Redai dili (Nov 2021)

Space Association Features of Domestic Tourist Flow Network in the Shanghai Metropolitan Area

  • Yan Shanshan,
  • Zhang Heqing,
  • Jin Chen

DOI
https://doi.org/10.13284/j.cnki.rddl.003394
Journal volume & issue
Vol. 41, no. 6
pp. 1313 – 1324

Abstract

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A metropolitan area refers to the central urban area and its surrounding hinterland. The area plays a strategic role in the development of its regional tourism economy. As a unique form and organization of regional spatial structure, tourist flows in metropolitan areas present different spatial structures and characteristics. However, the existing research on tourist flow is rarely explained from the perspective of metropolitan areas,. Therefore, this study examined the trip strategy data published by tourists, analyzed the spatial correlation characteristics of the tourist flow network in the Shanghai Metropolitan Area (SMA) from the node and network levels by employingsocial network theory and GIS spatial analysis methods and technologies, The results revealed the following: (1) the tourism nodes in SMAdisplayed obvious hierarchical structural characteristics, and the elite scenic spots occupied an important core position in the tourist flow network. Simultaneously, according to the comparative analysis of degree centrality and intermediary centrality, Shanghai tourism nodes, t could be categorized into four types: agglomeration, diffusion, equilibrium, and intermediary. (2) SMA presented a "single-core radial" spatial distribution pattern with Huangpu District at its center, and Huangpu District as the spatial diffusion source, with the mainstream diffusion directions of southwest (central Huangpu District-Songjiang District), southeast (central Huangpu District-Pudong New Area), northwest (central Huangpu District-Jiading District), and a few tourist flows spreading from central Huangpu District to Baoshan District and Chongming County in the north. (3) The topological structure of the Shanghai urban tourist flow network was characterized by low connection, strong diffusion, and balanced distribution. There were five condensed subgroups with high internal and low external correlations. The core-edge division of the network was significant, and the driving effect of the core area on the edge was limited. (4) There was an exponential relationship between tourist flow and the distance between scenic spots inSMA, which had an evident distance attenuation law. However, the attenuation degree in each distance segment was different, and the distance attenuation law of tourist flow was the most significant at 0–20km. Bycomparing the conclusions of this study with other types of domestic tourist flow networks, it was found that various types of domestic tourist flow networks had the same core-edge structure, but the difference lied in that other types of tourism flow networks showed the characteristics of a multi-center balanced structure, and the core nodes were usually high-grade scenic spots, while the tourist flow network in Shanghai was a "single-core radial" spatial structure with the central city as its core, and the core nodes were high-profile scenic spots without grades in the central city. This study provides an example for exploring analyzing the spatial characteristics of tourist flow networks by using the data of network travel notes and optimizing the spatial structure of tourism destinations in metropolitan areas.

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