辽宁石油化工大学学报

辽宁石油化工大学学报 ›› 2013, Vol. 33 ›› Issue (4): 105-108.

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基于聚类分析的我国各地区综合发展能力评价

王明珠,王莉华*   

  1. 辽宁石油化工大学经济管理学院,辽宁抚顺113001
  • 收稿日期:2013-02-01 出版日期:2013-12-25 发布日期:2017-07-14
  • 作者简介:王明珠(1988-),女,辽宁抚顺市,在读硕士。

 
Evaluation of Integrated Development Ability about Each Region of Our Country Based on Cluster Analysis

WANG MingzhuWANG Lihua   

  1. School of Economics and Management,Liaoning Shihua University,Fushun Liaoning 113001,China
  • Received:2013-02-01 Published:2013-12-25 Online:2017-07-14

摘要: 运用聚类分析方法,从经济发展能力、就业和工资、财政收入、城市建设水平、科技发展程度、教育水
平和社会保障程度等7个方面,对我国31个省市自治区的综合发展能力进行了整合分类分析。基于资源配置的不
同和政策实施方式的不同,将我国各地区综合发展能力划分为四大类。研究结果表明,彼此间存在显著差异,这种
差异反映我国各地区综合发展不协调的现状。提出了在保证我国各地区平稳快速发展的基础上缩小发展差异的对
策及建议。

关键词: 综合发展能力 , 聚类分析 , 差异 , 各地区 , 协调

Abstract:  

The cluster analysis method was used in this paper to analyze the comprehensive development ability of 31 provinces, cities and autonomous regions of China by the means of integrated classification ,from the economic development ability, employment and wages, fiscal revenue, urban construction level, the development of science and technology level, education level and social security level seven aspects. The comprehensive development ability of each region was divided into four major categories based on the differences of resource allocation and the ways of implementing policies. The research results show that there were significant differences between one another ,this difference reflected the present situation of uncoordinated development based on integrated developing ability of each region of our country. Accordingly, the countermeasures and suggestions for the steady and rapid developing synchronously throughout the whole regions were put forward.

Key words: Comprehensive development ability ,  Cluster analysis ,  Regional difference ,  ,  Different regions ,  Coordination

引用本文

王明珠,王莉华. 基于聚类分析的我国各地区综合发展能力评价[J]. 辽宁石油化工大学学报, 2013, 33(4): 105-108.

WANG Mingzhu,WANG Lihua.  

Evaluation of Integrated Development Ability about Each Region of Our Country Based on Cluster Analysis
[J]. Journal of Liaoning Petrochemical University, 2013, 33(4): 105-108.

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