Dynamic Pricing and Channel Management: Substitutes or Complements?

Description

Hotels distribute room inventory via Online Travel Agencies (OTAs) and other channels. The advancement of hospitality information systems makes dynamic channel management feasible and easy to implement. For instance, a hotel expecting rapid room sell-out might deactivate costlier channels, reducing traffic but retaining more revenue per unit. Despite its practical significance, dynamic channel management has received scant attention, perhaps because it appears to be equivalent to conventional capacity control and is thus considered subsumed by dynamic pricing. This, however, is not true. In the hospitality industry, uniform prices are typically implemented across channels, which limits the flexibility of controlling channel openings and closures solely through price adjustments. Consequently, dynamic channel management, if implemented, must be employed in conjunction with dynamic pricing, representing a significant shift from the literature. Inspired by modern practices in the hospitality industry, we consider a firm that sells a finite quantity of perishable products over a finite planning horizon through multiple channels. These channels differ in user traffic volume, customer characteristics, and commission fees. The firm aims to maximize net revenue by dynamically adjusting prices across different channels and managing channel availability. By modeling customer choices among different channels and demand for each channel as a function of the retail price, we will construct a series of stochastic dynamic programs and answer the following questions: What is the optimal dynamic pricing and channel management policy? Are dynamic pricing and dynamic channel management substitutes or complements? We will develop structural results and algorithms to answer these questions. We will investigate the value of dynamic pricing (resp. channel management) in the presence of dynamic channel management (resp. pricing) and explore scenarios where joint decision-making delivers the most or least benefit. Finally, we will extend the basic model to more general scenarios, such as when there is a constraint on the number of channels and the firm needs to choose the initial set of channels or when the firm sells multiple products. This project is the first to investigate the interplay of dynamic pricing and channel management in the hospitality industry, where current practices utilize heuristic rules for channel control that can often lead to suboptimal outcomes. The findings from this project are expected to enrich the revenue management literature, expanding the existing toolkit, and equipping practitioners with more effective strategies for revenue management.