Advanced demand and a critical analysis of revenue management

Pre-print; author's draftThis paper presents a theoretical framework of advanced demand through six propositions. The framework introduces the concept of acquisition and valuation risks and suggests that advanced demand distribution is rooted in the trade off between them. Furthermore, since advanced buyers may not consume, firms may be able to re-sell capacity relinquished. The study then proposes how refunds could provide additional revenue to firms. The study further suggests theoretical reasons why and when service firms are able to practice revenue management, suggesting that RM tools such as overbooking and demand forecasting may not be the only tools for higher revenue

Dynamic order acceptance and capacity planning within a multi-project environment.

We present a tactical decision model for order acceptance and capacity planning that maximizes the expected profits from accepted orders, allowing for regular as well as nonregular capacity.We apply stochastic dynamic programming to determine a profit threshold for the accept/reject decision as well as an optimal capacity allocation for accepted projects, both with an eye on maximizing the expected revenues within the problem horizon.We derive a number of managerial insights based on an analysis of the influence of project and environmental characteristics on optimal project selectionand capacity usage.Capacity planning; multi-project; Order acceptance; Stochastic dynamic programming;

Integrated service selection, pricing and fullfillment planning for express parcel carriers - Enriching service network design with customer choice and endogenous delivery time restrictions

Express parcel carriers offer a wide range of guaranteed delivery times in order to separate customers who value quick delivery from those that are less time but more price sensitive. Such segmentation, however, adds a whole new layer of complexity to the task of optimizing the logistics operations. While many sophisticated models have been developed to assist network planners in minimizing costs, few approaches account for the interplay between service pricing, customer decisions and the associated restrictions in the distribution process. This paper attempts to fill this research gap by introducing a heuristic solution approach that simultaneously determines the ideal set of services, the associated pricing and the fulfillment plan in order to maximize profit. By integrating revenue management techniques into vehicle routing and eet planning, we derive a new type of formulation called service selection, pricing and fulfillment problem (SSPFP). It combines a multi-product pricing problem with a cycle-based service network design formulation. In order derive good-quality solutions for realistically-sized instances we use an asynchronous parallel genetic algorithm and follow the intuition that small changes to prices and customer assignments cause minor changes in the distribution process. We thus base every new solution on the most similar already evaluated fulfillment plan. This adapted initial solution is then iteratively improved by a newly-developed route-pattern exchange heuristic. The performance of the developed algorithm is demonstrated on a number of randomly created test instances and is compared to the solutions of a commercial MIP-solver.Series: Schriftenreihe des Instituts für Transportwirtschaft und Logistik - Supply Chain Managemen

Game theoretic pricing models in hotel revenue management: an equilibrium choice-based conjoint analysis approach

This paper explores a game-theoretically founded approach to conjoint analysis that determines equilibrium room rates under differentiated price competition in an oligopolistic hotel market. Competition between hotels is specified in terms of market share functions that can be estimated using multinomial logit models of consumer choice. The approach is based on choice-based conjoint analysis that permits the estimation of attributes weights (“part-worths”) for an additive utility formulation of the utility function. From this, room rates that equilibrate the market, conditioned on the differences in services and facilities offered by competing hotels, can be determined. The approach is illustrated by an example

Joint pricing and ordering decisions for perishable products

Ph.DDOCTOR OF PHILOSOPH

Overbooking models for air cargo yield management

Master'sMASTER OF ENGINEERIN

Revenue management in airline operations : booking systems and aircraft maintenance services

