Can Virtual Humans Truly Substitute Humans? The Impact of Virtual Human Appearance Realism and Social Roles on Tourists' Word‐of‐Mouth Intention

Mengmeng Song et al.

International Journal of Tourism Research2026https://doi.org/10.1002/jtr.70218article
AJG 2ABDC A
Weight
0.37

Abstract

The integration of artificial intelligence technology with tourism has introduced a growing number of virtual humans to tourists. These digital agents serve not only as endorsers for tourist destinations but also as personnel to provide diverse immersive services for tourists. However, limited research has been considered on the varying effects caused by the roles they play. Therefore, this study, based on stereotype theory, constructs a mechanism model where virtual human appearance realism and social roles jointly influence tourists' word‐of‐mouth intention. The model is validated through two scenario experiments. Findings indicate that when virtual humans assume service‐oriented roles, high appearance realism is more effective in stimulating tourists' word‐of‐mouth intention, whereas when virtual humans assume endorsement‐oriented roles, low appearance realism is more effective. Perceived naturalness and perceived comfort serve as mediators and chain mediators in the aforementioned relationships.

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https://doi.org/https://doi.org/10.1002/jtr.70218

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@article{mengmeng2026,
  title        = {{Can Virtual Humans Truly Substitute Humans? The Impact of Virtual Human Appearance Realism and Social Roles on Tourists' Word‐of‐Mouth Intention}},
  author       = {Mengmeng Song et al.},
  journal      = {International Journal of Tourism Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/jtr.70218},
}

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Can Virtual Humans Truly Substitute Humans? The Impact of Virtual Human Appearance Realism and Social Roles on Tourists' Word‐of‐Mouth Intention

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.