Research project S2/001/02 (Research action S2)
Universities and public research centres are able to play a key role in encouraging knowledge-intensive economic activity and, as a result, also contribute to regional growth and development.
Although research has previously highlighted the importance of universities and research centres, recommendations in respect of specifying best practices for knowledge transfers are still somewhat more vague. In order to be able to contribute pro-actively, universities and research centres may use a number of knowledge-transfer mechanisms.
In so doing, however, it is advisable for them to make allowance for a broad spectrum of interactions with other relevant actors (from local and national authorities through to local and international companies and research partners).
The intention with this research project is to provide an insight into best practices for knowledge-creating bodies (such as universities and research centres): in what way(s) are these knowledge-creating bodies able to contribute to the development of sustainable, knowledge-intensive economic activity?
This leads us directly on to the central issues within this research proposal:
In accordance with what criteria might a portfolio of transfer mechanisms be created that will contribute to both regional as well as extra-regional interactions between knowledge-creating bodies and their environment?
What is the role and impact of moderating variables - situated within the fields of the knowledge-creating bodies (university/research centre) - on the effectiveness of the transfer mechanisms used?
What role do regional characteristics play in this regard?
And how important are the interactions between these different types of variables?
The specific tasks within the PROJECT are as follows:
A. Identification of assorted knowledge transfer mechanisms, moderating variables, and development of relevant indicators
The logical first step within this project covers the development of an exhaustive set of transfer mechanisms that are able to use the knowledge centres. Research suggests that the suitability/relevance of specific transfer mechanisms is tempered by both regional (industrial) characteristics (Audrestch, 1995; Varga, 1999) as well as those of the body/research group or individual researcher (Shane, 2001). For instance, factors that play a key role include the nature of the knowledge transfer strategy and the supporting infrastructure and resources. The range and nature of disciplines within a knowledge centre will have a bearing on the relevance of certain transfer mechanisms (Van Looy, Debackere & Andries, 2001). Ultimately, regional characteristics will determine aspects such as the possibility and relevance of any transfer mechanisms (Varga, 1999).
B. Identification of a set of relevant knowledge centres (total: n=48)
During the next stage, a set of relevant knowledge centres will be selected. The proposed framework for reflection mentioned earlier reveals two types of selection criteria: the first set relates to the characteristics of the knowledge-generating bodies; the second involves regional characteristics. The following criteria are suggested in relation to the knowledge centres:
a) size (small-large),
b) range of disciplines (specialised versus broad),
c) research orientation profile (basic versus applied),
d) acquired experience as regards knowledge transfer mechanisms (high versus low).
Regional innovation indicators will be used as regional characteristics. These will allow a distinction to be drawn between highly innovative regions and less innovative ones (European Report on S&T Indicators, 1997). Furthermore, the typology developed by Clarysse and Muldur (1997) may be used in order to chart Europe’s regional diversity in terms of innovation. The result will be an organisation containing 48 research bodies for analysis in 12 different regions.
Given the relevance in terms of developing policy recommendations, all of the major Belgian players (both universities as well as research centres) (n=10) are being included in the analysis. The majority of the sample will be located in Europe. As previous research (e.g. Porter, 1995) has hinted at differences in the enterprise-driven character of European versus North American universities and research centres, a comparative sample of knowledge centres in the US will be analysed (n=8).
C. Development of a typology of interactions based on the databank developed during Phase B. Research into the impact of moderating variables
On the basis of the databank developed during Phase B, relations between the different transfer mechanisms will be analysed in order to produce a classification of knowledge transfer configurations. As a first step, however, conventional descriptive and multivariate analysis techniques will be used in order to make allowance for moderating variables. Classification-orientated techniques will also be used in order to differentiate between configurations. Possible methods include cluster analysis, (q) factor analysis, multidimensional scale methods (MDS), hierarchical clustering and classification (Miller, 1978 & 1981; Miller & Friesen, 1986) as well as the "Anselin" method explained by Varga (1999). The intention is to produce a select number of economically described configurations. During a subsequent phase, typical cases will be analysed in detail for each resultant configuration cluster.
D. In-depth research involving a number of case studies for the various configuration types as a means of assessing their effectiveness.
Based on the typology from phase C, we shall investigate in detail the dynamics contained in the different configurations. Using interviews and a detailed longitudinal analysis of the applied mechanisms for knowledge transfer, more accurate insights will be obtained into the role and impact of the various mechanisms and the impact of interactions with the local and global environment. At the same time, historical developments will be charted as these may offer clues as to the development of transition paths (Van Looy, Debackere, Andries, 2001). For that reason, we will develop this particular phase’s interview protocol and document analysis so that they adhere to the philosophy behind longitudinal case studies (Pettigrew, 1990; Eisenhardt, 1991). Finally, the tangible effects of the applied transfer mechanisms will be widely documented within a longitudinal perspective: number and value of research contracts and their evolution over time, number of spin-offs and their economic characteristics (turnover, employment, etc.), number of grants and their revenue stream, etc.
E. Development of policy implications
Clearly, the approach outlined above will produce insights into the development of effective transfer mechanisms for a variety of situations. Analysis will produce policy recommendations at the level of knowledge-generating companies (crucial ingredients in improving knowledge transfer in view of the presence of moderating elements at the institutional and regional level). Moreover, the analysis will contribute to our understanding of regional development policy, followed above all by a regional development policy geared to encouraging innovation and knowledge-intensive economic activity. The above approach may result in the tentative formulation of development strategies that will set in train a shift from average to higher levels of knowledge-intensive regional activity. Finally, comparisons between knowledge centres in Europe and those in the United States may provide an insight into the European innovation paradox.
