The Structure and Evolution of the Tourism Economic Network of the Tibetan Plateau and Its Driving Factors

Abstract

Tourism is one of the core industries driving the economy on the Tibetan Plateau towards green development. Adopting the improved gravity model, social network analysis, and quadratic assignment procedure, this paper explores the structure and evolution characteristics of the tourism economic network on the Tibetan Plateau from 2015 to 2019. The results are as follows: (1) the tourism economic strength increased over time, but it was generally higher in Qinghai Province and lower in Tibet. (2) The network density exhibited an upwards trend overall. (3) The structure of the tourism economic network presented a significant core–periphery distribution pattern. Xining, Haixi, and Lhasa acted as a bridge between the spatial network structure of the tourism economy and had a structural hole advantage. However, some remote cities, such as Ali, Naqu, and Guoluo, had low network centricity. (4) The quadratic assignment procedure regression analysis showed that the A-level attractions and star-rated hotels significantly advanced the formation of the spatial association. This study concludes with recommendations for promoting tourism economic associations for policy-makers.

The Spatial Structure and Influencing Factors of the Tourism Economic Network in the Yangtze River Delta Urban Agglomeration

“…The core-periphery structure is a methodology used to delineate the core and peripheral areas of an overall spatial network of tourism economic connections and to measure the density of the economic connections between them [20,66,67].…”

“…Tourism reception capacity is an important criterion for measuring the service quality of a city, which, in turn, has a significant role in driving the tourism economy [71]. In general, ordinary travel agencies will prioritize the safety and comfort of accommodations when arranging tourists' itineraries, leading to closer tourism ties between cities with a higher tourism reception capacity [20]. Tourism information flow is a measure of the attention of city tourism networks, and the transmission of tourism information affects the aggregation and flow of tourism economic factors between cities, thus influencing the spatial pattern of the regional tourism economy [72].…”

“…The spatial network structure of the tourism economy in urban agglomerations can reflect the connections and correlations between different urban tourist destinations in the spatial domain, which plays an indispensable role in the tourism-industrial coordinated development of urban agglomerations [19]. Relevant studies have shown that exploring the spatial network structure of the tourism economy in urban agglomerations can effectively identify the roles and positions of different cities in the tourism development pattern; in turn, this can provide effective theoretical support in promoting the integrated development of tourism in urban agglomerations and optimizing the regional tourism spatial pattern [9,20,21]. Therefore, a rigorous and comprehensive analysis of the spatial network structure of the tourism economy in urban agglomerations is of great practical significance.…”

Impact of high-speed rail on tourism in China

“…Their tourism development benefits from the increased local accessibility on the one hand [ 40 ], and the diffusion effect from the tourism centres on the other [ 41 ]. Furthermore, the differentiation between the tourism centre and the non-tourism centre is closely related to the development of the tourism subdivided industry [ 42 ]. The impact of HSR has led to differences in the positioning of cities’ tourism functions.…”

Hierarchical Structure and Organizational Model of County Tourism Network of the Tibetan Plateau

“…In addition, the study area has become a typical objective for large-scale tourism destinations and complex spatial network structures with advantageous conditions such as rare tourism resources and rapid development of self-drive tourism. Chen et al [54] studied the tourism flow network and its driving factors on the Tibetan Plateau municipal spatial scale. Zhu et al [55] took the inbound tourism flow network as the research object and, from the perspective of comparative analysis of group tours and self-guided tours, revealed the structural characteristics and organizational patterns of Tibetan networks.…”