Designing and Evaluating Dynamic Pricing Policies for Major League Baseball Tickets

Abstract

Many firms have difficulty evaluating the impact of their pricing policy, which further inhibits their ability to design and implement dynamic pricing. We address this issue in the context of single-game ticket pricing for a Major League Baseball franchise. We develop and estimate a comprehensive demand model to help evaluate and design dynamic pricing policies for the franchise. Our model encompasses all relevant aspects of the demand generation process, including ticket quantity and stadium seat section choice. The demand model reveals factors that drive sports ticket revenue, such as the effect of home team performance on overall price sensitivity and the relationship between customers' arrival timing and product choice. We show that by leveraging these insights and allowing sufficient pricing flexibility, the franchise can achieve a potential revenue improvement of 17.2% through daily price re-optimization, which is comparable to the outcome of a clairvoyant policy in which the future evolution of demand is assumed to be known.

Keywords: Empirical OM, Pricing and Revenue Management, OM Practice