Destination Hyperreality through Generative Artificial Intel-ligence: Shaping Tourist Expectations, Satisfaction, and Loyalty
DOI:
https://doi.org/10.61132/ijema.v3i3.1303Keywords:
Destination Loyalty, Destination Satisfaction, Expectation–Reality Gap, Generative Artificial Intelligence, Hyperreal Destination ImageAbstract
The advent of Generative Artificial Intelligence (GenAI) has completely changed how travelers obtain information about destinations and create pre-trip impressions. Destination simulations produced by GenAI may produce hyperrealistic depictions of destinations that deviate from travelers' true experiences, perhaps impacting expectations and subsequent assessments. The purpose of this study is to investigate how hyperreal destination pictures are shaped using GenAI-based destination simulations and how this affects visitor expectation formation, the expectation–reality gap, destination satisfaction, and destination loyalty. Partial Least Squares–Structural Equation Modeling (PLS-SEM) was used as a quantitative method. 420 respondents who have used GenAI to research tourist destinations participated in the study. The links between Generative AI Destination Simulation, Hyperreal Destination Image, Tourist Expectation Formation, Expectation–Reality Gap, Destination Satisfaction, and Destination Loyalty were investigated by the suggested model. The results show that Hyperreal Destination Image is positively impacted by Generative AI Destination Simulation, which in turn improves the construction of visitor expectations. The Expectation–Reality Gap is widened by higher expectations, which has a detrimental impact on destination satisfaction and loyalty. Destination satisfaction has a favorable impact on Destination loyalty and the Expectation-Reality Gap are mediated by loyalty. These results imply that GenAI serves as a method for creating symbolic destination realities that influence travelers' assessments of their genuine experiences in addition to being an information medium.
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