Categorisation of cultural tourism attractions by tourist preference using location-based social network data: The case of Central, Hong Kong

Zhewei Liu, Anqi Wang, Karin Weber, Edwin H.W. Chan, Wenzhong Shi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

In contrast to traditional surveys collecting tourists' stated responses, location-based social network data provide information about tourists' observed behaviours. This study proposes a methodology to categorise cultural tourism attractions based on tourists' preferences detected by their citywide travel trajectories. It was applied to Central, a district in Hong Kong, by using Instagram data of tourists who geotagged certain attraction(s) in the study area from May 2018 to April 2020. Four categories were identified through cluster analysis, and a typology of cultural tourism attractions was proposed based on the importance of historical and contemporary features. The results show significant differences among the clusters and within Hong Kong's short-haul markets. Japanese tourists prefer ‘Heritage centres’ and ‘Art galleries/Performance venues’ while tourists from Thailand prefer ‘Historic sites’ and ‘Street markets’. The study contributes an innovative approach to differentiate cultural tourism attractions, which is helpful in targeting potential tourists.

Original languageEnglish
Article number104488
JournalTourism Management
Volume90
DOIs
Publication statusPublished - Jun 2022

Keywords

  • Cultural tourism
  • Hong Kong
  • Location-based big data
  • Social media
  • Tourist preference
  • Urban revitalization

ASJC Scopus subject areas

  • Development
  • Transportation
  • Tourism, Leisure and Hospitality Management
  • Strategy and Management

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