Pricing in Two-Sided Platforms with Artificial Intelligence

Authors

DOI:

https://doi.org/10.24215/18521649e040

Keywords:

two-sided platforms, artificial intelligence, algoritmic pricing

Abstract

I analyze the effect of using artificial intelligence algorithms in two-sided platform markets. When the algorithms rely solely on the firm's payoff values, the resulting prices are significantly higher than the theoretical equilibrium, a phenomenon known in the literature as algorithmic collusion. However, when the algorithms have access to more information, I find that market prices are similar to the theoretical predictions.

Author Biography

  • Alejandro Cichevski, Universidad del CEMA, Argentina

    Candidato a Doctor en Economía por la Universidad del CEMA, magíster en Economía Política por Boston University y en Economía por la Universidad de Montevideo. Actualmente se desempeña como economista en el Área de Política Económica y Mercados del Banco Central del Uruguay. Ha realizado trabajos de investigación y consultoría en áreas de economía laboral, finanzas corporativas y organización industrial.

References

Armstrong, M. (2006). Competition in two-sided markets. The RAND Journal of Economics, 37(3), 668–691.

Asker, J., Fershtman, C. y Pakes, A. (2022). Artificial intelligence, algorithm design, and pricing. AEA Papers and Proceedings, 112, 452–456. https://doi.org/10.1257/pandp.20221059

Assad, S., Clark, R., Ershov, D. y Xu, L. (2024). Algorithmic pricing and competition: Empirical evidence from the German retail gasoline market. Journal of Political Economy, 132(3), 723-771. https://doi.org/10.1086/726906

Brown, Z. Y. y MacKay, A. (2023). Competition in pricing algorithms. American Economic Journal: Microeconomics, 15(2), 109–156. https://doi.org/10.1257/mic.20210158

Calvano, E., Calzolari, G., Denicolo, V. y Pastorello, S. (2020). Artificial intelligence, algorithmic pricing, and collusion. American Economic Review, 110(10), 3267–3297. https://doi.org/10.1257/aer.20190623

Competition and Markets Authority. (2018). Pricing algorithms: Economic working paper on the use of algorithms to facilitate collusion and personalised pricing. Crown.

Harrington, J. E. (2018). Developing competition law for collusion by autonomous artificial agents. Journal of Competition Law & Economics, 14(3), 331–363. https://doi.org/10.1093/joclec/nhy016

Johnson, J. P., Rhodes, A. y Wildenbeest, M. (2023). Platform design when sellers use pricing algorithms. Econometrica, 91(5), 1841–1879. https://doi.org/10.3982/ECTA19978

Jullien, B., Pavan, A. y Rysman, M. (2021). Handbook of industrial organization. En K. Ho, A. Hortaçsu y A. Lizzeri (Eds.), Two side markets, pricing and network effects (pp. 485–592). https://doi.org/10.1016/bs.hesind.2021.11.007

Klein, T. (2021). Autonomous algorithmic collusion: Q-learning under sequential pricing. The RAND Journal of Economics, 52(3), 538–558. http://dx.doi.org/10.1111/1756-2171.12383

Reisinger, M. (2014). Two-part tariff competition between two-sided platforms. European Economic Review, 68, 168–180. https://doi.org/10.1016/j.euroecorev.2014.03.005

Rochet, J.-C. y Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990–1029. https://doi.org/10.1162/154247603322493212

Waltman, L. y Kaymak, U. (2008). Q-learning agents in a Cournot oligopoly model. Journal of Economic Dynamics and Control, 32(10), 3275–3293. https://doi.org/10.1016/j.jedc.2008.01.003

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Published

2025-08-18

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Articles

How to Cite

Cichevski, A. (2025). Pricing in Two-Sided Platforms with Artificial Intelligence. Económica, 71, 040. https://doi.org/10.24215/18521649e040