Is it necessary for the supply chain to implement artificial intelligence-driven sales services at both the front-end and back-end stages?

Abstract

This paper explores the application of artificial intelligence (AI) in supply chain management, focusing on its impact on service models at both the front and back ends of the supply chain (SC). We employ a Stackelberg game model to construct an SC system consisting of a single manufacturer and a single retailer, aiming to assess the impact of AI on SC performance and explore strategic selection considerations within this framework. Our findings are as follows: (1) AI implementation generally leads to lower product pricing, but its effect on market demand follows a nonlinear pattern. In particular, when the manufacturer integrates AI, the simultaneous use of AI by the retailer will not change the wholesale price but will lead to a decrease in the retail price and market demand. (2) In situations where the back-end cost efficiency is sufficiently high, the optimal choice for both the manufacturer and retailer might be to refrain from adopting AI. Conversely, adopting AI is preferable when the back-end cost efficiency is sufficiently low. Furthermore, when the back-end cost efficiency is moderate, the manufacturer benefits from adopting AI, but the retailer’s profit suffers. (3) Regardless of whether the manufacturer adopts AI, the retailer’s most prudent option is not to implement AI.