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Market, Firm, and Project-level Effects on the

Innovation Impact of FP R&D Projects

Costas Constantopoulos, Yiannis Spanos, Gregory Prastacos, Nicholas S. Vonortas

Abstract

This study considered specific market, firm, and project-level factors that exert

important influences on the success of R&D projects under the EU Framework

Programme. A quantitative analysis in a cross-European sample of collaborative R&D

projects, supported with relevant qualitative evidence, indicated that partnering firm

innovation experience, innovation protection mechanisms, effective management of

EU rules, and the existence of commercially driven projects that open up new

technological areas, were those factors with the strongest significant effect on project

success (i.e., product/process innovation, and technical knowledge creation). The

findings contribute to understanding of how and under what conditions collaborative

R&D projects result in innovation development and new knowledge creation.

Introduction

It is generally agreed that the EU Research Framework Programmes have played an

important role in developing the European knowledge base and that they have

demonstrated a significant level of additionality and European added value. Despite

that, however, the achievement of the Framework Programmes admittedly has been

more modest in terms of direct contribution to innovations. This is related to the so-

called “European Paradox”, a term connoting a strong research performance but

comparatively weak innovation and economic performance. Even though it should be

stressed from the outset that the production of specific commercialised innovations

has never been the core focus of the Framework Programmes, which has been the

strengthening of the European research system as a whole, the fact remains that a

closer connection between EU-funded R&D activity and commercialized innovation

needs to be set as a high priority if Europe is to achieve the Lisbon objectives (i.e.

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improvement of job & wealth creation; competitiveness; social cohesion & inclusion;

and environmental quality in the European Union).

Even though R&D is a core activity and a starting point (albeit not the only one) for

innovation, the link between the two is not straightforward. The commercial

exploitation of research results stemming from an R&D project is a complex process

governed by a multitude of factors, including the internal dynamics of the project per

se, as well as the motives and the innovation-related capabilities of the participants in

the project, and the characteristics of the market environment towards which the

prospective innovation is to be directed.

In this study, we seek to explore those complex links by examining the factors

underlying the success of collaborative Research & Development (R&D) projects

under the 5th and 6th Framework Programme for Research and Development.

Specifically, based on the extant literature (e.g., Doz, 1996; Gulati, 1998; Hagedoorn

et al., 2000; Hoegl et al, 2004), this study seeks to identify determinants of the

innovation impacts of publicly funded R&D projects along three broad directions,

namely market, firm, and project-related factors. The basic proposition we wish to

explore is that: (a) the ways a project is managed; (b) the resources, experience and

capabilities of partners; and (c) market conditions significantly affect the innovation

impacts of FP-funded R&D projects.

To explore and test this basic proposition we mainly utilize quantitative (i.e.,

questionnaire survey responses) collected on collaborative R&D behaviour and

outcomes via a massive data collection effort in a pan-European scale for the purposes

of the Innovation Impact project. In particular, the quantitative field survey consisted

of two separate questionnaires, one for industrial firms and one for research

organizations (i.e. universities, research institutes, etc) that were known (through the

CORDIS database) to have been involved in FP5 and FP6 R&D projects. Quantitative

evidence were further supported by a qualitative analysis (i.e., case studies), the

results of which will enrich the discussion and conclusions of the work at hand.

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The remainder of this paper is organized as follows. The next section presents the

basic concepts utilized and the research model of the study. An overview of the

determining conditions of R&D project success together with the basic theoretical

arguments is provided in the third section, followed by the presentation of the results

of the quantitative analysis. The last section presents a summary and conclusions.

Basic Concepts Defined

Innovation impacts: The concept of project success

Innovation impact as a general term is an admittedly broad and multidimensional

concept. It is therefore necessary to define specifically what is meant by this term in

the particular context of publicly funded R&D projects. For the present work, we

conceptualize innovation impact as comprising of the following two specific

dimensions: a) commercial exploitation outputs, which as the term implies represent

concrete commercialized results, such as a new product or a new technology as a final

product of the project; and b) technical knowledge creation. The former represent

immediate innovation outcomes of a project, and are the main dependent variables of

interest in this study. The latter refers to knowledge acquired by a participant through

the research activities in the project. This knowledge is reflected in such outcomes as

the development (or improvement) of tools and techniques, models and simulations,

or of prototypes, demonstrations and pilots. It is knowledge embodied in valuable

tangible results stemming from an R&D project, valuable in that, at least potentially,

they can be subsequently utilized and further developed into concrete product or

process technologies. More generally, this kind of knowledge is valuable in its own

right, even if it does not directly lead to product or process innovation. Its value lies in

the development of an organization’s capacity for innovation, that is, in the

advancement of its knowledge base (broadly construed), its experience and skills for

innovation. Technical knowledge development can be considered as the most rampant

outcome for participants in publicly-funded R&D projects. Taken together, product or

process innovation and technical knowledge constitute what we shall henceforth refer

to as project success.

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Factors affecting project success

As noted earlier, we seek to identify determinants of project success along the

dimensions of market, firm, and project-related factors. Regarding the term project-

related factors, we refer to “structural” features, such as the thematic area into which a

given project belongs, or the size of the consortium that has undertaken the research

work, as well as to management aspects of the project. These include social and

behavioral features in the management of the project team, such as communication,

coordination mechanisms, and learning processes. Moreover, in this category we

include management rules and practices imposed by the Commission to govern the

setup and workings of research consortia. The basic theoretical rationale as to the

influence of these factors on project success is that how a project is managed will

necessarily have a bearing on its outcomes. For example, mistrust and lack of

effective communication among partners will logically inhibit the degree of

knowledge sharing among them, thus leading to ineffective project execution, and

ultimately in failure to achieve its objectives.

Firm-related factors pertain to the resources, experience, and innovation-related

competencies of the partners involved in the project. More specifically, in this

category we include factors such as firm size and age, previous experience in

innovation activities, resources and skills for innovation, etc. We theorize that these

factors to an important extent determine the types, “quantity” and “quality” of

resources partners can commit to project implementation. As such, they should

significantly affect project success.

Market-related factors, on the other hand, involve the characteristics of the industry

and market in which the partners in a research consortium belong. To the extent that

market conditions are dynamic and highly competitive, a firm will be motivated to

engage seriously in innovation activities as a way to confront market pressures, and

therefore is more likely to commit resources in the implementation of the joint R&D

efforts and be strongly interested to project success.

The following diagram depicts schematically the relations implied by the arguments

given above.

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Figure 1: Research Model

Project Success: The Role of Market, Firm, and Project Characteristics

Market conditions

It is generally agreed in the extant literature on innovation that pressures from the

market environment induce firms to innovate (Damanpour, 1991). Factors such as

competitive intensity, market uncertainty, technological dynamism, and the stage of

the industry’s life-cycle are expected to have a bearing on the firms’ propensity to

innovate, or to adopt innovative technologies developed elsewhere. It follows that,

because few firms can innovate based on their own means, enterprises tend to enter

various cooperative arrangements with universities, public institutes, other firms

(including direct competitors) in order to develop innovative product or process

technologies. For example, Park et al., (2002), argued that firms need to participate in

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R&D consortia as a means to overcome market uncertainty and to exploit emerging

technological opportunities.

