Knowledge-based learning system
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Abstract[[abstract]]A major advantage that online retailers possess that their brick-and-mortar counterparts do not is their ability to continually vary item price. Given the competition among these retailers, it is increasingly becoming a necessity for brick-and-mortar retailers to develop a coherent and profitable pricing strategy. Recent advances in RFID technology can be beneficially utilized in this context. We develop a knowledge-based adaptive learning framework for item-level dynamic pricing in retail stores. Specifically, we consider retail stores that issue membership cards that the members may use to receive promotions and other benefits. Instantaneous snapshots of customers in the store and their characteristics are used to dynamically vary retail store item-level prices. Using simulation, we illustrate the dynamic of the proposed framework. Preliminary results confirm the beneficial aspects of such a framework for item-level dynamic pricing in a retail store environment.