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"双碳"背景下长三角农产品低碳物流效率及影响因素

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针对长三角农产品低碳物流效率问题,选取2013-2022 年长三角三省一市的农产品物流数据,利用非期望产出Super-SBM模型及GML指数,分别从静态与动态两个层面对长三角地区农产品低碳物流效率进行测算.结果显示:长三角农产品低碳物流效率平均水平仅 2022 年达到有效状态,各区域也具有较大的差异、且发展不平衡,效率从高到低依次为上海、安徽、浙江、江苏;GML指数均值呈递增趋势,技术进步是其增长的关键因素.通过Tobit回归模型分析该区域农产品低碳物流效率的影响因素,结果表明:物流效率与物流资源利用率和载货汽车数量呈显著正相关关系,与信息化水平呈显著负相关关系;政府支持未能通过显著性检验.
The Efficiency and Influencing Factors of Low-Carbon Logistics of Agricultural Products in the Yangtze River Delta Under the Background of"Double Carbon"
In view of the low-carbon logistics efficiency of agricultural products in the Yangtze River Delta,the logistics data of agricultural products in three provinces and one city in the Yangtze River Delta from 2013 to 2022 were selected,and the low-carbon logistics efficiency of agricultural products in the Yangtze River Delta region was measured from the static and dy-namic levels by using the undesirable output Super-SBM model and GML index,respectively,and the results showed that:the average level of low-carbon logistics efficiency of agricultural products in the Yangtze River Delta only reached an effective state in 2022,and there were large differences and unbalanced development in each region,the efficiency values from high to low Shanghai,Anhui,Zhejiang,and Jiangsu;the average value of the GML index showed an increasing trend,and techno-logical progress is the key factor for its growth.The Tobit regression model was used to analyze the influencing factors of low-carbon logistics efficiency of agricultural products in the region,and the results showed that the logistics efficiency was signifi-cantly positively correlated with the utilization rate of logistics resources and the number of trucks,and negatively correlated with the level of informatization.Government support failed the significance test.

double carbonYangtze River Deltalow-carbon logistics of agricultural productsSuper-SBM model of undes-ired outputGML indexTobit regression model

翟胜韬、王建民

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安徽理工大学 经济与管理学院,安徽 淮南 232000

双碳 长三角 农产品低碳物流 非期望产出Super-SBM模型 GML指数 Tobit回归模型

安徽省高校优秀科研创新团队项目

2023AH010026

2024

枣庄学院学报
枣庄学院

枣庄学院学报

CHSSCD
影响因子:0.219
ISSN:1004-7077
年,卷(期):2024.41(5)