The overall objective of this study is to understand the interface between research, technological advancement and innovation, especially as it relates to the collaborative projects funded by the European Framework Programmes for RTD.
This overall objective will be studied along the following two broad lines:
For this purpose, this study will:
The methodological approach to assessing the impact on innovation of RTD activities developed within EU Framework Programmes is based on a matrix-shaped model, which is characterised by a main workflow sequence from data sources and data collection to respond to the assessment tasks and to provide concrete evidence, also based on case studies, to lead to policy recommendations.
The methodological approach is based on:
1) the identification of the types of data which can help identifying the relationships between RTD and innovation;
2) the identification of the data sources of these data, considering
a. the micro (firm) level, the meso (sector) level and the macro (geographical) level. These data sources are EU/FP-related and EU/FP-independent;
b. the more general statistical and economic data related to innovation and competitiveness;
c. consolidated innovation-related indicators
3) the planning and execution of a survey aimed at firms involved in RTD and innovating, to work out microeconomic indicators but also organisational and behavioural patterns;
4) A micro-meso impact assessment analysis, aiming at elaborating the RTD-innovation relationship at
c. Geographical level
5) The construction of economic impact indicators of RTD-related innovation at the three mentioned levels (company, secotor and geographical level);
6) The economic impact evaluation if RTD-related innovation;
7) The benchmarking of the economic impact of innovation against general (meso and macro-)economic indicators;
8) The development of case-studies and use cases for the concrete application of the study principles, and
9) The elaboration of policy recommendations.
The analytical questions suggested by the partners closely reflect the overall objective of the study (see Annex). They deal with the microeconomic factors that affect the likelihood that research will lead to innovation (the introduction of a new/improved product, service, or production process). Microeconomic factors include the set of managerial, organizational, market, technology, and industry characteristics that are pertinent to innovation.
The objectives of the study as summarized in the previous section will translate into four lines of inquiry outlined below. The lines of inquiry correspond to the characteristics of the organization, the characteristics of the project, other micro-economic determinants, and lessons. Each is broken up into specific analytical questions.
The first line of inquiry looks at three very important questions: who participates, why, and how do they think about the FP projects in the overall scheme of things.Ø Q1: Which organizations have participated in the FP and how can they be differentiated from those that have not participated, including both those who tried and failed and those who have never tried? Ø Q2: Why did these organizations take part in the FP and what benefits did they actually receive from their participation? Ø Q3: What role do the FP projects play in the overall innovation strategy of the organization? How do companies manage their RTD portfolios inclusive of FP projects?
First, a picture of the ‘demographics’ of the organizations involved in the FP projects is needed [in terms of type (firms, research institutes, universities, etc), geographical location, age, size, sectoral position, market share, etc.]. The composition will be a factor in explaining the innovation output of the FPs.
With respect to this question, it is especially important that control group approaches complement the survey: the characteristics of successfully participating organizations have to be compared to those that have tried unsuccessfully, and those that never have tried. It will be only against this background that one would be able to distinguish between. Here, other data sources that CORDIS will have to be used as well.
Dimensions of the ‘characteristics of a company’ include general structural characteristics (size, sector, etc), but also the ‘technological orientation’ and the ‘orientation towards innovation’ (which could be identified e.g. by looking at the motivation’ of enterprises to participate.
The identification of ‘motivation’ of firms is very pertinent here. This concerns both (i) the motivation to participate in the FP, as well as (ii) the expectations vis a vis the outcome of the project (especially in terms of innovation output). We should also be able to juxtapose the ex-ante-expectations (motivations) and the results (or expected results) after completion of the projects. An important question would be in how far the ex-ante-motivation influences the translation of project results into product / process innovation.
The second line of inquiry focuses on the collaborative RTD projects and the ways they are managed for more effective innovation.Ø Q4: What kinds of projects did the participating organizations undertake in the FP and how do these projects compare, or relate to, others that they undertook either independently or in collaboration with others but with no subsidy?
Ø Q5: Management practice for collaborative RTD projects at all stages (design, application, implementation, post-project monitoring and exploitation of results)
Ø Q6: How do project-level characteristics, including consortium characteristics, type of prime contractor, managerial practice, and project-team dynamics affect the chances for research success and the chances of research result uptake for innovation and commercialization?Though the projects in the FP are all supposed to be pre-competitive, collaborative R&D projects, they are likely to differ with respect to their role within the portfolio of projects of the participant. This portfolio can be characterized along a number of dimensions (strategic importance, time horizon, scientific, technological and commercial and risk, etc.). We will have to identify the distribution of the projects along these dimensions and relate their position to the likelihood of and impact on innovation.Both structural characteristics of the projects (size, number of participants, duration etc.) as well as characteristics of their management practices are likely to have a bearing on their innovation output. It will be essential here to draw a picture on the structure of collaboration against the background of a general typology of the collaborative partners. Here, aspects like trust (have they [successfully] cooperated before?), managerial competence, and the ability to translate R&D outcomes into innovation are essential in combination. We will also have to relate the innovation success to specific dimension of the collaboration agreements (e.g. IPR, planning of follow-up etc)
The third line of inquiry concentrates on factors at the level of the organization and of the industry – including factors relating to the technological context as well as both the supply and the demand for innovative products and processes.
Ø Q7: How do firm-level characteristics including resources/capabilities, internal organization and management influence the likelihood of research result uptake for innovation and commercialization?
Ø Q8: How do industry and market characteristics affect the likelihood of research result uptake for innovation and commercialization?The analysis of micro-economic determinants of the impact of innovation would have to look into the technological and market context in which the participants aim to innovate and which might be more or less amenable to innovation, e.g. whether the markets are highly competitive or not, whether the position of the firm in the market is a dominant or a small one, what the specific market conditions in terms of regulation are. How far is the distance (‘time to market’) from an R&D project from market applications in the respective field of technology / in the respective market. These are factors which have to be controlled for when assessing the innovation performance of different projects.Micro-econometric methods linking the characteristics of individual participants, consortia and projects must be combined with meso-econometric analysis of the impact of market structure and characteristics of technology cycle in order to assess these impacts.
The fourth line of inquiry draws lessons for the improvement of innovation-related Programmes of the Community.
Ø Q9: What types of additionality with specific emphasis on innovation can be observed in FP5 and FP6? What can be done to improve additionality?
Ø Q10: What are the lessons for improving the RTD projects funded by the Community Research and Innovation Programmes (FP, CIP)?
 The propensity to innovate is, of course, significantly affected by many other factors that fall outside the realm of this study. Such factors reflect the prevailing macroeconomic environment (e.g., inflation, employment, interest rates, open economy issues), the specific time and regional context (e.g., war, specificity of factors of production), culture (e.g., risk taking behavior, work ethics, attitude to change), religion, etc. See Mokyr (1990) for an appraisal.