| Issue |
E3S Web Conf.
Volume 664, 2025
4th International Seminar of Science and Applied Technology: “Green Technology and AI-Driven Innovations in Sustainability Development and Environmental Conservation” (ISSAT 2025)
|
|
|---|---|---|
| Article Number | 01011 | |
| Number of page(s) | 9 | |
| Section | Artificial Intelligence and Human-Computer Interaction | |
| DOI | https://doi.org/10.1051/e3sconf/202566401011 | |
| Published online | 20 November 2025 | |
From algorithms to authenticity: Unpacking AI-riven emotional experiences in ethnic gastronomic tourism
1 Tour and Travel Business Program, Politeknik Negeri Bandung, Bandung, Indonesia
2 Tourism Destination Program, Politeknik Negeri Bandung, Bandung, Indonesia
3 Universitas Buana Perjuangan Karawang, Bandung, Indonesia
4 Universitas Pendidikan Indonesia, Bandung, Indonesia
* Corresponding author: eko.susanto@polban.ac.id
This study investigates how artificial intelligence (AI) and information quality influence personalisation and emotional experiences in ethnic gastronomic tourism. Using structural equation modelling (SEM) on data from 378 tourists, the research examines the role of AI capabilities in shaping perceived personalisation and emotional engagement, and how these, in turn, affect cultural authenticity, destination attractiveness, and revisit Intention. Results indicate that AI significantly enhances emotional experience and personalisation, indirectly strengthening authenticity and destination appeal—two key drivers of revisit intention. The proposed model explains 69.4% of revisit behaviour, highlighting the potential of AI to support emotionally engaging and culturally resonant tourism. While the findings underscore AI’s strategic value in designing personalised culinary experiences, the study also acknowledges limitations related to sample scope and self-reported measures. Future research could explore longitudinal effects and cross-cultural variations to deepen the understanding of AI’s role in sustainable tourism.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.