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Data · dataset · 2026

AI Creativity in Digital Entertainment Co-Creation: Creator Experience and Sharing Intention in Generative Travel Videos

Listed in ScienceDB

As generative artificial intelligence reshapes creative production, understanding its role in human–AI co-creation has become increasingly important for digital entertainment and user experience research.

Description

This study focuses on AI-assisted travel video creation and examines the psychological mechanisms through which AI-related creative stimuli influence users’ post-creation responses. Drawing on the stimulus–organism–response (SOR) framework, this study conceptualizes AI creativity, interactivity, and information quality as external stimuli; perceived entertainment, emotional attachment, and satisfaction as organismic psychological states; and sharing intention as the behavioral response.

It further integrates three analytical approaches: partial least squares structural equation modeling (PLS-SEM), artificial neural networks (ANN), and necessary condition analysis (NCA). The PLS-SEM results show that AI creativity and interactivity significantly enhance perceived entertainment, emotional attachment, and satisfaction, while information quality significantly improves emotional attachment and satisfaction but does not directly affect perceived entertainment.

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The ANN results further reveal that AI creativity is the most important predictor of satisfaction, followed by information quality and interactivity. The NCA results indicate that AI creativity, emotional attachment, and interactivity are necessary conditions for achieving high satisfaction. These findings shift the focus of generative AI research in tourism from audience responses to creator experience and highlight the central role of AI creativity in post-trip memory reconstruction, emotional connection, and content sharing, thereby extending the relevant literature.

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Inferred from text
Design 72% · Video 75%
Provenance · 1 source records, 13 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.396199 d agoJSON v1
FieldAssertionExtractorEvidence
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