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

9 Citations (Scopus)


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
JournalJournal of Travel Research
Publication statusAccepted/In press - 2021


  • 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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