619 / 2024-04-27 23:41:15

Personalized Pricing Strategies and Information Sharing in a Distribution Channel

Personalized Pricing,Information Sharing

We consider a distribution channel comprising a supplier and a retailer, where the retailer has the ability to collect customer data, use it to profile them, and personalize its retail prices based on this information. Depending on the retailer’s data collection ability, two personalized pricing strategies are studied. The retailer uses Behavior-Based Pricing (BBP) if it can only tell customers with any prior history apart; the retailer uses Fully Personalized Pricing (FPP) if it can accurately predict the customers’ true willingness-to-pay. Moreover, when the retailer shares the collected customer data, either in full or to a limited extent, with the supplier, the latter can also adopt the personalized pricing strategies in setting the wholesale price. Using a two-period game-theoretic model that takes into account the strategic behavior of the customers, we solve for the equilibrium results and compare them across different scenarios. Our analysis uncovers several counter-intuitive findings that generate interesting managerial insights. First, we show that the supplier and the retailer may have conflicting attitudes towards adopting personalized pricing strategies. Similarly, they may have opposing preferences on the information sharing mechanism. In addition, we show that even though personalized pricing leads to price segmentation, it can increase overall consumer surplus and social welfare due to the enhanced market expansion effect. Finally, we discuss the potential benefit of decentralization and show that compared to an integrated firm, total profits for the decentralized channel can be higher if the retailer uses FPP and the supplier does not.