SCIENTIA GEOGRAPHICA SINICA ›› 2019, Vol. 39 ›› Issue (2): 325-333.doi: 10.13249/j.cnki.sgs.2019.02.017

• Orginal Article • Previous Articles     Next Articles

Differentiated Knowledge Bases, Knowledge Networks, and Spatial Flows: Evidence from the Biomedical Cluster in Hamburg, Germany

Jili Xu(), Fan Yang, Desheng Xue()   

  1. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, Guangdong, China
  • Received:2017-11-20 Revised:2018-03-11 Online:2019-02-10 Published:2019-02-10
  • Supported by:
    Projects of International Cooperation and Exchanges of National Natural Science Foundation of China (41320104001), Research Funds for the Central Universities of China, Sun Yat-sen University (17lgjc04).

Abstract:

Knowledge spillover driven by industrial clusters has been considered as a key underpinning for boosting regional innovation. This article takes a case study of the biomedical cluster in Hamburg, Germany, examining social networks and spatial flow of both R&D talents and business talents in order to discuss the geographical features and formation mechanisms of knowledge spillover based on different angles and knowledge bases respectively. Empirical results indicate that: 1) Sensitivity to spatial distance of knowledge spillover based on different perspectives are differentiated. In contrast to knowledge network, knowledge flow to a greater extent relies on geographical proximity. 2) Geographical requirements of knowledge spillover of different knowledge bases differ from each other. Scientific knowledge spillovers and business knowledge spillovers are remarkably different at multi-scales with respect to linking intensity and spatial structure. 3) Local Production-Study-Research cooperation system centered on universities, research institutes, industry associations, and leading enterprises, national balanced R&D-intensive urban system of bio-industry, and selective international research collaborations with global leading regions make a joint effort to the formation of scientific knowledge network. Local diversified industrial structure, national polycentric urban system, and widespread international business collaborations with countries based on geographical, social, and institutional proximity collectively shape business knowledge network. Educational streaming, geographically balanced national talent training system, widespread spatial flow of talents across the country, and circular flow of talents in Western Europe and North America jointly form knowledge flows.

Key words: industrial cluster, innovation, knowledge network, knowledge flow, knowledge base, Germany

CLC Number: 

  • K902