Evolution and Driving Mechanism of Tourism Flow Networks in the Yangtze River Delta Urban Agglomeration Based on Social Network Analysis and Geographic Information System: A Double-Network Perspective

Abstract

This study’s purpose was to analyze the network structural characteristics, nodal roles, spatial structure, and evolution laws from the dual network perspective, and apply the Quadratic Assignment Procedure (QAP) to conduct correlation analysis and regression analysis on the influencing factors of tourism flow networks in the Yangtze River Delta urban agglomerations. Using a mixed-method of social network and spatial analysis, Ucinet and ArcGIS software were used to comprehensively analyze the nodes in the travel routes covered in travel notes. The results show that the density of tourism flow network increases on the whole, while the spatial difference decreases, and the overall network density value is much lower than the average of the network density of provinces. Degree centrality, closeness centrality, betweenness centrality and the core–periphery structure analysis were used to examine the tourism function, distribution function, connection function and the position of nodes in the network, and nodes were divided into various types of roles according to their function. Meanwhile, the role changes of each node in different periods were also investigated. This study also builds an evaluation model of the influencing factors of the evolution of tourism flow network structure and uses QAP to find that the tourism network is affected by factors such as tourism resource endowment, transportation convenience, economic development level, tourism reception and service capacity. The research results are helpful for the Chinese government and tourism enterprises to understand the spatial behavior of tourists and its evolution rules, and to clarify the role and status of node cities in the tourism flow network and their influencing factors. It is of great significance for the formulation of joint marketing measures and promotion of the sustainable development of tourism in the Yangtze River Delta urban agglomeration.

Analysis on the Spatial Structure and Interaction of Aviation Network and Tourism Efficiency Network in Major Cities in China

“…It can also be applied to regression analysis of matrices and examine interaction effects between multiple networks [45]. The method has been shown to be robust and reliable by several scholars [46][47], avoiding issues of multiple collinearities of independent variables in causality analysis.…”

Knowledge map of digital tourism: A bibliometric approach using CiteSpace

“…It usually refers to the system that combines spatial geographic information with tourism information under the network environment and virtually realizes the tourism information service system with a sense of authenticity in the computer network. It is a digital realization of the whole process of tourism (Wang et al, 2022).…”

Evaluation and Spatial Characteristics of Cooperation among Tourist Attractions Based on a Geographic Information System: A Case Study of The Yangtze River Delta Region, China

“…Yin et al identified a set of factors that affect tourism cooperation in China-ASEAN including differences in political system, governance, and income [28]. In addition to the abovementioned factors influencing cooperation between tourism destinations from the perspective of supply (including governments and enterprises), some scholars have also analyzed factors influencing cooperation between tourism destinations from the perspective of demand [29][30][31][32]. The multidestination tourism behavior of tourists is regarded as the driving factor of cooperation among tourism destinations [29][30][31][32].…”

“…In addition to the abovementioned factors influencing cooperation between tourism destinations from the perspective of supply (including governments and enterprises), some scholars have also analyzed factors influencing cooperation between tourism destinations from the perspective of demand [29][30][31][32]. The multidestination tourism behavior of tourists is regarded as the driving factor of cooperation among tourism destinations [29][30][31][32]. The spatial behavior and movement of tourists' free choice objectively connect different tourist destinations.…”

“…The spatial behavior and movement of tourists' free choice objectively connect different tourist destinations. Therefore, these tourist destinations can establish mutual trust, respect, and other interactive relations through communication, thus forming a mutually beneficial cooperative relationship [29][30][31][32].…”