Using Dynamic Programming Decomposition for Revenue Management with Opaque Products

Abstract

Opaque products enable service providers to hide specific characteristics of their service fulfillment from the customer until after purchase. Prominent examples include internet-based service providers selling airline tickets without defining details, such as departure time or operating airline, until the booking has been made. Owing to the resulting flexibility in resource utilization, the traditional revenue management process needs to be modified. In this paper, we extend dynamic programming decomposition techniques widely used for traditional revenue management to develop an intuitive capacity control approach that allows for the incorporation of opaque products. In a simulation study, we show that the developed approach significantly outperforms other well-known capacity control approaches adapted to the opaque product setting. Based on the approach, we also provide computational examples of how the share of opaque products as well as the degree of opacity can influence the results.

Optimal booking control in revenue management with two substitutable resources

“…The original intention of opaque selling is twofold: Expanding the customer base with relatively low product valuation, often via a discounted fare, while reducing the danger of cannibalization. It is an increasingly popular price differentiation tool for airlines and hotel chains, where hidden characteristics can be the precise flight route or schedule, type of aircraft, and/or the operating airline's brand name in the first case, and the location of a particular hotel property in the second case (Gönsch and Steinhardt 2013). Also, Post (2010) reports that airlines can increase revenues by offering products with a customer-selected degree of opacity.…”

“…Note that assumption (1) renders our product definition more general compared to the one used by Gönsch and Steinhardt (2013) who consider opaque products with only product-specific revenues. Our definition is appealing for practical and technical reasons.…”

“…3). Note also that Gönsch and Steinhardt (2013) focus on approximation techniques in the multiple resource case, while our research is devoted to exact approaches in the two resource case.…”

Resilient revenue management: a literature survey of recent theoretical advances

“…Petrick et al (2012) extend the model from Gallego et al (2004) to allow for arbitrary notification dates, demonstrating the benefits of flexible products with late notification dates. Gönsch and Steinhardt (2013) provide a more general view on flexible products by extending the classical dynamic program decomposition. Gönsch et al (2014) present similar results by adjusting product valuation in the deterministic linear optimisation model to capture the monetary benefits.…”

Dynamic Programming Decomposition for Choice-Based Revenue Management with Flexible Products

“…We refer to Talluri (2001) and Chen et al (2010) for revenue management with opaque products. In doing so, the need to store a commitment for later assignment is eliminated, and the solely resource-based state space is retained, which renders DPD possible again (see Gönsch and Steinhardt (2013) for DPD with opaque products). Other authors have sought to at least partially retain the flexibility.…”