A Framework for Destination Uniqueness Identification through Concept Modeling of Tourist-generated Travel Photos

Simple item page
dc.contributor.author Nguyen, Thuc
dc.contributor.author Vu, Huy Quan
dc.contributor.author Cybulski, Jacob L.
dc.contributor.author Nguyen, Lemai
dc.date.accessioned 2023-12-26T18:47:26Z
dc.date.available 2023-12-26T18:47:26Z
dc.date.issued 2024-01-03
dc.identifier.isbn 978-0-9981331-7-1
dc.identifier.other 2af816f1-9fa4-4466-96be-808e0aa87e90
dc.identifier.uri https://hdl.handle.net/10125/107063
dc.language.iso eng
dc.relation.ispartof Proceedings of the 57th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Geospatial Big Data Analytics
dc.subject concept modelling
dc.subject destination competitiveness
dc.subject destination uniqueness
dc.subject geotagged travel photos
dc.subject travel experience
dc.title A Framework for Destination Uniqueness Identification through Concept Modeling of Tourist-generated Travel Photos
dc.type Conference Paper
dc.type.dcmi Text
dcterms.abstract In the ever-changing tourism industry, destinations face the difficult task of defining their distinct identity to attract tourists in a highly competitive market. The advent of digital technology has not only revolutionized how content is created and shared, but it has also given tourists the power to influence how a destination is perceived. This study introduces the Destination Uniqueness Identification Framework (DUIF) leveraging concept modeling to analyze geotagged travel photos shared by travelers. DUIF aims to identify both common and unique travel experiences within a country and its cities from tourists’ perspectives. The proposed framework was validated through a case study of Australia, successfully pinpointing unique themes such as Sydney's light festivals and Melbourne's graffiti streets. This study provides valuable insights into the behaviors and preferences of tourists, which contribute to the existing literature on tourism research and offer useful information for destination marketers seeking to develop targeted marketing strategies.
dcterms.extent 10 pages
prism.startingpage 5629
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
0552.pdf
Size:
1.1 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Geospatial Big Data Analytics