The impact of the market environment on the success of such collaborative R&D

schemes is less clear, however. Whereas one can reasonably argue that intensive

competition or technological dynamism, or high volatility in customers’ preferences

induces firms to seek ways to respond to market demands though innovation

(Audretsch & Feldman, 1996), the impact of those very factors on the success of

innovation efforts should be indirect rather than direct. Market forces should exert an

impact on project success that is mediated by the motives and resources committed by

project participants. And this mediated effect can, in principle at least, be either

positive or negative. On the one hand, a highly competitive environment may force

partners to escalate commitment in the project, as it may represent a promising

vehicle for developing and implementing a creative response to those pressures (Ding

& Eliashberg, 2002). On the other hand, adverse market conditions may divert

attention to other pressing needs, thus diverting attention away from the collaborative

project (Linton et al., 2002). Under these circumstances, market conditions would

have a negative effect on the likelihood of project success.

In contrast, the effects of the stage of the respective market life-cycle at the time the

project is initiated will be less ambiguous. An emerging market, or a market at the

early stages of its development, will normally offer many opportunities for

innovation. At this “fluid” state of market conditions, first-mover advantages for those

firms succeeding to bring early into the market a technically and commercially

attractive technology will be great (Schilling, 2002; Min et al., 2006). Hence, project

participants would be motivated to commit as much resources as possible to lead the

project to success.

Firm characteristics

Firm-level characteristics refer to all internal attributes that facilitate (or inversely

inhibit) innovation; an internal environment that motivates the generation and flow of

ideas and importantly, the transformation into innovative products and services. There

is a large amount of literature that emphasizes such intra-firms features including

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resources and capabilities, and experience in innovation activities as critical

determining conditions for firms’ capacity, either in-house or in collaborative

arrangements, to develop innovations and exploit R&D results (e.g., Ahuja & Katila,

2004; Damanpour, 1991; Kimberly & Evanisko, 1981; Leonard-Barton, 1992).

Two such characteristics are firm age and size. Some researchers have suggested that

new firms tend to engage more often in collaborations as they generally lack the

necessary knowledge (Cohen & Levinthal, 1990), experience, financial and other

types of resources (Katila & Shane, 2005; Teece, 1986) for in-house innovation.

Conversely, established firms may have accumulated experience in collaborative

R&D, may have a more clear picture of the market, higher market share (Zaheer &

Bell, 2005), more products under development (Rothaermel & Deeds, 2004), wealthy

financial resources and a record of partnerships they have entered to (Sorensen &

Stuart, 2000). Generally, one would expect older firms, with their accumulated

experience, to be better at exploiting an emerging new technology, whereas younger

firms, with lower stakes and habituation in old technologies, to be better at exploring

new technological opportunities (Notteboom et al., 2006).

Another basic firm characteristic is firm size, usually expressed in terms of human,

financial or physical resources available (e.g. number of employees, total profits,

number of plants or manufacturing equipment). Research in different contexts, such

as in Europe (Huiban & Bouhsina, 1998a; Huiban & Bouhsina, 1998b; Premkumar &

Ramamurthy, 1997; Thong & Yap, 1995; Ventura & Marbella, 1997), India (Lal,

1999), and the US (Premkumar & Roberts, 1999) has provided evidence that large

firms are endowed with slack resources and tolerance to potential losses, a fact that

positively affects firms’ collaboration and project success. In principle, therefore, the

size of the project partner signifies the quantity and quality of resources it can commit

during project implementation. One would be inclined to hypothesize that the larger

the size, the more the odds for project success. However, there exist counter

arguments on the hypothesized direction of impact. For example, structural

contingency theory argues that organizations tend to become bureaucratized as size

increases, thus hampering organizational responsiveness (Liao, 2001). In this vein,

Acs and Audretsch, (1988) and Phillips (1965) argue that small firms may be more

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flexible, less bureaucratic and more adaptive to change and innovation. Hence, it

could be possible to argue that partners of a relatively small size will be more flexible

and committed to project success. These equivocal evidence concerning size effects

on project success demonstrate the need for further empirical analysis.

Another key determinant of a project’s likelihood to result in success is the mix of

resources contributed by partners during implementation. Many firms are entering

R&D collaborations not only to overcome the inherent risks associated with new

product or process development, but also to gain access to complementary resources

and capabilities (e.g., technological, financial, etc) owned by partner firms (Ernst &

Bleeke, 1993; Varadarajan & Cunningham, 1995). We concentrate on four key

complementary capabilities that the extant literature contents that are critical for

innovation: marketing skills, the capacity for speedily introduce new products or

services, integration capabilities, and the firm’s capacity to protect its innovative

position from rivals.

Often neglected in the practice of collaborative R&D, marketing skills appear

important for the implementation and exploitation of innovation (Kotler, 2003). Firms

participating in projects aiming at radical innovation for which markets are still

uncertain (or even not existing) tend to neglect marketing; this is ill-advised, however,

because precisely in these cases marketing has to form and develop a market from

scratch. In this instance, for example, one of the fundamental objectives of effective

marketing would be to shape and establish the credibility of the new product

technology to potential customers. More generally, it is widely accepted in the new-

product-development literature that the effective interaction between R&D and other

functions, such as production and marketing, is important for success (Dougherty,

2001; Argyres & Silverman, 2005). It follows that early consideration of marketing-

related issues and concerns is critical for the successful introduction of a new,

innovative product or process technology. McKenna (1995), for example, argued that

marketing strategies such as pricing (penetration/low price vs. high price), distribution

(direct selling vs. using intermediaries), and shaping awareness programmes

(advertising, promotions, publicity and public relations) are important for project

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success. According to Czuchry and Yasin (2003), the use of creative marketing

strategies improve the likelihood of project success.

Equally important is the ability for speed in developing and positioning a new product

into the market. Several studies have argued that relative speed in product

development is a source of competitive advantage, with firms faster in product

development having the option to expand lines more rapidly or renew products more

quickly (Abegglen & Stalk, 1985; Bower & Hout, 1988; Womack, Jones, & Roos,

1990). In addition, work conducted in technologically dynamic industries has found

substantial differences in the time required to complete development projects (Clark

& Fujimoto, 1991; Eisenhardt & Tabrizi, 1995; Iansiti, 1995). Faster product

development potentially offers advantages in earlier introduction of improved

components, even if all firms eventually employ the same ones, and in more rapid

response to evolving user needs. Extending these arguments in the realm of

collaborative R&D projects is straightforward; projects where partners are endowed

with the capacity to speedily bring new products into the market will be likely to be

more successful.

