Assessing the Value of Dynamic Pricing in Network Revenue Management

Dynamic pricing for a network of resources over a finite selling horizon has received considerable attention in recent years, yet few papers provide effective computational approaches to solve the problem. We consider a resource decomposition approach to solve the problem and investigate the performance of the approach in a computational study. We compare the performance of the approach to static pricing and choice‐based availability control. Our numerical results show that dynamic pricing policies from network resource decomposition can achieve significant revenue lift compared with choice‐based availability control and static pricing, even when the latter is frequently resolved. As a by‐product of our approach, network decomposition provides an upper bound in revenue, which is provably tighter than the well‐known upper bound from a deterministic approximation.