Abstract:

This paper, based on industrial cluster theory, uses principal component analysis (PCA) to establish an index system to evaluate the dominant competitiveness of energy industrial cluster, and applies SPSS16.0 software to analyze the factors, and identifies the principal factor influencing the dominant competitiveness in Xinjiang’s energy industry. According to Xinjiang’s 2003 to 2007 data, this paper measures their dominant competitiveness in Xinjiang’s  nine black energy-related industries. The results show that in Xinjiang’s black energy industrial clusters petroleum is stronger than coal, but with a short industrial chain and a low added value, meaning a low dominant competitiveness in Xinjiang’s black energy industrial clusters. In order to transform the resources advantages into industrial or economic advantages, this paper presents approaches to dominant competitiveness of Xinjiang’s energy industrial clusters.

Key words: industrial clusters, PCA, competitiveness, Xinjiang

摘要：

基于产业集群理论基础，通过调查研究和运用主成分分析法(PCA)构建了产业集群显性竞争力评价指标体系，运用SPSS16.0软件对各影响因素进行分析，识别出影响产业集群显性竞争力因素中的主成分，并以新疆为例进行实证研究，以新疆2003—2007年统计数据为基础，从静态和动态两方面对与新疆黑色能源相关的9个行业的显性竞争力进行测评，对计算结果进行分析和总结。结果表明：新疆黑色能源产业集群中，石油相关产业显性竞争力较煤炭相关产业强，但由于产业链短，产品附加值低，新疆黑色能源产业集群整体显性竞争力不高。为了更好地实现新疆由资源优势向产业优势进而向经济优势的转换，提出了提高产业集群竞争力的途径。

关键词: 产业集群, 主成分分析法(PCA), 竞争力, 新疆