UNDERSTANDING CLUSTERS OF TOURIST BEHAVIOR ASSOCIATIONS USING NETWORK ANALYSIS

Wei Fan, Davis Ka Chio Fong, Gang Li, Rob Law

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Identifying tourists’ associated behaviors enables industry practitioners to design suitable and efficient marketing strategies for different tourist groups. This study proposes the use of the relationships between tourists and their behaviors for constructing networks, and the adoption of the community detection method for clustering tourist behavior networks. With this approach, tourists’ behaviors can be clustered and visually investigated. Moreover, the evolution of groups of behaviors can be analyzed for obtaining insights into the origin of differences among different tourist groups. Survey data of visitors to Macao are used as a case study, and results provide valuable insights into tourists’ behaviors.

Original languageEnglish
JournalInternational Journal of Hospitality and Tourism Administration
DOIs
Publication statusAccepted/In press - 1 Jan 2019

Keywords

  • community structure
  • Network analysis
  • tourist behavior

ASJC Scopus subject areas

  • Tourism, Leisure and Hospitality Management

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