Based on the modified GM, the cooperative gravity values of 55 tourist attractions in the YRD were calculated, and a cooperative relationship matrix of tourist attractions was constructed. According to this matrix, Netdraw, a visualization tool in Ucinet 6.0 software, was used to build a cooperation network of 55 tourist attractions in the YRD (
Figure 2). Through the network diagram, we found that there were no isolated phenomena in the development of tourist attractions, and there was an obvious correlation in space; that is, there was a cooperative relationship among all the tourist attractions.
3.3.3. Centrality Analysis
To further analyze the characteristics of the cooperation network, this study measured the degree, closeness, and betweenness centralities of the 55 selected tourist attractions.
Table 4 shows the calculation results and the corresponding rankings of the indicators.
The highest and lowest degree centralities of the 55 tourist attractions were 100.000 and 48.148, respectively, with a mean of 64.242. The degree centrality values of tourist attractions in Suzhou, Hangzhou, and Shanghai were significantly higher than those of other tourist attractions; therefore, these tourist attractions were in a more central position in the network. The five lowest-degree centrality values were exhibited by Daming Temple, Slender Westlake, Hangzhou Xixi National Wetland Park, Long Wu Tea Town, and CCTV Wuxi Studios. These five tourist attractions are in a subordinate position in the network, possibly owing to their remote geographical locations and limitations in transportation and resources. This also indicates that the spatial imbalance in cooperation remains relatively obvious. In addition, mutual connections and cooperation among tourist attractions in the YRD are mainly conducted through tourist attractions in Shanghai, Suzhou, and Hangzhou. This is primarily because there are fewer spatial obstacles to cooperation among tourist attractions in the three cities mentioned above. First, most of these tourist attractions are in the hub position, and their geographical locations are superior. Second, the hub position provides better transportation conditions for strengthening tourism cooperation and affects the tourism links of other tourist attractions. In addition, these attractions have attracted tourists’ attention because of their high popularity. To meet their higher tourism needs, tourists travel to multiple destinations, thereby driving the tourism development of surrounding tourist attractions and, thus, forming cooperative ties.
The highest value was 100.000, the lowest was 65.854, and the mean was 75.219. These values are generally high, and the closeness centrality distribution is relatively balanced compared with that of the degree centrality. This shows that tourist attractions in the YRD cooperate quickly with each other. This may be a result of the following factors: First, with the deepening of the integrated development of tourism in the YRD, there are increasing numbers of cross-administrative regions and diversified products on a series of tourist routes, and the cooperation among tourist attractions across different administrative regions, such as provinces and cities, is getting closer. Second, because of the strengthening of the interactive and complementary capabilities of the tourism industry, the depth and breadth of cooperation among tourist attractions have been further enhanced. In addition, there are 18 tourist attractions with higher values nearer to the center than the average, including the Classical Gardens of Suzhou, Shantang Street, Hanshan Temple, Mudu Ancient Town, Lion Grove Garden, Tongli Ancient Town, Pingjiang Road Historic Street, and Zhouzhuang in Suzhou; Shanghai Oriental Pearl Radio and TV Tower and Sightseeing Hall Jinmao Tower in Shanghai; Yuantouzhu Scenic Area and Lingshan Buddhist Scenic Spot in Wuxi; Wuzhen and Xitang Ancient Town in Jiaxing; Nanxun Ancient Town and Tianmu Lake in Changzhou; and Qing He Lane and West Lake in Hangzhou. These tourist attractions are rich in tourism resources and are either well known, such as the Classical Gardens of Suzhou, Zhouzhuang, West Lake, and Wuzhen, or have superior locations and traffic conditions, such as Shanghai Oriental Pearl Radio and TV Tower and Sightseeing Hall Jinmao Tower. This indicates that tourist attractions with high tourism resource endowments have more connections to other tourist attractions in the tourism cooperation network.
- (4)
Betweenness centrality
The mean value of the betweenness centrality was 0.675, with 14 tourist attractions having greater betweenness centrality values than the mean: the Classical Gardens of Suzhou, Shantang Street, Hanshan Temple, Mudu Ancient Town, Lion Grove Garden, Tongli Ancient Town, Pingjiang Road Historic Street, Yuantouzhu Scenic Area, Nanxun Ancient Town, Lingshan Buddhist Scenic Spot, Wuzhen, Zhouzhuang, Tianmu Lake, and QianDao Lake. The total score of the betweenness centralities of these tourist attractions was 30.459, accounting for 82.180%, indicating that the formation of the most cooperative relations in tourist attractions was completed through these tourist attractions. Tourist attractions play an “intermediary” role in cooperation networks.
