区域物流发展多方法评价研究

发布时间：2018-01-29 18:21

本文关键词： 区域物流 logistic模型数据包络分析离差最大化 VAR模型　出处：《北京交通大学》2017年博士论文　论文类型：学位论文

【摘要】：区域物流推动区域经济发展的作用日益凸显,物流业已经成为区域经济新的增长点。但伴随着区域物流的不断壮大,其在发展过程中存在一定的问题,越来越需要对其进行具体的比较与评价,指明问题所在及提出改进的方向。针对上述情况,对我国区域物流发展进行较为系统与全面的评价已成为当务之急。本论文从五个方面对我国区域物流进行了评价与分析:第一,利用logistic模型,分析我国31省(市)及东、中、西部地区物流产业发展趋势,比较全国及相关区域的物流产业发展差异。同时建立“物流产业-经济-交通基础设施”复合系统,利用协同学理论考察我国东、中、西部地区相关协调度。第二,创建区域物流发展竞争与支撑二维评价指标体系。结合主成分分析法与K-均值聚类分析法将我国31个省(市)归类到高-中-低竞争与支撑聚类体系矩阵,清晰的描述出我国31个省(市)在“十二五”初期与末期处在矩阵中的位置,为“十三五”期间区域物流的改进方向提供理论依据。第三,结合我国31个省(市)2010～2014年物流投入与产出的数据,利用数据包络分析方法,系统的分析我国各省(市)的物流行业综合技术效率、纯技术效率和规模效率情况,得到位于物流技术前沿面的省(市)情况。同时考虑到各省(市)面临的外部环境不同,利用随机前沿分析模型,通过计算,剔除环境因素与随机因素影响,然后测算出的省(市)及区域物流效率值,有效避免环境及随机因素对相关效率的低估或高估现象,更为准确地进行省(市)及区域物流业的效率评价。第四,当利用若干个指标进行区域物流综合排序评价时,其相关指标并不是同等重要的,所以在评价的过程中要对不同的评价指标赋以不同的权重。权重在效率评价中是一个重要的指标标定系数,合理的分配权重是排序评价的一个重要步骤。因此,论文提出综合离差最大化模型,在属性综合离差(即属性组内离差与属性平均值组间离差)达到最大化时,建立规划模型,利用方案中现有数据,求解各属性值权重。利用该模型分别与灰色系统关联分析模型以及层次分析法相结合,客观的进行较少数量决策单元和具有双层评价指标的区域物流排序评价。第五,区域物流与区域经济的发展有着极为密切的联系,为定量的分析两者间的相互关系,选取经济与物流中的典型指标,利用VAR模型及面板数据模型,精细的研究我国东部、中西部及31个省(市)经济与物流相互间的协整与定量关系,量化其影响程度,为更好的促进二者的健康发展提供理论依据。本文通过对区域物流多方法评价的研究,有助于丰富区域物流评价系统理论,并为我国区域物流发展方向提供科学依据。
[Abstract]:The role of regional logistics to promote regional economic development is increasingly prominent, logistics industry has become a new growth point of regional economy, but with the continuous growth of regional logistics, there are certain problems in the process of development. There is a growing need to compare and evaluate them specifically, to indicate where the problem lies and to propose directions for improvement. It is urgent to evaluate the development of regional logistics in China systematically and comprehensively. This paper evaluates and analyzes regional logistics from five aspects: first, using logistic model. This paper analyzes the development trend of logistics industry in 31 provinces (cities), east, middle and west of China. This paper compares the development of logistics industry in the whole country and related regions. At the same time, it sets up the compound system of "logistics industry-economic-transportation infrastructure", and makes use of the synergetic theory to investigate the east and the middle of our country. Correlation degree of coordination in the western region. Second. To establish a two-dimensional evaluation index system of regional logistics development competition and support. Combining principal component analysis and K-means clustering analysis, 31 provinces (cities) in China are classified into high-middle-low competition and support cluster system matrix. It clearly describes the position of 31 provinces (cities) in the matrix at the beginning and the end of the 12th Five-Year Plan, which provides the theoretical basis for the improvement direction of regional logistics during the 13th Five-Year Plan period. Third. Based on the data of input and output of logistics from 2010 to 2014 in 31 provinces of China, the comprehensive technical efficiency of logistics industry in all provinces (cities) of China is analyzed systematically by using the method of data envelopment analysis. Pure technical efficiency and scale efficiency, the situation of province (city) located at the front of logistics technology is obtained. Considering the different external environment of each province (city), the stochastic frontier analysis model is used to calculate. Eliminate the environmental factors and random factors, and then calculate the provincial (city) and regional logistics efficiency value, effectively avoid the environment and random factors to the related efficiency of underestimation or overestimation. More accurate evaluation of the efficiency of the provincial (city) and regional logistics industry. 4th, when using a number of indicators to evaluate the comprehensive ranking of regional logistics, its related indicators are not equally important. Therefore, in the process of evaluation, we should assign different weights to different evaluation indexes. Weight is an important index calibration coefficient in efficiency evaluation, and rational distribution of weights is an important step in ranking evaluation. In this paper, a comprehensive deviation maximization model is proposed. When the attribute comprehensive deviation (i.e., the inter-group deviation between the attribute group and the attribute average group) is maximized, the planning model is established and the existing data in the scheme are used. The weight of each attribute value is solved, and the model is combined with the grey system correlation analysis model and the analytic hierarchy process (AHP), respectively. There is a close relationship between regional logistics and the development of regional economy. It is objective to carry out fewer decision-making units and regional logistics ranking evaluation with double-level evaluation index. 5th, regional logistics and the development of regional economy have a very close relationship. In order to quantitatively analyze the relationship between the two, select the typical economic and logistics indicators, using the VAR model and panel data model, fine research in eastern China. The cointegration and quantitative relationship between economy and logistics in the central and western regions and 31 provinces (cities) to quantify the degree of influence. In order to better promote the healthy development of the two to provide a theoretical basis. Through the study of multi-method evaluation of regional logistics, it is helpful to enrich the theory of regional logistics evaluation system. And provides the scientific basis for the development direction of the regional logistics in our country.
【学位授予单位】：北京交通大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：F224;F259.2

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