Algorithmic Price-Fixing Claims Terminated

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Highlights

  • In Gibson v. Cendyn Group LLC, No. 2:23-CV-00140-MMD-DJA (D. Nev. May 8, 2024), the court dismissed with prejudice a putative class action alleging that the defendant-hotel operators engaged in a price-fixing conspiracy by collectively using a software provider's products/algorithm for hotel room pricing recommendations.
  • The Gibson court reached this decision based on the plaintiffs' allegations that the hotel defendants signed up for the pricing software services at different times and on the insufficiency of allegations that the hotel defendants exchanged confidential information or agreed to be bound by the software's pricing recommendations or otherwise fix their prices.
  • The Gibson decision provides a roadmap for dismissal or summary judgment in other algorithmic price-fixing cases, where the alleged co-conspirators (spokes) subscribe to the software provider's allegedly anticompetitive algorithm (hub) at different points in time, no confidential or otherwise non-public information is exchanged, and/or the co-conspirators are not bound to accept the algorithm's pricing recommendations.

A Nevada federal court on May 8, 2024, dismissed with prejudice a putative class action alleging that a handful of Las Vegas hotel operators and a software provider broke antitrust laws by licensing and using a software program that made hotel room pricing recommendations.

Summary of the Court's Ruling

U.S. District Judge Miranda M. Du previously dismissed the plaintiffs' complaint in October 2023, finding numerous pleading deficiencies under the Sherman Antitrust Act, 15 U.S.C. § 1 et seq., and Twombly pleading standards.1 The plaintiffs filed an amended complaint in November 2023, adding more than 100 additional pages of allegations to bolster their claims, along with an additional count to challenge the set of vertical agreements between the hotels and software provider.2 The defendants again moved to dismiss in February 2024.3 After full briefing and a hearing,4 the court again dismissed the plaintiffs' complaint, this time with prejudice.

Factual Background

The proposed class comprised "all persons who rented hotel rooms on the Las Vegas Strip" from one of the defendants from Jan. 24, 2019, to the present.5 The plaintiffs alleged two claims in their amended complaint against five hotel entities (collectively referred to by the court as the Hotel Defendants) and a pair of software providers for the hotel management industry called Cendyn Group LLC and The Rainmaker Group Unlimited Inc. (collectively referred to by the court as Cendyn).6 Both claims were rooted in Section 1 of the Sherman Antitrust Act (15 U.S.C. § 1).7

As observed by the court, Cendyn offered two software products, GuestRev and GroupRev, licensed and used by the Hotel Defendants.8 Among other features, GuestRev recommended hotel room prices for individuals and GroupRev for groups and conferences.9 GuestRev launched in 2001 and GroupRev in 2013.10 In 2014, both products incorporated RevCaster, which collected public pricing information to be used as a factor in setting their pricing recommendations.11 The Hotel Defendants allegedly used these products at various points in time.12

In their first claim, the plaintiffs alleged a hub-and-spoke conspiracy "consisting of a series of vertical agreements between Cendyn (the hub) and Hotel Defendants (the spokes), with a rim made from the tacit agreements between Hotel Defendants to use Cendyn's GuestRev and GroupRev products knowing that their competitors were as well."13 In their second claim, the plaintiffs alleged the "Hotel Defendants entered into a series of vertical agreements with Cendyn to use GuestRev or GroupRev, which had the anticompetitive effect of artificially inflating hotel room prices, and thus harmed consumers."14

The Court's Holding on the Plaintiffs' First Claim

The court dismissed the plaintiffs' hub-and-spoke conspiracy claim on three main grounds. First, the court took issue with the differences in timing – across a 10-year period – that each Hotel Defendant began using the Cendyn products.15 The court held, "[I]t would be more plausible to infer a tacit rim when each spoke agreed to charge the price that the hub demanded as each spoke decided to enter into an agreement with the hub requiring each of the spokes to charge a certain price. But here, Plaintiffs do not allege that each spoke – Hotel Defendants – ever agreed to charge a price that the hub – Cendyn – demanded them to charge."16 Instead, all the plaintiffs alleged is that the Hotel Defendants began using Cendyn's products at different times over a 10-year period, failing to allege any plausible collusion.17

Second, the court found the claim deficient in alleging the "exchange of confidential information from one of the spokes to the other through the hub's algorithms, convincing the court that "there is no rim."18 Even the plaintiffs' attributions of machine learning to Cendyn's products fell short because, again, the allegations did not plausibly suggest the direct give-and-take of one hotel operator's confidential information to another, even if Cendyn used the information to benefit the system as a whole.19 The plaintiffs' failure to allege the exchange of confidential information also served as a basis to discredit the plaintiffs' reliance on a U.S. Department of Justice (DOJ) statement of interest filed in Duffy v. Yardi Systems, Inc. (Yardi), and on In re RealPage, Rental Software Antitrust Litigation (RealPage), both of which the court noted relied on the algorithmic exchange of confidential information between competitors.20 At most, the court found, the plaintiffs alleged that the Hotel Defendants consulted their competitors' public rates, which is not an unreasonable means to determine their own pricing.21

Third, the court held that the plaintiffs failed to allege that the Hotel Defendants bound themselves to the GuestRev and GroupRev pricing schemes, much less charge a uniform price.22 In fact, the plaintiffs went the opposite direction, alleging Cendyn encountered sustained difficulty getting customers to accept its recommended prices.23

