermore, ministries contributed 90 proposals 33. The evaluation found that 64%of all proposals came from the public research and education sector,
policy makers and companies. The devised Joint Vision and roadmaps, which include the milestones of innovation activities identified,
152.18 G. Reger, Technology foresight in companies: from an indicator to a network and process perspective, Technology analysis and Strategic management 13 (4)( 2001) 533 553.19 F. J. Contractor, P. Lorange (Eds.
Cooperative Strategies in International Business Joint ventures and Technology Partnerships Between Firms, 2nd ed.,Pergamon, Amsterdam, 2002.20 C a. Bartlett, S. Ghoshal, Managing Across Borders the Transnational
and enabling of interactions with companies in creating and sustaining an innovation chain. The paper informs on the outcomes of a project on the simulation of alignment tools to allow the creation of innovation chains in the field of micro and nanotechnology.
By means of‘scripts'and‘intended uses'which are built in by firms and developers in advance the possible representations of users, their mind-sets and roles as e g.,
Although firms and development teams usually have certain assumptions and develop visions of the future,
and digital TV providers, representatives from digital TV hardware companies and independent digital TV consultants.
Among the experts were people representing stakeholders from different perspectives (from a commercial broadcaster, regulatory institute, large multimedia retailing company, online social platform, university and big telecommunication player in Flanders.
and must be the core element of the company's culture 9 and adjustment of organisational strategy elements 6,
7. Furthermore there is evidence that firms'efforts are concentrated currently on activities targeted at strategy design,
Performance measurement systems FTA Strategy Implementation A b s T R A c T Despite the growing number of publications on firms'performance measurement systems (PMS), consensus
we argue that embedding FTA in the system would enable firms to steer solutions to possible challenges through joint-up decision making and implementation processes.
which is developed often poorly by firms 12, 25,29 31. The third phase takes place through six steps:
Rather than reducing the uncertainty firms and their stakeholders in the value chain confront, both individually and together,
embedding FTA within the proposed system would enable firms to steer solutions to possible challenges through joint-up decision making and implementation processes.
Finally, embedding FTA within the system proposed shall enable firms to steer solutions to possible challenges through joint-up decision making and implementation processes.
and Performance Measurements to Chart Your Company's Future, American Management Association, New york, 1993.22 U s. Bititci, A s. Carrie, L. Mcdevitt, Integrated performance measurement systems:
, Ernst-Reuter-Platz 7, 10587 Berlin, Germany 1. Introduction Both innovation and futures research have been identified as being crucial for the success of companies.
by Cooper 1, Tidd 2) and the use of futures research within individual companies has been studied on various occasions.
and how corporate foresight affects companies'innovative capabilities 5. In 2003, Chesbrough coined the term‘Open innovation'to describe the paradigm‘‘that firms can
and should use external ideas as well as internal ideas, and internal and external paths to market,
as firms look to advance their technology''6. Since Futures 59 (2014) 62 78 A r T I C L E I N F O Article history:
Indeed, empirical research shows that more and more companies have opened up their innovation processes and started to cooperate with others with regard to innovation 12.
Within each of these generations companies aimed to overcome disadvantages of the previous one to improve internal innovation processes
This initially analyzed the‘‘ability of firms to recognize the value of new information assimilate it and apply it to commercial ends''26.
which firms acquire, assimilate, transforms and exploit knowledge to produce a dynamic organizational capability''27.
Thus, firms need to have innovative capabilities and instruments to renew their strategic resources in order to maintain a competitive advantage 30.
and reasoning of companies to open up their innovation processes. The primary goal is to create or sustain a competitive advantage, i e.,
Thus, it supports companies'efforts to sense change and adapt or renew accordingly. In this context, the application of futures research methods can serve various goals such as testing strategies,
fast technological change and innovation speed to corporate foresight through the necessity of companies to renew their strategic resources as a result of these factors.
one of the previously listed three roles that corporate foresight should play within a company.
and as inside-out and outside-in processes (see 40 for three open innovation process archetypes) where external knowledge is brought into the company
in order to bring new experiences and external knowledge into the company. Among other things it led to the insight that significantly different characteristics are attributed to the brand than expected.
and led to strategic changes within the company. Thus, the project filled the third key role of foresight as described above
To coordinate and organize the PPP, a German company with limited liability (German: Gmbh) was selected as the legal form for the organization.
