Dynamic Pricing with Loss Averse Consumers and Peak-End Anchoring

Abstract

We analyze a dynamic pricing problem where consumer's purchase decisions are a ected by representative past prices, summarized in a reference price. We propose a new, behaviorally motivated reference price mechanism, based on the peak-end memory model proposed by Kahneman et al. (1993). Speci cally, we assume that consumers' reference price is a weighted average of the lowest and last price. Gain or loss perceptions with respect to this reference price a ect consumer purchase decisions in the spirit of prospect theory, resulting in a non-smooth demand function.We investigate how these behavioral patterns in consumer anchoring and decision processes a ect the optimal dynamic pricing policy of the rm. In contrast with previous literature, we show that peak-end anchoring leads to a range of optimal constant pricing policies even with loss neutral buyers. This range becomes wider if consumers are loss averse. In general, we show that skimming or penetration strategies are optimal, i.e. the transient pricing policy is monotone, and converges to a steady state, which depends on the initial price perception. The value of the steady state price decreases, the more consumers are sensitive to price changes, and the more they anchor on the lowest price.

Keywords: Dynamic Pricing, Deterministic Dynamic Programming, Behavioral Consumer Theory, Prospect Theory, Peak-end Rule