Analysis of the Chinese provincial air transportation network

Wen-Bo Du, Bo-Yuan Liang, Chen Hong and Oriol Lordan

Physica A: Statistical Mechanics and its Applications, 2017, vol. 465, issue C, 579-586

Abstract: The air transportation system is of a great impact on the economy and globalization of a country. In this paper, we analyze the Chinese air transportation network (ATN) from a provincial perspective via the complex network framework, where all airports located in one province are abstracted as a single node and flights between two provinces are denoted by a link. The results show that the network exhibits small-world property, homogeneous structure and disassortative mixing. The variation of the flight flow within 24 h is investigated and an obvious tide phenomenon is found in the dynamics of Chinese provincial ATN for high output level of tertiary industry. Our work will offer a novel approach for understanding the characteristic of the Chinese air transportation network.

Keywords: Chinese air transportation network; Structural property; Flight flow; Complex network (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S037843711630591X
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:465:y:2017:i:c:p:579-586

DOI: 10.1016/j.physa.2016.08.067

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().