How Generative Artificial Intelligence Transforms Destination Cultural Narratives: From a Media Ecology Perspective

Abstract

Generative artificial intelligence serves as an information medium that dynamically bridges tourists with destination cultural narratives. Drawing on the media ecology theory, this study employs a sequential mixed-methods design to explore how generative artificial intelligence adoption impacts tourists’ reactions during cultural tourism. Thematic analysis of 38 interviews was conducted to develop the conceptual model, subsequently validated through structural equation modeling using a survey of 733 tourists. The results demonstrate that tourists’ attitudes toward generative artificial intelligence adoption, shaped by its personalized and anthropomorphic features, manifest as trust and attachment, which mitigate tourists’ perceived information cocoon and subsequently promote destination-related behavioral intentions. Tourists’ self-efficacy in managing misinformation strengthens the negative relationship between their generative artificial intelligence attachment and evaluation of information cocoons. This study contributes new knowledge to the field of generative artificial intelligence adoption in cultural tourism and offers an enlightening idea for the advancement of the media ecology theory.

Keywords

generative artificial intelligence adoption information cocoon effect tourists’ behavioral intention media ecology theory cultural tourism mixed-methods

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