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基于“五位一体”总布局的省域经济社会发展综合评价体系研究 被引量:21

Research on the Comprehensive Evaluation System of Economic and Social Development Performance for Provinces Based on the View of Five-in-one General Arrangement
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摘要 笔者从"五位一体"总布局的视角构建了经济社会发展综合评价指标体系,运用群组G1-熵权主客观组合赋权评价方法,对中国31个省份的经济社会发展进行了综合评价,并基于此对其经济社会发展综合评价结果进行了聚类分析。研究结果表明:经济发展质量和效益、政府透明度、文化创新产业、社会保障制度、生态环境是影响经济建设、政治建设、文化建设、社会建设和生态文明建设"五位一体"总布局推进的关键因素,且各省份以"五位一体"总布局推进经济社会发展过程中存在不协调、不平衡、不可持续的问题。笔者认为,政府部门应结合关键因素出台相关政策措施,统筹推进基于"五位一体"总布局的经济社会发展。 The paper constructs the comprehensive evaluation index system from the direction of the five-in-one general arrangement.The paper makes the comprehensive evaluation on the economic and social development performance of 31 provinces in China's Mainland by using the group G1-entropy combination weighting methods.And the paper makes the cluster analysis for the comprehensive evaluation results of the economic and social development performance of 31 provinces.The result shows that the quality and efficien-cy of economic development,government transparency,cultural innovation industry,social security system and ecological environment are the key influence factors of the five-in-one general arrangement development including the economic,social,political,cultural construction and ecology civilization construction.And there are some inharmonious,unbalanced and unsustainable problems in the process of the economic and so-cial development that takes the direction of the five-in-one general arrangement.So the government should propose some measures suiting local conditions to promote the economic and social development based on the five-in-one general arrangement.
作者 李旭辉 朱启贵 LI Xu-hui;ZHU Qi-gui
出处 《中央财经大学学报》 CSSCI 北大核心 2018年第9期107-117,128,共12页 Journal of Central University of Finance & Economics
基金 国家社会科学基金重大项目“完善经济社会发展考核评价体系研究”(项目编号:14ZDA013) 国家统计局全国统计科学研究项目“基于五位一体总布局的主体功能区经济社会发展动态组合评价研究”(项目编号:2016LY49)。
关键词 “五位一体”总布局 经济社会发展 综合评价体系 组合赋权法 聚类分析 Five-in-one general arrangement Economic and social development Comprehensive evaluation system Combination weighting methods Cluster analysis
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