Abstract:

Urban tourism network structure is an important part of regional development research in China. However, previous studies have paid more attention to the urban tourism network structure characterized by physical indicators driven by government forces, ignoring the importance of virtual space network in the information age. Under the background of high-quality tourism development, urban agglomeration tourism should change from "hard connectivity" to "soft connectivity". The soft index represented by information relationship redefines the new urban tourism network and can better reveal the characteristics of regional tourism integration under different market dimensions from the perspective of "dual cycle". As the data acquisition of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is faced with many obstacles, the active tourism information relationship data in the Internet has brought new ideas to study the urban tourism network structure of the region. This paper constructs the data collection method of "city+city+tourism" based on the keyword co-occurrence in bibliometrics, the co-reference linkage in global urban network research, and the data collection method of "city+tourism" in online tourism research. Baidu Chinese search engine and Google English search engine are used to obtain the co-occurrence frequency of urban tourism information in the GBA. And the social network analysis method is used to explore the similarities and differences of urban tourism information connection strength and network structure characteristics from the domestic and international tourism market dimensions. The results show that the intensity and mean value of urban tourism information connection in the GBA increase gradually. The accumulation and diffusion of tourism information in the network, the information interaction and network relevance have been significantly improved. The trend of regional tourism integration is obvious, and the information connection pattern of domestic tourism market is more stable. The cities in the GBA have different network advantages in domestic and international tourism markets, and there are differences in tourism function division and market influence. It has formed a tourism market pattern in which the second tier cities with Dongguan, Foshan, Zhongshan and Zhuhai as the center lead the internal linkage, and the first tier cities such as Guangzhou, Hong Kong, Shenzhen and Macao lead the opening to the outside world. The core cities in the GBA have different modes of leading the development of small groups in domestic and international tourism markets. The tourism cooperation mode driven by the agglomeration of second tier cities such as Foshan, Zhongshan, Dongguan, Zhuhai and Huizhou dominates the domestic tourism market, and the first tier cities represented by Hong Kong, Guangzhou, Shenzhen and Macao cooperate with other cities to form a tourism linkage mode that dominates the international tourism market. In short, this paper uses the tourism information relationship data to break through the constraints of geographical distance, policy and economic development level, and reflects the hyperspace-time characteristics of urban tourism information network. In the field of tourism, it reveals the network structure of urban agglomeration reflected in the massive web content at home and abroad, which is a tourism functional organization system with clear division of labor and strong points. As a low-threshold information channel, the Internet gives the second tier cities in the domestic tourism market the opportunity to "flip", and the state of "the strong is always strong" in the first tier cities in the international tourism market will continue to exist, which makes this paper reveal the differences in the Matthew effect of tourism destinations in different market dimensions from the perspective of virtual space.

Key words: urban agglomeration, urban tourism information network, Guangdong-Hong Kong-Macao Greater Bay Area, network structure