The Court's Holding on the Plaintiffs' Second Claim

The plaintiffs' second claim – that the Hotel Defendants entered into vertical agreements with Cendyn in an unreasonable restraint of trade – fared no better.24 The court once again relied on the plaintiffs' failure to allege that the Hotel Defendants were bound to accept the GuestRev and GroupRev prices to hold that the software license agreements did not restrain trade.25

Takeaways and Practical Implications

The Gibson decision provides a roadmap for the dismissal of other factually similar algorithmic price-fixing cases. Gibson was one of a wave of algorithmic price-fixing cases across the hotel, casino and multifamily apartment industries. The legal theory and framework in Gibson is largely the same as in cases against RealPage, Yardi, Atlantic City casino hotels and several national hotel chains. The claims in these cases are most vulnerable to arguments that mere use of common software by the horizontal competitors that would form the rim of the hub-and-spoke conspiracy constitutes an actionable agreement under Section 1 of the Sherman Act. In the RealPage litigation, the court denied motions to dismiss based on allegations that the competitor multifamily apartment owners used RealPage's software to submit proprietary commercial data to RealPage for use in pricing recommendations and that they knew their competitors were doing the same. In Gibson, the court distinguished RealPage primarily based on the lack of allegations that the Hotel Defendants shared confidential information and the lack of allegations that the Hotel Defendants agreed to be bound by the Cendyn algorithms, which the court believed comprised "alternative and dispositive reasons" that the plaintiffs failed to allege a tacit agreement.26 Other cases with allegations closer to Gibson than RealPage can rely on the Gibson decision as a roadmap to dismissal.

In addition, the Gibson court's rejection of the plaintiffs' "machine learning" allegations in support of their theory led to an outcome different from other courts overseeing the current wave of algorithmic price-fixing claims. According to the Gibson court, even if software users share their confidential information with the algorithm/application but do not share such information directly with another user, the use of such confidential information to make the overall algorithm better at determining optimal pricing is not enough to plausibly suggest a tacit agreement to fix prices sufficient to survive a motion to dismiss.

Finally, for the same reasons, the Gibson decision casts doubt on the DOJ's arguments submitted in statements of interest in RealPage, Yardi and Cornish-Adebiyi v. Caesars Entertainment Inc.27 In particular, the DOJ's statements include two arguments that the Gibson court flatly rejected. First, the DOJ has argued that direct competitor-to-competitor communications are not required under Section 1. Instead, competitors communicating with the software provider as a common agent in "a unity of purpose or a common design or understanding" is sufficient to establish a tacit agreement among the horizontal competitors.28 In Gibson, as explained above, the court demanded more than use of a common pricing platform. Second, the DOJ has asserted that fixing the starting point of prices is per se illegal because it "disrupts the decentralized price-setting mechanism in the market," even if ultimate prices may deviate.29 In Gibson, however, the court credited arguments that Hotel Defendants are not required to – and often do not accept – the pricing recommendations generated by Cendyn's software, even if they all receive initial pricing recommendations from the software.

Notes 

1 Gibson, et al. v. MGM Resorts Int’l, et al., No. 2:23-cv-00140-MMD-DJA (D. Nev. Oct. 24, 2023).

2 Dkt. 144.

3 Dkts. 160-161.

4 Dkts. 167-169, 172, 176, 185.

5 Am. Compl. at 1.

6 Id. ¶¶ 28-34

7 Id. ¶¶ 351-370.

8 Memo. Op. at 2.

9 Id.

10 Id.

11 Id.

12 Id.

13 Id. at 3.

14 Id. at 16.

15 Id. at 5.

16 Id.

17 Id. at 6-7.

18 Id. at 9.

19 Id. at 10-13.

20 Id. at 8.

21 Id.

22 Id. at 6, 13-15

23 Id. at 6, 15.

24 Id. at 16-18

25 Id. at 17.

26 Id. at 5.

27 See Holland & Knight's previous alert, "DOJ 'Triples Down' on View that Use of Pricing Algorithms Can Support Price-Fixing Claims," April 14, 2024.

28 DOJ Statement of Interest, Cornish-Adebiyi v. Caesars Entertainment Inc., No. 1:23-cv-2536, Dkt. 96 at 9 (March 28, 2024) (internal quotation marks omitted); see DOJ Statement of Interest, In re RealPage Antitrust Litigation, Dkt. 628 at 21 (Nov. 15, 2023) ("[I]t suffices to show that RealPage proposed the price-fixing scheme to competing landlords, who were each aware that its competitors were also being invited to participate in the scheme, and the competitors adhered to it – generating a common understanding among the competitors that they would increase prices collectively by using RealPage."); see also DOJ Statement of Interest, Duffy v. Yardi Systems Inc., Dkt. 149 at 2-3 (March 1, 2024) (also attaching Statement of Interest filed in RealPage).

29 RealPage, DOJ Statement of Interest, Dkt. 628 at 20-22; Yardi, DOJ Statement of Interest, Dkt. 149 at 4; Cornish-Adebiyi, DOJ Statement of Interest, Dkt. 96 at 7.

DISCLAIMER: Because of the generality of this update, the information provided herein may not be applicable in all situations and should not be acted upon without specific legal advice based on particular situations.

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