基于超效率DEA-Tobit模型的物流企业经营效率评价研究

发布时间：2017-12-26 16:38

本文关键词：基于超效率DEA-Tobit模型的物流企业经营效率评价研究　出处：《成都理工大学》2015年硕士论文　论文类型：学位论文

【摘要】：物流业作为服务业的重要组成部分,已经成为落实扩大内需经济发展战略的重点,也是促进国民经济发展、产业结构优化升级的重要领域。近年来,物流业在国民经济和社会发展中的重要性日益增强,但我国物流企业的经营效率整体水平还不高,经营成本居高不下,阻碍了其对我国经济发展的支持作用。然而国际竞争日趋激烈,物流需求快速增长,新技术、新管理不断出现、资源环境约束日益加强,对我国物流企业提出了更高要求,进一步提高物流企业的经营效率就显得尤为重要。本文以物流上市企业的经营效率为研究对象,基于国内外现有的研究成果,通过对现有企业效率评价方法的比较,发现DEA(数据包络分析)在多投入多产出的复杂系统中优势较为明显,因此选用DEA方法为物流企业效率评价方法。从我国物流业特点与现状出发,充分考虑数据的可操作性,选取28家深沪两市上市物流公司为代表,建立物流企业的投入产出指标体系,选取2008-2013年28家物流上市企业的固定资产总额、员工人数、营业成本和管理费用作为投入变量,主营业务收入和净利润为产出变量,对各个物流上市企业在各个年份的投入产出变量进行了Pearson相关性检验。然后运用CCR、BBC模型对这6年间各物流企业的技术效率、纯技术效率和规模效率进行测算,从技术效率、纯技术效率和规模效率三方面分别进行分析,结合公司发展现状,分析了各物流上市企业历年相对效率的变化,找出决策单元非技术有效的原因,有针对性的提出有效的参考改进意见。再用超效率DEA模型将技术效率为1的有效决策单元重新排序,评价相对有效的决策单元的效率水平高低。另一方面,提出物流企业经营效率的内部外部影响因素假设,选择2008-2013年面板数据建立Tobit模型,对影响因素进行回归分析,运用Stata 12.0软件进行计算,找到影响物流企业经营效率的显著因素并分析其影响作用的大小,提出相应的改进建议。
[Abstract]:As an important part of the service industry, logistics industry has become the focus of economic development strategy to expand domestic demand, and it is also an important area to promote the development of national economy and optimize and upgrade industrial structure. In recent years, the importance of logistics industry in the development of national economy and society is increasing. However, the overall efficiency of logistics enterprises in China is not high enough, and the high cost of operation hinders its support for China's economic development. However, with the increasingly fierce international competition, the rapid growth of logistics demand, the continuous emergence of new technologies and new management, and the increasingly constraint of resources and environment, it has put forward higher requirements for our logistics enterprises. It is particularly important to further improve the operational efficiency of logistics enterprises. In this paper, the operating efficiency of listed logistics enterprises as the research object, based on the existing research results at home and abroad, through the comparison of the efficiency evaluation method of existing enterprises, DEA (Data Envelopment Analysis) advantage in complex multi input multi output system is obvious, so we choose DEA method for logistics enterprise efficiency evaluation method. From the characteristics of the logistics industry of our country and current situation, fully consider the data, selected 28 two cities of Shenzhen and Shanghai listed logistics company as the representative, input-output index system establishment of logistics enterprises, the total fixed assets, selecting 2008-2013 28 listed logistics enterprises the number of employees, operating costs and administrative expenses as the input variables, the main business income and net profit as output variables, listed for each logistics enterprise in each year in the input and output variables were analyzed by Pearson correlation test. Then, using the CCR BBC model on technical efficiency, the 6 years the logistics enterprises pure technical efficiency and scale efficiency was calculated from the technical efficiency, pure technical efficiency and scale efficiency of the three aspects were analyzed, combined with the current development of company, analyzes the change of the relative efficiency of listed logistics enterprise, to find out the reasons and effective technology the decision unit, aiming at putting forward effective reference. Using the super efficient DEA model, the efficient decision unit with a technical efficiency of 1 is reordered, and the efficiency level of the relatively effective decision unit is evaluated. On the other hand, assumptions puts forward the management efficiency of the logistics enterprise's internal and external influence, establish the Tobit model 2008-2013 panel data, regression analysis on the influencing factors, was calculated by Stata 12 software, find the significant factors affecting the operating efficiency of logistics enterprises and analyze the effects of the size, and puts forward the corresponding improvement suggestions.
【学位授予单位】：成都理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F259.23

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