ORCID
- Waqas Ali: 0000-0002-6200-8580
- Dulekha Kasturiratne: 0009-0000-1959-0918
- Irfan Ameer: 0000-0002-2379-7863
- Shikhar Bhaskar: 0000-0002-8835-1918
Abstract
This study examines whether generative AI can enhance tourist sentiment in online reviews by acting as a consistent and scalable form of digital engagement. Using a quasi-experimental Difference-in-Differences design, we analysed 11,393 reviews collected for six months from five Indian restaurants in a UK tourist city, where one restaurant adopted ChatGPT-generated responses and four served as controls. Results show that AI mediated responses produced a significant improvement in tourist sentiment, with similar effects across both social (Google, Facebook) and delivery-oriented platforms (Deliveroo, Just Eat, Uber Eats). Response features such as tone, personalisation, and length had limited additional influence, indicating that the presence of a response matters more than its specific stylistic qualities. The findings suggest that GAI-mediated responses influence tourist sentiment primarily by signalling organisational attentiveness and relational legitimacy, rather than through nuanced stylistic features of the response. The study demonstrates how AI can support post-visit engagement in tourism settings and offers practical guidance for firms seeking efficient strategies to manage online reviews and strengthen their digital service presence.
DOI Link
Publication Date
2026-03-06
Publication Title
Service Industries Journal
ISSN
0264-2069
Acceptance Date
2026-02-24
Deposit Date
2026-03-29
Additional Links
Keywords
generative AI, online reviews, quasi-experimental design, Service-Dominant Logic, Tourist sentiment
Recommended Citation
Ali, W., Kasturiratne, D., Ameer, I., & Bhaskar, S. (2026) 'Generative AI in digital engagement: a quasi-experimental study of tourist sentiment', Service Industries Journal, . Available at: 10.1080/02642069.2026.2638226
