丝绸之路经济带沿线区域低碳物流效率测度及影响因素研究
On Low-Carbon Logistics Efficiency of Regions along the Silk Road Economic Belt
李凤 1郭烨锋1
作者信息
- 1. 新疆财经大学,新疆 乌鲁木齐 830012
- 折叠
摘要
实现"双碳"目标,发展低碳物流是必由之路.文章选取2010-2020年丝绸之路经济带沿线的我国12个省、自治区、直辖市相关数据,采用三阶段DEA模型和全局Malmquist指数分析沿线区域低碳物流效率,并采用Tobit回归分析影响因素.结果表明:研究期内,丝绸之路经济带沿线区域低碳物流效率呈波浪式变化态势,并呈"中间高、两头低"的特征;地区科技水平越高越能有效减少低碳物流投入冗余,产业结构越合理越能有效减少人力资源浪费;加强融合基础设施建设、提升货物进口额和能源利用效率对提高低碳物流效率有促进作用,传统基础设施建设和纯新型基础设施建设则对低碳物流效率的提高有抑制作用.今后应积极推动传统物流产业数字化转型,进一步优化能源结构,助推低碳物流高质量发展.
Abstract
In the context of China's carbon peaking and carbon neutrality goals,the low-carbon logistics efficiency along the Silk Road Economic Belt has become an issue worth studying.This study selected data from provinces along the Silk Road Eco-nomic Belt from 2010 to 2020,analyzed their low-carbon logistics efficiency from both static and dynamic perspectives by us-ing three-stage DEA and global Malmquist index and analyzed its influencing factors by using Tobit regression.The research has found that excellent regional technological level can effectively reduce redundancy in low-carbon logistics investment,and a reasonable industrial structure can effectively reduce waste of manpower investment.The overall low-carbon logistics effi-ciency along the Silk Road Economic Belt shows a wave like development trend with the distribution characteristics of"high ef-ficiency in the middle and low efficiency at both ends"in each region.The integration of infrastructure construction,import val-ue of goods,and energy utilization all play a role in promoting low-carbon logistics efficiency.Traditional infrastructure con-struction and purely new-type infrastructure have an inhibitory effect on low-carbon logistics efficiency.In the future,it is of great necessity to actively promote the digital transformation of the traditional logistics industry,further optimize the energy structure,and promote the high-quality development of low-carbon logistics.
关键词
丝绸之路经济带/低碳物流效率/SBM模型/全局Malmquist指数/Tobit回归Key words
the Silk Road Economic Belt/low-carbon logistics efficiency/SBM model/global malmquist index/Tobit regres-sion引用本文复制引用
基金项目
国家社会科学基金(20CGL026)
新疆财经大学研究生科研创新项目(XJUFE2023K046)
新疆维吾尔自治区研究生创新项目(XJ2023G243)
出版年
2024
NETL
NSTL
维普
万方数据