Regional Development

Multi-scale evolution characteristics and influencing factors of spatial layout of logistics enterprises in Xinjiang

  • LI Songrui ,
  • LIN Qiuping ,
  • YANG Shangguang
Expand
  • 1. College of Business Administration, Xinjiang University of Finance & Economics, Urumqi 830012, Xinjiang, China
    2. Xinjiang Enterprise Development Research Center, Urumqi 830012, Xinjiang, China
    3. Business School, East China University of Science and Technology, Shanghai 200237, China

Received date: 2024-07-04

  Revised date: 2024-08-30

  Online published: 2025-04-18

Abstract

The National Development and Reform Commission’s “14th Five-Year Plan for the Construction of a Modern Circulation System” emphasizes “improving the regional logistics service network”, while the State Council’s “Overall Plan for the China (Xinjiang) Pilot Free Trade Zone” proposes “building a comprehensive logistics hub connecting Europe and Asia”. Therefore, studying the spatial layout of Xinjiang logistics enterprises is of great strategic significance to improving the regional logistics service network and building the Xinjiang Pilot Free Trade Zone. Using the geographic coordinate data of Xinjiang logistics enterprises from 1992 to 2022, this study examines the geographical spatial distribution across different scales. This study explores the spatial heterogeneity of formation mechanisms and influencing factors at county and grid levels. The results indicate that: (1) Xinjiang logistics enterprises exhibit agglomeration, forming an overall spatial pattern of a “single axis, single main core, and multiple sub-cores”, while locally developing into a primary core with multiple sub-cores.(2) At the county level, logistics enterprise hotspots and sub-hotspots remain concentrated in northern Xinjiang, constrained by the northern slope of the Tianshan Mountains. However, at a finer grid scale, the sub-hotspots eventually expand beyond this geographical barrier. (3) E-commerce parks, comprehensive bonded zones, and population density significantly influence the spatial layout of logistics enterprises across different scales. Additionally, natural environmental factors can interact nonlinearly and should not be overlooked. (4) Xinjiang should prioritize logistics park development, enhance port functionality, and drive economic growth. In response to local influencing factors, such as e-commerce, industrial parks, ports, and comprehensive bonded zones, logistics plans should be expressed based on local conditions. The research deepened the enterprise location theory and provided theoretical support and practical guidance for the construction of Xinjiang’s Eurasian logistics hub and the core area of the Silk Road Economic Belt.

Cite this article

LI Songrui , LIN Qiuping , YANG Shangguang . Multi-scale evolution characteristics and influencing factors of spatial layout of logistics enterprises in Xinjiang[J]. Arid Land Geography, 2025 , 48(4) : 739 -752 . DOI: 10.12118/j.issn.1000-6060.2024.404

