辨识产业集群的定性方法,过于依赖专家的主观判断,存在诸多局限性。基于投入产出表构建一个反映产业之间功能联系的矩阵,采用主成分分析定量辨识基于经济技术联系的区域产业集群。此外,设计了几个衡量集群内产业联系强度的系数来判定被辨识集群的合理性,并通过相关系数衡量集群内产业的空间集聚特性。以北京市1997年投入产出表上74个制造业行业为例,采用主成分分析方法辨别出14个产业集群,包括钢压延加工集群、有机化学制品集群、电子元器件集群以及棉毛纺织集群等。集群内产业功能联系紧密,相关产业内的企业在空间上集聚,符合产业集群的理论定义。
Recently, industrial cluster has been a hot focus in economics, management and geography. Regional and industrial policies are also oriented towards the promotion of industrial clusters. The identification of local clusters, however, is still poorly established. Qualitative methods of identifying industrial clusters, such as Industry Perception Method, rely heavily on the experts' subjective judgments and lack strict rules to make decisions, therefore confine to a number of limitation. For example, the regionally dominant firms may mislead the researchers' judgments. The cross-sectional comparison of industrial clusters in different regions could be difficult. This paper demonstrates that industrial clusters can be recognized using principle component analysis (PCA). Based upon a correlation matrix, which is derived from the input-output table and measures backward and forward industrial linkages, this paper applies PCA to identifing industrial clusters. Several indices are further developed to evaluate PCA's performance in identifying regional industrial clusters. Correlation analysis is then applied to testing the spatial agglomeration of related industries. Taking Beijing as a case, this paper identifies 14 industrial clusters based on the 1997 inputing output table. Industrial clusters are formed around smelting and pressing in ferrous metals, chemicals, electronics, textiles and car production etc. Industries in those clusters are strongly tied with each other through sale-purchase linkages, and agglomerate in similar locales.
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