摘要
多维邻近性是近些年国际学术界在区域创新及产业集群方向新的研究视角。本文首先从多维邻近视角出发探讨了地理邻近、认知邻近对高技术产业集群创新的影响机制,并据此提出4个待验假设;进而以我国国家级软件产业园产业集群为典型案例进行实证分析,并创造性地使用人工神经网络为前导的OLS回归分析方法对待验假设进行双重递进检验。实证结果显示:在高技术产业集群的发展和成熟阶段,地理邻近对集群创新绩效产生负的影响,但负影响递减;认知邻近对集群创新绩效产生正影响;集群外部知识的获取有利于集群创新绩效提升;集群直接创新投入也促进创新绩效的提高,但边际报酬递减。
With the rise of knowledge-based economy, high-tech industry clusters and their ability to innovate become the key reason for regional development. According to the tacit knowledge and knowledge spillover theory proposed, more and more academia begin to pay attention to the new view of Dimensions of Proximity in order to explore the essential fac- tors to the innovation of high-tech industry cluster. From the view of Dimensions of Prox- imity, this article analyzes how those proximities usually work on the innovation of high- tech industrial cluster, and serve a theoretical mechanism for this process. After a discus- sion on the mechanism between high-tech industry cluster innovation and proximities, this article proposes four hypotheses of the relationships between the geographical proximity, cognitive proximity and cluster innovation, and each of these relations is transformed into mathematical formula expression. Based on the data of national software industrial parks of China in recent five years, two methods are used in the empirical tests： artificial neural network and ordinary least squares （OLS）. According to the comparison among theoreti- cal mechanism and two empirical analysis results, this paper finally draws four conclusions as follows. Firstly, during the development period and mature period of high-tech indus- trial cluster development, geographic proximity has a positive influence on innovation per- formance of high-tech industrial cluster, but the marginal effects for this are decreasing with the development of cluster. Secondly, cognitive proximity has an active influence on cluster innovation. Moreover, the learning on external knowledge can promote the in- crease of innovation very much. Fourthly, the direct investment on research and develop- ment can enforce the capacity of innovation, but the marginal return for this is decreasing.
出处
《地理研究》
CSCD
北大核心
2011年第9期1592-1605,共14页
Geographical Research
基金
教育部人文社会科学规划课题(08JA790038)
湖南省社科基金课题(2010YBA049)
关键词
高技术产业集群
地理邻近
认知邻近
创新绩效
人工神经网络
high-tech industrial cluster
geographic proximity
cognitive proximity
inno vation performance
artificial neural network
