基于PCA和DEA的江苏省物流业碳排放效率评价

根据物流行业的特点并结合江苏省的实际情况，从物流业总体情况、交通运输、信息及人力资源等几大方面选取了8个投入指标，并以物流业增加值及货运汽车碳排放量为输出指标，构建出江苏省碳排放效率评价体系。针对传统方法的局限，利用主成分分析法对评价指标进行降维，并结合非期望产出处理等方法，再运用DEA方法对江苏省物流业碳排放的效率进行评价。研究表明，2010年江苏省13个城市中，南京、无锡等6个城市在综合效率、纯技术效率及规模效率上都达到了DEA有效，规模报酬不变，碳排放效率是最好的；而其他几个城市没有达到DEA有效，因此对这些城市的松弛变量分布进行分析并有针对性的提出了改善建议，旨在促进其物流业的可持续发展。

Evaluation of carbon emission efficiency of logistics industry in Jiangsu province based on the PCA and DEA method

Based on the characteristics of the logistics industry and the actual situation of Jiangsu Province,we build up carbon efficiency evaluation system of Jiangsu Province by selecting eight input indicators from aspects such as the overall logistics industry situation,transportation,information,human resources and so on,and choosing the added value of logistics and freight car emissions as output indicators.Aiming at the limitations of the traditional method,we make use of principal component analysis （PCA）to realize dimensionality reduction of the evaluation index,and combine with the unexpected output processing method,then use DEA to evaluate the carbon emissions efficiency of the logistics industry in Jiangsu Province.Research shows that among thirteen cities in Jiangsu Province in 2010,comprehensive efficiency,pure technical efficiency and scale efficiency of six cities,such as Nanjing,Wuxi,Yangzhou,have reached the DEA effectiveness and constant scale reward,and their carbon emissions efficiency is the best;the other cities haven’t reached the DEA efficiency.So we analyze the slack variable distribution of the DEA inefficient cities and put forward the improvement suggestions to pro-mote the sustainable development of the logistics industry.