On October 20, a California trial court granted summary judgment in favor of defendants in Mach v. Yardi Systems, Inc., rejecting class plaintiffs’ claims that defendants violated California’s antitrust law, the Cartwright Act, through their common use of rental pricing software. The decision, which relied on “critical” evidence produced by defendant Yardi Systems in discovery, marks the first case to address antitrust theories related to “algorithmic price-fixing” at the summary judgment stage.
The Mach plaintiffs’ complaint alleged that Yardi and rental property owners engaged in per se illegal rent price-fixing scheme facilitated by sharing nonpublic information on rental prices through Yardi’s software. Early in discovery, however, Yardi produced evidence which the court found directly refuted plaintiffs’ argument that defendants engaged in a “give-to-get” information-sharing scheme. Specifically, the court explained that, although property owners “enter their own information” into Yardi’s software, that information could only be used “for their own purposes,” and not for “the generation of price recommendations” for their competitors. And without evidence that Yardi’s software shared competitively sensitive information among competitors, the court held there was no basis to infer a horizontal or hub-and-spoke agreement between defendants in violation of the Cartwright Act.
The court also rejected class plaintiffs’ argument that the property owners’ common use of the same pricing algorithm was enough to violate the Cartwright Act, even if no competitively sensitive information was shared. As with their information-sharing theory, the court rejected this fallback argument because the plaintiffs lacked evidence of any horizontal agreement among defendants to adopt Yardi’s recommendations. Moreover, the court found persuasive the Ninth Circuit’s recent decision in Gibson v. Cendyn, which held that Las Vegas hotels’ common use of revenue management software to price hotel rooms did not violate federal antitrust laws. At bottom, the court explained, the Gibson and Mach plaintiffs both sought to rely on a “collection of independent, nonexclusive software licenses” to establish an antitrust conspiracy amongst competitors. But “adopting a common software application itself is not an antitrust violation,” the court held, because the law “does not require a business to turn a blind eye to information” or “decline to take advantage of a service” simply because “its competitors also use that service.”
The Mach decision adds to a growing body of state and federal decisions that reject algorithmic pricing theories without concrete evidence that sensitive information is shared amongst competitors. The Mach decision also suggests that software vendors can effectively defend themselves against such theories by demonstrating early in discovery that their products do not, in fact, collect or use their customers’ nonpublic information to generate pricing recommendations for other customers.