Exploring urban tourism crowding in Shanghai via crowdsourcing geospatial data

Beiqi Shi, Jinlin Zhao and Po-Ju Chen

Current Issues in Tourism, 2017, vol. 20, issue 11, 1186-1209

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.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://hdl.handle.net/10.1080/13683500.2016.1224820 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:rcitxx:v:20:y:2017:i:11:p:1186-1209

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rcit20

DOI: 10.1080/13683500.2016.1224820

Access Statistics for this article

Current Issues in Tourism is currently edited by Jennifer Tunstall

More articles in Current Issues in Tourism from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().