Geographic concentration of industries in Jiangsu, China: a spatial point pattern analysis using micro-geographic data

被引:11
|
作者
Zhang, Xiaoxiang [1 ,2 ]
Yao, Jing [2 ]
Sila-Nowicka, Katarzyna [2 ,3 ,4 ]
Song, Chonghui [5 ]
机构
[1] Hohai Univ, Dept Geog Informat Sci, Coll Hydrol & Water Resources, Nanjing, Peoples R China
[2] Univ Glasgow, Sch Social & Polit Sci, Urban Big Data Ctr, 7 Lilybank Gardens, Glasgow G12 8RZ, Lanark, Scotland
[3] Univ Auckland, Sch Environm, Auckland, New Zealand
[4] Wroclaw Univ Environm & Life Sci, Wroclaw, Poland
[5] Dept Nat Resources Jiangsu, Nanjing, Peoples R China
来源
ANNALS OF REGIONAL SCIENCE | 2021年 / 66卷 / 02期
关键词
C38; L60; R12; MANUFACTURING-INDUSTRIES; ECONOMIC TRANSITION; 2ND-ORDER ANALYSIS; AGGLOMERATION; LOCATION; SUNAN;
D O I
10.1007/s00168-020-01026-x
中图分类号
F [经济];
学科分类号
02 ;
摘要
Detection of geographic concentration of economic activities at different spatial scales has long been of interest to researchers from spatial economics, regional science and economic geography. Using a unique dataset from the first industrial land use survey of its kind in China, this research is the first effort attempting to explore spatial distribution particularly geographic concentration of industries in China using firm-level data. Distance-based functions and spatial cluster analysis are employed to detect the spatial scales as well as the geographic locations of industrial concentration. The results indicate that four of the five selected industries are in general concentrated in southern Jiangsu at small spatial scales (less than 5 km), while the chemical industry demonstrates an overall spatial dispersion pattern relative to the distribution of all other industries. Most industrial clusters have a radius of less than 2.5 km containing 20-60% of enterprises and 60-86% of employees from each selected industry, with larger clusters showing relatively weaker concentration. This research demonstrates the connections and complementarity of different approaches, complementing previous studies that use distance-based functions with spatial scan statistics.
引用
收藏
页码:439 / 461
页数:23
相关论文
共 50 条
  • [1] Geographic concentration of industries in Jiangsu, China: a spatial point pattern analysis using micro-geographic data
    Xiaoxiang Zhang
    Jing Yao
    Katarzyna Sila-Nowicka
    Chonghui Song
    [J]. The Annals of Regional Science, 2021, 66 : 439 - 461
  • [2] Measuring and Testing Spatial Mass Concentration with Micro-geographic Data
    Bonneu, Florent
    Thomas-Agnan, Christine
    [J]. SPATIAL ECONOMIC ANALYSIS, 2015, 10 (03) : 289 - 316
  • [3] A Spatial-Temporal Analysis of Cultural and Creative Industries with Micro-Geographic Disaggregation
    Boal-San Miguel, Ivan
    Cesar Herrero-Prieto, Luis
    [J]. SUSTAINABILITY, 2020, 12 (16)
  • [4] Testing for localization using micro-geographic data
    Duranton, G
    Overman, HG
    [J]. REVIEW OF ECONOMIC STUDIES, 2005, 72 (04): : 1077 - 1106
  • [5] Perks and pitfalls of city directories as a micro-geographic data source
    Albers, Thilo N. H.
    Kappner, Kalle
    [J]. EXPLORATIONS IN ECONOMIC HISTORY, 2023, 87
  • [6] The application of micro-geographic economic analysis in urban policy evaluation
    Hooton, Christopher Alex
    [J]. EVALUATION AND PROGRAM PLANNING, 2019, 72 : 125 - 135
  • [7] Urban Vulnerability Analysis Based on Micro-Geographic Unit with Multi-Source Data-Case Study in Urumqi, Xinjiang, China
    Zheng, Jianghua
    Yu, Danlin
    Han, Chuqiao
    Wang, Zhe
    [J]. REMOTE SENSING, 2023, 15 (16)
  • [8] GEOGRAPHIC COMPUTER SYSTEM FOR ANALYSIS AND GRAPHIC DEPICTION OF SPATIAL POINT DATA
    WITTICK, RI
    [J]. GEOGRAPHICAL ANALYSIS, 1976, 8 (03) : 319 - 328
  • [9] The Spatial Analysis on Hemorrhagic Fever with Renal Syndrome in Jiangsu Province, China Based on Geographic Information System
    Bao, Changjun
    Liu, Wanwan
    Zhu, Yefei
    Liu, Wendong
    Hu, Jianli
    Liang, Qi
    Cheng, Yuejia
    Wu, Ying
    Yu, Rongbin
    Zhou, Minghao
    Shen, Hongbing
    Chen, Feng
    Tang, Fenyang
    Peng, Zhihang
    [J]. PLOS ONE, 2014, 9 (09):