Innovation is also dependent in the firm’s capacity to integrate relevant knowledge

from multiple, distributed sources within organizational boundaries. It is widely

accepted in the literature that successful innovation requires the firm to be able to

integrate the various functions and activities required for developing and bringing a

new technology into the market. Integration is critical in order to facilitate

information flow within and between organizational units, accelerate innovation

process and finally achieve successful innovation output (Souder & Jenssen, 1999).

The product innovation literature often suggests that cross-functional integration is the

key to new product performance. As product development theorists suggest (Gupta,

Chyi, Romero- Severson, & Owen, 1994; Song & Dyer, 1995b), a higher level of

functional partition between marketing, manufacturing and R&D functions increases

the degree of mismatch between market demands and product developed, and

consequently endangers innovation performance. Because of its importance in new

product development, cross-functional integration between marketing, R&D and

manufacturing has become the main thrust of this stream of literature (Gupta et al.,

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1994; Moenaert & Souder, 1990; Song & Dyer, 1995a). In the context of

collaborative R&D, this generalizes in the ability to integrate the knowledge, skills

and expertise contributed by project participants.

A firm’s ability to protect, through legal and/or “competitive” means, its innovative

position from rivals’ attempt for imitation also constitutes an important capability

related to innovation (Silverman, 2000; Ziedonis, 2004; de Laat, 2005). Examples of

several industries (e.g. pharmaceuticals) support this view, as the firm’s capability to

secure patents to protect their discoveries proves a critical organizational process. In

this sense, and apart from legal mechanisms such as patents, skillful and committed to

innovation employees is also found as an asset positively related to innovation

(Huiban et al., 1998b; Kessler & Chakrabarti, 1999; Song & Parry, 1997) as they have

the capability to protect innovation.

Traditionally, economics and strategy have emphasized the importance of protecting

an innovation in order to be primary beneficiary of the innovation’s rewards, but the

decision about whether and to what degree to protect an innovation is actually

complex. There is a vast amount of literature discussing the issue of innovation

protection and whether this has a positive or negative impact on innovation

production and dissemination (see Lerner, 2000 for a review). Sometimes not

vigorously protecting a technology is to the firm’s advantage encouraging other

producers (and complementary goods providers) to support the technology that may

increase its rate of diffusion and its likelihood of rising to the position of dominant

design (Schilling, 2005). The three primary legal mechanisms used to protect

innovation in most countries are patents that protect an invention, trademarks that

protect words or symbols intended to distinguish the source of a good and copyrights

that protect an original artistic or literary work (Anton & Yao, 2004; Schilling, 2005).

Each mechanism is designed to protect a different type of product and service.

According to Schilling (2005), legal mechanisms for protecting innovation are more

effective in some industries than others because some industries are more flexible

inventing a patent or a copyright (Markman, Espina, & Phan, 2004). Firms that have

previously used legal means are more experienced for protecting innovation and gain

a competitive advantage. Protecting an innovation enable the firm to get the

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maximum of R&D returns from the innovation. These returns can be reinvested in

further developing technology, promoting the technology and producing

complementary goods. Protecting an innovation facilitate the firm to direct the

technology’s development, determine its compatibility with other goods and prevent

multiple incompatible versions of the technology from being produced by other firms

(Markman et al., 2004). This type of technological knowledge and capability makes

firms that participate to consortium to gain a more powerful position to the market.

A firm’s record of innovation activities is another firm-specific factor that will, in

principle, influence its capacity to engage successfully in collaborative R&D projects

(Pennings & Harianto, 1992; Veugelers, 1997). Two important facets of experience

with innovation activities relates with “intramural” and “extramural” R&D. A firm

that has engaged previously in R&D activities will have developed certain experience

in performing such activities. “Intramural” R&D in particular, connotes a firm’s

emphasis in exploring and exploiting technological opportunities. Innovation

“history” is also manifested in the firm’s innovation performance, usually expressed

as the percentage of its current turnover attributed to goods and services developed in

the recent past (Janssen et al., 2006). It is also reflected in a firm’s continuous

participation in FP projects. In general, a firm experienced in R&D and innovation

activities will likely have developed the necessary resources, skills and knowledge

necessary to further develop its innovative activities. It follows that it will also be able

to contribute significantly in collaborative R&D activities, to develop synergies with

its partners and to engage in collective learning.

Project-related factors

With the term project-related factors we refer to such typical features (i.e. basic

project characteristics) of any given FP project as, for example, the thematic area into

which it belongs or the size of the consortium that has undertaken the research work,

as well as to the management aspects of the project. These include social and

behavioral features in the management of the collaborative R&D project, such as i)

project objectives, ii) its technological “content”, iii) communication and iv)

coordination mechanisms, and v) learning processes.

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Basic project characteristics. Project size and duration is an obvious starting point for

considering project-level effects on project success. Beginning with size, the number

of participants in a consortium is a basic dimension of project size. A large

consortium would, in principle, significantly affect projects’ team dynamics and be

strongly associated with performance (Ancona & Caldwell, 1992b; Jehn, 1995; Smith

& Lipsky, 1994b). With respect to product/process innovation outcomes, as Schilling

(2005) points out, the efforts and expertise of multiple (as opposed to just a few)

partners in an R&D project foster problem solving, and hence, size is positively

related to success. Up to a certain point, however, since an “excessive” number of

participants may bring a greater likelihood of social loafing and free riding, thereby

decreasing the extent of learning (Gibson & Vermeulen, 2003; Wong, 2004).

The length of the time span during which project members have worked and shared

experiences with one another positively affects their communication, and in turn,

projects’ performance (Gibson, 1999; Hoang & Rothaermel, 2005; Katz, 1982). As

project’s duration increases, learning may become more effective (Parkhe, 1991) and

standard work patterns emerge fostering trust and cohesion, which in turn positively

affect project performance and success (Katz, 1982){Katz, 1982).

Another important “basic” characteristic of a project consortium is the extent of

participation of partners coming from the industry (as opposed to participants

representing the research and academic communities), expressed as a fraction of

project size. Since firms are ultimately those that innovate, it is reasonable to argue

that consortia in which there is a greater number partners coming from the industry

there will also be an increased tendency towards producing product / process

innovation. Even with respect to indirect dimensions of project success, such as the

creation of technical knowledge, it is reasonable to argue that firms are likely to be

more motivated to produce such knowledge, as it can serve as a stepping stone for

further development ultimately leading to a concrete product or process innovation. In

contrast, it could be argued, albeit in a somewhat stylized manner, that partners

coming from the research community are mainly interested in more abstract forms of

knowledge, leading to research publications rather than prototypes and models to be

subsequently developed into commercialized product or process technologies.

