IDEAS home Printed from https://ideas.repec.org/a/taf/rcitxx/v20y2017i11p1186-1209.html
   My bibliography  Save this article

Exploring urban tourism crowding in Shanghai via crowdsourcing geospatial data

Author

Listed:
  • Beiqi Shi
  • Jinlin Zhao
  • Po-Ju Chen

Abstract

Urban tourism is booming and, as a result, crowding is now recognized as a social constraint in many tourist cities. When related to sustainability, tourism crowding must be considered. However, the way tourists experience crowding is still a neglected topic in urban tourism research. In this study, we proposed a new approach to exploit tourism crowding from crowdsourcing geospatial data which goes beyond the scale, timeliness, and cost of traditional on-site questionnaire surveys. The new approach is based on analysis of 446,273 ‘check-in’ geotagged data from Weibo in Shanghai. The data provided a hotspot distribution of popular urban tourist attractions and a range of factors related to tourism crowding. These data provided deep insights into the relationship between crowdedness and popularity of tourist attractions. This empirical work can be extended to urban tourism crowding management environments for sustainable development of tourist attractions.

Suggested Citation

  • Beiqi Shi & Jinlin Zhao & Po-Ju Chen, 2017. "Exploring urban tourism crowding in Shanghai via crowdsourcing geospatial data," Current Issues in Tourism, Taylor & Francis Journals, vol. 20(11), pages 1186-1209, August.
    • Handle: RePEc:taf:rcitxx:v:20:y:2017:i:11:p:1186-1209
    DOI: 10.1080/13683500.2016.1224820
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13683500.2016.1224820
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13683500.2016.1224820?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jie Yin & Xiang-min Zheng & Ruey-Chyn Tsaur, 2019. "Occurrence mechanism and coping paths of accidents of highly aggregated tourist crowds based on system dynamics," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-16, September.
    2. Borowiecki, Karol Jan & Pedersen, Maja U. & Mitchell, Sara Beth, 2023. "Using big data to measure cultural tourism in Europe with unprecedented precision," Discussion Papers on Economics 5/2023, University of Southern Denmark, Department of Economics.
    3. Jie Yin & Yahua Bi, 2020. "Benign or disordered development? Assessment and simulation of security of highly aggregated tourist crowds in China," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-21, October.
    4. Cheng Shi & Yujia Zhai & Dongying Li, 2023. "Urban tourists’ spatial distribution and subgroup identification in a metropolis --the examination applying mobile signaling data and latent profile analysis," Information Technology & Tourism, Springer, vol. 25(3), pages 453-476, September.
    5. Ding Ding & Yunhao Zheng & Yi Zhang & Yu Liu, 2024. "Understanding attractions’ connection patterns based on intra-destination tourist mobility: A network motif approach," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:rcitxx:v:20:y:2017:i:11:p:1186-1209. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/rcit .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.