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深圳服装业空间演化及影响因素分析
引用本文:章文,黎夏. 深圳服装业空间演化及影响因素分析[J]. 热带地理, 2014, 34(4): 534-543
作者姓名:章文  黎夏
作者单位:(中山大学 地理科学与规划学院//广东省城市化与地理环境空间模拟重点实验室,广州 510275)
基金项目:国家自然科学基金项目(41371376)
摘    要:基于服装企业点状数据,采用核密度、标准差椭圆、热点探测和Ripley's K函数相结合的点模式空间分析方法,对比研究了1995、2000、2005和2010年深圳服装企业空间分布特征,进而利用负二项回归模型检验主要区位的影响因素,结果表明:深圳服装业随时间演变,核密度高值区域日渐明朗,整体呈现集中分布态势,标准差椭圆面积有所收缩,热点区域在扩大,西部热点区倾向北移,中部热点区得到进一步强化,集聚特征呈现“先增后减”趋势,集聚范围逐年扩大;负二项回归结果表明:产业集聚、区域协作和制度因素对服装业空间演化有着显著影响,其中产业集聚和制度因素影响逐渐加强,而区域协作在城市产业发展中寻求着空间动态平衡。深圳服装业空间演化惯性效应突出,因企业对集聚经济内在需求和区位环境等外部需求产生的路径依赖,约束了产业后续空间演化的各项特征。

关 键 词:服装业  空间演化  点模式  负二项回归模型  深圳  

Spatial Evolution and Determinants of Garment Enterprises in Shenzhen
ZHANG Wen,LI Xia. Spatial Evolution and Determinants of Garment Enterprises in Shenzhen[J]. Tropical Geography, 2014, 34(4): 534-543
Authors:ZHANG Wen  LI Xia
Affiliation:(Geography and Planning School,Sun Yat-sen University//Guangdong Key Laboratory for Urbanization and Geo-simulation,Guangzhou 510275,China)
Abstract:Garment industry belongs to the traditional industry in the city. During more than 20 year urban development, Shenzhen garment industry has evolved from its infancy to maturity. Based on the garment enterprises point data, by using kernel density estimation, standard deviation ellipse, hot spots and Ripley's K function as point pattern study methods, a comparative study was made in this paper on spatial distribution and clustering phenomenon of Shenzhen garment enterprises in 1995, 2000, 2005 and 2010. After that with the negative binomial regression model, determinants that affect the location of garment enterprises as well as their variation of impact among subdistricts in Shenzhen were validated. The research results indicate that garment enterprises developed fast during 1995-2000 and manifested some different spatial distribution for every 5 years. Changing over time, the high kernel density value zones of garment industry increased obviously, which showed the concentrated distribution trend: the area of standard deviation ellipse contracted, hotspots area expanded with western hotspot moving northward and central hotspot being further reinforced, spatial clustering revealed “increase-decrease” tendency and the clustering range extended annually. The results of negative binomial regression model demonstrate that, from the perspective of Shenzhen subdistricts, industrial agglomeration, regional cooperation and institutional factors had the significant impact on the spatial evolution of garment industry, in which the industrial agglomeration and institutional factors were strengthened gradually while regional cooperation was searching the spatial dynamic balance throughout the development of Shenzhen and its adjacent cities garment industries. Because enterprises’ internal demand of agglomeration economies and their external demand of regional conditions generated the path-dependence, the spatial evolution of Shenzhen garment industry had prominent inertial effect, which constrained and influenced the subsequent characteristics of the industrial spatial evolution.
Keywords:garment industry   spatial evolution  point pattern   negative binomial regression model  Shenzhen  
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