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In this same line of reasoning, if the leader of the project comes from the industry it is

reasonable to expect greater motivation and efforts towards commercialized or at least

potentially commercializable outcomes. Intuitively, a consortium team to be

successful, given the difficulties associated with the task per se and the complexities

involved in the management of a team consisting of individuals from different

organizations, it must have strong leadership. Leadership is a process in which an

individual influences the progress of other team members toward the attainment of a

goal. In this sense it is not surprising that effective project leadership has been

reported as one of the most important factors for directing and steering projects

successfully, especially in those situations concerning new product development

(McDonough III & Griffin, 1997; Sarin & McDermott, 2003; Keller, 2003). Recent

studies (Edmondson, 2003; Edmonson, 1999; Lovelace, Shapiro, & Weingart, 2001)

suggest that the characteristics and traits of group leaders significantly affect the work

climate and learning in teams by setting a positive and safe environment and resolving

issues that would otherwise result in extensive, dysfunctional conflict. Cumulatively,

these actions are most likely to increase group members’ feeling of freedom to

express task-related doubts, engage in constructive dialogue (Lovelace et al., 2001),

and establish trust and collaboration within the team (Norrgren & Schaller, 1999). It is

also more likely that a strong leader coming from industry will exert influence and

guidance towards creative application of acquired knowledge for commercial ends

(Edmonson, 1999).

FP projects are governed on the basis of a formalized body of rules and management

practices imposed by the EC. These rules extent from issues related to financial

regulation to issues concerned with the content and procedures for drafting and

enforcing consortium agreements among partners in a given project. Rules imposed

by the EC can be viewed as the process by which EU influences, to varying degrees,

the behavior and output of the consortium through the use of power, authority and a

wide range of bureaucratic, formal and informal mechanisms (e.g., reporting system,

milestones, funding scheme) in order to achieve project objectives and satisfactory

performance (c.f. Geringer & Hebert, 1989b). In fact, these rules are essential for the

EU authorities to manage, monitor, and control the vast portfolio of project financed

at any given time.

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It is less clear, however, whether these rules and practices exert any causal influence

on project success. If EU rules and practices represent an effective means for

monitoring FP projects at the Commission authorities’ level, this does not necessarily

mean that these mechanisms will cause the project to result in commercialized

innovation. Admittedly, these mechanisms will enable project managers to streamline

activities, monitor partner’s performance based on their allocated tasks, and to

communicate effectively and in a structured way with the EU authorities, but this does

not appear to have a bearing on the scientific and technical success of the project. One

could reasonably assume that participants experienced in following these rules and

practices will be able to deal with the purely management aspects of the project more

efficiently than those who are not. Hence, we propose that being accustomed with EU

rules and procedures will be unrelated to project success. However, it might be

possible that certain aspects of these rules may facilitate or, in contrast, inhibit various

choices made during project implementation. For example, it could be the case that

rules concerning tasks breakdown could help (or force) project managers to better

streamline activities, or it could be the opposite: formal obligation to divide tasks in a

manner that does not suit the technical idiosyncrasies of the project, might contribute

to project failure. The same line of reasoning holds with issues related to partners’

selection and negotiation procedures. For instance, rules dictating the multi-national

character of project participants might force the selection of partners that are unsuited

for the project at hand and ignore partners that might be more appropriate. Given the

inconclusive character of the arguments above, further empirical research is

warranted.

Nature of the project. One of the most important constitutive factors of the “nature”

of a project is the extent to which it is originally directed or not towards innovation.

This is reflected, for example, in the selection criteria and in the evaluation process

through which the project was actually chosen for financing. In the case of the EU’s

FP5 and FP6 projects, there are certain thematic areas with different goals and

priorities, starting from basic research with no explicit (and perhaps not even implicit)

view towards innovation, to ones that have an explicit orientation towards innovation.

One could reasonably argue that when innovation is indeed a programmatic objective,

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projects in this area will be more likely, ceteris paribus, to produce product or process

innovation. On the other hand, however, one could also argue that an overly narrow

emphasis on innovation and market driven results might lead to fewer possibilities for

producing radically new technical knowledge.

Relatedly, when the original project idea stems from one or more partners coming

from the industry, one would logically expect that this would have a positive effect on

project success. This is because industrial partners have, in principle at least, more

motives to produce technical knowledge that can be eventually developed into a

concrete new product or process technology.

Orientation towards innovation is also reflected in the partners’ motives to participate

into a specific R&D project. Partners’ project objectives may result from or be

consistent with their long-term technological strategy, and/or may be a response to a

constraint (legal, social, ecological) or an opportunity/ risk (technological or financial

for instance) (Cardinal & Marle, 2006). In the economics literature, firms’ motives

and therefore objectives for participating in cooperative R&D principally relate with

the possibility to enhance R&D productivity through cooperation on relevant inputs,

as well as to the ability to change the appropriability conditions in order to

commercialize R&D outputs (Geroski, Machin, & Reenen, 1993). Other motives,

unrelated to R&D per se, include improved market access through partners, and

securing government subsidies (Sakakibara, 2002). Specifically with respect to how

cooperation in the input factor markets enhances R&D productivity, the extant

literature focuses on three primary motivations: fixed-cost sharing among R&D

participants, the realization of economies of scale in R&D, and the avoidance of

“wasteful” duplication (D'Aspremont & Jacquemin, 1988; Katz, 1986; Katz, Ordover,

Fisher, & Schmalensee, 1990; Motta, 1992). All three are scale-based motives and

they imply that the principal purpose of cooperative R&D is to set cost-sharing rules.

Another motive to participate in cooperative R&D relates with sharing and/or

reducing risks and uncertainties (Hagedoorn, 1993). R&D partnerships pool risk and

thus raise firm incentives to undertake R&D. Risk is pooled directly at the partnership

level, as a result of a larger number of participants in a research project, and at the

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individual member organization level in those free resources that can allow

undertaking additional projects. In addition, firms frequently confront significant

market and technological uncertainties, particularly for longer-term, strategic

research. High uncertainty has a serious negative effect on private sector incentives.

R&D partnerships may lower such uncertainties by both spreading them among

partners and by limiting the exposure of each one (Ahuja, 2000).

Previous research suggests that one of the most important factors in R&D consortia

success is partner’s previous experience in R&D (Child & Yan, 1999; Fiol & Lyles,

1985). The implicit assumption is that there are learning effects that enable firms to

develop a ‘relational capability’ that is useful in managing inter-organizational

relationships (Dyer & Singh, 1998). Indeed, Kale, Dyer and Singh (2002) suggest that

some partners, based on repeated experience in managing certain inter-organizational

forms, have developed superior capabilities at managing them. Given organizations’

heterogeneity and differences in prior R&D experience, we would expect that some

project members eventually develop superior capabilities at managing particular

organizational forms such as consortia. In support of this argument, (Anand &

Khanna, 2000) found that firms with greater prior R&D consortia experience generate

significantly higher performance. They reasoned that firms learn to create more value

as they accumulate experience in consortia. Simonin (1997) found that greater R&D

consortia experience is linked with project member’s abilities to effectively select

consortium partners, manage consortium conflicts, etc.

Overall, a project that is building upon pre-existing R&D efforts will be more likely

to lead to success. Irrespective whether these past efforts were carried out in the

context of an earlier FP project, in a national R&D programme, in a privately funded

collaborative project, or in-house by one or more of the partners, accumulated

learning and experience in the specific technology area will provide project members

with criteria for judging the efficacy of courses of actions, and to better anticipate and

respond effectively to the inevitable technological and managerial challenges related

to the focal project.

