Embracing the power of AI in retail platform operations: Considering the showrooming effect and consumer returns

Abstract

This study examines a duopoly market comprising an online retail platform and a physical store, both of them selling experience-based products to consumers who are unaware of the products’ fitness. The platform could introduce artificial intelligence (AI) technology into retail operations to address consumers’ fitness uncertainty and then gain market share, while the physical store could exert a service effort to recapture the market, potentially facilitating showrooming behavior. Operational decisions including pricing, AI application, and service effort exertion are investigated in the cases where consumers are allowed and unallowed to return unsuitable products. We first develop a theoretical model of dual-channel retailing to determine the equilibrium operational decisions for the supply chain members, and then examine the interactions between these operational decisions and consumers’ showrooming behaviors. Subsequently, we perform numerical simulations to verify the robustness of the theoretical findings. Results indicate that both AI application and service efforts exertion will strengthen consumers’ showrooming effect, especially when the cost of AI application is relatively low. Moreover, regardless of whether the store implements the service effort or not, the platform prefers to apply AI technology when consumers are allowed to return products. Furthermore, the physical store will always exert a service effort, and with the service effort, the application of AI technology in the retail platform operation could effectively mitigate the impact of consumer return on supply chain members.