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Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks

This study uses social network analysis and modified gravity model methods to empirically analyse the network spatial correlation structure and spatiotemporal development trend of 21 cities in Guangdong Province from 2000 to 2020 based on tourism economic development data. The findings show that, fi...

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Detalles Bibliográficos
Autores principales: Zhang, Lijuan, Marzuki, Azizan, Liao, Zhenjie, Zhao, Kaixiong, Huang, Zhihao, Chen, Wenfu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382668/
https://www.ncbi.nlm.nih.gov/pubmed/37520942
http://dx.doi.org/10.1016/j.heliyon.2023.e18570
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author Zhang, Lijuan
Marzuki, Azizan
Liao, Zhenjie
Zhao, Kaixiong
Huang, Zhihao
Chen, Wenfu
author_facet Zhang, Lijuan
Marzuki, Azizan
Liao, Zhenjie
Zhao, Kaixiong
Huang, Zhihao
Chen, Wenfu
author_sort Zhang, Lijuan
collection PubMed
description This study uses social network analysis and modified gravity model methods to empirically analyse the network spatial correlation structure and spatiotemporal development trend of 21 cities in Guangdong Province from 2000 to 2020 based on tourism economic development data. The findings show that, first, Zhuhai has the greatest potential for growth as the centre of the spatial and temporal evolution trend of the network structure of the tourism economy in Guangdong Province, ahead of Shenzhen, Huizhou, Zhaoqing, Zhongshan, Jiangmen and Dongguan. However, Guangzhou, the capital city of Guangdong Province, is experiencing a decline in such influence and development. Second, there is a counter-trend growth in the number of tourism-related economic links among the 21 cities. Although Guangdong's tourism economic network intensity is strong, there is still room for further optimisation. Third, the results of the overall network indicators show that there is a need for further improvement in network density, grade and efficiency to help reduce the relative development gap of the cities' tourism and effectively improve the overall development of Guangdong's tourism economy. Finally, based on the core–periphery structure, this study proposes relevant suggestions for the sustainable development of Guangdong's tourism industry.
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spelling pubmed-103826682023-07-30 Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks Zhang, Lijuan Marzuki, Azizan Liao, Zhenjie Zhao, Kaixiong Huang, Zhihao Chen, Wenfu Heliyon Research Article This study uses social network analysis and modified gravity model methods to empirically analyse the network spatial correlation structure and spatiotemporal development trend of 21 cities in Guangdong Province from 2000 to 2020 based on tourism economic development data. The findings show that, first, Zhuhai has the greatest potential for growth as the centre of the spatial and temporal evolution trend of the network structure of the tourism economy in Guangdong Province, ahead of Shenzhen, Huizhou, Zhaoqing, Zhongshan, Jiangmen and Dongguan. However, Guangzhou, the capital city of Guangdong Province, is experiencing a decline in such influence and development. Second, there is a counter-trend growth in the number of tourism-related economic links among the 21 cities. Although Guangdong's tourism economic network intensity is strong, there is still room for further optimisation. Third, the results of the overall network indicators show that there is a need for further improvement in network density, grade and efficiency to help reduce the relative development gap of the cities' tourism and effectively improve the overall development of Guangdong's tourism economy. Finally, based on the core–periphery structure, this study proposes relevant suggestions for the sustainable development of Guangdong's tourism industry. Elsevier 2023-07-21 /pmc/articles/PMC10382668/ /pubmed/37520942 http://dx.doi.org/10.1016/j.heliyon.2023.e18570 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Zhang, Lijuan
Marzuki, Azizan
Liao, Zhenjie
Zhao, Kaixiong
Huang, Zhihao
Chen, Wenfu
Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks
title Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks
title_full Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks
title_fullStr Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks
title_full_unstemmed Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks
title_short Spatial and temporal evolution of Guangdong tourism economic network structure from the perspective of social networks
title_sort spatial and temporal evolution of guangdong tourism economic network structure from the perspective of social networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10382668/
https://www.ncbi.nlm.nih.gov/pubmed/37520942
http://dx.doi.org/10.1016/j.heliyon.2023.e18570
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