地理科学进展 ›› 2017, Vol. 36 ›› Issue (7): 843-852.doi: 10.18306/dlkxjz.2017.07.006

• 研究论文 • 上一篇    下一篇

中国星级仓库的区位选择行为与等级差异

刘思婧1(), 李国旗1,2,*(), 金凤君2   

  1. 1. 西南交通大学交通运输与物流学院,综合交通运输智能化国家地方联合工程实验室,成都 610031
    2. 中国科学院地理科学与资源研究所,北京 100101
  • 出版日期:2017-07-31 发布日期:2017-07-31
  • 作者简介:

    作者简介:刘思婧(1984-),女,四川成都人,博士,讲师,硕士生导师,主要从事物流规划与区域发展研究,E-mail: liusijing666@126.com

  • 基金资助:
    国家自然科学基金项目(41501123,71703219);中央高校基本科研业务费专项资金项目(2682016CX051)

Location choice behaviors and hierarchical differences of star warehouses in China

Sijing LIU1(), Guoqi LI1,2,*(), Fengjun JIN2   

  1. 1. School of Transportation & Logistics, Southwest Jiaotong University, National United Engineering Laboratory of Integrated and Intelligent Transportation, Chengdu 610031, China;
    2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Online:2017-07-31 Published:2017-07-31
  • Supported by:
    National Natural Science Foundation of China, No.41501123, No.71703219;Fundamental Research Funds for the Central Universities of China, No.2682016CX051

摘要:

星级仓库区位认识对优化城市仓储空间和合理配置仓储用地资源有重要意义。以2008-2014年237个中国星级仓库为样本,综合运用区位关系识别、距离测度和典型案例分析等方法,揭示地域、行业、职能分异与星级仓库区位选择行为相互关系,阐明了不同等级城市的星级仓库区位统计规律,以及物流职能、交通圈层结构与星级仓库区位形成的内在作用机制。研究表明:①星级仓库分布于4个直辖市、22个副省级和省会城市、37个地级市、24个县/县级市,不同等级城市平均拥有星级仓库数分别为16.5、4.77、1.78和1.58个,呈“倒三角形”分布形态;行业分布呈现“通用和大宗仓储分散、专业性仓库集中”特征;办公和经营场所区位呈“共用和分离相对均衡”特征;②星级仓库区位受“供给+需求”共同驱动,省会及以上城市具有公共服务职能的星级仓库区位总体呈“近郊—远郊”布局模式,地级市以自营服务职能为主的星级仓库总体呈“中心—边缘”布局模式;③城市等级与星级仓库物流距离成正比且存在明显的类型分异,其中公私兼营和自营仓储型仓库受母公司区位影响,郊区化趋势滞后于提供公共服务的地产租赁和公共仓储型仓库。

关键词: 星级仓库, 区位特征, 等级差异, 距离, 郊区化, 中国

Abstract:

Locational characteristics of star warehouses are of key importance to optimizing urban warehouse spatial configuration and allocating storage land resources. Using data of 237 sample star warehouses in China from 2008 to 2014 and location relationship identification, distance measurement, and representative case study methods, this study examined the relationship between the location choice behaviors of star warehouses and regions and service objects and functions. Through the analysis of differences between the scope of warehouse space, logistics functions, traffic networks, and location of star warehouses in cities of different levels and scales, the statistical result and internal mechanism are revealed. The results show that: (1) The selected warehouses are distributed in 4 municipalities, 22 provincial-level cities and sub-provincial-level cities, 37 prefecture-level cities, and 24 counties with a ratio of 16.5: 4.77: 1.84: 1.67, which formed a distribution pattern of upside-down triangle compared to the city size hierarchy. Star warehouses for general uses were scattered, and specialized warehouses showed concentrated distribution, with both co-agglomeration and spatial separation characteristics. (2) The location choice behaviors of star warehouses are driven by supply and demand side factors. Star warehouses of provincial capital and above cities with public service functions are often located in the suburbs and the exurb areas. Star warehouses of prefectural-level cities with self-serving functions are often located in central and peripheral areas. (3) Distance of star warehouses shows a positive correlation with the level of cities. Constrained by the location of parent companies, suburbanization of warehouses with joint public-private ownership and proprietary lagged behind real estate leasing and public warehouses.

Key words: star warehouses, locational characteristics, hierarchical differences, distance, suburbanization, China