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Publication date: 10 January 2025

Zahy Ramadan and Jad Ramadan

While the fields of artificial intelligence (AI) and avatars are growing at a very fast pace, studies are still scarce. This study aims to fill the gap in the literature relating…

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Abstract

Purpose

While the fields of artificial intelligence (AI) and avatars are growing at a very fast pace, studies are still scarce. This study aims to fill the gap in the literature relating to the implications of highly realistic avatars as well as the consequences of AI-led co-creation on hospitality services in the Metaverse.

Design/methodology/approach

The authors adopted an exploratory qualitative methodology to study the role of AI avatars in the Metaverse within the hospitality context. The study involved interviews with both elite figures and consumers as primary data and also incorporated secondary data sourced from comments on a YouTube video related to avatars.

Findings

Based on data triangulation, the extracted themes dealt with four key areas: (1) avatars’ relational encounters in hospitality, (2) avatars’ realism, (3) self-representation and self-perception skewness and (4) AI co-creation. The findings show that while avatars’ realism would increase the authenticity of virtual social connections, engagement and monetization, the issue of a self-misrepresentation will diminish the effect of virtual encounters. That avatars will be AI led and will digitally cocreate reviews and recommendations further accentuates the findings.

Originality/value

This research advances the field by addressing the literature gap on AI-led avatar realism and co-creation in hospitality services within the Metaverse. It explores the nuanced ways that highly realistic avatars can enhance engagement and self-representation while simultaneously posing challenges related to authenticity and trust. The study provides a foundation for further exploration of AI’s transformative potential in virtual hospitality contexts.

Details

Consumer Behavior in Tourism and Hospitality, vol. 20 no. 1
Type: Research Article
ISSN: 2752-6666

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