Each KIC had to bring together three independent partners from at least three different EU member states, with at least one partner from higher education and one private company 53.
and the internal ambitions of multiple companies resulted in the shared vision of an integrated organization designed to drive innovation in ICT that would benefit from the different yet complementary assets and resources of industrial and academic partners.
and private companies turned out to be difficult. This was credited mostly to differences in opinion and expectations.
whereas companies were interested more in exploiting and diffusing innovations to a broader market. Also Rijkswaterstaat was interested primarily in innovations that addressed societal challenges
while companies inherently seek to satisfy shareholders, thus predominantly aiming for business performance. Table 5 Networked foresight activities in the EIT ICT Labs. No.
or a real-as-life setting Projects 3. 3 Testbeds and simulation tools Integrates hardware and software platforms and simulation tools across companies in order to test applications,
Therefore, it applies instruments to utilize the need of companies to innovate collaboratively on the one side
technology commercialization in large firms: results of a quantitative benchmarking study, R&d Management 37 (2007) 383 397.5 R. Rohrbeck, H. Gemu nden, Corporate foresight:
De Moor et al. develop a novel approach for incorpooratin more user-driven innovation strategies in companies'product development processes using‘living lab'research.
2010 13 public, companies, researchers, universities and organisaations Preselection of prioritised themes took place within an expert group that delivered input for a workshop with a user panel
we completed our understanndin with an assessment of the European positiio both in qualitative and quantitative terms, based on the analysis of company documents, business and policy reports.
In this context, customer expectations need to be managed carefully for a company to remain successful and building trust and awareness are part Adaptive foresight in the creative content industries Science and Public policy February 2010 24 of the equation.
and companies should not lose sight of this when defining their strategies and business models. The above technology and social/societal trends and the way they interact with one another provide intereestin insights for market players devising business plans
company customer interactions shift towards more interconnected and less predictable behaviours; influence of user demographics (e g. age and gender) on use patterns;
a closed and regulated market which is dominated by a few globally actiiv companies. Open innovation society: a situation where all Figure 4. Positioning of the four scenarios Competitive business environment Oligopolistic business environment Negative public attitude towards creative content, lack of demand Positive public
When New technologies Cause Great Firms to Fail. Boston, MA: Harvard Business school Press. Eriksson, E A and K M Weber 2008:
advanced technollog firms or private sector advisors connected in some way to the national policy agenda and/or senior decision-makers.
from the traditional push towards more user-driven innovation strategies in the information and communications technologies domain has urged companies to place the user at the core of their innovation process in a more systematic way.
companies that aim to occupy or sustain a leading market position in the ICT industry have increasinngl been forced into accelerated product developmeen
and a consortium of companies (I-City, Microsoft and Concentra). This paper is revised a version of a paper presented at the Third International Seville Seminar on Future-oriented technology analysis:
The new context has urged companies to put user needs at the core of their innovation strategies in a more systematic and structured way.
and is considered to be influenced by‘change agents'(e g. private firms, influential individuals etc.).In the theory of diffusionism, the first group of people who adopt the new technology (innovators
Severra scholars have focused on the fact that there are still only a few companies that effectively involve the customer or user in the innovation process (Alam, 2002;
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 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.
