Paper Number
ICIS2025-1717
Paper Type
Complete
Abstract
Algorithmic viewer targeting (AVT) has been increasingly used to attract traffic in live streaming commerce. Once viewers are acquired through AVT, interactive engagement is central in converting viewer traffic into product sales. As a result, AVT requires close coordination with engagement-based information provision to retain viewer attention and drive conversions. This study advances the understanding of AVT effectiveness by examining how targeted viewers (those attracted through AVT) and organic viewers respond differently to two key sources of information in livestreaming: streamer expressions, including both informative and persuasive content, and viewer comments, comprising both self-generated and other-generated comments. We also explore the heterogeneity across two common types of streamers: influencers and non-influencers. Our findings contribute to the growing literature on the mechanisms and effectiveness of AVT in live streaming and offer practical insights for optimizing information strategies with AVT across various livestreaming contexts.
Recommended Citation
Lin, Qinping; Tian, Jing; Wang, Lei; and Jia, Ning, "Is Algorithm Enough? An Informational Perspective on Viewer Targeting in Live-Streaming Commerce" (2025). ICIS 2025 Proceedings. 17.
https://aisel.aisnet.org/icis2025/hti/hti/17
Is Algorithm Enough? An Informational Perspective on Viewer Targeting in Live-Streaming Commerce
Algorithmic viewer targeting (AVT) has been increasingly used to attract traffic in live streaming commerce. Once viewers are acquired through AVT, interactive engagement is central in converting viewer traffic into product sales. As a result, AVT requires close coordination with engagement-based information provision to retain viewer attention and drive conversions. This study advances the understanding of AVT effectiveness by examining how targeted viewers (those attracted through AVT) and organic viewers respond differently to two key sources of information in livestreaming: streamer expressions, including both informative and persuasive content, and viewer comments, comprising both self-generated and other-generated comments. We also explore the heterogeneity across two common types of streamers: influencers and non-influencers. Our findings contribute to the growing literature on the mechanisms and effectiveness of AVT in live streaming and offer practical insights for optimizing information strategies with AVT across various livestreaming contexts.
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Comments
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