For the first time, an appellate court has sided with class action plaintiffs pursuing price-fixing claims against defendants that allegedly used algorithms to set prices and output. The Third Circuit reversed a New Jersey district court’s dismissal of a suit against Atlantic City hotels in which the plaintiffs claimed that the defendants’ use of a common algorithmic software platform was an anticompetitive hub-and-spoke pricing-fixing conspiracy that resulted in higher prices and lower occupancy for hotel rooms.
The decision creates a split with the Ninth Circuit in a nearly identical case involving the same software and highlights the potential antitrust risk for companies using commercially available algorithmic software to set prices or occupancy, particularly when it involves sharing nonpublic information and high rates of compliance with the algorithm’s recommendations.
Background
In Cornish-Adebiyi v. Caesars Entertainment, the Third Circuit revived a putative price-fixing class action whose plaintiffs—casino-hotel guests who rented rooms from various properties in Atlantic City—alleged that several casino-hotels and Cendyn Group violated Sherman Act Section 1 by using Cendyn’s Rainmaker algorithmic-pricing software to coordinate hotel room rates. The complaint alleged a hub-and-spoke price-fixing conspiracy where the casino-hotel defendants provided their current, nonpublic room pricing and occupancy data to Rainmaker, which used the data to generate recommended room rates. As alleged, these pricing recommendations were automatically uploaded into the casino-hotels’ property-management systems, and the defendants accepted Rainmaker’s recommendations approximately 90% of the time. The plaintiffs claimed that this allowed the defendants to maintain inflated room rates without fear that competitors would undercut them.
The district court dismissed the complaint in September 2024, concluding that the plaintiffs had not plausibly alleged the requisite horizontal agreement among the competing casino-hotels. The district court found that the casino-hotels knowingly and purposefully used the same software, not that they agreed with one another to fix prices. The court also relied on the fact that the casino-hotels adopted Rainmaker over a 14-year period, that the plaintiffs had not sufficiently explained how Cendyn allegedly pooled or exchanged confidential data, and that each casino-hotel retained final pricing authority.
The Third Circuit reversed and remanded for further proceedings.
The Third Circuit’s Decision
The Third Circuit held that the complaint had plausibly and sufficiently alleged a hub-and-spoke price-fixing conspiracy. The court concluded that the plaintiffs plausibly alleged that Cendyn operated as the hub and the casino-hotels as the spokes, with the “rim” supplied by allegations that the casino-hotels knowingly provided current, nonpublic pricing and occupancy data to a shared pricing agent, received recommendations informed by competitors’ data, and overwhelmingly followed those recommendations.
The court emphasized that the complaint alleged more than parallel use of the same vendor: Rainmaker allegedly functioned as a “shared pricing agent” that coordinated pricing for a majority of the Atlantic City casino-hotel market. For example, Cendyn allegedly urged “uniform adoption” of the algorithm and told the casino-hotels that Rainmaker “would generate significantly higher prices for each [casino-hotel] than if each one did so independently without use of that platform.” Cendyn also allegedly touted users’ access to competitors’ real-time, nonpublic pricing and ability to generate higher prices and profits, while avoiding price wars.
In particular, the court found that the plaintiffs had alleged parallel conduct and plus factors sufficient to overcome the defendants’ motion to dismiss.
The court found that the plaintiffs adequately alleged parallel conduct by alleging both contemporaneous use of Cendyn’s pricing software during the class period and synchronized movement in prices and occupancy (rising room rates and falling occupancy rates). The Third Circuit rejected the defendants’ argument that staggered adoption over 14 years defeated parallelism. In the court’s view, the relevant alleged conduct was not the initial adoption of Rainmaker at different points in time, but the casino-hotels’ continuous deployment of the pricing tool, continuous delegation of pricing decisions to the software, and subsequent synchronous pricing and output movements during the class period.
