[PDF] Competitive Impacts Of Continuous Pricing Mechanisms In Airline Revenue Management eBook

Author : Alexander R. Papen
Publisher :
Page : 142 pages
File Size : 22,84 MB
Release : 2020
Category :
ISBN :

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Traditionally, airlines have been limited to a set of fixed price points to distribute their fare products. The advent of IATA’s New Distribution Capability (NDC), however, will soon enable airlines to quote any fare from a continuous range. In theory, such continuous pricing could increase revenues by extracting more of the consumer surplus, through its ability to offer fares closer to the customer’s willingness-to-pay. This thesis examines the impacts of continuous pricing in competitive airline networks through simulation in the Passenger Origin-Destination Simulator (PODS). To this end, both class-based and classless RM methods for continuous pricing are presented. Class-based continuous RM relies on the same underlying forecasting and optimization models as traditional RM, while quoting a single continuous fare. Classless RM, on the other hand, completely abandons the notion of pre-specified fare classes, but instead forecasts and optimizes over a temporal dimension. Simulations show that the improved pricing granularity from continuous pricing results in revenue gains of 1-2% when adopted by all airlines, while the gain for the first-mover might be as high as 10-15%. These revenue gains are driven by the ability of continuous pricing to generate lower fares, in-between existing price points, towards the end of the booking horizon. These lower fares, in turn, result in the stimulation of new demand and capture of high-yield business passengers from competitors. We conclude by showing that an airline with traditional RM can reduce, or even reverse, the impact of a competitor moving to continuous pricing by inserting additional price points, adjusting its own RM system settings, or discounting its upper fares. Compared to the current general practice of fare matching, these less transparent competitive responses could have negative impacts on revenues throughout the industry when airlines repeatedly respond to each other’s pricing actions.

Author : Yanbin Long (Researcher in aeronautics and astronautics)
Publisher :
Page : 0 pages
File Size : 19,68 MB
Release : 2022
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This thesis also explores potential response strategies by the competing airlines. We discover that competitors can reverse the first-mover's revenue gain by modifying their fare structures while still using traditional RM methods. We conclude that although adopting segmented continuous pricing is promising in theory, its actual gains depend heavily on the competitive situation and the responses made by other airlines.

Author : Nicholas James Liotta
Publisher :
Page : 132 pages
File Size : 30,62 MB
Release : 2019
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The development of the New Distribution Capability for airlines has raised interest within the airline industry in “continuous pricing”, where fares offered to customers are not limited to a set of pre-determined price points. This thesis provides an overview of experiments on four revenue management (RM) methods proposed for the practical implementation of continuous pricing. Two of these methods, termed class-based RM for continuous pricing, utilize existing forecasting and seat protection optimization methods to determine what fares to offer. The other two methods, termed classless RM, calculate optimal fares based on the maximization of expected revenue contribution at a given point in time during the booking process. This thesis examines the performance of probabilistic bidprice and unbucketed dynamic programming methods for both the class-based and the classless methods for continuous pricing. The continuous pricing methods are compared with traditional class-based methods in unrestricted fare structures using the Passenger Origin Destination Simulator. Compared to a baseline with six fare classes, when two competing airlines both implement class-based continuous pricing, revenues can increase by up to 1%, and, when both airlines implement classless pricing, they can gain up to 2% in revenue. When only one airline implements continuous pricing in a competitive setting, revenue gains of 10–13% are possible over the six-fare class baseline. These larger gains mostly come at the expense of the competitor, which loses revenue and bookings. For all cases, as the number of fare classes in the baseline increases, the revenue gains of continuous pricing are diminished and may even become revenue losses under certain conditions. The positive results of the continuous pricing methods are a result of the increased price granularity offered by continuous pricing. It is this price granularity that causes most of the revenue gains when a competitor airline does not switch to continuous pricing. The price granularity effect also explains why increasing the number of fare classes with the traditional class-based RM methods can generate as much and sometimes more revenue than the continuous pricing methods.

