Tourism destination stereotypes and generative artificial intelligence (GenAI) generated images

Jingjie Zhu, Lingxue Zhan, Jie Tan and Mingming Cheng

Current Issues in Tourism, 2025, vol. 28, issue 17, 2721-2725

Abstract: Generative artificial intelligence (GenAI) has started transforming the tourism industry with wide research implications. While recognising its transformative power, tourism literature failed to identify the dark side of GenAI. Using advanced image analytics across 10 tourism destinations, this research investigates how GenAI-generated images reinforce tourism destination stereotypes. Our findings reveal that GenAI tends to generate highly homogenised images, which cannot fully capture the diversity of destinations, leading to stereotypes. This study advances extant tourism literature by providing critical insights into the complex relationships between generative artificial intelligence and tourism.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/13683500.2024.2381250 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:rcitxx:v:28:y:2025:i:17:p:2721-2725

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rcit20

DOI: 10.1080/13683500.2024.2381250

Access Statistics for this article

Current Issues in Tourism is currently edited by Jennifer Tunstall

More articles in Current Issues in Tourism from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().