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Paper Type

Complete

Paper Number

1172

Description

Live Streaming E-commerce (LSE) refers to a technology-enabled business model that embeds live streaming into e-commerce, where streamers sell products and interact with the viewers in real-time. When stores use human streamers, they benefit from high Synchronicity Interaction (SI), which causes users’ engagement. However, when stores use artificial intelligence (AI) streamers to replace human streamers, it is unclear whether high SI human streamers are more effective than low SI AI streamers at selling products. This study examines drivers of whether AI streamers are more or less effective at selling products than human streamers. We find that human and AI streamers perform differently, and product categories moderate this effect. Our results contribute to the LSE and business value of AI literature and offer insight to platforms and stores seeking to better leverage AI technology and technology designers interested in developing more effective AI streamers.

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Aug 10th, 12:00 AM

Human versus AI? Investigating the Heterogeneous Effects of Live Streaming E-commerce

Live Streaming E-commerce (LSE) refers to a technology-enabled business model that embeds live streaming into e-commerce, where streamers sell products and interact with the viewers in real-time. When stores use human streamers, they benefit from high Synchronicity Interaction (SI), which causes users’ engagement. However, when stores use artificial intelligence (AI) streamers to replace human streamers, it is unclear whether high SI human streamers are more effective than low SI AI streamers at selling products. This study examines drivers of whether AI streamers are more or less effective at selling products than human streamers. We find that human and AI streamers perform differently, and product categories moderate this effect. Our results contribute to the LSE and business value of AI literature and offer insight to platforms and stores seeking to better leverage AI technology and technology designers interested in developing more effective AI streamers.

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