Author : Michael David Wittman
Publisher :
Page : 228 pages
File Size : 21,68 MB
Release : 2018
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Even as the distribution and sale of commercial airline tickets has shifted in recent years from physical reservation offices to the Internet, many airline commercial processes remain highly reliant on pre-Internet technologies and standards. This legacy infrastructure compels airlines to publish a discrete set of prices in each market they serve, and to select prices for each itinerary from among only this limited set of possible price points. Recent advancements in distribution technology, such as the New Distribution Capability (NDC), offer airlines the chance to break away from these constraints. These new standards enable the creation of customized offers with prices that could be generated dynamically in real time. While airlines have shown interest in these new technologies, practical methods for integrating dynamic pricing into existing airline revenue management (RM) and distribution systems have yet to be defined and evaluated by academics or practitioners. In this work, we propose the first mechanisms for dynamic pricing designed specifically for use in the airline industry. By selectively providing increments or discounts based on demand segmentation and estimates of willingness-to-pay (WTP), our mechanisms can increase airline revenues by stimulating new bookings from price-sensitive travelers while encouraging more price-inelastic travelers to buy up to higher price points. Moreover, the methods are compatible with the pricing, RM, and distribution systems currently used by airlines today. Our dynamic pricing heuristics emerge from the development of a novel theoretical model of customer choice. Using the model, we introduce a new concept called "conditional WTP" to describe how a customer's willingness-to-pay for an itinerary can change depending on the other alternatives available in his choice set. We show how assuming an unchanging maximum WTP for air travel, as in past work on dynamic pricing, can lead to overestimation of WTP in competitive environments, and describe how an airline's estimates of conditional WTP play an integral role in our dynamic pricing mechanisms. We test our dynamic pricing methods in the Passenger Origin-Destination Simulator (PODS): a robust agent-based booking simulation that models the interactions between passengers and airlines. In a complex, competitive network, we find that our heuristics can increase airline revenues by up to 1 - 4% from traditional pricing and RM alone. Incrementing prices can result in revenue gains through an increase in yield, and discounting can lead to higher revenues through demand stimulation and share shift from other airlines. In both cases, we identify a phenomenon we call "forecast spiral-up" which increases yield by protecting more seats for higher-value fare classes. We also develop a variant of the heuristic in which multiple substitutable flights are priced simultaneously, leading to additional revenue gains. Finally, we provide the first in-depth assessment of the practical implications of dynamic pricing for the airline industry. We focus on airline concerns that dynamic pricing could lead to price wars, excessive discounting, and a race to the bottom. We also evaluate some of the potential legal implications and customer reactions that could emerge as dynamic pricing becomes more commonplace. These analyses provide new insight on how airline competition could potentially change as dynamic pricing is integrated into traditional airline processes.

Author : Ben Vinod
Publisher : Springer Nature
Page : 417 pages
File Size : 18,24 MB
Release : 2021-05-28
Category : Business & Economics
ISBN : 3030704246

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This book chronicles airline revenue management from its early origins to the last frontier. Since its inception revenue management has now become an integral part of the airline business process for competitive advantage. The field has progressed from inventory control of the base fare, to managing bundles of base fare and air ancillaries, to the precise inventory control at the individual seat level. The author provides an end-to-end view of pricing and revenue management in the airline industry covering airline pricing, advances in revenue management, availability, and air shopping, offer management and product distribution, agency revenue management, impact of revenue management across airline planning and operations, and emerging technologies is travel. The target audience of this book is practitioners who want to understand the basics and have an end-to-end view of revenue management.

Author : Bazyli Szymański
Publisher :
Page : 0 pages
File Size : 47,13 MB
Release : 2023
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ISBN :

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After decades of development of revenue management (RM) systems, airlines have until recently been limited to a set of fixed fare classes and, in turn, price points, to distribute their fare products. The advent of IATA's New Distribution Capability will allow airlines to forego these limitations, allowing them to quote any fare from a continuous range. In theory, such continuous pricing could increase revenues by extracting more of the consumer surplus, through its ability to offer more granular fares closer to customer willingness-to-pay (WTP). This thesis provides a theoretical assessment and extensions of existing algorithms for continuous pricing, and discusses the market implications of moving away from fixed price points through competitive simulations. On the theoretical side, we contribute to the understanding of the existing bid price algorithms for single fare quote continuous pricing with static and dynamic optimization, two widely accepted approaches in the airline industry. For the static algorithms, in a simplified single leg, single period setup we prove the uniqueness and convergence of classless continuous Probabilistic Bid Price (ProBP) bid prices as well as the convergence of class-based continuous ProBP to classless ProBP bid prices, answering the question about the equivalence of the two optimizers. As we show, however, these results do not carry over to a realistic setup with multiple time periods. The dynamic optimization approach with classless Unbucketed Dynamic Programming (UDP) is built on a theoretically more established mathematical formulation. However, in its popular implementation it suffers from an inherent Poisson variance assumption, often considered a major limitation given that demand variance in reality is typically higher than the mean. To address that shortcoming, building on earlier work for traditional class-based RM, we introduce classless UDP with batch arrivals, where multiple customer arrivals are assumed within each DP time slice, leading to higher demand variance in the DP formulation. We show that when actual demand variance matches the batch arrival DP input, the new approach is an improvement over the standard classless UDP: the use of batch arrivals leads to higher airline revenues and flatter bid prices, even though the approach only emulates higher variance and the simulated passengers do not arrive in batches. Through PODS simulations, we show that through increased responsiveness to demand fluctuations and the ability to quote a closer-to-optimal price, the airline implementing continuous pricing can see revenue gains as high as 3% without affecting the revenues of traditional RM competitors, but that these gains are highly sensitive to airline's price elasticity estimates. To this end, we developed competitor adjustment for continuous pricing: a heuristic adjusting elasticity estimates used for fare quotation based on day-to-day deviations in competitor fares. When limited to price increments, the method was shown to bring further sustained revenue improvements of up to 0.5% for the implementing airline by capitalizing on the differences between conditional and maximum WTP, all while not negatively affecting competitor revenues.

