Optimal Pricing with Speculators and Strategic Consumers

Contingent Preannounced Pricing Policies with Strategic Consumers

Optimal Dynamic Pricing of Perishable Items by a Monopolist Facing Strategic Consumers

We introduce a dynamic pricing model for a monopolistic company selling a perishable product to a finite population of strategic consumers (customers who are aware that pricing is dynamic and may time their purchases strategically). This problem is modeled as a stochastic dynamic game in which the company’s objective is to maximize total expected revenues, and each customer maximizes the expect...

Dynamic versus Static Pricing in the Presence of Strategic Consumers

The stochastic nature of demand suggests that firms can benefit from applying dynamic pricing strategies, where pricing decisions are postponed until information about demand is revealed. Many service providers, however, announce prices in advance and do not frequently adjust them as a response to market conditions (i.e., static pricing). This may seem suboptimal when demand is high and the fir...

Product bundling or reserved product pricing? Price discrimination with myopic and strategic consumers

a r t i c l e i n f o Mixed bundling (MB), in which products are sold separately and as a bundle, is a form of second degree price discrimination. In this study we examine how MB and its variants compare against reserved product pricing (RPP), a form of co-promotion. Used by Amazon.com, among others, RPP consists of the firm offering individual products and then enticing single product buyers w...

Dynamic Pricing with Online Learning and Strategic Consumers: An Application of the Aggregating Algorithm

We study the problem faced by a monopolistic company that is dynamically pricing a perishable product or service and simultaneously learning the demand characteristics of its customers. In the learning procedure, the company observes the sales history over consecutive planning horizons and predicts consumer demand by applying an aggregating algorithm (AA) to a pool of online stochastic predicto...