Dynamic Pricing with Loss Averse Consumers and Peak-End Anchoring

Javad Nasiry, I. Popescu
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引用次数: 227

Abstract

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.
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具有损失规避消费者和峰端锚定的动态定价
本文研究了基于峰端记忆模式的一种新的、行为驱动的参考价格机制的动态定价含义。该模型表明,消费者依赖于一个参考价格,即最低价格和最近价格的加权平均值。相对于这个参考价格,厌恶损失的消费者对感知到的损失比收益更敏感。我们发现,对于相应的动态定价问题,一定范围的不变定价策略是最优的。消费者越是锁定最低价格,这个区间就越宽;与之前的文献相反,当买家处于损失中性时,这个区间就会持续存在。在暂态状态下,最优定价策略是单调的,并收敛于稳态价格,且低价锚点越极端、越显著,稳态价格越低。我们的研究结果表明,行为规律,如峰端锚定和损失规避,限制了变化价格的好处,并警告说,深度折扣对公司最优价格和利润的不利影响可能比以前的模型预测的更持久。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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