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

Socpus ID

84984911577 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84984911577

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