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Reduced demand uncertainty and the sustainability of collusion: How AI could affect competition

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  • O’Connor, Jason
  • Wilson, Nathan E.

Abstract

We model how a technology that perfectly predicts one of two stochastic demand shocks alters the character and sustainability of collusion. Our results show that mechanisms that reduce firms’ uncertainty about the true level of demand have ambiguous welfare implications for consumers and firms alike. An exogenous improvement in firms’ ability to predict demand may make collusion possible where it was previously unsustainable or more profitable where it previously existed. However, an increase in transparency also may make collusion impracticable where it had been possible. The intuition for this ambiguity is that greater clarity about the true state of demand raises the payoffs both to colluding and to cheating. Our findings on the ambiguous welfare implications of reduced uncertainty contribute to the emerging literature on how algorithms, artificial intelligence (AI), and “big data” in market intelligence applications may affect competition.

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  • O’Connor, Jason & Wilson, Nathan E., 2021. "Reduced demand uncertainty and the sustainability of collusion: How AI could affect competition," Information Economics and Policy, Elsevier, vol. 54(C).
    • Handle: RePEc:eee:iepoli:v:54:y:2021:i:c:s0167624520301268
    DOI: 10.1016/j.infoecopol.2020.100882
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    Cited by:

    1. Martin, Simon & Rasch, Alexander, 2024. "Demand forecasting, signal precision, and collusion with hidden actions," International Journal of Industrial Organization, Elsevier, vol. 92(C).
    2. Werner, Tobias, 2021. "Algorithmic and human collusion," DICE Discussion Papers 372, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    3. Martin, Simon & Rasch, Alexander, 2022. "Collusion by algorithm: The role of unobserved actions," DICE Discussion Papers 382, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    4. Simon Martin & Alexander Rasch, 2022. "Collusion by Algorithm: The Role of Unobserved Actions," CESifo Working Paper Series 9629, CESifo.
    5. Jorge Lemus & Fernando Luco, 2021. "Price Leadership and Uncertainty About Future Costs," Journal of Industrial Economics, Wiley Blackwell, vol. 69(2), pages 305-337, June.
    6. Timo Klein, 2021. "Autonomous algorithmic collusion: Q‐learning under sequential pricing," RAND Journal of Economics, RAND Corporation, vol. 52(3), pages 538-558, September.
    7. Aleksandar B. Todorov, 2022. "Algorithmic pricing and concerted behaviour – competitive challenges?," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 90-107.
    8. Fourberg, Niklas & Marques-Magalhaes, Katrin & Wiewiorra, Lukas, 2022. "They are among us: Pricing behavior of algorithms in the field," WIK Working Papers 6, WIK Wissenschaftliches Institut für Infrastruktur und Kommunikationsdienste GmbH, Bad Honnef.
    9. Martin, Simon & Schmal, W. Benedikt, 2021. "Collusive compensation schemes aided by algorithms," DICE Discussion Papers 375, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    10. Fourberg, Niklas & Marques Magalhaes, Katrin & Wiewiorra, Lukas, 2023. "They Are Among Us: Pricing Behavior of Algorithms in the Field," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 277958, International Telecommunications Society (ITS).
    11. Marcel Wieting & Geza Sapi, 2021. "Algorithms in the Marketplace: An Empirical Analysis of Automated Pricing in E-Commerce," Working Papers 21-06, NET Institute.
    12. Sandra Maria Correia Loureiro & Jorge Nascimento, 2021. "Shaping a View on the Influence of Technologies on Sustainable Tourism," Sustainability, MDPI, vol. 13(22), pages 1-18, November.

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    More about this item

    Keywords

    Artificial Intelligence; Uncertainty; Collusion; Price Discrimination; Antitrust;
    All these keywords.

    JEL classification:

    • K12 - Law and Economics - - Basic Areas of Law - - - Contract Law
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L40 - Industrial Organization - - Antitrust Issues and Policies - - - General

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