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The morphological structure and influence factors analysis of China's domestic civil aviation freight transport network

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  • Li, Hongchang
  • Li, Junru
  • Zhao, Xiaojun
  • Kuang, Xujuan

Abstract

Civil aviation freight transport (CAFT) in China plays an important role in social and economic development. However, research on the morphological structure of China's CAFT network and its influence factors remains rare. In this paper, we focus on this topic by using a new data set of China's domestic routes from 2015 to 2019. With the complex network theory, we make an empirical study on the morphological structure of China's domestic CAFT network, and try to explore the nexus between the attributes of the network and the influence factors. The results show that China's domestic CAFT network is in line with the small world network model, which has a low average path length and a high clustering coefficient. The centrality of the network presents a saddle distribution with dense in the east and west, while sparse in the central. The results also indicate that there are many localized networks dominated by a few core airports. A number of regional hub cities exist, which are mainly located in the west of China. The development of China's CAFT highly depends on the civil aviation passenger transport (CAPT) network, and is highly affected by GDP, the industrial structure and the geographical location of cities. Finally, we give several policy suggestions, including developing the freight dedicated airports, establishing independent freight transport network system, vigorously developing core and intermediate hub cities, as well as constructing the regional network.

Suggested Citation

  • Li, Hongchang & Li, Junru & Zhao, Xiaojun & Kuang, Xujuan, 2022. "The morphological structure and influence factors analysis of China's domestic civil aviation freight transport network," Transport Policy, Elsevier, vol. 125(C), pages 207-217.
    • Handle: RePEc:eee:trapol:v:125:y:2022:i:c:p:207-217
    DOI: 10.1016/j.tranpol.2022.06.008
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