234 / 2024-04-23 17:00:39

Personalized Pricing in a Retail Platform with Imperfect Consumer Recognition

Personalized pricing,Recognition accuracy,Retail platform,Hybrid selling mode,Game theory

Retail platforms (e.g., JD.com and Amazon) and the third-party sellers have conduct personalized pricing that provides consumers with different prices based on the recognition of their preferences. This paper investigates the optimal pricing scheme of firms and the effects of personalized pricing on firms in a hybrid selling mode, which consists of two horizontally differentiated firms, i.e., a retail platform and a third-party seller, and a mass consumer. Using an analytical model, we find that there exist multiple equilibria where the retail platform and the third-party seller may conduct uniform pricing or personalized pricing. With a low commission rate, both firms may implement uniform pricing when the consumer recognition accuracy is medium but adopt personalized pricing when the product value is not very high. Otherwise, it is in the best interest of the retail platform to exit the market and the third-party seller adopts personalized pricing. By contrast, the retail platform may conduct personalized pricing while the third-party seller set uniform prices when the commission rate or the recognition accuracy is high. Our results reveal that the adoption of personalized pricing does not necessarily hurt firms since it can soften competition by the strategic concession behavior of the retail platform. In addition, the profits of firms change non-monotonically with the consumer recognition accuracy, conditional on the transformation of equilibrium.