考虑消费者跨期囤货的AI直播供应链促销研究

A Study on AI-Powered Live Streaming Supply Chain Promotions Considering Consumers’ Intertemporal Stockpiling Behavior

摘要: 本文构建了一个由品牌商与采用AI主播的网络零售商组成的两期直播供应链博弈模型，考察在消费者存在跨期购买与囤货行为的情境下，不同促销策略对供应链定价与利润分配的影响。研究比较了“买一送一”(BOGO)、“阶段性降价”(PR)与“天天低价”(EDLP)三类典型促销机制。研究结果发现：在AI直播背景下，当消费者持有成本较高时，BOGO策略因有效激励即时批量购买而优于EDLP；PR策略仅在持有成本与边际估值因子满足特定区间条件时才具备优势。进一步地，BOGO策略下的批发价格与供应链利润均随持有成本上升而提高，而PR策略则呈现相反趋势。相比之下，EDLP策略凭借其价格稳定性及对跨期行为协调需求的弱依赖，在持有成本较低或信息不对称程度较高的环境中展现出更强的稳健性。在AI驱动的直播电商环境中，消费者的囤货行为如何影响供应链上下游之间的博弈均衡，也为品牌商与采用数字人技术的零售商在促销策略选择、定价协同与AI投入回报优化方面提供了重要的理论依据与实践启示。

Abstract: This paper constructs a two-stage live-streaming supply chain game model involving brand manufacturers and online retailers employing AI hosts. It examines how different promotional strategies impact supply chain pricing and profit distribution when consumers engage in cross-period purchasing and stockpiling behaviors. The study compares three typical promotional mechanisms: Buy One Get One Free (BOGO), Periodic Discounting (PR), and Everyday Low Pricing (EDLP). Findings reveal that under AI-streaming conditions, when consumer holding costs are high, the BOGO strategy outperforms EDLP by effectively incentivizing immediate bulk purchases. The PR strategy only gains an advantage when holding costs and marginal valuation factors fall within specific ranges. Furthermore, wholesale prices and supply chain profits under BOGO increase with rising holding costs, while PR exhibits the opposite trend. In contrast, the EDLP strategy demonstrates greater robustness in environments with low holding costs or high information asymmetry, owing to its price stability and minimal reliance on intertemporal behavioral coordination. How consumer stockpiling behavior influences the equilibrium of supply chain interactions within AI-driven livestream e-commerce also provides crucial theoretical foundations and practical insights for brands and retailers utilizing digital avatar technology in promotional strategy selection, pricing coordination, and optimizing AI investment returns.