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Finally, project success is influenced by the intrinsic nature of the technology that it

strives to explore. The extent to which an emerging technological field is inherently

risky, or complex, or distant from the core technological area of the partners involved,

will necessarily have a bearing on the likelihood of success. The direction of the

influence, however, that is whether the influence will be positive or negative is less

clear. For example, a certain degree of risk is “necessary” if the project is to come up

with a novel technological solution. Viewed from the opposite angle, a prospective

technology for which there is no risk at all would most probably be a technology with

little, if at all, opportunities for developing an innovation in the full meaning of the

word. An overly “risky” technology, on the other hand, would mean excessive

challenges to be met, greater ambiguity and uncertainty with respect to the every-day

choices to be made in the course of implementation, and eventually a greater

likelihood for failure. The same holds for the degree of scientific and technical

complexity and the distance from partners’ preexisting technological expertise. For

instance, research into new areas at the technological frontier as opposed to research

targeted towards improving and developing existing products and processes is

inherently more difficult to result in immediate success. On the other hand, however,

the returns, should that be possible, would be much greater.

Project management factors. The extant literature generally considers project

management factors (e.g., management practices, project objectives, communication,

learning processes) as important predictors of both project performance and the final,

collective knowledge and/or technology outcome produced (see for example Pelled,

Eisenhardt, & Xin, 1999; Pfeffer, 1983; Smith et al., 1994a; or Mathieu et al., 2008

for a review).

When project objectives are known and accepted by each partner, for instance, it is

likely that the project will lead to knowledge sharing and creation among project

members. So, apart from EU regulations, the existence of clear and precise objectives

further contributes to the project overall performance results. It is critical for the

success and performance of the project, that its objectives are known and accepted by

each partner. The allocation of tasks and responsibilities among partners is the basis

for determining the level of project performance and technology outcome (Yan &

18

Gray, 1994). Having clear and precise objectives in R&D consortia, however, is not

always possible or even desirable. Partners often cannot agree on common objectives

that will effectively serve their respective individual interests. Moreover, given

information asymmetry and the presence of hidden agendas, partners often have to

tolerate a certain degree of objective and goal ambiguity.

Moreover, many analysts vividly demonstrate the significance of communication and

coordination mechanisms to project performance and technology outcome.

Communication can influence the impacts of these project innovation outputs, in

terms of trans-national mobility of researchers and improved ability to work in

different cultural contexts. According to Hoegl and Gemuenden (2001), for instance,

communication provides a means for the exchange of information among members

(Pinto & Pinto, 1990), whereas coordination leads to the development and agreement

of a common task-related goal structure. It is important to the quality of project

collaboration that members are able to coordinate effectively with all other members.

At the same time, effective coordination creates and strengthens links among

members, allows partners to embark into dissemination activities, and contributes to

the development of novel applications within time and budget schedules. It seems that

is important to the quality of project collaboration that members are able to

communicate directly with all other members (i.e. communication structure) because

the exchange of information exclusively through mediators (e.g., leader) is time

consuming and a possible cause of faulty transmission. It is critical that members

share their information openly with each other (Gladstein, 1984; Pinto et al., 1990). A

lack of openness within a project (i.e., holding back important information) hinders

the integration of members’ knowledge and experience on their common task.

In addition, cohesion and trust have been widely proposed as important antecedents of

project performance and collective technology outcome (Harrison, 2001; Webber &

Donahue, 2001). Several studies have confirmed a positive association between

cohesion, trust and innovation (Hoegl et al., 2001). In cohesive and trustful projects,

members achieve high levels of interaction and agreement (Shaw, 1981), as well as

increased intra-project safety and satisfaction (O'Reilly Iii, Caldwell, & Barnett,

1989). Trust and cohesion are especially valuable in R&D projects as partners become

19

committed to each other for producing new tools, models, and practices (Kumar,

1996). Mullen and Copper (1994), for instance, postulate that it is primarily the

commitment to the task (as an indicator of cohesion) that presents a significant effect

on R&D project performance and technology outcome, while Gully, Devine and

Whitney (1995) in their meta-analysis conclude that cohesion impacts performance,

particularly if the task demands intensive coordination and communication (e.g.,

innovative tasks).

In the evolution and the success of a cooperative R&D project, learning processes are

also central to the evolution of a cooperative R&D project (Doz, 1996b; Inkpen &

Currall, 2004). Sharing knowledge, seeking feedback and discussing errors among

partners are highly likely to lead to specific, commercializable innovation outputs

(Rothaermel et al., 2004; Zahra & George, 2002). Such behaviors can result in higher

shared understanding that aligns collective action (Fiol, 1994; Senge, 1990), and build

a common memory system of task knowledge that contributes to problem detection

and resolution (Orr, 1990) and to the coordination of partners’ experiences and

expertise (Liang, Moreland, & Argote, 1995). This shared knowledge enhances

members’ ability to efficiently execute project tasks within time and cost boundaries

(Wong, 2004).

In a similar vein, several authors argue that organizations require knowledge

recombination and leveraging skills to pursue product line extensions or new product

development (e.g., Kogut & Zander, 1996; Liebeskind, 1996; Smith et al., 2005).

Consortia with well developed learning mechanisms, conversely, are likely to be more

adept at continually revamping their knowledge stock by spotting trends in their

external environment, internalizing and transforming this knowledge. Being adept has

two dimensions: timing and costs. First, a developed learning capacity facilitates the

advancement of production and technological competences at the opportune moment.

Moreover, as consortium gains experience and assimilates valuable information, the

cost and risk associated with learning activities decrease over time. Both result in the

development of an innovation output that bears the potential of sustainable

competitive benefits.

20

Analysis and Results

As noted earlier two separate questionnaires were developed, one for the participating

industrial firms and another one for the research organizations (ROs) (universities,

research institutes, etc.). We concentrate on the results from the enterprise

questionnaire here, as enterprises constitute a much more reliable field for identifying

possible innovation impacts. Both sets of data have been analyzed with similar

methodologies (i.e., confirmatory factor analysis, logistic and OLS regression),

however, and occasionally we may refer to the results from the RO sample as well. In

total, 3379 enterprises across EU Member States provided data, whereas the second

sample consisted of 1981 ROs. In both samples, however, we had a very large

proportion of missing data. As a result, the effective sample sizes used for the

substantive analyses were much lower1.

Variables

Project success (i.e., the dependent variable of the study), as already mentioned, was

conceptualized to comprise two dimensions: product or process innovation and

technical knowledge creation. We measured innovation with two dummy variables,

indicating whether the project resulted in product and process innovation. Technical

knowledge creation was measured with a three-item Likert-type scale, measuring the

significance of knowledge-oriented outcomes, such as development of tools and

techniques, and prototypes. These outcomes embody knowledge of a technical nature

that can provide the basis for further development leading (eventually) to

commercialization. Concerning the independent variables (i.e., market, firm, and

project-related factors), we utilized objective measures (e.g., for firm age or firm

size), dummy-coded variables (e.g., for the use of patents), or Likert-type scales (e.g.,

for communication practices or learning processes).

