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Evolution and Determinants of an Air Transport Network: A Case Study of the Chinese Main Air Transport Network

Min Su (), Weixin Luan (), Zeyang Li (), Shulin Wan () and Zhenchao Zhang ()
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Min Su: School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China
Weixin Luan: School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China
Zeyang Li: School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China
Shulin Wan: School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China
Zhenchao Zhang: School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China

Sustainability, 2019, vol. 11, issue 14, 1-20

Abstract: The Chinese main air transport network (CMATN) is the framework for air passenger transport in the country. This study uses complex networks and an econometric model to analyze CMATN’s evolution and determinants. In terms of overall network structure, the network has always shown small-world properties, with smaller average path lengths (2.06–2.15) and larger clustering coefficients (0.68–0.77), while its cumulative degree distribution follows an exponential function. City passenger volumes conform to the degree power law function, which means that the more destinations a city connects to, the higher its passenger traffic will be. In major hub cities, such as Beijing, Shanghai, and Guangzhou, control power decreases, while Chengdu, Kunming, Chongqing, Xi’an, Urumqi, and other cities play an increasingly important role in CMATN. In terms of main route passenger volumes and formation, increases in GDP and tourism have had a promoting effect, while high-speed rail (HSR) poses a threat to overlapping routes. CMATN is primarily located in the central and eastern regions, focusing on China’s economy, tourism, and efficient HSR development. Although the competition from HSR affects the overall network structure of CMATN based on its influence on specific routes, we believe that the impact is limited due to the different transport attributes of the two networks. The research results of this study can become an information source for decision makers and provide a reference for air transport to seek sustainable development.

Keywords: air transport network; high-speed rail; complex network theory; binary logit model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2019
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