基于DEA模型的沿海九省物流效率分析
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摘要
运用DEA模型,选取交通运输业从业人数、物流业固定资产投资、等级公里数作为投入指标,选取物流业增加值、货运量周转量、地区GDP作为产出指标,对2012—2016年沿海九省的物流效率进行分析和评价。结果表明,浙江省、河北省、江苏省及辽宁省的物流效率的DEA为有效,而广东省、福建省、广西壮族自治区、海南省和山东省的物流效率的DEA为非有效。对影响沿海九省物流效率的因素分析结果表明,各个指标的影响程度不同,投入指标中的交通运输、仓储及邮政业从业人员与等级公里数对沿海九省的物流效率影响较大,影响程度为0.031;产出指标中的货运周转量对沿海九省物流效率的影响较大,影响程度为0.133。据此,建议物流DEA有效的省份继续保持自身的优势并发挥带头作用,加大力度发展城市群物流,建立完善的现代物流管理体制;而物流DEA非有效的省份借鉴其他省份成功的经验,结合自身实际情况作出相应调整。
The DEA model is used to analyze and evaluate the logistics efficiency of China's nine coastal provinces from 2012 to 2016 by selecting the number of people employed in the transportation industry, the ?xed asset investment in the logistics industry and the graded mileage as input indicators, and the added value of the logistics industry, the turnover of freight volume and regional GDP as output indicators. The results show that the DEA of logistics ef?ciency is effective in Zhejiang Province, Hebei Province, Jiangsu Province and Liaoning Province, but not in Guangdong Province, Fujian Province, Guangxi Zhuang Autonomous Region, Hainan Province and Shandong Province. The analysis results of the factors that affect the logistics ef?ciency of the nine coastal provinces show that the degree of in?uence of each index is different. The transportation, warehousing,postal workers and graded mileage in the input index have a great in?uence on the logistics ef?ciency of the nine coastal provinces, with the degree of in?uence being 0.031. The freight turnover in the output index has a great in?uence on the logistics ef?ciency in the nine coastal provinces, and the in?uence degree is 0.133. Therefore, it is suggested that provinces with effective logistics DEA should continue to maintain their own advantages and play a leading role in developing logistics in urban agglomerations and establishing a sound modern logistics management system. The provinces with non-effective logistics DEA should learn from the successful experience of other provinces and make corresponding adjustments according to their own actual conditions.
The DEA model is used to analyze and evaluate the logistics efficiency of China's nine coastal provinces from 2012 to 2016 by selecting the number of people employed in the transportation industry, the ?xed asset investment in the logistics industry and the graded mileage as input indicators, and the added value of the logistics industry, the turnover of freight volume and regional GDP as output indicators. The results show that the DEA of logistics ef?ciency is effective in Zhejiang Province, Hebei Province, Jiangsu Province and Liaoning Province, but not in Guangdong Province, Fujian Province, Guangxi Zhuang Autonomous Region, Hainan Province and Shandong Province. The analysis results of the factors that affect the logistics ef?ciency of the nine coastal provinces show that the degree of in?uence of each index is different. The transportation, warehousing,postal workers and graded mileage in the input index have a great in?uence on the logistics ef?ciency of the nine coastal provinces, with the degree of in?uence being 0.031. The freight turnover in the output index has a great in?uence on the logistics ef?ciency in the nine coastal provinces, and the in?uence degree is 0.133. Therefore, it is suggested that provinces with effective logistics DEA should continue to maintain their own advantages and play a leading role in developing logistics in urban agglomerations and establishing a sound modern logistics management system. The provinces with non-effective logistics DEA should learn from the successful experience of other provinces and make corresponding adjustments according to their own actual conditions.
引文
[1]邹筱,刘亚楠.湖南省新型城镇化与物流业关联机制实证研究[J].湖南工业大学学报, 2017,31(6):83-88.
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[3]MIN Hokey,JOO Secony Jong. Benchmarking the Operational Ef?ciency of Third Party Logistics Providers Using Data Envelopment Analysis[J]. Supply Chain Management,2006,11(3):7259-7265.
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[5]MARKOVITS-SOMOGYI R,BOKOR Z. Assessing the Logistics Ef?ciency of European Countries by Using the DEA-PC Methodology[J]. Transport,2014,29(2):137-145.
[6]柳键,邱国斌.基于DEA模型的我国物流投入产出效率分析[J].物流工程与管理,2011,33(1):5-9.
[7]张雪青.“一带一路”区域物流协同发展分析[J].统计与决策,2016(8):108-110.
[8]詹荣富,黄立军.粤港澳大湾区各地物流效率现状原因及对策分析[J].物流工程与管理,2018,40(11):19-22.
