【作者】 王雪平；

【导师】 赵军；

【作者基本信息】 西北师范大学 ， 自然地理学， 2006， 硕士

【摘要】 金融网点空间格局是金融企业的各个办事机构在一定的社会、经济条件下进行金融网点区位选择过程中产生的。面对激烈的市场竞争和日益复杂的社会经济环境，科学地认识金融网点空间分布格局显得尤其重要。本文总结了金融空间格研究的理论基础，介绍了论文的研究方法和思路，对金融网点空间分布的类型确定了研究的定性指标：最近邻点指数，中心位置，分布密度和集中程度。在此基础上对文章研究的数据分析处理技术路线和GIS图形处理流程进行详细的说明。并根据以上空间分布的指标对兰州市区的金融网点的空间分布进行了研究。根据调查获得的金融网点数据，建立了金融网点空间数据库中，依据最近邻点指数公式求得R值为1.01，表明兰州市金融网点分布为随机分布类型。在形成这种分布类型的因子中，无疑是兰州市这一种特殊的城区分布形式起了主导作用。由于兰州市区特殊的地理布局形式，决定了其金融网点中心与传统意义的城区中心不重合。兰州市市区的中项中心位于(103°30′53.7″E，36°27′27.7″N)处；平均中心位于(103°30′29.5″E，36°27′34.7″N)处，两者几乎重合。但与本区的政治、经济和文化中心东方红广场(104°27′33.5″E，37°43′34.7″N)相距较远。考虑本区平均中心和中项中心几乎重合，在研究中只进行平均中心的离散和集中程度分析。计算得城关区、七里河区、安宁区、西固区分别为20％、37％、8％、35％，表明中心点七里河区离散程度最大，西固区和七河区离散程度相近、安宁区离散程度最低。在现状分析的基础上，本文运用网格多因素综合分值法进行了兰州市金融网点布局影响因素研究。采用标准网格法划分出192852个影响单元，避免了人为划分单元造成的主观性，也适宜于用计算机进行数据、图件处理。影响金融网点空间布局的因素很多，本研究抽取了比较重要的几个方面进行分析，其中包括人口分布密度、公交便捷度、商服繁华度、医院辐射度、学校辐射度等因素指标，并用特尔斐法和因素成对比较法确定各因子的权重，然后结合兰州市交通线路图、商业网点现状图和人口分布图等，运用定量化手段，即GIS的空间分析方法建立综合数据库，并利用ACCESS数据库软件，计算各单元总分值，得到金融网点影响要素权重。最后，在定量分析的基础上，依据兰州市2001—2010年城市总体规划中的城市总体规划，结合定性分析，提出兰州市金融网点布局方案，以使此方案更加科学化、合理化，并具有长期指导作用。更多还原

【Abstract】 Financial networks spatial pattern is established during the location selection of administrative body of financial enterprise .Facing the intense market competition and the complex socio-economic environment, to make clear the financial networks spatial distribution pattern is particularly important.This paper summarizes the financial theoretical principle of financial spatial pattern, introduces a detailing research methods and the train of thought of this research, and identifies the researching qualitative indicators of the types of financial networks spatial pattern: nearest neighbor index, the center position, the density and distribution of concentration. Based on this, data analysis and GIS technology line are introduced. The spatial structure of financial networks in Lanzhou urban was studied according to the researching qualitative indicators.Financial networks spatial databases is established on the grounds of surveying financial data networks .R is 1.01 according to the nearest neighbor index formula, which means financial networks distribution of Lanzhou City is random distribution. The spatial geographical layout of Lanzhou city is the key factor to form this random distribution. Also it is the determinant factors to make the center of financial networks do not coincide with the traditional significance City Center. The mean center of Lanzhou City lies in 103°30’53.7"E, 36°27’27.7"N and its average center lies in 103°30’29.5"E, 36°27’34.7"N, these two enters are almost coincidence with each other. But the center is far away from Dongfanghong Square(104°27’33.5"E, 37°43’34.7"N ), the region’s political, economic and cultural center. This paper only analysis the dispersion degree and concentration considering the coincidence of mean center and average center. The dispersion degree of Chengguan district, Qilihe district, Anning district and Xigu district are 20%、37%、8%、35% separately, which indicates that the separation degree of Qilihe district is the highest and the Anning district is the lowest.On the basis of the analysis of current situation, with the method of Grid and multiple elements, the thesis disserts the optimized distribution of Lanzhou financial center. Using the method of grid, it divided Lanzhou urban into 192,852 units to assess can avoid the subjectivity of partition by artificial and suit for computer to process data and images.There are many factors to impact the financial network distribution, including population density, transit convenient level, business services for the downtown, etc., this paper selects some factors to analysis applying the Dlphi method and every-two-factor-comparing-method to ascertain the weighs of estimating factors. Then comprehensive database is established combining traffic map, current commercial networks and population distribution map of Lanzhou city. Finally, on the basis of quantitative analysis combining qualitative analysis, the paper works on the layout of Lanzhou financial network distribution.更多还原