Competitive Markovian pricing
研究了零售商在竞争环境中采用马尔可夫定价（随机折扣）的效果，发现竞争加剧可能反而让双方零售商都受益，并给出了管理启示。
Dynamic pricing is often complicated by strategic customer behavior. One tactic utilized by retailers to manage strategic customer behavior, known as Markovian pricing, is to offer price discounts at random intervals to prevent customers from predicting when the next discount will occur, thereby simplifying their strategic waiting behavior. In this article, we study Markovian pricing in competitive settings. We show that retailers can effectively adopt Markovian pricing in competitive environments, establish the optimality of flash discounts under competitive Markovian pricing, and find surprisingly that increased levels of competition may benefit both retailers. We confirm the robustness of these insights and also establish their limits of applicability in two model extensions. Our findings suggest that retailers engaging in competitive Markovian pricing should refrain from naïvely applying common wisdom toward third-party price-monitoring and comparison services and reconsider the efforts in growing their loyal customer base, and more broadly highlight the unique properties of competitive Markovian pricing.