Algorithmic Pricing, Competition, and Consumer Welfare

Authors

  • Eric Mitchell Author

Keywords:

algorithmic pricing, competition, consumer welfare, digital markets, antitrust

Abstract

This policy review examines algorithmic pricing, competition, and consumer welfare. The organizing question is how policy should distinguish efficiency-enhancing adaptation from conduct that weakens rivalry or exploits consumers. Ten related scholarly sources are synthesized through a decision-centered framework spanning problem definition, mechanism, measurement, evaluation, implementation, and governance. The review does not invent experiments, pooled estimates, or unreported quantitative results. It instead evaluates the strength and transferability of the available evidence, with particular attention to inferring collusion or welfare improvement from price correlation alone. The resulting framework links technical or empirical performance to explicit use conditions and identifies tests that should precede wider adoption in digital and data-intensive markets.

References

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  2. Brown, Z. Y., & MacKay, A. (2023). Competition in Pricing Algorithms. American Economic Journal Microeconomics, 15(2), 109-156. https://doi.org/10.1257/mic.20210158
  3. Calvano, E., Calzolari, G., Denicolò, V., & Pastorello, S. (2020). Artificial Intelligence, Algorithmic Pricing, and Collusion. American Economic Review, 110(10), 3267-3297. https://doi.org/10.1257/aer.20190623
  4. Do, C. T., Tran, N. H., Huh, E. N., Hong, C. S., Niyato, D., & Han, Z. (2016). Dynamics of service selection and provider pricing game in heterogeneous cloud market. Journal of Network and Computer Applications, 69, 152-165. https://doi.org/10.1016/j.jnca.2016.04.012
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  6. Harrington, J. E. (2022). The Effect of Outsourcing Pricing Algorithms on Market Competition. Management Science, 68(9), 6889-6906. https://doi.org/10.1287/mnsc.2021.4241
  7. Kastius, A., & Schlosser, R. (2021). Dynamic pricing under competition using reinforcement learning. Journal of Revenue and Pricing Management, 21(1), 50-63. https://doi.org/10.1057/s41272-021-00285-3
  8. Ma, R. T. B. (2015). Usage-Based Pricing and Competition in Congestible Network Service Markets. IEEE/ACM Transactions on Networking, 24(5), 3084-3097. https://doi.org/10.1109/tnet.2015.2500589
  9. Shah-Mansouri, H., Wong, V. W. S., & Huang, J. (2017). An Incentive Framework for Mobile Data Offloading Market Under Price Competition. IEEE Transactions on Mobile Computing, 16(11), 2983-2999. https://doi.org/10.1109/tmc.2017.2688402
  10. Zha, L., Yin, Y., & Du, Y. (2017). Surge Pricing and Labor Supply in the Ride-Sourcing Market. Transportation research procedia, 23, 2-21. https://doi.org/10.1016/j.trpro.2017.05.002

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Published

2026-08-05

Issue

Vol. 1 (2026): Archive

Section

Policy Review

License

Copyright (c) 2026 Markets, Organizations & Public Value

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.