Mapping innovative clusters in national innovation systems - Alfred Spielkamp; Katrin Vopel (Zentrum für Europäische Wirtschaftsforschung (ZEW), 1998)
In the following paragraphs we will discuss the ?mapping of innovative clusters in national innovation systems?. For this we have used a data set of almost 3.000 firms that participated in the first and fifth survey of the Mannheimer Innovation Survey (which is comparable with CIS data). The Community Innovation Survey (CIS) is an initiative of the EU Commission and a joint survey of DG XIII/SPRINT/EIMS and Eurostat. To begin with we will, in the context of a definition of innovation systems, highlight the outline conditions for innovations in Germany, focusing above all on the basis of innovations, science and engineering. This is followed by a step-by-step empirical analysis of the mapping of innovative clusters at the company level which is based on the Community Innovation Survey set of data; and finally the structural influences (size-effect, effects of sectors/industries) on the innovative behaviour or innovative styles are presented. The explanatory power of structural influences on the innovative behaviour will also be analysed as well as the influence of other variables such as information flows and cooperation patterns within the innovation system of Germany. In the summary at the end of this paper we will suggest starting points for potential implications for innovation policy in order to be able to develop generic and specific policies for the different industry clusters. As far as we know from firms innovating at a certain level of organisation, they use a special portfolio of information and knowledge transfer strategies that can not simply be transferred to firms which are not (yet) innovative. While accepting that innovative inhouse activities are necessary to keep track with international developments and competition, a highly innovative atmosphere within the economy which supports innovative activities should be among the main goals of innovation policy. Furthermore, firms need to have an absorptive capacity to transform knowledge into innovations that bring economic success.
Keywords: O32; O38; 330; Systems of Innovation; Cluster Analysis; Knowledge Distribution; Research and Technology Policy; Innovation; Industrielle Forschung; Technologietransfer; Wissenstransfer; Innovationspolitik; Schätzung; Deutschland