Research on the Spatial Network Effect of Urban Tourism Flows from Shanghai Disneyland
Abstract
:1. Introduction
2. Literature Review
3. Methods
3.1. Network Node Analysis Method
3.1.1. Node Centrality
3.1.2. Closeness Centrality
3.1.3. Betweenness Centrality
3.1.4. Structural Holes
- (1)
- Effective size. Refers to the size of the individual network minus the redundancy of the network. The calculation formula is:
- (2)
- Efficiency. Refers to the ratio of the effective size of tourism nodes to the actual size.
- (3)
- Constraints. Reflects the degree to which a node directly and indirectly depends on other tourism nodes. The calculation formula is:
3.2. Network Node Analysis Method
3.2.1. Network Size
3.2.2. Network Density
3.2.3. Network Centralization
- (1)
- Degree centralization. This is the degree of network centrality calculated according to the method of degree centrality. The calculation formula is:
- (2)
- Closeness centralization. This is the degree of network centrality calculated according to the method of closeness centrality. The calculation formula is:
- (3)
- Betweenness centralization. This is the degree of network centrality calculated according to the method of betweenness centrality. The calculation formula is:
3.2.4. Core–Periphery Analysis
4. Data Selection and Sample Analysis
4.1. Data Selection
4.2. Sample Analysis
5. Analysis
5.1. Network Node Analysis
5.1.1. Analysis of Network Nodes before the Opening of Disneyland
5.1.2. Analysis of Network Nodes after the Opening of Disneyland
5.2. Overall Network Analysis
5.3. Analysis of Effects
5.3.1. Network Nuclear Overhauser Effect
5.3.2. Matthew Effect of Nodes
5.3.3. Combined Effects of Nodes
6. Discussion, Conclusion, and Policy Implications
6.1. Discussion
6.2. Conclusions
6.3. Policy Implications
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Type | Ratio (%) | Type | Ratio (%) | ||
---|---|---|---|---|---|
Travel days | one-day trip | 26.54 | Companion | couple | 7.05 |
two-day trip | 34.36 | parents | 8.48 | ||
three-day trip | 22.90 | friends | 29.00 | ||
other | 16.20 | child | 24.81 | ||
Means of transportation | high-speed rail | 34.39 | alone | 19.41 | |
airplane | 44.06 | lovers | 11.25 | ||
train | 13.34 | City transportation | metro/bus | 88.96 | |
vehicle | 2.20 | other | 11.04 | ||
self-drive | 6.01 | ||||
Source of tourists | In descending order: Jiangsu, Zhejiang, Beijing, Guangdong, Liaoning, Shandong, Fujian, Tianjin, Sichuan, Anhui, Hubei, Chongqing, Hunan, Hebei, Shaanxi, Jilin, Henan, Jiangxi, Yunnan, Heilongjiang, Shanxi, Gansu, Xinjiang, Hainan, Inner Mongolia, Guangxi, Guizhou, Tibet, Qinghai, Ningxia |
Before Opening | After Opening | |
---|---|---|
Degree centralization | 2.170% | 2.730% |
In-degree centralization | 1.768% | 1.628% |
Out-degree centralization | 1.708% | 2.296% |
In-closeness centralization | 49.950% | 42.920% |
Out-closeness centralization | 52.360% | 59.500% |
Betweenness centralization | 17.010% | 18.820% |
Ucinet6.0 Core–Peripheral Analysis | Gephi0.9.2 Degree (d) Filter Analysis | |||||
---|---|---|---|---|---|---|
Core Node | Peripheral Node | The First Layer (d ≥ 2) | The Second Layer (2 > d ≥ 1) | The Third Layer (1 > d ≥ 0.2) | The Fourth Layer (d < 0.2) | |
Before opening | The Bund, the Oriental Pearl TV Tower, Yu Garden, Nanjing Road, Chenghuang Temple | other nodes | The Bund | the Oriental Pearl TV Tower, Nanjing Road, Chenghuang Temple, Tianzifang | Yu Garden, People’s Square, Shanghai Museum, Xintiandi, Madame Tussauds, China Arts Museum, Waibaidu Bridge, Shanghai World Financial Center, Lujiazui | other nodes |
After opening | Disneyland, Chenghuang Temple, The Bund, Yu Garden, the Oriental Pearl TV Tower | other nodes | The Bund | Disneyland, the Oriental Pearl TV Tower, Chenghuang Temple, Yu Garden, Tianzifang, Nanjing Road | Waibaidu Bridge, Xintiandi, Shanghai Museum, People’s Square, Shanghai Science and Technology Museum, China Arts Museum, Wukang Building, Madame Tussauds, 1933 Old Millfun, Lujiazui, Shanghai World Financial Center, Shanghai Museum of Natural History, Sinan Mansions, Qibao Old Street, Zhujiajiao | other nodes |
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Chen, H.; Wang, M.; Zheng, S. Research on the Spatial Network Effect of Urban Tourism Flows from Shanghai Disneyland. Sustainability 2022, 14, 13973. https://doi.org/10.3390/su142113973
Chen H, Wang M, Zheng S. Research on the Spatial Network Effect of Urban Tourism Flows from Shanghai Disneyland. Sustainability. 2022; 14(21):13973. https://doi.org/10.3390/su142113973
Chicago/Turabian StyleChen, Hao, Min Wang, and Shanting Zheng. 2022. "Research on the Spatial Network Effect of Urban Tourism Flows from Shanghai Disneyland" Sustainability 14, no. 21: 13973. https://doi.org/10.3390/su142113973