Major antitrust suit alleges 6 hotel chains, with Bay Area locations, colluded to fix prices
A major antitrust class action landed in federal court in San Francisco on Friday, alleging that six major hotel operators colluded to fix prices for their rooms using AI-powered software that provides pricing recommendations.
Plaintiffs and proposed class representatives are eight individual consumers who stayed at one or more of the hotel chains in the last four years.
The 41-page complaint alleges that Integrated Decisions and Systems, Inc. or "IDeaS" of Minnesota, and its parent company, SAS Institute, Inc, created and licensed software called "G3 RMS," that is the hotel industry's leading "revenue management system."
The defendants allegedly promote their system as a way that industry operators can gain "competitive advantage" in pricing decisions, but it is actually an algorithmic tool to fix prices in an anticompetitive manner.
The suit targets six familiar hotel chains: Hilton Worldwide Holdings Inc, Wyndham Hotels & Resorts, Inc, Four Seasons Hotels and Resorts US Inc, Omni Hotels and Resorts Inc, and Hyatt Hotel Corporation, in addition to Choice Hotels International Inc, which includes the budget conscious brands Comfort, Quality Inn, Sleep Inn, Econo Lodge, and Rodeway Inn. Collectively the defendants have thousands of hotels in the United States.
The suit alleges price fixing in a number of major geographical markets including the San Francisco-Oakland-Fremont, CA Metropolitan Statistical Area which includes San Francisco, Alameda, Marin, San Mateo, and Contra Costa counties, where all of the defendants operate hotels.
In San Francisco, each of the defendants have at least one hotel property except for Choice, which has properties just outside of the city.
The Sherman Act has long forbidden competitors from agreeing to fix prices. Because finding evidence of an explicit agreement is difficult, many cases are based on proving a tacit agreement by inferring from actions of competitors that would not make business sense in the absence of an agreement.
Agreements to fix prices are anticompetitive.
For example, if two competitors in the same market each offer the same product, consumers will tend to buy the lower-priced alternative.
In the absence of collusion, each competitor would be incentivized — at least up to a point — to undercut the other's pricing. That type of price competition would benefit the consumer. However, if each competitor knew that it could raise prices and its competitor would do the same thing, each could charge prices — "supra-competitive prices" in economic jargon — that would benefit each competitor at the expense of the consumer.
The complaint alleges that defendants have set up a way to automate the process of price fixing through use of an algorithm powered by artificial intelligence. The way it allegedly works is that IDeaS's clients, all competitors with each other, agree to supply IDeaS with proprietary, non-public, and sensitive information about their room availability, demand, and pricing. The information is provided continuously, in real time, so that IDeaS always knows what all of its client-competitors have available in a given market.
G3 RMS then provides individualized pricing recommendations to its clients designed to maximize their revenue. The complaint alleges that the recommendations are made at the granularity of pricing for individual classes of rooms. The recommendations update constantly, no less than daily, and often several times a day. According to the complaint, recommendations are almost always adopted automatically by the hotel operators. Plaintiffs allege, for example, that Choice adopted the recommendations 93 percent of the time.
Clients are marketed the software with claims that its pricing recommendations are better than any human person could do on his or her own and therefore management can essentially outsource all pricing decisions to the algorithm. In their marketing materials, defendants allegedly say that use of the system will increase hotel revenue from 8 to 15 percent.
According to plaintiffs, "by sending their sensitive confidential pricing and occupancy information to a third party to process, analyze, and develop supra-competitive prices, the [defendants] are able to achieve the same result as if they secretly met in a back room and exchanged their information and agreed to a supra-competitive price."
Plaintiffs make a number of allegations that they argue give powerful support to their claims.
First, they allege that when clients use the system, their occupancy actually declines even as their revenue rises. Falling occupancy is predicted by the algorithm and is expected. However, "every defendant is currently charging the highest or near-highest average rates for hotel rooms in its history despite a lack of corresponding increase in occupancy demand."
Second, that clients are overtly encouraged and incentivized to follow the recommendations because "the more faithfully co-conspirators adopt IDeaS' pricing recommendations, the more revenue and profit each will earn."
Finally, that the algorithm is not static. Because it is based on artificial intelligence, the "algorithm is constantly learning, thereby becoming more adept at setting supra-competitive prices as it receives additional data. Therefore, as long as users continue to provide IDeaS with non-public, transaction-level data, the algorithm's recommended prices will become increasingly effective at overcharging hotel guests."
Based on that, plaintiffs predict that "the harm to competition and injury to consumers alleged herein will worsen over time."
So-called "algorithmic pricing" is a relatively new area in antitrust law but it has attracted concern from antitrust regulators. The complaint quotes a former commissioner of the Federal Trade Commission who said that "Just as the antitrust laws do not allow competitors to exchange competitively sensitive information directly in an effort to stabilize or control industry pricing, they also prohibit using an intermediary to facilitate the exchange of confidential business information."
The commissioner then posed the question, "Is it OK for a guy named Bob to collect confidential price strategy information from all the participants in a market, and then tell everybody how they should price? If it isn't OK for a guy named Bob to do it, then it probably isn't ok for an algorithm to do it either."
Invitations to comment on the complaint from IDeaS and SAS were not immediately accepted. Plaintiffs' lawyers also did not respond to a request for comment.
