Optimization of Purchase Intentions for Agricultural Products via Live-streaming Based on Bayesian Learning

With the rapid development of live-streaming and the implementation of rural revitalization, selling agricultural products via live-streaming has become an important means to achieve rural revitalization. However, the issues of quality control, supply chain, and after-sales service of the agricultural products harm the customers’ experience and the satisfaction of purchasing these products, leading to customers reducing purchase intentions. Therefore, the live-streaming platforms for supporting farmers and agricultural products have an urgent need to find the optimal strategy to increase customers’ purchase intentions. To satisfy the urgent need, this paper adopts the Bayesian learning method to model the beliefs updating of the customers’ purchase intentions for agricultural products and explores the optimal information delivery strategies for live-streaming platforms to improve customers’ purchase intentions. According to the study’s findings, in order to increase customers’ purchase intentions, live-streaming Platforms should choose different information delivery strategies for customers with different preferences. In addition, the live-streaming platforms should pay more attention to customers with high preferences, because they are more likely to purchase products and can bring greater benefits. The results of this paper could provide managerial insights to the live-streaming platforms about choosing appropriate information delivery strategies.