Live-Streaming Strategies in a Fresh Agricultural Product E-Commerce Supply Chain with Spoilage Compensation: Influencer Live Streaming vs. AI Live Streaming

Considering the high logistics costs and damaged-product compensation in the fresh agricultural product supply chain, this study investigates the optimal strategy selection between influencer live streaming and AI live streaming. Taking an e-commerce supply chain consisting of a supplier, a logistics service provider, and an influencer as the research object, this paper develops pricing decision models under two live streaming formats and systematically analyzes the impacts of key parameters, including the unit compensation price, consumer waiting cost, influencer’s traffic, market size, et al., on the supply chain’s strategies and profits. The results show that, from the supplier’s perspective, influencer traffic is not always beneficial. The supplier profit first decreases and then increases with traffic, exhibiting a U-shaped relationship. From the supply chain perspective, higher traffic always increases total profit. The analysis further shows that the optimal formats choice, under both influencer live streaming and AI live streaming, depends critically on consumer waiting cost, the unit compensation price, and market size. High waiting cost and a large market favor AI live streaming, whereas low waiting cost combined with a high compensation price makes influencer live streaming more advantageous. The findings provide theoretical support and managerial insights for live streaming mode selection decisions in fresh e-commerce supply chains.