Research on Dynamic Operation Strategy of Live E-commerce Considering Online Viewers and Reference Price

As a rapidly growing e-commerce format, live-streaming has increasingly drawn attention from both academia and industry for its operational management. However, existing studies mainly focus on static analyses, with limited attention to the dynamic operation of live-streaming e-commerce. This paper investigates a live-streaming e-commerce supply chain composed of a platform, a streamer, and a manufacturer. By incorporating factors such as the average number of online viewers, reference price, conversion rate, product quality reputation and streamer influence, a demand function for live-streaming e-commerce is constructed. Under four decision-making scenarios involving consumer returns and platform cost-sharing, a differential game model is employed to characterize the dynamic operation of the supply chain, and the dynamic equilibrium strategies and performance levels across different scenarios are comparatively analyzed. Results indicate that: (1) both the reference price effect and the average number of online viewers positively affect the profits and effort levels of supply chain members; (2) consumer returns cause significant profit losses for supply chain members, and though reducing the corresponding effort inputs may save costs in the short run, such reduction can lead to long-term losses that exceed those savings; (3) when the platform’s unit revenue is relatively high, sharing the manufacturer’s quality control costs can achieve a Pareto improvement for the entire supply chain; and (4) all decision variables are maximized under the centralized decision-making mode, while the cost-sharing mode surpasses it in quality control effort and product reputation only when the cost-sharing ratio is sufficiently high.