Class Action Lawsuits and Algorithms to Determine Selling Rates in Travel

What is Competitive Revenue Management?

Traditional revenue management forecasts demand and optimizes inventory controls based on a supplier’s internal data. With schedule and fare transparency, a growing consensus emerged in the early 2000s that competitor selling fare data could be leveraged to improve inventory controls that reflected current market conditions. Airlines publish their fares to fare aggregators like ATPCO who in turn disseminate the fares to intermediaries like Global Distribution Systems (GDS) and airlines. An airline has the option to respond to a new fare filed by a competitor by matching the fare, or filing a fare that is above or below the competitor’s fare. This fare management process precedes revenue management. Over the past two decades, Competitive Revenue Management has become an established practice in the travel industry [Page, C?té, Savard, 2005; Ratliff and Vinod, 2005; Zhang and Kallesen, 2008; Hartmans, 2008; Kumar, et. al. 2021; Vinod, 2021 (Chapter 7)].?

In lodging, Competitive Revenue Management starts with revenue managers identifying the competitive set (or "comp set") for their property. This includes properties in the same neighborhood that are considered competitors. Hotel competitive sets are asymmetric [Vinod, 2022] and can be determined from an OTA's click stream data. Hotel rates that are published to internal systems like the hotel CRS are based on the hotel’s pricing strategy, perceived value of the brand, room types and associated room attributes, and neighborhood. Competitive Revenue Management in lodging involves using automated tools to monitor competitors' websites for information on selling rates. Vendors like QL2, RateGain, and Amadeus Hospitality's Demand360 offer services that allow hotels to track competitors' selling rates for future dates. This data is used to adjust inventory controls within the hotel's CRS to recommend the best available rate (BAR). In addition, hotels can also subscribe to Smith Travel Research (STR) for access to historical selling rates at various properties.

Besides airlines and hotels, car rental companies and cruise lines monitor competitor rates to augment their revenue management strategies. For instance, rental car companies closely monitor competitor capacity (available cars in the lot) and rates at airport locations to adjust walk-up rates for walk-up customers.?

Decision-making associated with publishing reference fares and inventory control for airlines; and establishing the rate structure and room inventory control for hotels are always internal to the travel supplier, and strategies used are a closely guarded secret [Vinod, 2024].?

Class Action Lawsuits

The casinos allegedly colluded to manipulate hotel room rates using the Cendyn Group's Rainmaker algorithm, according to the claims filed in Atlantic City. The lawsuit alleges that although occupancy rates have decreased and gaming revenues have only slightly increased, room revenue reported to the New Jersey Casino Control Commissions has climbed significantly. Numerous legal actions have been brought, including Altman v. Caesars Entertainment, Blair-Smith v. Caesars Entertainment, and Fabel v. Boardwalk 1000 [Toutant, 2024].?

In Cornish-Adebiyi v. Caesar’s Entertainment, the plaintiffs allege that competing casino hotels are violating the Sherman Antitrust Act, an U.S. antitrust law passed in 1890, by using Rainmaker to algorithmically set prices “while knowing and precisely because all other Casino-Hotel Defendants had agreed to do the same.”?

The defendants in these lawsuits are casino hotel operators, Cendyn that markets Rainmaker, and competitor selling rate data providers such as Amadeus, and CoStar’s Smith Travel Research.?

In the matter of Cornish-Adebiyi v. Caesars Entertainment, the Federal Trade Commission (FTC), and the Department of Justice (DOJ) jointly filed a statement of interest with the District of New Jersey [Office of Public Affairs Press Release, 2024]. It says that to avoid breaking antitrust regulations, hotel companies cannot band together on room price by using algorithms to perform tasks that would otherwise need to be done manually by a real person. The government argues that hotels that use algorithms to determine room rates are breaking antitrust laws, supporting plaintiffs who are suing Caesars Entertainment and other casinos [Weinstein, 2024. At question is whether casino-hotel entities combined their independent decision-making authority??

Conclusion

The objective of Competitive Revenue Management is to optimize inventory controls that results in a priced air itinerary for airlines or the best available rate for a hotel. Creating the reference fares or hotel rate structure is an independent internal process that is used as input by revenue management.?

The plaintiffs' claims that there was price-fixing are untrue. Customers do not fully comprehend revenue management's value proposition. Perhaps we need an infographic explaining how revenue management helps travel suppliers make more money while also enabling customers to afford travel by providing a range of prices at different times prior to departure.?

There is now doubt regarding the future of competitive revenue management in the travel sector because of these potential class action lawsuits. Travel suppliers can still utilize demand estimates and residual capacity to set inventory limits if revenue management is unable to use rival selling fares and rates as input in the future [Cross, 1997; Vinod, 2021).

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References

1.??????????? Cross, R. G. (1997) Revenue Management: Hard Core Tactics for Market Domination, ISBN 0-553-06734-6. Broadway Books, New York, NY: .

2.???????????? Kumar, R, Wang, W., Arunachalam, S.K., Simrin, S.K., Guntreddy B.R., Walczak, D. (2021) Competitive Revenue Management Models with Loyal and Fully Flexible Customers. Journal of Revenue and Pricing Management,? https://doi.org/10.1057/s41272-021-00311-4

3.???????????? Hartmans, G. (2008) Competitor fare availability monitoring and usage, AGIFORS Revenue Management Study Group, Tahiti, French Polynesia, May.?

4.??????????? Office of Public Affairs Press Release (2024) Justice Department and Federal Trade Commission File Statement of Interest in Hotel Room Algorithmic Price-Fixing Case, U.S. Department of Justice, March 28, https://www.justice.gov/opa/pr/justice-department-and-federal-trade-commission-file-statement-interest-hotel-room ?

5.???????????? Page, J-F, C?té, J-P, Savard, G. (2005) A new framework for revenue management and pricing optimization based on bilevel programming, AGIFORS Revenue Management Study Group, Capetown, South Africa, May.?

6.???????????? Ratliff, R. and Vinod, B. (2005) Airline pricing and revenue management: a future outlook. Journal of Revenue and Pricing Management, 4, 3, 302–307.

7.????????????????????????? Toutant, Charles (2023) Antitrust Lawsuits Multiply—And There's an Algorithm at the Center of It All, Law.com, August 2023, https://www.law.com/njlawjournal/2023/08/23/antitrust-lawsuits-multiply-and-theres-an-algorithm-at-the-center-of-it-all/?slreturn=20240308175807

8.???????????? Weinstein, Jeffrey (2024) Spotlight shines brighter on algorithmic price-fixing in hospitality, Hotel Investment Today, April 1,

9.??????????? Vinod, B. (2021); The Evolution of Yield Management in the Airline Industry: Origins to the Last Frontier, ISBN-13:?978-3030704230, ISBN-10:?3030704238, Springer Nature, Switzerland, May.

10.??????? Vinod (2022) Revenue Management in the Lodging Industry: Origins to the Last Frontier, ISBN: 978-3-031-14304-5, ISBN: 978-3-031-14302-1, Springer Nature, Switzerland, November.

11.??????? Vinod, B. (2024) Mastering the Travel Intermediaries: Origins and Future of Global Distribution Systems, Travel Management Companies, and Online Travel Agencies, ISBN 978-3-031-51523-1, Springer Nature, Switzerland, May

12.??????? Zhang, D., Kallesen, R. (2008) Incorporating competitive price information into revenue management, Journal of Revenue and Pricing Management, 7(1), 17-26.