The use of a single instrument (participant survey) to collect all variables poses the

threat of common method bias. To test for this possibility we used Harman’s single 1 Specifically, the effective sample size for the analysis of product and process innovation as dependent variables consisted of 280 observations, whereas for technical knowledge was 526 cases.

21

factor test, which indicated that common method bias was not a serious issue for our

data.

Results

We examined the effects of three sets of factors, namely: market related, firm related,

and project related factors on project success (i.e., new product or process innovation,

and technical knowledge). The impact of the three sets of factors on product/process

innovation was assessed using logistic regression analysis, whereas their impact on

the production of technical knowledge was assessed using ordinary regression

(OLS)2. The results are presented here based on the three different dependent

variables of the study, namely: product innovation, process innovation, and technical

knowledge.

Product innovation. The most statistically significant factors influencing product

innovation were the basic firm characteristics (marginally significant), the innovation

history of the organization, the nature of the project, and the role of the respondent in

the project (i.e., manager or producer or user of the technology) Among these, the

nature of the project appears to be the one with the most significant contribution. The

lack of significant contribution of firm resources and capabilities and project

management (as sets of variables) is quite notable.

Focusing on the individual coefficients, in particular, we found the history of

innovation protection through “complex” technologies to be positively and

significantly affecting the odds of the project resulting in product innovation for the

participant enterprise. It appears therefore that the more a firm is using “complexity of

technology” and by keeping qualified people in the firm as a general means to protect

its innovations, the more likely it is to come up with product innovation as a result of

its involvement in an FP project. Moreover, firms that have engaged in past

intramural R&D were about 10 times more likely than the rest to produce product

innovation in FP-financed R&D projects. This is a very strong result; in fact, it is the

2 Logistic regression was particularly appropriate since product and process innovation were measured through dummy-coded variables. Conversely, OLS regression was utilized for technical knowledge since this was measured through a Likert-type scale.

22

strongest coefficient found with respect to product innovation. It suggests that firm

history in R&D activity, particularly in-house research, plays a key role in the

development of product innovation. Also, firms for which participation in the focal

project was their first-time involvement in FP programmes were found more than

twice as likely to report project success, in terms of product innovation, in comparison

to “old-timers”.

Furthermore, the extent to which the set-up and rules imposed by the EC regarding

partners’ selection and negotiations are perceived as facilitating project success

appeared to exert a positive influence on the likelihood for product innovation. This

finding should not be interpreted as implying a causal relationship between EU rules

and product innovation, but rather that those firms experienced with the provisions

and rules set by the Commission experienced no difficulty in this particular regard to

achieve innovation. Additionally, projects characterized as having commercial

objectives and that are considered risky were also found more likely to result in

product innovation. In contrast, those projects that are considered to be involved in

the exploration of “new” technological areas were significantly less likely to produce

innovative products. We found support for the possibility of an inverted U-shaped

relationship between innovation and the extent to which a project is risky or exploring

“new areas”. Our results suggested that projects driven and motivated by clear

commercial objectives, which are also mildly risky, were more likely to result in

success in terms of product innovation.

Process innovation. The most statistically significant factors affecting process

innovation included industry effects (which were found insignificant for product

innovation), firms’ innovation history (as was found also for product innovation), the

role of the respondent in the project (again as was the case for product innovation),

and project management features. Among these, the nature of the project appeared to

be the one with the most significant contribution, a result that coincides with the one

found for product innovation. As in the case of product innovation, the contribution of

firm resources and capabilities on process innovation was not significant.

23

More specifically, firm size was found positively and significantly related to process

innovation. Larger firms were somewhat more likely to engage in process innovation.

In addition, a firm’s capacity to “introduce new products speedily” was found to be

negatively associated with process innovation. In contrast, the coefficient for

“integration capabilities” was found positive and significant. In the extant literature on

innovation it is consistently argued that the capacity for integrating internal and

external to the firm activities and functions is a critical prerequisite for implementing

innovation. Our finding is clearly in line with this argument. Also, we found a

significant and negative coefficient for “innovation protection through legal means”.

This variable refers to the use of patents and other IPR-related means for protecting

the firm’s innovative position. A possible explanation here is that patenting mostly

refers to products that can be imitated by rival firms; in contrast, process innovation,

which usually reflects tacit knowledge, is more difficult to be imitated and hence there

is less need to be protected by a patent. Process innovation is also more difficult to be

patented.

As with the case of product innovation, the set of variables reflecting a firm’s

“innovation history” is clearly the most important in explaining variation in process

innovation. In particular, we found that a firm that has engaged in “extramural R&D”

was about twice as likely to report process innovation because of its participation in

the FP project. Similarly, we found strong positive coefficients for the “introduction

of process innovation in the past three years”, and for the “percentage of turnover

from new/improved products introduced in the past three years”. It is therefore

reasonable to argue that firms experienced in innovation activities, both process and

product innovations, are more likely to report process innovation as an outcome of the

FP project. Interestingly, those firms that engaged in innovation activities by imitating

others were found less likely to report process innovation. The final significant

coefficient in this set is the positive effect of “first participation in FP”. This is

consistent with the result obtained for product innovation; there is strong evidence

that “newcomers” in FP programmes are more likely to engage in projects that

ultimately prove successful.

24

Regarding the nature of the project, those projects “building on past R&D activities”

and those that are characterized as “new area” and “complex” were more likely to

result in process innovation. Recall that with respect to product innovation we have

evidenced that “risky” projects were more successful whereas “new area” projects

were less likely to be successful.

Technical knowledge. Technical knowledge is the third dimension of project success

examined in this study. It represents an intangible output of an FP project, one that is

indirect in the sense that its immediate consequence is not directly manifested in the

market place. Nevertheless, such intangible knowledge can be very significant as it

contributes to the participating firms’ capacity for future innovation.

The factors with the greatest statistically significant effect on technical knowledge

were “firm resources and capabilities” and the “nature of the project”. Specifically,

firm resources and capabilities as a set of factors accounted for a relatively large

proportion of explained variance (together with the “project nature” set). However, of

the individual coefficients only “legal means as a means for innovation protection”

was found positive and significant. Regarding the nature of the project, several

variables were statistical significant predictors of technical knowledge creation (e.g., a

dummy variable indicating whether the project idea has been generated by industrial

partners, the number of industrial partners in the consortium, variable indicating

whether projects “built on past R&D activities”, had clear “commercial objectives”,

or characterized as “risky”).

Concerning project management effects, the coefficient of “clear project objectives”

was found negative and significant. New technical knowledge creation is a complex

process of exploration and discovery, where clear objectives set out from the

beginning do not always prove valid or productive. Other significant coefficients in

pertained to the positive effects on technical knowledge of “cohesion and trust” and

“learning processes” within the project team. Finally, in relation to market effects, and

in contrast to product and process innovation, we found “dynamism” in customer

preferences to have a positive influence on technical knowledge creation. Volatility in

25

customer preferences appeared to induce the development of new technological

knowledge.

