The dynamic pricing problem from a newsvendor's perspective

The dynamic pricing problem concerns the determination of selling prices over time for a product whose demand is random and whose supply is fixed. We approach this problem in a novel way by formulating a dynamic optimization model in which the demand function is isoelastic but the random demand process is quite general. Ultimately, what we find is a strong parallel between the dynamic pricing and dynamic inventory models. This parallel leads to a reinterpretation of the dynamic pricing problem as a price-setting newsvendor problem with recourse, which is useful not only because it yields insights into the optimal solution, but also because it leads to additional insights into how pricing recourse affects the actions and profits of a price-setting newsvendor. We make contributions in three areas: First, we develop structural properties that define an optimal pricing strategy over a finite horizon and investigate how that policy impacts a newsvendor's optimal procurement policy and optimal expected profit. Second, we establish a practical and efficient algorithm for computing the optimal prices. Third, we examine how market parameters affect the optimal solution through a series of numerical experiments that utilize the algorithm.