Cluster Performance reconsidered: Structure, Linkages and Paths in the German Biotechnology Industry, 1996-2003

This paper addresses the evolution of biotechnology clusters in Germany between 1996 and 2003, paying particular attention to their respective composition in terms of venture capital, basic science institutions and biotechnology firms. Drawing upon the significance of co-location of "money and ideas", the literature stressing the importance of a cluster's openness and external linkages, and the path dependency debate, the paper aims to analyse how certain cluster characteristics correspond with its overall performance. After identifying different cluster types, we investigate their internal and external interconnectivity in comparative manner and draw on changes in cluster composition. Our results indicate that the structure, i.e. to which group the cluster belongs, and the openness towards external knowledge flows deliver merely unsystematic indications with regard to a cluster's overall success. Its ability to change composition towards a more balanced ratio of science and capital over time, on the other hand, turns out as a key explanatory factor. Hence, the dynamic perspective proves effective illuminating cluster growth and performance, where our explorative findings provide a promising avenue for further evolutionary research

What can CIS data tell us about technological regimes and persistence of innovation?

This paper analyses the link between technological regimes and persistence in innovation at the firm level. It reviews the literature on persistence of innovation, measurement issues and technological regimes. It weighs up the advantages and disadvantages of using Community Innovation Survey (CIS) data in this debate. Technological regimes and innovation persistence are analysed with a balanced panel of around 4,000 firms that responded to the latest three waves of the UK version of the CIS. Key explanatory variables include measures of appropriability, cumulativeness, technological opportunity and closeness to the science base. We find that certain links between type of industry and characteristics of technological regime are more appropriate for analysis using CIS data, whereas others remain problematic

Patterns of innovation in UK industry: exploring the CIS data to contrast high and low technology industries

This paper is divided into two parts. The first part is an examination of the OECD classification of industries into high, medium and low technology industries, to look at the basis for this classification and to use that as a benchmark with which to classify the Community Innovation Survey (CIS) data for the UK into similar groupings. The industries are ranked according to their research intensities and the rankings between the two datasets are compared. Some features of the UK rankings are highlighted and anomalies between the two datasets pointed out. The second part of the paper goes on to use the OECD classification into high, medium and low technology industries, applied to the CIS dataset, to contrast patterns of innovation in high technology industries with those in low technology industries. We build on the three types of innovation surveyed in the CIS, namely product, process and organisational innovation and contrast those types across high and low technology sectors. The expected relationship between high technology industries and product innovation holds - that enterprises tend to do more product innovation, the higher their research intensity. But process innovation does not conform to this pattern and there is not such a clear division between high and low technology industries. However the way they do process innovations differs with high technology industries more reliant on internal resources whereas lower technology industries tend to do it using external resources in collaboration with others. Organisational innovation is more complex, with certain types of innovation done as widely by lower technology industries as by the more research intensive industries. This supports the idea that all types of innovation should be considered, with the diffusion of ICTs making an impact across the technological spectrum of industries and showing up in various forms of organisational innovation