Inconspicuous Personalized Pricing
研究了一种将个性化定价嵌入动态定价框架的策略，通过不频繁调整价格来隐藏其使用，模拟分析表明该策略在消费者到达频率适中时利润提升最大，对在线平台有参考价值。
ABSTRACT Emerging tracking data enable precise predictions of individuals' reservation values. However, firms may be reluctant to overtly adopt personalized pricing. This paper proposes a strategy that embeds personalization within a dynamic pricing framework, tailoring prices privately while committing to infrequent adjustments to obscure its use. Simulation analyses based on both theoretical and empirically estimated distributions of consumer valuations reveal that profits rise most when consumer arrivals are moderately frequent. Increasing the precision of individual‐level demand estimates broadens the range of products for which this strategy is profitable. These findings suggest the approach may be an auspicious strategy for online platforms.