Table 1 summarizes the results of our quantitative analysis. For reasons of

completeness, the last two columns report the obtained results for ROs.

Table 1: Results of Quantitative Analysis

ENTREPRISES RESEARCH ORGANIZATIONS

Ind. Variables Product Process Technical Knowledge Product Process

MARKET-RELATED

Market environment: dynamism in customer preferences +

Emerging prospective field - -

FIRM-RELATED

“Basic”

Size class +

EU(27) +

“Firm’s resources and capabilities”

Capacity for “speed” -

Integration capability +

Innovation protection: legal means - +

Innovation protection: “complex” technology +

“Firm’s innovation history”

Intramural R&D in the past 3 years +

Extramural R&D in the past 3 years + +

Development of new or improved goods and services introduced in the past 3 years: (ROs sample only) +

Creation of spin-off introduced in the past 3 years: (ROs sample only) +

Product Innov (New-To-The-Market) introduced in the past 3 years: Industry / Patents introduced in the past 3 years: (ROs sample only)

-

Product Innov (New-To-The–Firm) introduced in the past 3 years: Industry / IPR introduced in the past 3 years: (ROs

- -

26

ENTREPRISES RESEARCH ORGANIZATIONS

Ind. Variables Product Process Technical Knowledge Product Process

sample only)

New Process Innovation introduced in the past 3 years: Industry / Award licenses to firms introduced in the past 3 years: (ROs sample only)

+

Innovation performance (% turnover from new/improved products) +

First participation in FP? (yes/no) + +

PROJECT-RELATED

“Basic”

FP - FP6 (vs.FP5 ) +

Proj_type

Fraction - % of partners from industry +

“Eu rules”

Practices in line with EU rules +

EU rules’ impact on: partner selection/negotiations + +

“Nature” of the project

IDEA - The project’s idea comes from industrial partners (yes/no) +

PAST-RD - The project builds on past R&D activities (yes/no) + +

Project objectives: commercial + +

Project objectives: funding & reduce risk +

Project objectives: “technological” + +

Project objectives: “networking” -

Nature of project: “risky” + +

Nature of project: “new area” - + -

Nature of project: “complex” +

Role - Respondent is manager/ or user/ or technology producer (yes/no) + +

“Project management”

# of partners having worked with +

27

ENTREPRISES RESEARCH ORGANIZATIONS

Ind. Variables Product Process Technical Knowledge Product Process

# of partners having not worked with -

Clear project objectives - +

Communication (within team) -

Cohesion/Trust +

Learning within team: Intuition -

Learning within team: Interpretation + +

Learning within team: Integration

Discussion and Conclusions

Over the last decades, a vast amount of scientific work documenting, conceptualizing

and analyzing the significance of R&D and innovation for the survival and success of

organizations has been published (Nonaka & Takeuchi, 1995; Damanpour, 1996;

Bell, 2005). However, and despite the proliferation of studies, our understanding of

the interrelationships between R&D and innovation performance remains relatively

inconsistent and characterized by low levels of explanation (e.g., Drazin &

Rothaermel, 2005; Anderson et al., 2004). The work at hand attempts to inform these

inconsistencies by offering an integrative understanding of those market, firm, and

project level factors that affect the success of collaborative R&D projects (i.e.,

commercializable innovation outcomes and technical knowledge) under the 5th and

6th EU Framework Programme for Research and Development. FP projects offer a

fertile ground for effectively exploring the complex links between R&D and

innovation, as they bring together partners from a wide spectrum of economic and

social activities (e.g., universities, research institutions, governmental agencies,

technology brokers, manufacturing firms, services corporations).

In this study, we make a fundamental classification between market, firm, and project

level factors that are shown to exert important influences on collaborative R&D

28

projects (Doz, 1996; Gulati, 1998; Hagedoorn et al., 2000; Hoegl et al, 2004). Market

conditions refer to the characteristics of the industry and market (e.g., competition

intensity, dynamism) in which the partners belong. Firm characteristics, on the other

hand, consist of factors related to the resources, experience, and innovation-related

competencies of the partners of the R&D project. Finally, project-level factors include

structural features (e.g., size and duration of the project) and management issues (e.g.,

communication and coordination mechanisms, learning processes, management rules

and practices imposed by the Commission). The underlying rationale for this

categorization is rooted in established models of inter-organizational collaboration

(e.g., Zollo et al., 2002; Fey & Birkinshaw, 2005; Hoang & Rothaermel, 2005), which

suggest that partner-specific, market-specific, and project-specific conditions shape

the extent to which collaborations result in knowledge accumulation, create new

growth opportunities, and enable partnering firms to achieve their innovation

objectives.

The results of our empirical analysis provided very weak support for the proposition

that market conditions strongly influence the various aspects of project success (i.e.,

product-process innovation, technical knowledge creation). A plausible explanation is

that the very nature of the projects undertaken in the Framework Programme is of a

“technology-push” orientation rather than “technology-pull”. In other words, it may

be that the typical project is driven by a promising emerging technology, usually in its

very early stage of development, and for which there is no clear market opportunity

for exploiting it, at least in the short to medium term. As such, the partners are driven

by a motive to explore rather than exploit a technology, which presumably is not

mature enough for prospective commercialization. In such circumstances, market

conditions may be largely “irrelevant”.

Another plausible explanation is that the measures used to capture market conditions

in the survey were specified at an aggregate level not allowing for expressing the

differences between and across sectors and technological trajectories. Qualitative

evidence we obtained during data collection3 (i.e., case studies) seems to support this

3 Besides the questionnaire survey, Innovation Impact project also included a series of 70 in-depth case studies that offers a more detailed view of the dynamics developed among partners during the R&D

29

assertion by indicating differences in behaviour among enterprises in four types of

markets. For instance, companies operating in competitive markets with high

technology/innovation intensity tended to make better and more direct use of FP

projects in their commercialization plans. Many of enterprises in this category show a

strong involvement in Framework Programmes and a strategic role of EU funds in the

R&D process. That is, the FP R&D funding is well integrated with the company

research activity. FP projects are mainly carried out to make applied research and to

exploit the innovative results coming from it. In contrast, FP projects seemed much

less directly linked to innovation plans and competitiveness for enterprises in other

types of sectors. The reasons varied by the type of competitive situation and type of

technology in the sector. For enterprises in monopolistic/oligopolistic sectors with

high technology/innovation intensity, examples of direct and consistent commercial

exploitation of FP project results are fairly rare even though these companies tend to

be well experienced with FP projects. Exploitation, when it happened, was in niche

markets. For enterprises in monopolistic/oligopolistic sectors with low

technology/innovation intensity FP-funded R&D projects apparently have a minor

role in the overall company strategy, largely due to the marginal relevance of

innovation in these sectors. For most such companies FP projects have offered at least

indirect gains such as networking opportunities and development of standards,

creation of databases. Direct commercial exploitation is fairly unlikely. Finally, for

enterprises in competitive sectors with low technology/innovation intensity, the

answers vary. In the case of the small part of enterprises that base their activity on

R&D and have long experience in FP projects the European projects have become a

structural instrument of financing the company development, technological

development through networking, acquiring qualified competences. For the remaining

enterprises of this class the FP projects funds are not part of an integrated research

activity.

