Exploring Urban Tourism Crowding In Shanghai Via Crowdsourcing Geospatial Data
Keywords
crowdsourcing geospatial data; exploratory spatial data analysis; popularity of tourist attractions; tourism crowding; urban tourism
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.
Publication Date
8-18-2017
Publication Title
Current Issues in Tourism
Volume
20
Issue
11
Number of Pages
1186-1209
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1080/13683500.2016.1224820
Copyright Status
Unknown
Socpus ID
84984911577 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84984911577
STARS Citation
Shi, Beiqi; Zhao, Jinlin; and Chen, Po Ju, "Exploring Urban Tourism Crowding In Shanghai Via Crowdsourcing Geospatial Data" (2017). Scopus Export 2015-2019. 5160.
https://stars.library.ucf.edu/scopus2015/5160