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Evolution characteristics and influencing factors of information network in Guangdong-Hong Kong-Macao Greater Bay Area.

Authors :
Yang, Zhichen
Wu, Yuxi
Ma, Zilong
Wang, Fangfang
Chen, Rongjian
Wang, Yixuan
Tian, Zaoli
Kuang, Jiali
Chen, Yisen
Chen, Aichun
Source :
PLoS ONE; 5/17/2024, Vol. 19 Issue 5, p1-21, 21p
Publication Year :
2024

Abstract

In the context of the digital information era, the impact of "The Internet Plus," "Big Data," and other technologies on urban social development has been far beyond any preceding era, under the influence of information technology, urban agglomeration space exhibits a new layout. Based on the search engine data of eleven cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2012 to 2021, this research constructs the inter-city information network strength linkage matrix to examine the evolution characteristics of city network structure and its driving causes. The results reveal that (1) the overall information linkage strength exhibits a pattern of steadily growing the radiating effect from the leading cities of Guangdong, Shenzhen, and Hong Kong to the surrounding cities, and a closer and more balanced information linkage network is gradually built. (2) Guangzhou-Shenzhen-Hong Kong-Guangdong-Hong Kong-Macao Greater Bay Area information linkage absolute control advantage, four cities Foshan, Dongguan, Zhuhai, Macao regional hub position steadily highlighted. The entire information connection network of the urban agglomerations tends to be flat and polycentric at the same time. (3) The regional core-edge hierarchy is well established, with the four cities of Guangzhou, Dongguan, Shenzhen, and Hong Kong creating a northwest-southeast orientation. The core metropolis regions of Guangdong, Hong Kong, and Macao in the Greater Bay Area increasingly exert a radiation spreading effect to the northeast and southwest. (4) The urban economy, transportation distance, and information infrastructure have substantial effects on the information connection intensity network of urban clusters. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19326203
Volume :
19
Issue :
5
Database :
Complementary Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
177326059
Full Text :
https://doi.org/10.1371/journal.pone.0298410