Regarding firm characteristics, the empirical analysis has indicated a positive effect

of firm size on process innovation, but not on product innovation or the production of

technical knowledge from FP projects. This may indicate that larger firms are more project. The complete reporting of this qualitative evidence, however, is not within the scope of the present study, but will be used in this section for illustrative purposes.

30

inclined to pursue process innovation, presumably as they have more pressing needs

to optimize their large-scale productive operations.

Case study analysis, however, showed a more variegated picture. SMEs reported a

generally strong strategic alignment with FP projects and explicit goals related to

innovation outputs such as developing a prototype, developing a patentable

technology, or developing a complementary technology that will enhance

competitiveness. Medium-sized companies seem to have reaped the largest innovation

benefits from FP project participation, as these organizations can achieve critical mass

for R&D in a focused area. They are often either established players in their industry

or quickly growing players that have overcome the threshold of successful

commercialization of a first generation of innovation-based products or process

technology. In general, these companies have explicit strategy and goals for

innovation. They often take a leading role in projects, and are most frequently found

as coordinators, in parallel with Research Organizations. Small sized firms (<50

employees), on the other hand, often remain too focused on a core technology and too

centred on research (compared to development) in order to be able to sustain market-

driven development and commercialization in their own right.

Empirical results were rather weak regarding the effect of innovation-related

capabilities of partnering organizations – e.g., ability to introduce new products

speedily, legal means of innovation protection, integration capability – on the

likelihood of product/process innovation and technical knowledge creation. In

particular, concerning the coefficient of legal means of innovation protection, we

found a negative coefficient with respect to process innovation and a positive one

with respect to technical knowledge. The negative effect is perhaps explained by

recognizing that process innovation as highly idiosyncratic and tacit to the firm does

not need protection through legal means. In contrast, the positive coefficient is in line

with expectations: firms having the resources and experience to protect their

innovations through patents and other IPR-related legal means have the motive to

pursue the development of technical knowledge, which they can subsequently protect

from possible imitation in the hope they can develop it into a concrete product or

process innovation. Finally, we found a significant positive coefficient for the effect

31

of the capability to protect innovation through complex technology on product

innovation. Being able to keep qualified people in-house and developing complex

technologies that competitors find it difficult to imitate implies that the firm has

valuable technological capabilities that would allow it to pick promising R&D

projects to participate and contribute substantively towards their success.

Furthermore, a strong empirical finding is that prior experience of an organization

with R&D and innovation-related activities (i.e., innovation history) positively and

significantly affects project success. First, we found that experience in both intramural

and extramural R&D positively affects product innovation. Extramural R&D also

positively influenced process innovation. Past innovation performance, as manifested

in the percentage of turnover attributed to new products introduced in “the past three

years” also had a positive effect on process innovation (a positive effect on product

innovation would be more likely, however). In addition, we observed that firms that

have a history of imitation (i.e., introduction of new-to-the-firm products, as opposed

to new-to-the-market innovations) were less likely to report process innovation. This

implies that a “history” of imitation in fact inhibits the likelihood for project success.

Qualitative analysis corroborated innovation history role by demonstrating that

building up a broader innovation culture through the year was an important

underpinning factor behind product and process innovation success. Firms with a

history of explicit R&D and innovation structure proved more successful in producing

innovation results.

A rather intriguing finding pertains to the positive effect of first-time participation in

FP projects on both product and process innovation. One would be tempted to

consider this to imply that “newcomers” are more motivated to drive FP projects to

success. There is no reason, however, to believe that they are systematically more

capable to drive FP projects to success than other participants are. On the other hand,

there may be a tentative link here with the size findings above: SMEs will on average

tend to participate less, and many of them only once.

Regarding the effects of EU rules, we argued that their principal value is to allow the

efficient and effective management and monitoring of a vast portfolio of projects by

32

the EU authorities. At the level of the individual project, their value is to create an

administrative platform, within which internal activities are developed, implemented,

and monitored. These rules serve as the official mechanisms by which the project

manager is made accountable to the sponsor. Accordingly, the positive coefficients

found with respect to EU rules’ impact on partner selection and negotiation on

product innovation and on technical knowledge suggests that those partners that are

comfortable with those kinds of rules are able to select the best possible partners,

hence increasing the odds of success.

The nature of the project appears to be a very important determinant of project

success, as both the quantitative and qualitative analysis indicated. Projects that are

driven by commercial objectives from the outset were found more likely to result in

product innovation and to lead to technical knowledge creation. In contrast, projects

aiming at networking seem less successful in terms of generating new knowledge. In

addition, the nature of a project, in terms of being risky, exploring a new

technological area, or being scientifically complex, influenced project success in

important ways. First, the degree of risk affected positively both product innovation

and knowledge creation, but in both cases the degree of project risk exhibited an

inverse U-shaped relationship to the dependent variables: excessive risk appears to

lead to diminishing returns as regards the likelihood for product innovation and

knowledge creation. Overall, R&D projects that were commercially driven, risky,

complex, and in new areas (for process innovation) tended to be more successful.

With regards to the management aspects of the project, quantitative results

demonstrated a less decisive role for project success. More specifically, clear and

agreed upon objectives were found to have a negative impact on technical knowledge.

This may suggest that clear objectives from the very beginning of a project could

leave little room for creative exploration and experimentation, thus limiting

opportunities for novel results. In contrast, we estimated positive effects for cohesion

and trust and interpretative learning on technical knowledge creation; hence,

indicating the importance of internal social and behavioral dynamics during project

implementation.

33

Qualitative evidence, on the other hand, emphasized more on the importance of

project management conditions. For instance, case studies revealed the value of the

continuous management support and follow-up on the part of the coordinator, with a

particular focus on the scientific and administrative obligations contracted between

the project consortium and the EU. Successful projects shared a positive assessment

of the capabilities of the coordinator, both as an R&D performer and as a “manager”.

Each of these capabilities, however, seem necessary but not sufficient for success, as

there were cases where even such well-managed projects failed at the level of

innovation outcomes due to e.g., insufficiency of the R&D results, rights conflicts

between partners beyond the control of the coordinator or the frameworks of the

instruments, or changing market conditions rendering project outcomes obsolete.

In conclusion, the present work demonstrates the value of market, firm and project-

level characteristics for understanding the success of collaborative R&D projects

within the EU Framework Programme. Confronting effectively size tensions,

establishing appropriate protection mechanisms depending on the type of innovation

produced, taking advantage of prior innovation activities, managing effectively EU

rules during project implementation and carrying out R&D projects with explicit

commercial objectives, constitute critical conditions for the success of collaborative

R&D projects.

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