Publication Type

PhD Dissertation

Version

publishedVersion

Publication Date

1-2026

Abstract

Against the backdrop of hotel livestreaming e-commerce, this study explores the impact of AI streamers’ interactivity on consumers’ purchase behavior and its underlying mechanism. Based on the Information Richness Theory, the research first conducts a quasi-experiment using real livestreaming data from OTA platforms. Through propensity score matching and regression model testing, it is found that high-interactivity AI streamers significantly increase product clicks, purchase order, and consumption amount in livestreaming, with consistent support from multiple robustness tests.

Further a between-subjects experiment (N = 172) verifies that high interactivity of AI streamers significantly enhances consumers’ perceived information richness and purchase intention, and confirms that perceived information richness plays a partial mediating role between AI streamer interactivity and purchase behavior. This study not only expands the application boundaries of human-AI interaction and consumer behavior theories in the AI livestreaming scenario but also provides practical implications for the hotel industry to optimize AI streamer design.

Finally, semi-structured interviews reveal consumers’ real experiences and psychological mechanisms regarding AI livestreaming, indicating that price advantage and information sufficiency are the basic conditions triggering consumption, while interactive capability is a key factor influencing AI livestreaming effectiveness. However, AI streamers still have inherent disadvantages in establishing emotional connections.

Keywords

AI streamer, Interactivity, Information richness, Consumer purchase behavior, Hotel livestreaming

Degree Awarded

Doctor of Business Admin

Discipline

Business Administration, Management, and Operations | Marketing

Supervisor(s)

CHANG, Han-Wen Hannah

First Page

1

Last Page

118

Publisher

Singapore Management University

City or Country

Singapore

Copyright Owner and License

Author

Available for download on Thursday, June 17, 2027

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