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http://hdl.handle.net/10397/113429
Title: | AI-generated imagery in sustainable gastronomy tourism : a study from bottom-up to top-down processing | Authors: | Chan, J | Issue Date: | Jun-2025 | Source: | Tourism management, June 2025, v. 108, 105093 | Abstract: | This study utilized image-based experimental methods to explore the intersection of sustainability, gastronomy tourism, and Artificial Intelligence (AI), with a focus on promoting ‘climate-conscious food’. This term refers to the food produced through eco-friendly practices. Despite the benefits of climate-conscious food for individuals, the environment, and local tourism, its adoption remains limited. Conceptualized on visual information processing, this research comprises two studies employing bottom-up and top-down processing. It confirms that the type of content in AI-generated images, specifically “Food Presentation” versus “Preparation Process,” significantly influences consumers' perceptions of food quality and their purchasing intentions. This effect is moderated by consumers' knowledge of climate-conscious food and their level of environmental concern. By providing empirical evidence analyzed through multivariate statistical techniques, this study offers valuable practical and theoretical insights into how AI can promote climate-conscious food, thereby advancing sustainable gastronomy tourism. | Keywords: | AI-generated imagery Bottom-up Climate-conscious food Gastronomy tourism Top-down processing |
Publisher: | Elsevier Ltd | Journal: | Tourism management | ISSN: | 0261-5177 | EISSN: | 1879-3193 | DOI: | 10.1016/j.tourman.2024.105093 |
Appears in Collections: | Journal/Magazine Article |
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