A growing number of companies offer artificial intelligence-powered revenue management platforms, which leverage big data and sensitive business information from multiple firms to optimize pricing, output, and other operational decisions for their clients. Over the past 18 months, dozens of antitrust lawsuits have alleged that such platforms facilitate price-fixing among rivals. Barak Orbach explores the strength of the allegations and the antitrust implications of such revenue management platforms.
Problems of excess demand and excess supply are prevalent in markets for services and perishable goods, where firms operate with costly fixed capacities and face demand fluctuations. For example, airlines and hotels can be thinly occupied at times and overbooked at others. Revenue management (RM) systems utilize data to optimize the business operations of companies facing such challenges.
American Airlines pioneered revenue management with the introduction of its semi-automated reservation system, Sabre, in the 1960s. Over the past six decades, RM systems have evolved significantly and are now deployed in many industries. Contemporary RM systems harness the power of big data and artificial intelligence tools to provide real-time optimization. They automate data gathering and analysis and automate operational decisions, including price adjustments and customized promotions. However, the costs of developing and maintaining advanced RM systems are significant. RM platforms offer alternatives to the integration of RM systems within firms. They operate data infrastructures and offer clients RM services, including price-optimization recommendations.
Scholars and commentators have warned that the deployment of RM systems and platforms may harm consumers because these technologies are engineered to maximize profits, not to intensify competition. For example, the parallel deployment of RM systems by rivals in a concentrated industry may result in tacit algorithmic collusion, whereby each system learns that friendly rivalry is more profitable than aggressive competition because competitive aggression would likely be reciprocated by other systems. The concerns are even greater in the case of RM platforms that serve competitors and utilize clients’ sensitive business information to generate optimization recommendations. In such situations, centralized optimization services may replace independent decision-making processes.
RM Services in Rental Housing Markets
RM platforms for the apartment rental industry emerged in the early 2000s, building on the success of RM systems in the airline and hospitality industries. Algorithmic pricing—automated price adjustments based on real-time market intelligence—is one of the core features of these platforms.
In 2008, the trade magazine Multifamily Executive explained that “revenue management software . . . evaluates market conditions to set rents and terms for a given unit,” and noted that property management companies that implemented such RM systems saw “an immediate impact on the rents [they were] able to charge, often to levels they [had] never imagined possible.” Three years later, The New York Times reported that “[f]or about a decade the country’s biggest landlords . . . have been using powerful software tools to set rental rates on new and renewing leases. . . . [T]he software weighs competitors’ rental rates, market conditions, seasonal trends and hundreds of other variables to recommend the highest feasible rent for each apartment at a given time.”
In October 2022, ProPublica published an investigative report arguing the reliance of large landlords on the services of RealPage, a dominant RM platform for housing rentals, contributed to sharp rises in rent prices in America. A few days after the publication of this report, a private antitrust lawsuit against RealPage and some of its large clients was filed in California. Since then, dozens of similar lawsuits challenging the legality of RealPage’s RM business model have been filed. Similar lawsuits challenge the legality of the business models of other RM platforms, such as Yardi (RealPage’s key rival) and Rainmaker (RM services for hotel casinos).
In these lawsuits, plaintiff lawyers and state attorneys general alleged that RM platforms facilitated price-fixing agreements in violation of Section 1 of the Sherman Act. Over 40 cases against RealPage were consolidated into multidistrict litigation in the Middle District of Tennessee. In December 2023, the court ruled that a class of multifamily home renters had “plausibly alleged an antitrust conspiracy in violation of the Sherman Act” and, therefore, allowed those plaintiffs to continue to discovery. Two months earlier, another district court ruled that a complaint against Rainmaker and casino hotels in Las Vegas suffered from “numerous pleading deficiencies” and gave the plaintiff an opportunity to file an amended complaint.
The Department of Justice and Federal Trade Commission filed statements of interest in cases concerning the RM platforms of RealPage, Yardi, and Rainmaker.
Antitrust Concerns
Optimization of business operations is an essential mode of competition. It enables companies to enhance efficiency, cut costs, improve customer satisfaction, and adapt to evolving market dynamics. Effective operational optimization requires a capacity to monitor and quickly respond to changes in competitors’ offerings, prices, and promotions. This capacity becomes even more vital in markets for fungible products and services, where potential customers can easily compare products and prices.
When rivals in concentrated markets possess monitoring and response capacities, they often realize that their actions and profitability are interdependent and sometimes deduce that a friendly rivalry is more beneficial than aggressive competition. In antitrust terminology, this interdependence is referred to as “tacit collusion” or “conscious parallelism.” The Supreme Court has described conscious parallelism as “a common reaction of firms in a concentrated market that recognize their shared economic interests and their interdependence with respect to price and output decisions.” The Supreme Court has repeatedly emphasized that conscious parallelism, unlike coordinated conduct of rivals (“concerted action”), is not in itself unlawful.
However, centralized facilitation and reinforcement of interdependence may constitute unlawful concerted action. For example, in Eastern States(1914) and The Sugar Institute (1936), the Supreme Court held that trade associations that facilitated interdependence among their members formed unlawful conspiracies in violation of the antitrust laws.
