On the Nature and Geography of Innovation and Interactive Learning: A Case Study of the Biotechnology Industry in the Aachen Technology Region, Germany

Abstract

So far, relatively little research has been done on sectoral differences of innovation processes. In order to learn more about these differences, we apply the knowledge base concept which helps us to characterize the nature of critical knowledge that is indispensable for innovation activities. Two knowledge bases are distinguished: the analytical (science based) and the synthetic (engineering based) knowledge base. This paper focuses on the emerging biotechnology industry in the Aachen Technology Region in Germany. It aims to identify the knowledge base which is crucial for the development of new products and processes. Additional questions are as follows: How intense are cross-sectoral knowledge transfers and labour mobility? In which way can we observe innovation-oriented systemic interactions within the region and to which extent are the biotechnology firms connected to extra-regional knowledge sources? In order to investigate these questions, we apply social network analyses and descriptive statistics. Our results show that the knowledge base that is crucial for innovation activities is primarily of analytical nature. Interactive learning of biotechnology firms within the region is clearly dominated by industry -university links, while the vertical dimension of co-operative innovation processes is rather shaped on national and global scales for most firms.

On the Implications of Knowledge Bases for Regional Innovation Policies in Germany

“…This concept stresses that industries differ substantially with regard to their specific knowledge base, of which three are distinguished: analytical (science-based), synthetic (engineering-based) and symbolic (creativity-based). On the basis of the results of three case studies in Germany representing these three types of knowledge bases, namely biotechnology in Aachen (analytical), automotive in South-West Saxony (synthetic), and the computer game industry in Hamburg (symbolic), we can conclude that there are differences among industries with different knowledge bases concerning the character of networks, innovation patterns, and knowledge exchange partners (as shown in previous publications, see Plum 2011;Plum, Hassink 2011, but also with regard to the needs for innovation policy (as shown in this paper). It is questionable, however, to what extent these differences can only be explained by differences in knowledge bases.…”

“…As written in the introduction, detailed results of the research on network patterns found in the clusters have been published elsewhere (Plum 2011;Plum, Hassink 2011. After introducing the cases in the following section, what we will do in the next is to present the hitherto unpublished policy findings of our research in order to shed light on differences in policy needs between industries with different knowledge bases.…”

“…It aims at establishing networks between relevant stakeholders from science, industry, development agencies and capital involved in and giving support to innovation processes in life sciences, with particular focus on biotechnology and medical engineering. Our main empirical outcome was that the analytical knowledge base was crucial for innovation activities in biotechnology industry in the Aachen Technology Region (Plum, Hassink 2011). The interactive learning of biotechnology firms within the region is clearly dominated by industry-university links, while for most firms the vertical dimension of co-operative innovation processes tends to be shaped at the national and global scales.…”

“…The paper presents the research results of three case studies representing these three types of knowledge bases, namely biotechnology in Aachen (analytical), automotive in South-West Saxony (synthetic), and computer game industry in Hamburg (symbolic and synthetic). Detailed results on the knowledge base and network characteristics of these case studies are published elsewhere (Plum 2011;Plum, Hassink 2011; in this paper we will focus on the policy implications of these results.…”

“…The biotech cluster is located in the former old industrial Aachen Technology Region (TR), which lies in the westernmost part of the State of North Rhine-Westphalia and borders on Belgium and the Netherlands (for more details, see Plum, Hassink 2011). Its population is about 1.3 million living in five counties (Kreise) and the major city, Aachen (240,000).…”