Exploring the impact of differences between AI streamers and human streamers on consumer purchase intention in live e-commerce: A grounded theory approach

作者
Jie Li,Jinni Chen,Yi Shi,Yi Cui
出处
期刊:PLOS ONE [Public Library of Science]
卷期号:20 (10): e0334530-e0334530
标识
DOI:10.1371/journal.pone.0334530
摘要

With the rapid development of live e-commerce, AI streamers have gradually emerged as a new industry trend. However, significant differences exist between AI streamers and human streamers in terms of interaction styles, emotional expression, and user experience. How these differences influence consumer purchase intention has not yet been systematically investigated. Based on this, the present study employs grounded theory and the stimulus-organism-response model to explore the mechanism through which the differences between AI streamers and human streamers in live e-commerce affect consumer purchase intention. Data were collected through in-depth interviews and analyzed using open coding, axial coding, and selective coding. A research model was constructed, incorporating sensory differences, affective differences, and functional differences (stimulus factors), perceived entertainment and social presence (organism factor), and purchase intention (response factor), with consumer purpose as a moderating factor. Our results reveal that AI and human streamers differ in sensory, affective, and functional dimensions. Under purchase motivation, AI streamers, with their standardized and concise sensory presentation, better meet the need for quick decision-making, thus outperforming human streamers in functional differences. In contrast, under viewing motivation, human streamers excel in all three dimensions. These differences affect purchase intention through the mediating roles of perceived entertainment and social presence. Consumer purpose (purchase vs. viewing) moderates these effects. This study bridges the gap in understanding how AI and human streamers’ differences shape consumer behavior, offering practical insights for e-commerce platforms to optimize streamer strategies and guiding the anthropomorphic development of AI streamers.
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