CTI's promotional activities significantly improved the innovation performance of the firms that they supported with respect to six different measures of innovation performance.
than‘structurally similar'firms without such activities. To show this, we used matched-pairs analysis for a set of firms supported by CTI
and the corresponding control groups for the period 2002 2004. Matching methods based on direct comparisons of participating
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 identified the subsidized firms in the period 2000 2002 from the CTI database. 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.
2004). ) We estimated the propensity scores with respect to the likelihood of receiving a CTI subsidy. We then applied four different matching methods
in order to find the structurally similar‘twin'firms for every subsidized firm. 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.
We constructed a subsidy quotient: the amount of R&d promotion divided by the R&d budget of the firm in the same period.
We were able to distinguish between firms with a high (higher than the median) and a low subsidy quotient (lower than the median),
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.
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;
Fifthly, we provide a detailed discusssio of our methodology for estimating the impaac of CTI subsidies on the innovation performance of firms.
For example, programmes offeriin financial support for small or young firms are intennde to stimulate additional R&d
He has published extensivvel on the economics of innovation, technology diffusion, determinants of the performance of firms,
He teaches and researrche on statistics and econometrics, especially on measures of economic inequality, the construction and maintenance of panels 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.
2007), less than 10%of Swiss firms perceive a lack of public R&d promotion to be a strong,
i e. estimations of the impact of policy, proceed by means of an ex post assessment of the activities of the firms that have received subsidies.
Such evaluatiion can be subject to selection-bias problems becaaus subsidized firms are not a random group.
In this study we apply matching methods to evaluate the impact of R&d subsidies on the innovatiio performance of subsidized firms.
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
Most studies use contemporraneou data on the states of subsidized and non-subsidized firms (as in this paper.
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 firms with less than 200 employees+for firms adopting CIMT for first time Donzé (2002), Switzerland Programme of promoting use of CIMT (CIM Programme, 1990 1996) 463 Matched-pair analysis (several alternative methods) Change in CIMT intensity (1990 1996):+
+for firms with less than 200 employees+for firms adopting CIMT for first time Lach (2002), Israel R&d grants from Office of Chief Scientist at Ministry of Industry and Trade (1990 1995) 325 Difference
+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
+Almus and Czarnitzki (2003), Germany R&d subsidies to East german firms (1994,1996, 1999) 622 Matched-pairs analysis (calliper matching) R&d intensity:+
+for firms with less than 200 employees+for firms with low intensity of CIMT use Görg andstrobl (2007), Ireland R&d grants from (Industrial Development Agency (IDA) Ireland and Forbairt
small domestic firms:++medium domestic firms: no effect; large domestic effects: -all size classes of foreign firms:
no effect Bérubé and Mohnen (2007), Canada R&d tax credits versus R&d tax credits+R&d grants 584 Matched-pairs analysis (nearest neighbour matching) Firms with tax credits
+R&d grants are more innovative than firms with only tax credits for 6 out of 8 innovation indicators Notes:+(
+-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
only for small firms. The USA study is the only one, which finds a negative effect for R&d spending,
meaning that subsidies were crowding out private R&d spending. Although all the studies in Table 1 refer to the firm as the analytical entity,
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;
These firms made up our sample of subsidized firms. Start-ups, nonprofit organizations and mergers were excluded from this sample becaaus their specific characteristics could be not identiffie in our pool of control firms.
Further firms that had ceased to exist by December 2003 were also remoove from the sample. The final sample contained 307 subsidized firms.
These firms received a shortenne version of the questionnaire of The swiss Innovattio Survey 2002.3 185 firms completed the questionnaire (see Table A1 in the Appendix to this paper for information on the response rates by scientiifi field.
A further 14 subsidized firms were identiffie among the participants of The swiss Innovation Survey 2002.
Hence, the sample we used for the study contained data on 199 firms (64.8%of the subsidized firms.
Additional information on the determiinant of the propensity scores (see section on Method) was collected through a telephone survey of the 122 subsidized firms that did not complete the postal survey.
This additional information allowed us to estimate the propensity scores based on data for all 307 subsidized firms.