[9]CHARNES A,COOPER W W,RHODES E. Measuring the Efficiency of Decision Making Units[J]. European Journal of Operational Research,1978(2):429-444.
[10]BANKER R D,CHARNES A,COOPER W W. Some Models for Estimating Technical and Scale Inef?ciencies in Data Envelopment Analysis[J]. Management Science,1984,30(9):1078-1092.
[11]李芳,龚新蜀,黄保连,等.基于DEA分析法的干旱区绿洲产业结构优化评价:以新疆为例[J].生态经济,2012(12):36-39.
[12]李红锦,李胜会.基于DEA模型的城市群效率研究:珠三角城市群的实证研究[J].软科学, 2011,25(5):91-95.
[13]王琴梅,谭翠娥.对西安市物流效率及其影响因素的实证研究:基于DEA模型和Tobit回归模型的分析[J].软科学,2013,27(5):70-74.
[14]肖丹,刘联辉.基于SE-DEA模型的广东城市物流效率评价分析[J].物流技术,2011,30(11):101-103.
[15]乐小兵,王瑛.基于DEA模型的广西物流服务效率评价研究[J].科技管理研究,2014,34(5):54-57.
[16]孟魁.基于三阶段DEA方法的中部六省物流效率评价[J].统计与决策,2014(2):57-60.
[17]COELLI T J,RAO D S P,O'DONNELL C,et al. An Introduction to Ef?ciency and Productivity Analysis[M].2nd ed. NewYork:Springer Science&Business Media Inc,2005:60-65.
[18]田淑英,许文立.基于DEA模型的中国林业投入产出效率评价[J].资源科学,2012,34(10):1944-1950.
[19]曾珍香,顾培亮,张闽. DEA方法在可持续发展评价中的应用[J].系统工程理论与实践,2000,20(8):114-118.
[2]SEHINNAR A P. Measuring Productive Efficiency of Public Service Provision[D]. Pennsylvania:University of Pennsylvania,1980:143-148.
[3]MIN Hokey,JOO Secony Jong. Benchmarking the Operational Ef?ciency of Third Party Logistics Providers Using Data Envelopment Analysis[J]. Supply Chain Management,2006,11(3):7259-7265.
[4]CULLINANE K,WANG T. The Efficiency Analysis of Container Port Production Using DEA Panel Data Approaches[J]. OR Spectrum,2010,32(3):717-738.
[5]MARKOVITS-SOMOGYI R,BOKOR Z. Assessing the Logistics Ef?ciency of European Countries by Using the DEA-PC Methodology[J]. Transport,2014,29(2):137-145.
[6]柳键,邱国斌.基于DEA模型的我国物流投入产出效率分析[J].物流工程与管理,2011,33(1):5-9.
[7]张雪青.“一带一路”区域物流协同发展分析[J].统计与决策,2016(8):108-110.
[8]詹荣富,黄立军.粤港澳大湾区各地物流效率现状原因及对策分析[J].物流工程与管理,2018,40(11):19-22.
[9]CHARNES A,COOPER W W,RHODES E. Measuring the Efficiency of Decision Making Units[J]. European Journal of Operational Research,1978(2):429-444.
[10]BANKER R D,CHARNES A,COOPER W W. Some Models for Estimating Technical and Scale Inef?ciencies in Data Envelopment Analysis[J]. Management Science,1984,30(9):1078-1092.
[11]李芳,龚新蜀,黄保连,等.基于DEA分析法的干旱区绿洲产业结构优化评价:以新疆为例[J].生态经济,2012(12):36-39.
[12]李红锦,李胜会.基于DEA模型的城市群效率研究:珠三角城市群的实证研究[J].软科学, 2011,25(5):91-95.
[13]王琴梅,谭翠娥.对西安市物流效率及其影响因素的实证研究:基于DEA模型和Tobit回归模型的分析[J].软科学,2013,27(5):70-74.
[14]肖丹,刘联辉.基于SE-DEA模型的广东城市物流效率评价分析[J].物流技术,2011,30(11):101-103.
[15]乐小兵,王瑛.基于DEA模型的广西物流服务效率评价研究[J].科技管理研究,2014,34(5):54-57.
[16]孟魁.基于三阶段DEA方法的中部六省物流效率评价[J].统计与决策,2014(2):57-60.
[17]COELLI T J,RAO D S P,O'DONNELL C,et al. An Introduction to Ef?ciency and Productivity Analysis[M].2nd ed. NewYork:Springer Science&Business Media Inc,2005:60-65.
[18]田淑英,许文立.基于DEA模型的中国林业投入产出效率评价[J].资源科学,2012,34(10):1944-1950.
[19]曾珍香,顾培亮,张闽. DEA方法在可持续发展评价中的应用[J].系统工程理论与实践,2000,20(8):114-118.