摘要
文章选取中国30个省份为研究对象,采用考虑非期望产出的SBM-Undesirable模型,并构建DEA-Malmquist指数模型,运用探索性数据分析法分析物流业全要素能源效率的时空演变,将各地区的减排潜力定量划分为4种类型,比较在设定的3种不同情景下,物流业减排潜力的大小。研究结果表明:物流业全要素能源效率指数的时间演变趋势为上升-下降-上升,全要素能源效率指数均值为0.974,全局总体发展呈波动状态,技术进步的降低桎梏了物流业的发展;空间格局方面,全局正相关性整体趋势呈上升-下降-上升-下降的波动格局,局部邻近地区之间表现出正向影响的空间效应,而表现高水平的地区未能发挥出辐射带动作用;各地区所属类型划分不同,不同情景下各地的减排潜力存在巨大差异,决策者的偏好不同会影响地区物流业的减排空间,导致减排责任分摊结果不同。
The paper selected 30 provinces in China as the research object,by considering the unexpected output of SBMUndesirable model,and built DEA-Malmquist index model.With using exploratory data analysis,analyzed the spatio-temporal evolution of total factor energy efficiency in logistics industry.The regional quantitative reduction potential was divided into four types,and compared the differences of the logistics industry emissions reduction potential in three different scenarios.The results show that the time evolution trend of the total factor energy efficiency index in logistics industry was uptrenddowntrend-uptrend,while the average value of the total factor energy efficiency index was 0.974.The overall development was in a state of fluctuation,and the reduction of technological progress had hindered the development of the logistics industry.In terms of spatial pattern,the overall positive correlation showed a fluctuating pattern of uptrend-downtrend-uptrenddowntrend.The spatial effect of positive influence was indicated in local neighboring areas,while the areas with high level fallen to play a radiation-driven role.Because different regions belonged to different types,that there were huge diverse in the emission reduction potential of different regions under various scenarios.Different preferences of decision makers would affect the emission reduction space of regional logistics industry,which lead to different results of emission reduction responsibility allocation.
作者
李健
刘恋
LI Jian;LIU Lian(Research Center of Circular Economy and Corporate Sustainable Development,Tianjin University of Technology,Tianjin 300384,China;Department of Management and Economic,Tianjin University,Tianjin 300072,China)
出处
《环境科学与技术》
CAS
CSCD
北大核心
2019年第11期222-231,共10页
Environmental Science & Technology
基金
教育部哲学社会科学研究重大课题攻关项目(15JZD021)
天津市科技计划项目(18ZLZDZF00190).
关键词
全要素能源效率
时空演变
影子价格
减排潜力
total factor energy efficiency
spatio-temporal evolution
shadow price
emissions reduction potential
