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基于组合赋权法的我国CO2排放量影响因素的评价研究
引用本文:孟凡生,李美莹.基于组合赋权法的我国CO2排放量影响因素的评价研究[J].运筹与管理,2014,23(1):157-165.
作者姓名:孟凡生  李美莹
作者单位:哈尔滨工程大学 经济管理学院,黑龙江 哈尔滨 150001
基金项目:国家自然科学基金面上项目(71072075);国家软科学项目(2010GXQ5D328);黑龙江省社会科学重大咨询项目(12G003)
摘    要:为客观和准确地挖掘和评价我国CO2排放量影响因素,选取技术投入、对外贸易开放程度、产业结构、能源消费结构、经济增长水平、人口规模和绿色植被用地面积等因素作为评价依据,构建我国CO2排放量影响因素指标体系。在此基础上,基于组合赋权法构建我国CO2排放量影响因素评价模型,实证分析2000~2011年我国CO2排放量影响因素。组合赋权法结果显示:技术投入、产业结构、能源消费结构、经济增长和绿色植被用地面积是影响我国CO2排放量的主要因素。组合赋权法在我国CO2排放量影响因素评价分析的运用,提高了评价的客观性和科学性,为进一步确定CO2排放量影响因素提供有价值的参考。

关 键 词:可持续发展  碳排放  影响因素评价  组合赋权  
收稿时间:2012-12-15

Research on Influence Factors of Carbon Dioxide Emissions in China Based on the Method of Combination Weights
MENG Fan-sheng,LI Mei-ying.Research on Influence Factors of Carbon Dioxide Emissions in China Based on the Method of Combination Weights[J].Operations Research and Management Science,2014,23(1):157-165.
Authors:MENG Fan-sheng  LI Mei-ying
Affiliation:School of Economics and Management, Harbin Engineering Umiversity, Harbin 150001, China
Abstract:We select technology investment, open degree of foreign trade, industrial structure, energy consumption structure, economic growth level, population scale and green vegetation land area as the object of evaluation, construct index system of influence factors of carbon dioxide emissions in China, in order to objectively and exactly dig and evaluate the influence factors of carbon dioxide emissions in China. Establish influence factors of carbon dioxide emissions evaluation model based on the method of combination weights. Select relevant data from 2000~2011 in China to carry out empirical analysis for the influence factors of carbon dioxide emissions. Empirical results show technology investment, industrial structure, energy consumption structure, economic growth level, green vegetation land area are the key influence factors of carbon dioxide emissions in China. The use of combination weights to evaluate and analyze the influence factors of carbon dioxide emissions in China improves the objective and scientific evaluation result. Moreover, provides a valuable reference for further confirmation of carbon dioxide emissions influence factors.
Keywords:sustainable development  carbon dioxide emissions  influence factors evaluation  combination weights  
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