Research on the Structural Characteristics and Evolutionary Process of China's Tourism Investment Spatial Correlation Network.

The paper uses the revised gravity model to measure the intensity of tourism investment spatial correlation, constructs the spatial correlation matrix of tourism investment, and uses the social network method to analyze the structural characteristics and evolutionary process of tourism investment spatial correlation network based on 31 provinces in China from 2000 to 2016. The findings revealed: (1) The spatial correlation quantity of interprovincial tourism investment continues to grow, with Beijing, Jiangsu, Zhejiang, Shanghai, Shandong, and Guangdong at the top of the list. (2) Overall network density and correlation are rising, and the spatial correlation of interprovincial tourism investment is increasingly close. Network hierarchy and network efficiency are decreasing, and network stability has been enhanced. (3) Degree centrality and closeness centrality of each province have shown a significant increase; Beijing, Shandong, Guangdong, Jiangsu, Zhejiang, and Shanghai are the top six and in the center of the network. Most provinces have improved betweenness centrality, Beijing, Guangdong, Shandong, Liaoning, Shaanxi, and Hunan have a strong betweenness centrality with strong intermediary capacity. (4) The core area mainly includes eastern and central provinces, and the periphery areas mainly include western and northeastern provinces. The network connection density of the core and periphery areas shows an increasing trend, while the network linkage density between the core and periphery areas shows a downward trend.

Research on the Spatial Structure of the European Union's Tourism Economy and Its Effects.

With the implementation of European integration policies such as the single market, the Euro and the Schengen Visa, the EU member states are developing closer economic ties through tourism, and their level of tourism integration is constantly improving. Taking the 28 EU member states as research objects, this paper constructs a tourism economic connection network among them, measures the strength of their tourism economic connections from 1995 to 2018 by using the modified gravity model and social network method, and analyzes the spatial structure characteristics and effects of the EU tourism economy. The results are as follows: (1) The tourism economic ties of EU member states are growing increasingly close, enhancing network stability. (2) Germany, France, Italy, Austria and the United Kingdom are the top five countries in the degree centrality and closeness centrality rankings, meaning that they are located in the center of the network and have great influence, and the network is becoming increasingly concentrated. Germany, Italy, Sweden, Austria and France play an important intermediary role in the network, and the centrality of most member states has increased. (3) The core areas are mainly concentrated in Western Europe, Southern Europe, Mediterranean mainland countries and Central Europe, while the marginal areas are mainly concentrated in Eastern Europe, Northern Europe and Mediterranean island countries; the network connection density of the core area, the network connection density of the marginal area, and the network connection density between the core and marginal area overall show an increasing trend. (4) Improvements in the complete network connectedness and a reduction in graph efficiency can significantly reduce differences in EU tourism economic development levels and improve spatial equity.

Local-Migrant Interaction in Everyday Life in an Ancient Tourism Town.

Daily interaction is a primary means of understanding social change which is of vital importance for community well-being. In tourism host communities, daily interactions among different resident groups reflect tourism's effects which are directly related to tourists' experiences and community harmony. In this exploratory article, grounded theory was applied to analyze daily interactions between locals and migrants in Zhouzhuang, the first ancient tourism town in China, based on in-depth interviews. A model framework was also constructed. The results pinpoint subjective interaction intention and objective interaction opportunities as two influencing factors which operate reciprocally and directly influence locals' and migrants' daily interactions. The findings suggest that many locals and migrants experience clear communication boundaries in daily interactions. Both groups' subjective interaction intentions were influenced by their cultural backgrounds, group perceptions, and original social networks, all of which are difficult to modify within a short time. Therefore, increasing objective communication opportunities is a key way to promote intergroup interaction and integration. These findings provide theoretical and practical implications for tourism host communities' well-being and sustainable development.