Trust, interactional consistency, and site immersion: How AI tour guides shape cultural heritage experiences

Cultural heritage institutions are increasingly adopting AI tour guides to enhance visitor experiences, yet limited research has explained how such technologies shape visitor satisfaction through psychological mechanisms. Drawing on the Stimulus-Organism-Response (S-O-R) framework, this study develops and tests an integrated model linking AI tour guide service quality, visitors' psychological states, and visit satisfaction. Survey data were collected from 178 visitors who used AI tour guides at the Nanjing Museum, and the proposed model was examined using partial least squares structural equation modeling (PLS-SEM). The results show that AI tour guide service quality significantly enhances visitors' trust, interactional consistency, and site immersion, which in turn positively affect visit satisfaction. Among these psychological states, trust exerts the strongest effect on satisfaction and shows the strongest mediating role. Interactional consistency and site immersion also significantly mediate the relationship between service quality and satisfaction. In contrast, the moderating effects of individual differences were generally weak. Residential area showed an unadjusted moderating effect on the relationship between interactional consistency and satisfaction, but this finding should be interpreted cautiously because the moderation analyses were exploratory and involved multiple tests. These findings suggest that the value of AI tour guides in cultural heritage settings depends not only on functional service quality but also on their ability to foster trust, contextual interaction, and immersive place-based experiences. This study extends S-O-R research to AI-assisted cultural heritage tourism and offers practical implications for designing more trustworthy, context-sensitive, and experience-oriented AI tour guide services. This provides practical insights for further optimizing the design of AI tour guided services for cultural heritage sites, enhancing the digital visitor experience, and strengthening cultural heritage preservation and cultural education outreach.

Authors

Institutions

Publication Details

Journal
Acta Psychologica
Published
2026-07-17
DOI
https://doi.org/10.1016/j.actpsy.2026.107481
Primary Topic
Museums and Cultural Heritage
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trust, interactional consistency, and site immersion: How AI tour guides shape cultural heritage experiences

Chen Keke, Yi-Xiang Wang, Zehua Li
Acta Psychologica
Museums and Cultural Heritage
article

Trust, interactional consistency, and site immersion: How AI tour guides shape cultural heritage experiences

Chen Keke, Yi-Xiang Wang, Zehua Li
article en

Abstract

Cultural heritage institutions are increasingly adopting AI tour guides to enhance visitor experiences, yet limited research has explained how such technologies shape visitor satisfaction through psychological mechanisms. Drawing on the Stimulus-Organism-Response (S-O-R) framework, this study develops and tests an integrated model linking AI tour guide service quality, visitors' psychological states, and visit satisfaction. Survey data were collected from 178 visitors who used AI tour guides at the Nanjing Museum, and the proposed model was examined using partial least squares structural equation modeling (PLS-SEM). The results show that AI tour guide service quality significantly enhances visitors' trust, interactional consistency, and site immersion, which in turn positively affect visit satisfaction. Among these psychological states, trust exerts the strongest effect on satisfaction and shows the strongest mediating role. Interactional consistency and site immersion also significantly mediate the relationship between service quality and satisfaction. In contrast, the moderating effects of individual differences were generally weak. Residential area showed an unadjusted moderating effect on the relationship between interactional consistency and satisfaction, but this finding should be interpreted cautiously because the moderation analyses were exploratory and involved multiple tests. These findings suggest that the value of AI tour guides in cultural heritage settings depends not only on functional service quality but also on their ability to foster trust, contextual interaction, and immersive place-based experiences. This study extends S-O-R research to AI-assisted cultural heritage tourism and offers practical implications for designing more trustworthy, context-sensitive, and experience-oriented AI tour guide services. This provides practical insights for further optimizing the design of AI tour guided services for cultural heritage sites, enhancing the digital visitor experience, and strengthening cultural heritage preservation and cultural education outreach.

Acta PsychologicaVol. 269
Nanjing University of Science and Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 2%
Museums and Cultural Heritage
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.