Information sharing and channel structure in e-commerce supply chain considering data-driven marketing - Feifei Han; Mei Wang; Zhengze Wu (PLoS ONE, 2025)
E-tailers such as Amazon and Tmall can accurately recognize consumer interest in product categories and grasp current consumer trends through product recommendation algorithms and data-driven analysis. In this study, we develop a game-theoretic model to investigate the encroachment and information sharing decisions considering data-driven marketing (DDM). Our outcomes reveal that the manufacturer has the incentive to reduce the wholesale price to incentivize the e-tailer to increase the DDM effort when the spillover effect is high and the marginal cost is low. When the manufacturer encroaches on the direct channel, the e-tailer may share information if the spillover effect is low. Moreover, we derive the conditions under which the manufacturer encroaches on the direct channel. Lastly, we extend the model to the case where the agency channel exists, and we find that the manufacturer should select the agency channel only if the marginal cost of DDM effort is moderate and the commission rate is low. Our study provides useful insights for managers to understand and make channel choice and information sharing decisions in the e-commerce supply chain.