TY - JOUR
T1 - Revisiting Tourism Destination Image: A Holistic Measurement Framework Using Big Data
AU - Bui, Vinh
AU - Alaei, Ali Reza
AU - Vu, Huy Quan
AU - Li, Gang
AU - Law, Rob
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work described in this paper was partially supported by a grant funded by Southern Cross University.
Publisher Copyright:
© The Author(s) 2021.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - big data
KW - destination image
KW - destination management
KW - multimodal TDI model
KW - user-generated content
UR - http://www.scopus.com/inward/record.url?scp=85109728971&partnerID=8YFLogxK
U2 - 10.1177/00472875211024749
DO - 10.1177/00472875211024749
M3 - Journal article
AN - SCOPUS:85109728971
SN - 0047-2875
JO - Journal of Travel Research
JF - Journal of Travel Research
ER -