The court then found that the plaintiffs adequately alleged several plus factors. First, the plaintiffs alleged a motive to conspire, pointing to financial hardship in the Atlantic City casino-hotel market and a market structure conducive to collusion in the form of high barriers to entry, limited substitutes, and a concentrated market structure. Second, the court credited allegations that maintaining high room prices despite declining occupancy was contrary to each casino-hotel’s independent economic interest to compete more aggressively for increased occupancy. According to the court, this is especially true for casino-hotels because filling rooms can drive gaming and other on-premises revenue, giving them “even more incentive” to fill rooms to capacity. Third, the court credited allegations of exchanges of nonpublic commercial information through Cendyn, opportunities to coordinate at industry events, knowledge of competitors’ relationships with Cendyn, and a sudden departure from long-standing business practices.
The court separately rejected the defendants’ argument that the conspiracy theory failed because each casino-hotel retained authority to override Rainmaker’s recommendations. The court emphasized that “[p]rices are fixed when they are agreed upon,” regardless of whether conspirators always adhere to the agreed prices. Moreover, the court also noted allegations that Cendyn constrained users’ ability to deviate from the recommended price by requiring a special override of the recommended price and had a scoring system based on how often casino-hotels overrode the recommendation.
At the same time, the court cautioned that not all use of shared pricing tools or common software is an antitrust violation.
Implications
As the first federal circuit court decision to squarely allow a hub-and-spoke algorithmic price-fixing theory to survive the pleading stage, this decision bolsters class action plaintiff and government cases in this evolving area of antitrust law and provides a roadmap for future litigation.
A few important themes arise from the Third Circuit’s decision:
- Concentrated industries that use shared-pricing-software vendors or platforms face higher risks of litigation, particularly when the vendor or its software aggregates real-time, nonpublic competitor data and returns price recommendations to competitors.
- A hub-and-spoke pricing theory can be sustained even without explicit evidence of horizontal agreement between the defendants—the agreement to use the algorithm itself may serve as the mechanism of coordination, especially when users know that their competitors are likely using the same software or the vendor touts high levels of industry “compliance” with its pricing recommendations.
- Future antitrust plaintiffs are likely to rely heavily on the Third Circuit’s holding that plaintiffs need not plead the inner workings of proprietary algorithms before discovery.
- Market anomalies (e.g., prices rising while demand falls) combined with specific industry characteristics will likely be used as plus-factor evidence of actions against self-interest.
- Staggered software-adoption timelines and the absence of a clear starting point for alleged coordination may not be reliable defenses against algorithmic-pricing claims as in prior cases.
Takeaways
Finally, observe a few practical takeaways when using, or considering using, algorithmic pricing tools:
- If possible, use internal proprietary or custom pricing software rather than commercially available software that competitors may also be using.
- Avoid pricing software that combines competitors’ nonpublic pricing information into a pricing algorithm, especially if the software provides pricing recommendations based on the combined data.
- If the company submits nonpublic pricing (or output/capacity) data to a software vendor, ensure that the data are not commingled with competitors’ data and that the algorithm makes any pricing or occupancy recommendation based only on the user’s own data (or other data that are not competitors’ confidential, competitively sensitive data).
- Do due diligence on a pricing-software vendor’s claims about the number of industry participants using its software, any statements about compliance rates with its pricing recommendations, and any claims about the software’s ability to increase prices and profits especially in the face of lower demand, sales, or output.
- Identify any default settings in pricing software, ensure that the software maintains the company’s ability to readily deviate from any pricing recommendations or defaults, and document the frequency of the company’s deviation from any pricing recommendations.
- Continue to observe fundamental antitrust-compliance guidance, including being on alert at or avoiding software-vendor-organized events where competitors are present and the vendor or competitors could share information about competitors’ use of pricing software and other pricing-related strategies.
If you have any questions, or would like additional information, please contact one of the attorneys on our Antitrust team.
You can subscribe to future advisories and other Alston & Bird publications by completing our publications subscription form.