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Imbalance and breakout in the post-epidemic era: Research into the spatial patterns of freight demand network in six provinces of central China

Author

Listed:
  • Yin Huang
  • Runda Liu
  • Shumin Huang
  • Gege Yang
  • Xiaofan Zhang
  • Yin Qin
  • Lisha Mao
  • Sishi Sheng
  • Biao Huang

Abstract

This study aims to explore the freight demand network spatial patterns in six provinces of central China from the perspective of the spread of the epidemic and the freight imbalance and breakout. To achieve this purpose, the big data of “cart search” demand information provided by small and medium freight enterprises on the freight information platform are analyzed. 343,690 pieces of freight demand big data on the freight information platform and Python, ArcGIS, UCINET, and Gephi software are used. The results show that: (1) The choke-point of unbalanced freight demand network is Wuhan, and the secondary choke-points are Hefei and Zhengzhou. (2) In southern China, a chain reaction circle of freight imbalance is formed with Wuhan, Hefei, and Nanchang as the centers. In northern China, a chain reaction circle of freight imbalance is formed with Zhengzhou and Taiyuan as the centers. (3) The freight demand of the six provinces in central China exhibits typical characteristics of long tail distribution with large span and unbalanced distribution. (4) The import and export of freight in different cities vary greatly, and the distribution is unbalanced. This study indicates the imbalance difference, chain reaction, keys and hidden troubles posed by the freight demand network. From the perspectives of freight transfer breakout, freight balance breakout, freight strength breakout, and breakout of freight periphery cities, we propose solutions to breakouts in the freight market in six provinces of central China in the post-epidemic era.

Suggested Citation

  • Yin Huang & Runda Liu & Shumin Huang & Gege Yang & Xiaofan Zhang & Yin Qin & Lisha Mao & Sishi Sheng & Biao Huang, 2021. "Imbalance and breakout in the post-epidemic era: Research into the spatial patterns of freight demand network in six provinces of central China," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-18, April.
    • Handle: RePEc:plo:pone00:0250375
    DOI: 10.1371/journal.pone.0250375
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    2. Jayson S. Jia & Xin Lu & Yun Yuan & Ge Xu & Jianmin Jia & Nicholas A. Christakis, 2020. "Population flow drives spatio-temporal distribution of COVID-19 in China," Nature, Nature, vol. 582(7812), pages 389-394, June.
    3. Haimeng Liu & Chuanglin Fang & Qian Gao, 2020. "Evaluating the Real-Time Impact of COVID-19 on Cities: China as a Case Study," Complexity, Hindawi, vol. 2020, pages 1-11, November.
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