The 996 firms that participated in The swiss Innovattio Survey 2002 and reported the introduction of innovations in the period 2000 2002 built the pool of non-subsidized firms from
which a control group was constructed (KOF panel database). For the firms that finished their projects subsidiize by the CTI during the first half of the period 2000 2002,
i e. until the middle of 2001, we reckon that they would still have had one -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.
For the firms that compleete their subsidized R&d during the second half of the reference period, particularly in the year 2002, it is questionable,
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.
For the remaining 28%of the firms it is possible that only part of the impact could be realized before the end of 2002.
This means that including the firms'contribution of at least the same amount as the CTI subsidy, about CHF400,
Table 3 shows the distribution of subsidies among firms by scientific field. Enterprises with more than one project were classified by the scientific field of the project with the highest subsidy.
The share of firms with projects in machinery, apparatus construuctio and information technology is about 22,
%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.
material sciences are represented better among firms (about 24%)than among projects (about 12%.%The subsidized firms are characterized further by the industry affiliation and the number of employees in full-time equivalents (firm size.
52%of promoote firms belonged to mechanical and electrical machinery, electronics and instruments. This was the dominant group among subsidized firms in accordaanc with the importance of these capital goods industtrie for Swiss manufacturing with respect to generated value added,
employment and innovativeneess even if it is represented rather over. Chemical and pharmaceutical firms, which are on average the most innovative Swiss firms,
are quite underrepreesente among the subsidized firms (4%),reflecctin the strong tendency of this branch of aboveaveerag investment in R&d.
With the exception of wholesale trade the service sector is represented in the sample of the subsidized firms only by business services (computer services
engineering, business consulting, etc. about 21%.%Small firms with up to 50 employees have a share of about 55%,firms with more than 200 employees a share of only about 25%,firms with more than 500 employees a share of about 10%.
%Both the distribution among industries and among firm size classes seem to be in accordance with the policy pursued by the CTI of promoting mainly small-and medium-sized enterprises in all sections of the economy;
there is even a tendency to promote small-rather than medium-sized firms. Method Our main hypothesis is that the CTI support,
particulaarl through co-financed research projects in cooperratio with universities, would show on average a significantly higher innovation performance,
as measured by output innovation measures (e g. sales share of innovative products), than‘structural similaar firms without such activities.
We used several matching methods to demonstrate this. 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
X. Thus, besiide the group of firms, which are subsidized by CTI in a certain time period,
CTI database, authors'calculations Table 3. Subsidized enterprises by scientific field 2000 2002 Scientific field Number of firms Percentage Construction technology 11 5. 5
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
of which‘structurrall similar'firms are selected according to a‘proximity'criterion (control group). The comparisso of the two states for subsidized
and nonsubsiidize firms is performed by comparing the means of the innovation performance variables for the‘treated'firms
and the‘twin'‘non-treated'firms matched to the‘treated'ones according to a proximity criterion.
1983) to a monodimennsiona (scalar) propensity score which comprehhend the entire information of all relevant characteristics. 5 The state of a firm belonging to the group of the‘treated'firms is described by d=1,
then the performance difference betwwee the two firms is defined as: Y=Y1i-Y0i (1) In a first step we estimated by a probit model the propensity scores P (X i e. we estimated the probabiilit of a firm having a research project subsidized by the CTI as a function of a vector X of firm characterristic As independent variables
In a second step all firms were distributed to adjusttmen cells according to the quintiles of the propennsit scores estimated by the equation in Table A2.
The search for a‘twin'firm is restricted then only to the firms of the same adjustment cell,
we used four different matching methods to identify the structurally similar firms out of the pool of the nontreeate firms.
and Pj are propensity scores for the firms i and j, respectively. The treated firm can have a higher
According to the third method, kernel matching, a weighted sum of all available control group firms inside an adjustment cell, not a single‘twin'firm as in the other two methods, is ascribed to every
The performance difference between the treated and the non-treated firms is defined now as:(4) where ij w is the weighting factor({}0 1;
This weight is high for small‘distances'betwwee a pair of firms, low for large‘distances'and also contains a linear term.
