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Research on the Spatial and Temporal Distribution of Logistics Enterprises in Xinjiang and the Influencing Factors Based on POI Data

Author

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  • Pengcheng Lv

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China)

  • Xiaodong Li

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China)

  • Haoyu Zhang

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China)

  • Xiang Liu

    (College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China)

  • Lingzhang Kong

    (College of Economics and Management, Xinjiang University, Urumqi 830047, China)

Abstract

Based on the POI data of logistics enterprises in Xinjiang in 2012, 2016, and 2020, the ArcGIS spatial analysis technique, geographic detector, and other methods were used for the quantitative analysis of the spatial and temporal distributions of logistics enterprises in Xinjiang during 2012–2020 and the influencing factors. The following findings were obtained in the present study: (1) there was a significant difference in the distributions of logistics enterprises in Xinjiang at different development stages, with unbalance among areas; further, there was a higher number of logistics enterprises in Northern Xinjiang compared with Southern Xinjiang; (2) the spatial distribution of logistics enterprises in Xinjiang was generally characterized by a “northeast–southwest” trend; there was a periodic shift in the distribution center from northeast to southwest; the distribution center remained in Bayingolin Mongol Autonomous Prefecture in 2012 and 2020, and shifted to Changji Hui Autonomous Prefecture in 2016, close to the junction of the two areas; (3) the agglomeration of logistics enterprises in Xinjiang was positively correlated with the scale; the kernel density analysis results revealed that there was obvious spatial differentiation characterized by “multi-center development with core agglomeration and patch distribution at the edge”, and the hotspot areas of logistics enterprises were distributed in major cities, with small variations; the Tianshan Mountain North Slope Economic Belt was the main agglomeration area of logistics enterprises; (4) the results from the geographic detector show that the regional GDP, regional total retail sales of consumer goods, regional utilization of foreign direct investment, and regional fixed assets investment were factors that influenced the spatial distribution of logistics enterprises in Xinjiang, thereby significantly promoting the stable and rapid development of logistics enterprises.

Suggested Citation

  • Pengcheng Lv & Xiaodong Li & Haoyu Zhang & Xiang Liu & Lingzhang Kong, 2022. "Research on the Spatial and Temporal Distribution of Logistics Enterprises in Xinjiang and the Influencing Factors Based on POI Data," Sustainability, MDPI, vol. 14(22), pages 1-22, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14845-:d:968806
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    References listed on IDEAS

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    1. Julie Cidell, 2011. "Distribution Centers among the Rooftops: The Global Logistics Network Meets the Suburban Spatial Imaginary," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 35(4), pages 832-851, July.
    2. Rivera, Liliana & Sheffi, Yossi & Welsch, Roy, 2014. "Logistics agglomeration in the US," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 222-238.
    3. Kang, Sanggyun, 2020. "Warehouse location choice: A case study in Los Angeles, CA," Journal of Transport Geography, Elsevier, vol. 88(C).
    4. Xinbao Tian & Meirong Zhang, 2019. "Research on Spatial Correlations and Influencing Factors of Logistics Industry Development Level," Sustainability, MDPI, vol. 11(5), pages 1-18, March.
    5. Dongxu Chen & Dongping Song & Zhongzhen Yang, 2022. "A review of the literature on the Belt and Road Initiative with factors influencing the transport and logistics," Maritime Policy & Management, Taylor & Francis Journals, vol. 49(4), pages 540-557, May.
    6. Meiling He & Jiaren Shen & Xiaohui Wu & Jianqiang Luo, 2018. "Logistics Space: A Literature Review from the Sustainability Perspective," Sustainability, MDPI, vol. 10(8), pages 1-24, August.
    7. Yongyi Su & Jin Qin & Peng Yang & Qiwei Jiang, 2019. "A Supply Chain-Logistics Super-Network Equilibrium Model for Urban Logistics Facility Network Optimization," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-12, January.
    8. Yang, Zhiwei & Chen, Xiaohong & Pan, Ruixu & Yuan, Quan, 2022. "Exploring location factors of logistics facilities from a spatiotemporal perspective: A case study from Shanghai," Journal of Transport Geography, Elsevier, vol. 100(C).
    9. Meiling He & Lei Zeng & Xiaohui Wu & Jianqiang Luo, 2019. "The Spatial and Temporal Evolution of Logistics Enterprises in the Yangtze River Delta," Sustainability, MDPI, vol. 11(19), pages 1-20, September.
    10. Yang Zhong & Aiwen Lin & Zhigao Zhou, 2019. "Evolution of the Pattern of Spatial Expansion of Urban Land Use in the Poyang Lake Ecological Economic Zone," IJERPH, MDPI, vol. 16(1), pages 1-14, January.
    11. Kumar, Indraneel & Zhalnin, Andrey & Kim, Ayoung & Beaulieu, Lionel J., 2017. "Transportation and logistics cluster competitive advantages in the U.S. regions: A cross-sectional and spatio-temporal analysis," Research in Transportation Economics, Elsevier, vol. 61(C), pages 25-36.
    12. Giuliano, Genevieve & Kang, Sanggyun, 2018. "Spatial dynamics of the logistics industry: Evidence from California," Journal of Transport Geography, Elsevier, vol. 66(C), pages 248-258.
    13. Nan Jing & Wenxue Cai, 2010. "Analysis on the spatial distribution of logistics industry in the developed East Coast Area in China," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 45(2), pages 331-350, October.
    14. Yunfeng Hu & Yueqi Han, 2019. "Identification of Urban Functional Areas Based on POI Data: A Case Study of the Guangzhou Economic and Technological Development Zone," Sustainability, MDPI, vol. 11(5), pages 1-15, March.
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