Fine-Grained Buy-Many Mechanisms Are Not Much Better Than Bundling
Sepehr Assadi, Vikram Kher, George Li, Ariel Schvartzman

TL;DR
This paper introduces buy-$k$ mechanisms that interpolate between buy-one and buy-many, showing they can bound revenue gaps with simple mechanisms like bundling, but small menu options may still lead to exponential revenue gaps.
Contribution
The paper defines buy-$k$ mechanisms and proves they limit revenue gaps with bundling, offering new insights into mechanism complexity and revenue approximation.
Findings
Buy-$k$ mechanisms bound revenue gaps to $O(n^2)$ for additive buyers.
Small menu options (k = Θ(n^{1/2-ε})) can still cause exponential revenue gaps.
Buy-$k$ mechanisms overcome the infinite revenue issue of buy-one models.
Abstract
Multi-item revenue-optimal mechanisms are known to be extremely complex, often offering buyers randomized lotteries of goods. In the standard buy-one model, it is known that optimal mechanisms can yield revenue infinitely higher than that of any "simple" mechanism -- the ones with size polynomial in the number of items -- even with just two items and a single buyer (Briest et al. 2015, Hart and Nisan 2017). We introduce a new parameterized class of mechanisms, buy- mechanisms, which smoothly interpolate between the classical buy-one mechanisms and the recently studied buy-many mechanisms (Chawla et al. 2019, Chawla et al. 2020, Chawla et al. 2022). Buy- mechanisms allow the buyer to buy up to many menu options. We show that restricting the seller to the class of buy- incentive-compatible mechanisms suffices to overcome the bizarre, infinite revenue properties of the…
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Taxonomy
TopicsAuction Theory and Applications · Consumer Market Behavior and Pricing · Digital Platforms and Economics