References

[1] O’Connor K. Global city regions and the location of logistics activity[J]. Journal of Transport Geography, 2010, 18(3): 354-362.
[2] Julie C. Concentration and decentralization: The new geography of freight distribution in US metropolitan areas[J]. Journal of Transport Geography, 2010, 18(3): 363-371.
[3] 王成金, 张梦天. 中国物流企业的布局特征与形成机制[J]. 地理科学进展, 2014, 33(1): 134-144.
  [Wang Chengjin, Zhang Mengtian. Spatial pattern and its mechanism of modern logistics companies in China[J]. Progress in Geography, 2014, 33(1): 134-144.]
[4] 潘方杰, 王宏志, 宋明洁, 等. 基于GIS的中国A级物流企业时空演变特征及其影响因素[J]. 长江流域资源与环境, 2020, 29(10): 2186-2199.
  [Pan Fangjie, Wang Hongzhi, Song Mingjie, et al. Study on the spatio-temporal evolutionary characteristics and the influencing factors of A-grade logistics companies in China based on GIS[J]. Resources and Environment in the Yangtze Basin, 2020, 29(10): 2186-2199.]
[5] Sun B W, Li H M, Zhao Q. Logistics agglomeration and logistics productivity in the USA[J]. The Annals of Regional Science, 2018, 61(2): 273-293.
[6] Rivera L, Sheffi Y, Welsch R. Logistics agglomeration in the US[J]. Transportation Research Part A, 2014, 59(11): 222-238.
[7] 张璐璐, 赵金丽, 宋金平. 京津冀城市群物流企业空间格局演化及影响因素[J]. 经济地理, 2019, 39(3): 125-133.
  [Zhang Lulu, Zhao Jinli, Song Jinping. Spatial evolution and influencing factors of logistics enterprises in Beijing-Tianjin-Hebei urban agglomeration[J]. Economic Geography, 2019, 39(3): 125-133.]
[8] 李天宇, 陆林, 张海洲, 等. 长三角城市群A级物流企业空间演化特征及驱动因素[J]. 经济地理, 2021, 41(11): 157-166.
  [Li Tianyu, Lu Lin, Zhang Haizhou, et al. Evolution characteristics and driving factors of A-level logistics enterprises in the Yangtze River Delta urban agglomeration[J]. Economic Geography, 2021, 41(11): 157-166.]
[9] Zhang Y W, Kong J, Zhang Y, et al. Case study of stratification, spatial agglomeration, and unequal logistics industry development on western cities in China[J]. Journal of Urban Planning and Development, 2022, 148(2): 1-13.
[10] 李国旗, 金凤君, 陈娱, 等. 基于POI的北京物流业区位特征与分异机制[J]. 地理学报, 2017, 72(6): 1091-1103.
  [Li Guoqi, Jin Fengjun, Chen Yu, et al. Location characteristics and differentiation mechanism of logistics industry based on points of interest: A case study of Beijing[J]. Acta Geographica Sinica, 2017, 72(6): 1091-1103.]
[11] 张大鹏, 曹卫东, 姚兆钊, 等. 上海大都市区物流企业区位分布特征及其演化[J]. 长江流域资源与环境, 2018, 27(7): 1478-1489.
  [Zhang Dapeng, Cao Weidong, Yao Zhaozhao, et al. Study on the distribution characteristics and evolution of logistics enterprises in Shanghai metropolitan area[J]. Resources and Environment in the Yangtze Basin, 2018, 27(7): 1478-1489.]
[12] 千庆兰, 陈颖彪, 李雁, 等. 广州市物流企业空间布局特征及其影响因素[J]. 地理研究, 2011, 30(7): 1254-1261.
  [Qian Qinglan, Chen Yingbaio, Li Yan, et al. Spatial distribution of logistics enterprises in Guangzhou and its influencing factors[J]. Geographical Research, 2011, 30(7): 1254-1261.]
[13] 曹卫东. 城市物流企业区位分布的空间格局及其演化——以苏州市为例[J]. 地理研究, 2011, 30(11): 1997-2007.
  [Cao Weidong. Spatial pattern and location evolution of urban logistics enterprises: Taking Suzhou as an example[J]. Economic Geography, 2011, 30(11): 1997-2007.]
[14] 张圣忠, 柴廷熠. 西安市物流企业空间格局演化及影响因素分析[J]. 世界地理研究, 2021, 30(6): 1275-1285.
  [Zhang Shengzhong, Chai Tingyi. Spatial evolution and influencing factors of logistics enterprises in Xi’an[J]. World Regional Studies, 2021, 30(6): 1275-1285.]
[15] 程秀娟, 李晶晶, 杨洁辉, 等. 河南省物流业空间格局——基于百度地图和面板数据[J]. 人文地理, 2018, 33(5): 114-122.
  [Cheng Xiujuan, Li Jingjing, Yang Jiehui, et al. Spatial patterns of Henan logistics industry based on a geographic analysis of Baidu maps and panel data[J]. Human Geography, 2018, 33(5): 114-122.]
[16] 蒋天颖, 伍婵提, 陈改改. 浙江省A级物流企业时空格局特征研究[J]. 地理科学, 2017, 37(11): 1720-1727.
