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The model and empirical analysis of knowledge spillover effects in hi-tech industry clusters
Huang Zhiqi
2013, 34(1):
154-162.
Knowledge spillover is a prominent phenomenon of hi-tech industrial clusters. From the perspective of spin-off companies, a data model, which mainly includes key elements, such as knowledge spillover, knowledge loss, R&D, and knowledge acquisition, is built to carry out a dynamic analysis. Based on the dynamic panel data model, an empirical analysis is conducted to analyze the effect and difference between R&D and knowledge spillover by using the estimation method of System GMM. The result of the analysis shows that although R&D exerts a remarkable regional difference and time delay effect on the innovation ability of industrial cluster, and a negative effect of knowledge spillovers i.e. corporate knowledge loss will appear in the hi-tech industry cluster within the short term; if enterprises continue to increase their investment in R&D, the accumulative effect of knowledge spillover will arise, there would be a long term effect of knowledge spillover, that is, the total amount of knowledge will increase inside the cluster, and each enterprise is able to have the opportunity to get and utilize more external knowledge, thus a virtuous circle of knowledge generation and upgrade will be formed in the hi-tech industrial cluster.
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