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,
the means of the variables measuring innovation performance of the group of the treated firms and the group of the‘twin'non-treated firms were compared.
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;
This subsidy quotient measured the relative magnitude of the subsiidy10 We divided the subsidized firms into two groups:
one group with firms with a subsidy quotient higher than the median(‘high-subsidy'firms) and a second one with firms with a subsidy quotient lower than the median(‘low-subsidy'firms.
Then, we calcullate the difference of the means between subsidiize and non-subsidized firms separately for the‘high-subsidy'and the‘low-subsidy'firms.
Hence,‘high-subsidy'firms would show a larger impact than the‘low-subsidy'ones. 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
indicators, of the subsidized and the non-subsidized firms for four different matching methods. We calculated the differrenc of the means of the two categories of firms (subsidized, non-subsidized) for six innovation variables and four matching methods,
i e. for 24 differren cases. 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)}
-=-2 0 0 ij ik k i k d ij j i ik k i k d A g G P P B G
4. Summary of results with respect to receiving a subsidy for various matching methods Variable Significantly higher means of subsidized than of nonsubsiidize firms (after matching) Nearest neighbour Calliper Kernel Local linear regression
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.
Having controlled for the size and age of the firms, sector affiliation, region, export propensity,
and the existence of continuous R&d activiitie in the propensities equation, these performannc differences have to be traced with good reason to the main difference between the two groups of firms,
Subsidized firms show a significanntl higher innovation performance than structuralll similar non-subsidized enterprises. The detailed results in terms of figures for each innovation measure and each method are found in Tables A3 A6 in the Appendix.
For example, coluum 1 in Table A3 shows the mean value (score) for every innovation indicator for all available non-subsidized firms before matching.
Column 2 presents the mean values for the matched non-subsidized firms, i e. those firms that were seleccte (out of the pool of non-subsidized firms) by the matching method used (in this case:‘
‘nearest neighbour'method) as‘similar'to the subsidized ones. The figures in the latter case are systematically larger than in the former case,
reflecting the fact that firms with a high innovation performance are seleccte by the applied method to match subsidized firms that are expected to be highly innovative in ordde to obtain grants.
Column 3 shows the corresponndin figures for the subsidized firms. Column 4 shows the difference between the mean values for the subsidized firms (column 3) and the mean values of the matched non-subsidized firms (column 2). Finally, column 5 presents the results
of tests of the statistical significance of the differences in column 4. These results show that there are substantial differeence in innovation performance.
A further interesting point, particularly for policy-makers, is subsidized that firms seem to be significantly more innovative especially in terms of new products than non-subsidized ones.
Comparison of the innovation performance of high subsidy'and‘low subsidy'firms Table 5 contains a qualitative summary of the resuult of the comparison of the differences of the innovation performance of high-subsidy
particularly for policy-makers, that subsidized firms seem to be significantly more innovative, especially in terms of new products,
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
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.
'and the non-subsidized firms is significantly higher (at the 10%level) for all four matching methods than the respective differeence for the‘low-subsidy'firms (i e. significanntl positive difference of the differences).
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.
This is understandable given that all subsidized collaborration are between firms and universities that provide cooperating firms with knowledge that is primarily of high technological value.
This does not mean that higher subsidies cannot generate (additioonal economic success: 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
For example, column 1 in Table A7 shows the differences betwwee subsidized firms with subsidy quotients smaller than the median and the corresponding matched non-subsidized firms.
