基于DEA与灰色关联模型的中西部18省物流业效率研究  

Study on Efficiency of Logistics Industry of 18 Provinces in Central and Western Regions Based on DEA and Grey Correlational Model

作　　者：周林荣[1] 骆欣[1] ZHOU Lin-rong;LUO Xin(School of Management,Zunyi Normal University,Zunyi 563006,China)

机构地区：[1]遵义师范学院管理学院,贵州遵义563006

出　　处：《遵义师范学院学报》2022年第3期53-58,共6页Journal of Zunyi Normal University

基　　金：2022年贵州省教育厅人文社科项目“新时代贵州特色农业经济高质量发展与绿色发展的耦合协调路径研究”(2022QN010)。

摘　　要：采用经典DEA-CCR与DEA-BCC模型分析了中西部18省物流业的效率,并运用灰色关联模型分析投入与产出要素对物流业效率的影响程度。结果表明,2018年我国中西部18省的物流业综合技术效率偏低,中部明显高于西部。根据DEA投入过剩与产出不足投影规则,18省物流业效率经过3次调整可以实现DEA有效,说明资源要素的合理优化很重要。投入因素与产出因素对物流业效率的影响程度相当,其中运输线路里程数对物流业效率影响最大。This paper took DEA-CCRand DEA-BCCto analyze the efficiency of logistics industry of 18 provinces in central and western regions,and used grey correlational model to study the influential degree of logistics industry caused by input and output factors.The result showed that the comprehensive skill efficiency was low in 18 provinces in central and western regions of China,and the central regions were comparatively more advanced than the western among them.According to the projection rules of DEA excess input and insufficient output,the efficiency of logistics industry in 18 provinces can make DEA work after three adjustments,which showed that the reasonable optimization of resource factors was very important.Input factors and output factors had the same impact on the efficiency of logistics industry,among which the mileage of transportation line had the greatest impact on the efficiency of logistics industry.

关 键 词：数据包络分析(DEA) 灰色关联模型 物流业效率 影响因素 

分 类 号：U1[交通运输工程]