In addition, the top 15 tourist attractions with a betweenness centrality score not only included popular tourist attractions in Shanghai, Hangzhou, Suzhou, and Nanjing but also Nanxun Ancient Town in Huzhou, Tianmu Lake in Changzhou, and Xitang Ancient Town in Jiaxing. This shows that not only do some popular tourist attractions, as the collection and distribution centers of tourism flows, have the “intermediary” function for connecting tourist attractions but also some unpopular tourist attractions show an outstanding “intermediary” ability. These tourist attractions are key “intermediaries” in the cooperation networks of tourist attractions in the YRD.
It is worth noting that the bottom five tourist attractions regarding the betweenness centrality are the Nanjing Pearl Spring Scenic Area, Shanghai Urban Planning Exhibition Center, Yu Garden, Shanghai Haichang Ocean Park, and Shanghai Wild Animal Park. It is difficult for them to play intermediate or dominant roles in a cooperation network. In short, from the perspective of the centrality value, 55 tourist attractions in the YRD have universal cooperative relations. Tourist attractions with strong tourism distribution functions, obvious location advantages, and high tourism resource endowments not only have a significant central position in the cooperation network but also have a strong intermediary role.
3.3.4. Cohesive Subgroup Analysis
Cohesive subgroup analysis can explain the clustering characteristics of each node in a network. Cohesive subgroup analysis was designed to explore the internal substructure of the network, divide the subgroups under certain conditions, and identify the members of each subgroup. Therefore, the application of cohesive subgroup analysis can further determine whether there are “small groups” in the cooperation network that reveal which tourist attractions in the YRD have closer cooperation links. We used the CONCOR program in Ucinet 6.0 to conduct cluster analysis on the internal structure of the cooperation network and obtained the cohesive subgroup density table (
Table 5) and tree diagram of the YRD tourist attraction cooperation network.
The cooperation network of tourist attractions in the YRD has an obvious multilevel subgroup structure. The cohesive subgroups (
Table 6) can be further divided into four subgroups at level 2. First, is the southeastern cooperative subgroup of the YRD, which is composed of 11 tourist attractions. From the spatial perspective, this subgroup is based on the tourist attractions in Hangzhou as the core and drives the common development of the tourist attractions in Shaoxing and Zhoushan.
Second, is the eastern cooperation subgroup of the YRD, including 27 tourist attractions in Shanghai, Suzhou, Wuxi, and Jiaxing. Spatially, the Shanghai second subgroup consists of Yu Garden, the Shanghai World Financial Center Observatory, the Top of Shanghai Observatory, the Shanghai Urban Planning Exhibition Center, the Temple of the City God, Shanghai Haichang Ocean Park, Shanghai Science and Technology Museum, Shanghai Wild Animal Park, Shanghai Disney Resort, Madame Tussauds, Sightseeing Hall Jinmao Tower, Shanghai Oriental Pearl Radio and TV Tower, Small Lujiazui, and Tongli Ancient Town. Hanshan Temple, Mudu Ancient Town, Lion Grove Garden, Shantang Street, Pingjiang Road Historic Street, and the Classical Gardens of Suzhou form the main body of the Suzhou second subgroup, and the tourist attractions in Wuxi and Jiaxing are dependent on the two subgroups.
Third, is the central cooperative subgroup of the YRD, including QianDao Lake in Hangzhou and Tianmu Lake in Changzhou, which are located at the periphery of the entire network.
Fourth, is the northern cooperative subgroup of the YRD, including 15 tourist attractions in Nanjing and Yangzhou. Nanjing’s tourist attractions have close cooperation, whereas Yangzhou’s tourist attractions are in a relatively marginal position. The inner density of these four subgroups is close to 1, indicating that the members of these cohesive subgroups are closely connected and frequently interact through information sharing and cooperation.
According to the subgroup division at the third level of the cohesive subgroups (
Table 6), tourist attractions can be divided into seven subgroups. Tourist attractions in Shanghai and Suzhou are at the core of the tourist attraction cooperation network and have a strong tourism correlation effect on each cohesive subgroup. Owing to its comprehensive economic strength and transportation-hub-center status, Shanghai has become a single cohesive subgroup, driving the cooperation and development of Wuxi and Jiaxing tourist attractions through radiation and diffusion. Suzhou is rich in tourism resources and has a good reputation that is favored by tourists. Most of its domestic tourist attractions formed a single cohesive subgroup. In addition, among these seven cohesive subgroups, the 1st, 3rd, 4th, and 6th cohesive subgroups are all formed by tourist attractions in the same province (city) and adjacent geographical locations. It can be inferred that provincial (city) administrative divisions may have an important impact on regional tourism cooperation. Therefore, removing policy obstacles is the premise for promoting regional tourism cooperation.