Asymmetric Consumer Learning and Inventory Competition
Management Science
Intertemporal Pricing with Strategic Customer Behavior
Management Science
Dynamic Pricing Strategies with Reference Effects
Operations Research
Revenue Management with Costly Price Adjustments
Operations Research
Strategic Capacity Rationing when Customers Learn
Manufacturing & Service Operations Management
Supply Chain Dynamics and Channel Efficiency in Durable Product Pricing and Distribution
Manufacturing & Service Operations Management
The value of modeling with reference effects in stochastic inventory and pricing problems
Expert Systems with Applications: An International Journal
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We study the dynamic pricing implications of a new, behaviorally motivated reference price mechanism based on the peak-end memory mode. This model suggests that consumers anchor on a reference price that is a weighted average of the lowest and most recent prices. Loss-averse consumers are more sensitive to perceived losses than gains relative to this reference price. We find that a range of constant pricing policies is optimal for the corresponding dynamic pricing problem. This range is wider the more consumers anchor on lowest prices, and it persists when buyers are loss neutral, in contrast with previous literature. In a transient regime, the optimal pricing policy is monotone and converges to a steady-state price, which is lower the more extreme and salient the low-price anchor is. Our results suggest that behavioral regularities, such as peak-end anchoring and loss aversion, limit the benefits of varying prices, and caution that the adverse effects of deep discounts on the firm's optimal prices and profits might be more enduring than previous models predict.