  [Jiang Tianying, Wu Chanti, Chen Gaigai. Spatio-temporal pattern of Zhejiang A-class logistics enterprise[J]. Scientia Geographica Sinica, 2017, 37(11): 1720-1727.]
[17] 陈治亚, 周于轶. 基于POI的物流业空间集聚特征分析——以浙江省为例[J]. 铁道科学与工程学报, 2022, 19(10): 2862-2872.
  [Chen Zhiya, Zhou Yuyi. Analysis of spatial agglomeration characteristics of logistics industry based on POI: Taking Zhejiang Province as an example[J]. Journal of Railway Science and Engineering, 2022, 19(10): 2862-2872.]
[18] 李小建. 经济地理学研究中的尺度问题[J]. 经济地理, 2005, 25(4): 433-436.
  [Li Xiaojian. Scale and economic geography inquiry[J]. Economic Geography, 2005, 25(4): 433-436.]
[19] 林秋平, 李松芮, 杨上广, 等. 乌鲁木齐市物流企业区位时空演化、影响因素和发展策略研究[J]. 干旱区地理, 2024, 47(7): 1252-1262.
  [Lin Qiuping, Li Songrui, Yang Shangguang, et al. Spatiotemporal evolution, influencing factors, and development strategies of logistics enterprise location in Urumqi City[J]. Arid Land Geography, 2024, 47(7): 1252-1262.]
[20] 潘方杰, 万庆, 冯兵, 等. 中国物流企业空间格局及多尺度特征分析[J]. 经济地理, 2021, 41(6): 97-106.
  [Pan Fangjie, Wan Qing, Feng Bin, et al. Multi-scale analysis of spatial pattern characteristic of the logistics companies in China[J]. Economic Geography, 2021, 41(6): 97-106.]
[21] 蒋天颖, 史亚男. 宁波市物流企业空间格局演化及影响因素[J]. 经济地理, 2015, 35(10): 130-138.
  [Jiang Tianying, Shi Ya’nan. The spatial pattern evolution and influencing factors of logistics enterprises in Ningbo[J]. Economic Geography, 2015, 35(10): 130-138.]
[22] 王瑞, 蒋天颖, 王帅. 宁波市港口物流企业空间格局及区位选择[J]. 地理科学, 2018, 38(5): 691-698.
  [Wang Rui, Jiang Tianying, Wang Shuai. Spatial pattern and location selection of port logistics enterprises in Ningbo[J]. Scientia Geographica Sinica, 2018, 38(5): 691-698.]
[23] Liu S J, Zhu C J, He N N, et al. Role of mountains and rivers in the formation of logistics enterprises’ spatial pattern in the central urban areas of Chongqing[J]. Journal of Mountain Science, 2022, 19(7): 2060-2074.
[24] 王劲峰, 徐成东. 地理探测器: 原理与展望[J]. 地理学报, 2017, 72(1): 116-134.
  [Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1): 116-134.]
[25] Fotheringham A S, Yang W B, Kang W. Multiscale geographically weighted regression (MGWR)[J]. Annals of the American Association of Geographers, 2017, 107(6): 1247-1265.
[26] Yu H C, Fotheringham A S, Li Z Q, et al. Inference in multiscale geographically weighted regression[J]. Geographical Analysis, 2020, 52(1): 87-106.
[27] Yang R, Xu Q, Long H L. Spatial distribution characteristics and optimized reconstruction analysis of China’s rural settlements during the process of rapid urbanization[J]. Journal of Rural Studies, 2016, 47: 413-424.
[28] 杨忍, 刘彦随, 龙花楼, 等. 中国村庄空间分布特征及空间优化重组解析[J]. 地理科学, 2016, 36(2): 170-179.
  [Yang Ren, Liu Yanshui, Long Hualou, et al. Spatial distribution characteristics and optimized reconstructing analysis of rural settlement in China[J]. Scientia Geographica Sinica, 2016, 36(2): 170-179.]
[29] 刘敏, 郝炜. 山西省国家A级旅游景区空间分布影响因素研究[J]. 地理学报, 2020, 75(4): 878-888.
  [Liu Min, Hao Wei. Spatial distribution and its influencing factors of national A-level tourist attractions in Shanxi Province[J]. Acta Geographica Sinica, 2020, 75(4): 878-888.]
[30] 张佰发, 苗长虹, 冉钊, 等. 核心-边缘视角下的黄河流域县域经济差异研究[J]. 地理学报, 2023, 78(6): 1355-1375.
  [Zhang Baifa, Miao Changhong, Ran Zhao, et al. Economic differences among counties in the Yellow River Basin from the core-periphery perspective[J]. Acta Geographica Sinica, 2023, 78(6): 1355-1375.]
[31] 周侃, 殷悦, 陈妤凡. 城市群水污染物排放的驱动因素及尺度效应[J]. 地理学报, 2022, 77(9): 2219-2235.
  [Zhou Kan, Yin Yue, Chen Yufan. Driving factors and scale effects of water pollutant discharge in the urban agglomeration[J]. Acta Geographica Sinica, 2022, 77(9): 2219-2235.]
Outlines

/