一种基于数据包络分析的低碳出行对绿色交通发展的研究
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摘要
为了明确低碳出行对城市交通绿色性发展的积极贡献作用,从人、车、路、交通基础设施和交通环境五个层面提取衡量低碳出行对城市交通绿色性发展的主要指标,并引入数据包络分析方法中C~2R模型的等价变换线性规划模型,以广州市2005年—2012年低碳出行投入和产出的统计数据为例,借助SPSS和DEAP等数据分析工具进行实证研究.研究结果表明:随着能源的紧张和私人机动车辆的增加,发展公共交通事业已成为城市绿色交通发展的第一要素.
In order to clear the positive contribution of the low-carbon transportation to urban green traffic development in our country,the main indicators of low carbon policy to green traffic development are extracted from five aspects: the people,vehicles,roads,transportation infrastructure and transportation environment. Then the equivalent transformation model of linear programming model of C~2R is used in data envelopment analysis. Take Guangzhou city as the example to collect the relevant index data from 2005 to 2012,using SPSS and DEAP as the analysis tools to deal with the input and output of low-carbon transportation statistics data. The results of contribution rate show that,with the increase of energy tension and private motor vehicles,the development of public transport enterprise has become the first thing to the urban green traffic development.
In order to clear the positive contribution of the low-carbon transportation to urban green traffic development in our country,the main indicators of low carbon policy to green traffic development are extracted from five aspects: the people,vehicles,roads,transportation infrastructure and transportation environment. Then the equivalent transformation model of linear programming model of C~2R is used in data envelopment analysis. Take Guangzhou city as the example to collect the relevant index data from 2005 to 2012,using SPSS and DEAP as the analysis tools to deal with the input and output of low-carbon transportation statistics data. The results of contribution rate show that,with the increase of energy tension and private motor vehicles,the development of public transport enterprise has become the first thing to the urban green traffic development.
引文
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[2]BRAM K,TOMAS A,SARA V,et al.Tackling fragmented last mile deliveries to nan stores by utilizing spare transportation capacity:A simulation study[J].Sustainability,2018,10(3):653-664.
[3]LI Jing,KEVIN L,GUO M.Urban residents’response to and evaluation of low-carbon travel policies:Evidence from a survey of five eastern cities in China[J].Journal of Environmental Management,2018,217(1):47-55.
[4]MARINA V G,HARRY G,HUGO P.Transport innovation:Coping with the future[J].Transportation Planning&Technology,2003,26(6):437-447.
[5]SCHEINER J.Social inequalities in travel behavior:Trip distances in the context of residential self-selection and lifestyles[J].Journal of Transport Geography,2010,18(6):679-690.
[6]曾曦,王慈光.Logit模型的改进及其在客流分担率预测中的应用——以成渝城际铁路为例[J].交通科学与工程,2007,23(4):50-53.ZENG Xi,WANG Ciguang.Improvement of Logit model and its application in forecasting the distribution rations of passenger flows on CHENG-YU intercity railroad[J].Journal of Changsha Communications University,2007,4(23):50-53.
[7]孙秀倩.综合运输枢纽与城市交通的协调发展[J].科技信息,2010(11):521,525.SUN Xiuqian.The coordinated development of urban traffic and Integrated transport hub[J].Science&Technology Information,2010(11):521,525.
[8]李明伟,云俊,官淑琪.基于回归模型的ITS对城市交通畅通性贡献研究[J].数学的实践与认识,2015,45(22):74-80.LI Mingwei,YUN Jun,GUAN Shuqi.Research the contribution rate of ITS to urban traffic smooth based on regression model[J].Mathematics in Practice and Theory,2015,45(22):74-80.
[9]MARCIO D A,SUZANA K R.Eco-efficiency management program(EEMP):A model for road fleet operation[J].Transportation Research Part D:Transport and Environment,2004,9(6):497-511.
[10]冉立平,翟凤勇.基于DEA的中国建筑业人力资本贡献率实证分析[J].系统管理学报,2010(12):702-705.RAN Liping,ZHAI Fengyong.Empiricalanalysis on contribution rate of human capital in China’s constructionindustry based on DEA[J].Journal of System&Management,2010(12):702-705.
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