Dynamic pricing with stochastic reference effects based on a finite memory window
Dynamic pricing with stochastic reference effects based on a finite memory window
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基于有限内存窗口的具有随机参考效应的动态定价
DOI：
10.1080/00207543.2016.1221160
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发表时间：
2017
影响因子：
9.2
通讯作者：
Mengqi Liu
中科院分区：
文献类型：
--
作者：
Wenjie Bi;Guo Li;Mengqi Liu
受最新的实证研究启发，我们假设消费者的记忆是有限的，并且他们对先前价格的回忆服从一阶马尔可夫随机过程，从而提出了一个新的参考价格更新模型。研究了一个具有随机参考效应和有限记忆的动态定价模型。与指数平滑模型一致，我们指出，参考效应导致最优价格路径单调收敛到期望的稳态价格。随着消费者变得厌恶亏损，稳定区间往往会扩大。我们的数值实验结果与某些模型在消费者随机回忆记忆假设下的结果不同。最优价格路径在稳定状态附近持续波动，而不是保持不变。第一价格对存储窗口和长期利润的影响随着存储窗口长度的增加而减小。
Inspired by the latest empirical studies, we propose a new updating model for reference prices by assuming that consumers’ memories are limited and their recall of previous prices obeys a first-order Markov stochastic process. We investigate a dynamic pricing model with stochastic reference effects and finite memory. Consistent with the exponential smoothing model, we indicate that reference effects lead to monotonic convergence of the optimal price path to an expected steady-state price. The steady-state range tends to widen as consumers become loss-averse. The results of our numerical experiments differ from findings of certain models under the assumption of stochastic recall memory of consumers. The optimal price path fluctuates consistently around the steady state instead of remaining constant. The effect of the first price on the memory window and long-term profits decreases as the length of memory window increases.