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Spatial Pattern Evolution and Influencing Factors of Tourism Flow in the Chengdu–Chongqing Economic Circle in China
by
Huang, Yang
, Chen, Yuesheng
, Chen, Xuejun
in
China
/ Cities
/ Data processing
/ Density
/ Economic analysis
/ Economics
/ GDP
/ Gross Domestic Product
/ Hotels
/ Hotels & motels
/ influencing factors
/ Keywords
/ Network analysis
/ Per capita
/ Research methodology
/ Roads & highways
/ Social network analysis
/ Social networks
/ Social organization
/ Spatial analysis
/ spatial pattern
/ Tourism
/ Tourism development
/ tourism flow
2023
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Spatial Pattern Evolution and Influencing Factors of Tourism Flow in the Chengdu–Chongqing Economic Circle in China
by
Huang, Yang
, Chen, Yuesheng
, Chen, Xuejun
in
China
/ Cities
/ Data processing
/ Density
/ Economic analysis
/ Economics
/ GDP
/ Gross Domestic Product
/ Hotels
/ Hotels & motels
/ influencing factors
/ Keywords
/ Network analysis
/ Per capita
/ Research methodology
/ Roads & highways
/ Social network analysis
/ Social networks
/ Social organization
/ Spatial analysis
/ spatial pattern
/ Tourism
/ Tourism development
/ tourism flow
2023
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Spatial Pattern Evolution and Influencing Factors of Tourism Flow in the Chengdu–Chongqing Economic Circle in China
by
Huang, Yang
, Chen, Yuesheng
, Chen, Xuejun
in
China
/ Cities
/ Data processing
/ Density
/ Economic analysis
/ Economics
/ GDP
/ Gross Domestic Product
/ Hotels
/ Hotels & motels
/ influencing factors
/ Keywords
/ Network analysis
/ Per capita
/ Research methodology
/ Roads & highways
/ Social network analysis
/ Social networks
/ Social organization
/ Spatial analysis
/ spatial pattern
/ Tourism
/ Tourism development
/ tourism flow
2023
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Spatial Pattern Evolution and Influencing Factors of Tourism Flow in the Chengdu–Chongqing Economic Circle in China
Journal Article
Spatial Pattern Evolution and Influencing Factors of Tourism Flow in the Chengdu–Chongqing Economic Circle in China
2023
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Overview
Based on Ctrip’s ‘tourism digital footprint’, the spatial pattern of tourism flows in the Chengdu–Chongqing Economic Circle from 2018 to 2021 is explored, social network analysis and spatial visualisation of tourism information data are conducted, and factors affecting the network structure of tourism flows are analysed using linear weighted regression methods. The results show that tourism flows in the Chengdu–Chongqing Economic Circle show a significant ‘dual core’ polarisation effect. At the end of 2019, as a turning point, the density value of the tourism flow network shows an irregular inverted ‘U’ distribution. Kuanzhai Alley, Hong Ya Dong and Chunxi Road have irreplaceable competitive advantages in the tourism flow network. The density of highways, the number of star-rated hotels and the regional GDP per capita are positively correlated with the effective size of the structural hole of the administrative unit. Finally, based on the research results, countermeasures are proposed to optimise the tourism development of the Chengdu–Chongqing Economic Circle.
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