Extracting Network Patterns of Tourist Flows in an Urban Agglomeration Through Digital Footprints: The Case of Greater Bay Area
Network patterns of tourist flows can reveal differences in tourism resources among destinations from the perspective of network science, providing valuable suggestions for tourism managers and policymakers to promote the balanced and sustainable development of tourism. This paper focuses on urban a...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9706203/ |
| _version_ | 1828152218429161472 |
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| author | Jiarui Mou |
| author_facet | Jiarui Mou |
| author_sort | Jiarui Mou |
| collection | DOAJ |
| description | Network patterns of tourist flows can reveal differences in tourism resources among destinations from the perspective of network science, providing valuable suggestions for tourism managers and policymakers to promote the balanced and sustainable development of tourism. This paper focuses on urban agglomerations, a highly developed spatial form of integrated cities, and proposes a research framework to extract the network patterns of tourist flows through digital footprints. Based on an illustrative case study using geo-located travel blog data from Qunar.com, we built a tourist flow network for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), China. The analysis shows: (1) GBA’s tourist flow network is obviously heterogeneous, showing a pattern of “four cores and three poles”; (2) the strong “administrative barrier effect,” revealed by community detection within the network, is the main obstacle to integrating regional tourism; (3) strengthening the infrastructure of tourism mediation cities such as Guangzhou, Zhuhai, and Shenzhen, so as to avoid the “structural hole” caused by the tourist flows between cities, is an urgent issue that the GBA government needs to address. To summarize, the research framework can provide a theoretical basis and concrete suggestions for the planning and management of the tourism industry in urban agglomerations. |
| first_indexed | 2024-04-11T22:08:39Z |
| format | Article |
| id | doaj.art-17b5305232a145c0a7dfa35ca8dd61f4 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T22:08:39Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-17b5305232a145c0a7dfa35ca8dd61f42022-12-22T04:00:38ZengIEEEIEEE Access2169-35362022-01-0110166441665410.1109/ACCESS.2022.31496409706203Extracting Network Patterns of Tourist Flows in an Urban Agglomeration Through Digital Footprints: The Case of Greater Bay AreaJiarui Mou0https://orcid.org/0000-0002-1733-1290College of Resources, Shandong University of Science and Technology, Tai’an, ChinaNetwork patterns of tourist flows can reveal differences in tourism resources among destinations from the perspective of network science, providing valuable suggestions for tourism managers and policymakers to promote the balanced and sustainable development of tourism. This paper focuses on urban agglomerations, a highly developed spatial form of integrated cities, and proposes a research framework to extract the network patterns of tourist flows through digital footprints. Based on an illustrative case study using geo-located travel blog data from Qunar.com, we built a tourist flow network for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), China. The analysis shows: (1) GBA’s tourist flow network is obviously heterogeneous, showing a pattern of “four cores and three poles”; (2) the strong “administrative barrier effect,” revealed by community detection within the network, is the main obstacle to integrating regional tourism; (3) strengthening the infrastructure of tourism mediation cities such as Guangzhou, Zhuhai, and Shenzhen, so as to avoid the “structural hole” caused by the tourist flows between cities, is an urgent issue that the GBA government needs to address. To summarize, the research framework can provide a theoretical basis and concrete suggestions for the planning and management of the tourism industry in urban agglomerations.https://ieeexplore.ieee.org/document/9706203/Tourist flowdigital footprintnetwork scienceurban agglomerationGuangdong-Hong Kong-Macao Greater Bay Area |
| spellingShingle | Jiarui Mou Extracting Network Patterns of Tourist Flows in an Urban Agglomeration Through Digital Footprints: The Case of Greater Bay Area IEEE Access Tourist flow digital footprint network science urban agglomeration Guangdong-Hong Kong-Macao Greater Bay Area |
| title | Extracting Network Patterns of Tourist Flows in an Urban Agglomeration Through Digital Footprints: The Case of Greater Bay Area |
| title_full | Extracting Network Patterns of Tourist Flows in an Urban Agglomeration Through Digital Footprints: The Case of Greater Bay Area |
| title_fullStr | Extracting Network Patterns of Tourist Flows in an Urban Agglomeration Through Digital Footprints: The Case of Greater Bay Area |
| title_full_unstemmed | Extracting Network Patterns of Tourist Flows in an Urban Agglomeration Through Digital Footprints: The Case of Greater Bay Area |
| title_short | Extracting Network Patterns of Tourist Flows in an Urban Agglomeration Through Digital Footprints: The Case of Greater Bay Area |
| title_sort | extracting network patterns of tourist flows in an urban agglomeration through digital footprints the case of greater bay area |
| topic | Tourist flow digital footprint network science urban agglomeration Guangdong-Hong Kong-Macao Greater Bay Area |
| url | https://ieeexplore.ieee.org/document/9706203/ |
| work_keys_str_mv | AT jiaruimou extractingnetworkpatternsoftouristflowsinanurbanagglomerationthroughdigitalfootprintsthecaseofgreaterbayarea |