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Buyer-Optimal Algorithmic Consumption

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  • Shota Ichihashi
  • Alex Smolin

Abstract

An algorithm recommends a product to a buyer based on the product's value to the buyer and its price. We characterize an algorithm that maximizes the buyer's expected payoff and show that it strategically biases recommendations to incentivize lower prices. Under optimal algorithmic consumption, informing a seller about the buyer's value does not affect the buyer's expected payoff but leads to a more equitable distribution of payoffs across different values. These results extend to Pareto-optimal algorithms and multiseller markets.

Suggested Citation

  • Shota Ichihashi & Alex Smolin, 2023. "Buyer-Optimal Algorithmic Consumption," Papers 2309.12122, arXiv.org, revised Sep 2024.
    • Handle: RePEc:arx:papers:2309.12122
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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