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Spatiotemporal Characteristics and Factors Influencing Urban Tourism Market Network in Western China: Taking Chengdu as an Example

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  • Chen-Hao Xue

    (College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China
    College of management, Northwest Minzu University, Lanzhou 730030, China)

  • Yong-Ping Bai

    (College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China)

Abstract

Urban tourism network attention is important for measuring the competitiveness of the urban tourism industry, tourism attraction, and cultural soft power. In this study, we explored the spatiotemporal patterns and factors influencing network attention in the tourist source market and discussed how tourism cities can increase network attention, thus improving the competitiveness of urban cyberspace and developing soft power. Taking Chengdu as a research case, we obtained data on its tourism network attention from 31 provinces (autonomous regions and municipalities) between 2011 and 2021. We measured the spatiotemporal characteristics of network attention using the inter-annual change index, seasonal concentration index, potential tourists’ concentration coefficient, and ESDA model and analyzed the factors affecting spatiotemporal changes in network attention using the geographic weighted regression (GWR) model. The results revealed that from 2011 to 2021, the network attention of Chengdu tourism showed an overall “M”-type fluctuation trend, with significant seasonal differences and disequilibrium and significant differences in space, signifying an overall “∩”-shaped distribution trend. This suggested a weak negative spatial correlation. Further, the number of mobile Internet users, people in higher education per 100,000 people, per capita gross domestic product, urbanization rate, and passenger throughput are important factors that affect the network attention of Chengdu tourism. Thus, these results can be used by cities in western China to optimize the network attention rating system of urban tourism, strengthen the promotion of urban image, build a sustainable city, and transform network traffic into effective economic growth.

Suggested Citation

  • Chen-Hao Xue & Yong-Ping Bai, 2023. "Spatiotemporal Characteristics and Factors Influencing Urban Tourism Market Network in Western China: Taking Chengdu as an Example," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8135-:d:1148908
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    1. Kalyan Singhal & Qi Feng & Ram Ganeshan & Nada R. Sanders & J. George Shanthikumar, 2018. "Introduction to the Special Issue on Perspectives on Big Data," Production and Operations Management, Production and Operations Management Society, vol. 27(9), pages 1639-1641, September.
    2. Yuzhen Li & Guofang Gong & Fengtai Zhang & Lei Gao & Yuedong Xiao & Xingyu Yang & Pengzhen Yu, 2022. "Network Structure Features and Influencing Factors of Tourism Flow in Rural Areas: Evidence from China," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    3. Aaronson, Daniel & Brave, Scott A. & Butters, R. Andrew & Fogarty, Michael & Sacks, Daniel W. & Seo, Boyoung, 2022. "Forecasting unemployment insurance claims in realtime with Google Trends," International Journal of Forecasting, Elsevier, vol. 38(2), pages 567-581.
    4. Guanghai Zhang & Hongying Yuan, 2022. "Spatio-Temporal Evolution Characteristics and Spatial Differences in Urban Tourism Network Attention in China: Based on the Baidu Index," Sustainability, MDPI, vol. 14(20), pages 1-15, October.
    5. Li, Xiang (Robert) & Lai, Chengting & Harrill, Rich & Kline, Sheryl & Wang, Liangyan, 2011. "When east meets west: An exploratory study on Chinese outbound tourists’ travel expectations," Tourism Management, Elsevier, vol. 32(4), pages 741-749.
    6. Peixue Liu & Xiao Xiao & Jie Zhang & Ronghua Wu & Honglei Zhang, 2018. "Spatial Configuration and Online Attention: A Space Syntax Perspective," Sustainability, MDPI, vol. 10(1), pages 1-15, January.
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    1. Fengzhi Sun & Zihan Li & Mingzhi Xu & Mingcan Han, 2024. "New Changes in Chinese Urban Tourism Pattern under the Impact of COVID-19 Pandemic: Based on Internet Attention," Sustainability, MDPI, vol. 16(14), pages 1-22, July.

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