Revisiting Tourism Destination Image: A Holistic Measurement Framework Using Big Data

Vinh Bui, Ali Reza Alaei, Huy Quan Vu, Gang Li, Rob Law

Research output: Journal article publicationJournal articleAcademic researchpeer-review

49 Citations (Scopus)

Abstract

Understanding and being able to measure, analyze, compare, and contrast the image of a tourism destination, also known as tourism destination image (TDI), is critical in tourism management and destination marketing. Although various methodologies have been developed, a consistent, reliable, and scalable method for measuring TDI is still unavailable. This study aims to address the challenge by proposing a framework for a holistic measure of TDI in four dimensions, including popularity, sentiment, time, and location. A structural model for TDI measurement that covers various aspects of a tourism destination is developed. TDI is then measured by a comprehensive computational framework that can analyze complex textual and visual data on a large scale. A case study using more than 30,000 images, and 10,000 comments in relation to three tourism destinations in Australia demonstrates the effectiveness of the proposed framework.

Original languageEnglish
Pages (from-to)1287 - 1307
JournalJournal of Travel Research
Volume61
Issue number6
DOIs
Publication statusPublished - Jul 2022

Keywords

  • big data
  • destination image
  • destination management
  • multimodal TDI model
  • user-generated content

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation
  • Tourism, Leisure and Hospitality Management

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