Xiaofeng Shao

Xiaofeng Shao


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 June 2026 in Sustainability
Verified
Journal Article
Open access
PDF file
YLYuntao Lian
Yuntao Lian
QSQilong Shao
Qilong Shao
XSXiaofeng Shao
Xiaofeng Shao
ZZZunling Zhu
Zunling Zhu
Multimodal artificial intelligence-generated content (AIGC) is reshaping museum digital exhibitions through dynamic content generation, contextual storytelling, and interactive feedback. Despite its growing adoption, the impact of AIGC’s experiential attributes on visitors’ digital exhibition experience intention remains underexplored. Drawing on the Technology Acceptance Model (TAM), this study develops an integrative framework incorporating AIGC technology acceptance, perceived immersion, content creativity, interaction quality, cognitive evaluations, and affective responses. Data were collected from 481 visitors with prior digital exhibition experience and analyzed using PLS-SEM. The results indicate that AIGC technology acceptance significantly influences perceived ease of use, perceived usefulness, and digital exhibition experience intention; interaction quality enhances usability and exerts a direct effect on intention; and immersion and content creativity primarily shape intention through perceived enjoyment while also exhibiting direct effects. These findings extend TAM to multimodal AIGC-enabled museum contexts and provide empirical evidence to guide the design of culturally meaningful, interactive, and engaging digital exhibition experiences.