Columns 3 and 4 show the differeence between subsidized firms with subsidy quotieent larger than the median, column 4 refers to the statistical significance of these differences.
the difference between subsidized and non-subsidized firms, for example, for the sales shares of products that are new worldwiid for firms with small subsidy quotient increases from 7. 10 percentage points to 12.60 percentage points
for firms with large subsidy quotients. The respecctiv increase for the sales shares of new producct
Conclusion Based on a matched-pairs analysis of 199 firms supporrte by the CTI in the period 2000 2002 and a control group of 996 firms that were supported not by the CTI,
we found that the CTI promotion significcantl improved the innovation performance of supported firms with respect to six different measurre of innovation performance.
Subsidized firms are mainly small-and medium-sized enterprises (perhaps too many micro-firms among them)
Further, subsidized firms represent a wide spectrum of manufacturing firms, the concentration on firms for machinery,
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.
Comparison of subsidized/non-subsidized enterprises, matched by‘nearest neighbour'method Measures of innovation performance All non-active firms before matching Non-active firms after matching (control group) Active
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
5=very high) Mean values are used for product and process innovations Number of non-subsidized firms=996;
number of subsidized firms=199 Standard errors are in brackets under the means Two-tailed t-test used for difference of means Table A4.
Comparison of subsidized/non-subsidized enterprises, matched by‘calliper'method Measures of innovation performance All non-active firms before matching Non-active firms after matching (control group 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
*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.
Comparison of subsidized/non-subsidized enterprises, matched by‘kernel'method Measures of innovation performance All non-active firms before matching Non-active firms after matching (control group) 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
Comparison of subsidized/non-subsidized enterprises, matched by‘local linear regression'method Measures of innovation performance All non-active firms before matching Non-active firms after matching (control group
) 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
*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.
Results with respect to magnitude of subsidy quotient for 2000 2002, calculated using‘nearest neighbour'method Measures of innovation performance Subsidized firms:
subsidy quotient>median Subsidized firms: subsidy quotient<median Difference of means of subsidized/nonsubsiidize firms Statist. signif.
test level 10%)Difference of means of subsidized/nonsubsiidize firms Statist. signif. 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
Results with respect to magnitude of subsidy quotient (2000 2002) using‘calliper'method Measures of innovation performance Subsidized firms:
subsidy quotient>median Subsidized firms: subsidy quotient<median Difference of means of subsidized/nonsubsiidize firms Statist. signif.
test level 10%)Difference of means of subsidized/nonsubsiidize firms Statist. signif. 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
Appendix (continued) Table A. 9. Results with respect to magnitude of subsidy quotient (2000 2002) using‘kernel'method Measures of innovation performance Subsidized firms:
subsidy quotient>median Subsidized firms: subsidy quotient<median Difference of means of subsidized/nonsubsiidize firms Statist. signif.
test level 10%)Difference of means of subsidized/nonsubsiidize firms Statist. signif. 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
Results with respect to magnitude of subsidy quotient (2000 2002) using‘local linear regression'method Measures of innovation performance Subsidized firms:
subsidy quotient>median Subsidized firms: subsidy quotient<median Difference of means of subsidized/nonsubsiidize firms Statist. signif.
test level 10%)Difference of means of subsidized/nonsubsiidize firms Statist. signif. 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
It is used here analogously for firms subsidized by the CTI. 5. See Heckman et al. 1999) for a survey on various matching procedures.
an=2. 7768 (H/1. 34) N-1/5 where N is the number of observations of the control group or the group of treated firms,
In order to minimize the influence of this error we distinguish only two‘crude'groups of subsidized firms.
The effects of public R&d subsiddie on firms'innovation activities: the case of Eastern Germaany Journal of Business and Economic Statistics, 21 (2), 226 236.
Matched-pair analysis based on business survey data to evaluate the policy of supporting the adoption of advannce manufacturing technologies by Swiss firms, KOF Working Paper No. 65, July 2002.
Government R&d funding and Company Behavioour Measuring Behavioural Additionality. OECD: Paris. OECD 2006b. OECD Reviews of Innovation policy:
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