知识分布、衰减程度与产业集群创新模式的内在机制研究

doi:10.16381/j.cnki.issn1003-207x.2018.12.018

Abstract

Abstract: It has not been fully understood what the mechanisms are responsible for industrial cluster's innovation. In this paper, to investigate the mechanisms and effects of knowledge distribution and depreciation on industrial cluster's innovation patterns, endogenous knowledge spillover willingness and absorptive capacity are cossidered from the perspective of knowledge flow. Then, a modified industrial cluster's evolutionary model is proposed, including three kinds of innovation patterns. The simulation experiment is carried out on a cluster network. The results of simulation indicate that blending innovation demonstrates the best of innovative output, and different evolutionary paths of innovative output are presented between the external absorptive innovation and internal independent innovation. And in terms of the external absorptive innovation and blending innovation, industrial cluster with evenly knowledge distribution performs the best of innovative output, followed by industrial cluster with concentrated knowledge distribution and industrial cluster with heterogeneous knowledge distribution, while in terms of internal independent innovation, the best of innovative output comes from the industrial cluster with concentrated knowledge distribution. In addition, sensitivity for knowledge depreciation shows the phased differences among three kinds of innovation patterns. The conclusions would have good theoretical and practical significance for industrial cluster's innovation and sustainable development.

Key words: knowledge distribution, knowledge depreciation, knowledge spillover, absorptive capacity, innovation patterns

CLC Number:

ZHANG Ying-qing, FAN Ru-guo, LUO Ming. A Study on the Inner Mechanisms of Knowledge Distribution, Depreciation on Industrial Clusters' Innovation Patterns[J]. Chinese Journal of Management Science, 2018, 26(12): 186-196.

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A Study on the Inner Mechanisms of Knowledge Distribution, Depreciation on Industrial Clusters' Innovation Patterns

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