In American Column & Lumber(1921) and Maple Flooring(1925), the Supreme Court distinguished informed operational optimization that relies on statistical reports from the exchange of sensitive business information among rivals. Information exchange, the Court concluded, is an expression of coordination and, therefore, may constitute an agreement in restraint of trade. In contrast, informed optimization that does not involve such coordination is generally permissible, because “[c]ompetition does not become less free merely because the conduct of commercial operations becomes more intelligent.” The Court, therefore, emphasized that it “was not the purpose or the intent of the Sherman [Act] to inhibit the intelligent conduct of business operations.”
Relying on these precedents and subsequent ones, courts have repeatedly recognized coordination facilitated by third parties may establish an unlawful conspiracy. For example, in Toys ‘R’ Us (7th Cir. 2000) and the eBook Case (2d Cir. 2015), powerful retailers facilitated coordination among their suppliers. Such arrangements are known as hub-and-spoke conspiracies, whereby a third party (the “hub”) facilitates an unlawful conspiracy agreement (the “rim”) among rivals through a set of vertical agreements or interactions (the “spokes”).
The lawsuits against RealPage and other operators of RM platforms allege that their utilization of nonpublic sensitive business information of rival companies formed unlawful hub-and-spoke conspiracies.
The Agreement Requirement
Section 1 of the Sherman Act prohibits agreements that unreasonably restrain trade. To satisfy the agreement requirement at the motion to dismiss phase, a plaintiff must allege sufficient facts to raise a plausible inference of unlawful agreement. More precisely, the plaintiff must allege parallel conduct and plus factors whose holistic evaluation permits such a plausible inference. “Plus factors” are economic factors above and beyond parallel conduct that are consistent with coordinated action and inconsistent with independent conduct, such as evidence of the exchange of sensitive business information among rivals. At the summary judgment phase, after discovery, the plaintiff must present evidence of parallel conduct and plus factors that tends to exclude the possibility that the alleged conspirators acted independently.
While courts persistently refer to the framework of parallel conduct and plus factors, it is difficult to locate judicial opinions where a court held that the plaintiff adequately alleged, let alone proved, the existence of an agreement without evidence of interdependence and coordination. Proof of interdependence requires “evidence that shows that the parallel acts were against the apparent individual economic self-interest of the alleged conspirators.” Proof of coordination, in turn, typically requires evidence of “a high level of interfirm communications” or evidence of exchange of sensitive business information.
The decisions on motions to dismiss in the cases against RealPage and Rainmaker applied the foregoing legal standards. RealPage’s public statements provided that the company’s RM services (a) rely, in part, on clients’ sensitive business information and (b) guide clients’ pricing decisions. The class that survived the motion to dismiss argued that the clients’ choices to rely on RealPage’s RM services constituted parallel conduct and that they used RealPage’s pricing recommendations, believing that their rivals would do the same. These factual allegations raised a plausible inference of interdependence. Additionally, the “most persuasive” plus factor was the “simple undisputed fact” that RealPage aggregated clients’ “proprietary commercial data” to generate optimization recommendations. In contrast, the original complaint in the case against Rainmaker and its clients failed to allege interdependence and misuse of sensitive business information.
The Agencies’ Approach
The statements of interest of the DOJ and FTC in the cases against RealPage, Yardi, and Rainmaker presented two key legal claims that the court rejected in the RealPage matter.
First, the Agencies argued that the parallel conduct and plus factors framework “is not the only way to prove concerted action circumstantially.” Instead, they argued that Interstate Circuit(1939) and its progeny permit the inference of agreement in situations where rivals accept an invitation to collude. This argument is based on a misreading of Interstate Circuit. It also conflicts with the Supreme Court’s decision in Twombly (2007), which rejected the proposition that “plus factors are not required to be pleaded to permit an antitrust claim based on parallel conduct to survive dismissal.”
Second, the Agencies argued that algorithmic price fixing is a per se violation of Section 1 of the Sherman Act. However, courts are reluctant to apply the per se illegality rule in cases that do not involve traditional straightforward price-fixing conspiracies. Additionally, courts have persistently used the rule of reason analysis in cases of information exchange.
The Future of RM Platforms
Theories of algorithmic collusion typically refer to concerns that interdependence resulting from the parallel deployment of AI-powered optimization systems may be more effective and more stable than traditional price-fixing agreements. The cases against RealPage and other RM platforms address a different form of algorithmic collusion, whereby a single entity allegedly facilitates and reinforces interdependence among rivals and, in some instances, replaces independent decision-making of rivals with centralized decision-making. Under the established precedent, arrangements of this kind may constitute an unlawful agreement in restraint of trade.
Some commentators have argued that the standards guiding the analysis of interdependence under antitrust law are outdated and should be reformed. However, it is far from clear that antitrust law should impose restrictions on firms’ independent operational optimization. What should be clear is that the use of nonpublic sensitive business information of firms to generate optimization recommendations for other firms is a facilitating practice that likely violates Section 1 of the Sherman Act.
Articles represent the opinions of their writers, not necessarily those of the University of Chicago, the Booth School of Business, or its faculty.