Although the principles of Revenue Management (RM) have vaguely been used in business for a long time, an increasing number of organizations are implementing well structured RM systems in the last few decades due to the developments in science and technology, especially in economics, statistics, operations research and computer science. The improvements in information and telecommunication technologies, wide use of Internet, rise of e-commerce and successful supply chain management strategies have enabled organizations to model and solve complex RM problems. This dissertation research concentrates on airlines, the earliest and leading user of RM. Today, airlines face serious financial problems due to the increasing costs and competition. They continuously explore new opportunities especially in terms of RM to make profit and survive. In this study, two problems are analyzed within this scope; airline booking process with adapted options approach and aircraft maintenance order control through RM. First; a new approach, financial options approach, is proposed to sell tickets in airline reservation systems. The options are used to overcome the uncertainty in air travel demand and competitors' actions. The seat inventory control problem is formulated with overbooking and embedded options respectively. Then a simulation study is conducted the potential of using options in airlines booking process. Accordingly, empirical results show that they present an opportunity both to utilize capacity more efficiently and to value seats more precisely compared to overbooking approach. Secondly; a peak load pricing concept is applied for aircraft maintenance order control problem. Aircraft maintenance centers face with peak loads in some seasons and the capacity is underutilized in other seasons. A peak load pricing model is proposed to shift some of the price elastic demand from peak seasons to off-peak seasons to balance demand and supply around the year. A dynamic programming algorithm is developed to solve the model and a code is written in C++. Results show that the model improves both annual capacity loading factors and revenues without causing a discomfort from the perspective of the customers. The details of both studies are presented in this dissertation research. [PUBLICATION ABSTRACT

Pricing and revenue management: The value of coordination

Cataloged from PDF version of article.The integration of systems for pricing and revenue management must trade off potential revenue gains against significant practical and technical challenges. This dilemma motivates us to investigate the value of coordinating decisions on prices and capacity allocation in a stylized setting. We propose two pairs of sequential policies for making static decisions-on pricing and revenue management-that differ in their degree of integration (hierarchical versus coordinated) and their pricing inputs (deterministic versus stochastic). For a large class of stochastic, price-dependent demand models, we prove that these four heuristics admit tractable solutions satisfying intuitive sensitivity properties. We further evaluate numerically the performance of these policies relative to a fully coordinated model, which is generally intractable. We find it interesting that near-optimal performance is usually achieved by a simple hierarchical policy that sets prices first, based on a nonnested stochastic model, and then uses these prices to optimize nested capacity allocation. This tractable policy largely outperforms its counterpart based on a deterministic pricing model. Jointly optimizing price and allocation decisions for the high-end segment improves performance, but the largest revenue benefits stem from adjusting prices to account for demand risk

Optimization models for joint airline pricing and seat inventory control : multiple products, multiple periods

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 153-157).Pricing and revenue management are two essential levers to optimize the sales of an airline's seat inventory and maximize revenues. Over the past few decades, they have generated a great deal of research but have typically been studied and optimized separately. On the one hand, the pricing process focused on demand segmentation and optimal fares, regardless of any capacity constraints. On the other hand, researchers in revenue management developed algorithms to set booking limits by fare product, given a set of fares and capacity constraints. This thesis develops several approaches to solve for the optimal fares and booking limits jointly and simultaneously. The underlying demand volume in an airline market is modeled as a function of the fares. We propose an initial approach to the two-product, two-period revenue optimization problem by first assuming that the demand is deterministic. We show that the booking limit on sales of the lower-priced product is unnecessary in this case, allowing us to simplify the optimization problem. We then develop a stochastic optimization model and analyze the combined impacts of fares and booking limits on the total number of accepted bookings when the underlying demand is uncertain. We demonstrate that this joint optimization approach can provide a 3-4% increase in revenues from a traditional pricing and revenue management practices. The stochastic model is then extended to the joint pricing and seat inventory control optimization problem for booking horizons involving more than two booking periods, as is the case in reality. A generalized methodology for optimization is presented, and we show that the complexity of the joint optimization problem increases substantially with the number of booking periods. We thus develop three heuristics. Simulations for a three-period problem show that all heuristics outperform the deterministic optimization model. In addition, two of the heuristics can provide revenues close to those obtained with the stochastic model. This thesis provides a basis for the integration of pricing and revenue management. The combined effects of fares and booking limits on the number of accepted bookings, and thus on the revenues, are explicitly taken into account in our joint optimization models. We showed that the proposed approaches can further enhance revenues.by Claire Cizaire.Ph.D