Spatial Network Structure and Influencing Factors of the Urban Tourism Economy in China

An Empirical Study Based on 284 Prefecture-Level Cities

Bibliographic Data

ID22006232
AuthorsLing-Ling Fan (0000-0002-7112-9261, Jiangxi Science and Technology Normal University), Yalan Shi (0000-0003-2295-6073, Huaqiao University, corresponding author), Xiao-Yan Wang (0000-0003-3009-8638, Changzhou Vocational Institute of Textile and Garment)
Year2025
Volume15
Issue4
Publication date2025-10-01
Open AccessYes
TypeARTICLE
VenueSAGE Open (JOURNAL)
Journal identifiersISSN: 2158-2440 • E-ISSN: 2158-2440
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/21582440251406093
OpenAlexW7115008005
LanguageEN
References cited36

Tourism increasingly reflects living standards, with its economic impact steadily growing. This research employs a modified gravity model and social network analysis to assess tourism-driven economic linkages among 284 Chinese prefecture-level cities (2007–2019). It investigates the spatial network structure of urban tourism sectors and identifies key influencing factors. The findings indicate that tourism economic connections have been consistently strengthened, but such connections’ overall level remains low, with significant intercity disparities, reflecting the “Matthew effect” prevalent in core cities. The interconnected web of urban tourism economies demonstrates strong mutual influence and ripple effects. The network’s structure is strengthening, but its unity could be enhanced. Furthermore, the spatial network is characterized by a “diamond” configuration, with the Beijing-Tianjin-Hebei region, the Yangtze River Delta, the Pearl River Delta, the Wuhan area, and the Chengdu-Chongqing regions serving as pivotal axes connected by boundaries, demonstrating an evolution from points to lines and from lines to surfaces. The layout of urban tourism economies is really shaped by a few key things. Being close to other cities, having different attractions, and not being on the same level economically tends to bring cities together. On the flip side, if cities have very different industries, that can actually create some distance between them when it comes to tourism. This study puts forward specific strategies and suggestions

Economic impact analysis · Empirical research · Gravity model of trade · Social network analysis · Tourism · Tourism geography · Yangtze river · Diverse Aspects of Tourism Research · Global Urban Networks and Dynamics · Regional Economics and Spatial Analysis

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Open DOIOpen Access