Decrease the price now, increase it later: a novel approach to demand learning and dynamic pricing of new experiential products through the lens of construal level theory

In revenue maximization problems with unknown demand, limited price revisions enhance perceived fairness, requiring careful price adjustments by sellers of new experiential products with shorter life-cycles. Under the same context, the study explores a scenario where the unknown demand function belongs to a set of possible demand curves. We propose a pricing policy incorporating consumers’ perceived fairness, quantified using psychological distance from temporal construal theory. Findings reveal that the proposed policy achieves a regret of \(O({log}^{j}N)\) $O({\mathit{log}}^{j}N)$ . We also demonstrate the efficacy of our pricing policy through a series of exhaustive numerical simulations and a lab experiment.