Author : Curt Cramer
Publisher : Springer Nature
Page : 122 pages
File Size : 31,98 MB
Release : 2021-11-10
Category : Business & Economics
ISBN : 3658337214

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The book provides a comprehensive overview of current practices and future directions in airline revenue management. It explains state-of-the-art revenue management approaches and outlines how these will be augmented and enhanced through modern data science and machine learning methods in the future. Several practical examples and applications will make the reader familiar with the relevance of the corresponding ideas and concepts for an airline commercial organization. The book is ideal for both students in the field of airline and tourism management as well as for practitioners and industry experts seeking to refresh their knowledge about current and future revenue management approaches, as well as to get an introductory understanding of data science and machine learning methods. Each chapter closes with a checkpoint, allowing the reader to deepen the understanding of the contents covered.This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.

Author : Jeffrey Stuart Zickus
Publisher :
Page : 138 pages
File Size : 48,21 MB
Release : 1998
Category : Airlines
ISBN :

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Airline revenue management entails protecting enough seats for late-booking, high-fare passengers while still selling seats which would have otherwise gone empty at discounted fares to earlier-booking customers. In the evolution of revenue management to network origin-destination control, previous research has shown that revenue gains of some seat optimization algorithms can be much lower than others. One possible reason is the process by which demand estimates are generated; namely, forecasting and detruncation. Forecasting is used to estimate passenger demand based on historical flight data, while detruncation makes projections of what demand would have been in cases where the historical data has been constrained by a capacity limitation. This thesis explores the question of the interaction between forecasting methods, detruncation methods, and seat optimization algorithms on a simulated airline network, using the Passenger Origin-Destination Simulator (PODS) revenue management simulation tool, which models a network environment with two competing airlines. Changes in the forecasting and detruncation methods in combination with the seat optimization algorithms were tested in order to see what revenue impacts resulted. Additionally, passenger loads, forecasts, and fare class availability were examined to understand the reasons behind the observed revenue results. The simulations showed that seat optimizers which had relatively poor performance using a standard forecasting and detruncation method had substantial revenue increases when different forecasting and detruncation combinations were implemented. The results also indicate that the better combination of forecasting and detruncation causes higher revenues for all seat optimization methods tested, as a better passenger mix is realized due to higher levels of detruncation and more accurate forecasts. However, the sensitivity of the seat optimizers to the forecasting and detruncation methods remains mixed. Inferior detruncation (or forecasting) methods on a network can offset the revenue gains resulting from improvement to origin-destination control from leg-based control for some seat optimization algorithms.

Author : Ben Vinod
Publisher : Springer Nature
Page : 182 pages
File Size : 29,88 MB
Release : 2023-05-26
Category : Business & Economics
ISBN : 3031254562

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Over the past decade, Artificial Intelligence has proved invaluable in a range of industry verticals such as automotive and assembly, life sciences, retail, oil and gas, and travel. The leading sectors adopting AI rapidly are Financial Services, Automotive and Assembly, High Tech and Telecommunications. Travel has been slow in adoption, but the opportunity for generating incremental value by leveraging AI to augment traditional analytics driven solutions is extremely high. The contributions in this book, originally published as a special issue for the Journal of Revenue and Pricing Management, showcase the breadth and scope of the technological advances that have the potential to transform the travel experience, as well as the individuals who are already putting them into practice.

Author : Kalyan T. Talluri
Publisher : Springer Science & Business Media
Page : 731 pages
File Size : 14,48 MB
Release : 2006-02-21
Category : Business & Economics
ISBN : 0387273913

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Revenue management (RM) has emerged as one of the most important new business practices in recent times. This book is the first comprehensive reference book to be published in the field of RM. It unifies the field, drawing from industry sources as well as relevant research from disparate disciplines, as well as documenting industry practices and implementation details. Successful hardcover version published in April 2004.