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Mechanisms with money are commonly designed under the assumption that agents are quasi-linear, meaning they have linear disutility for spending money. We study the implications when agents with non-linear (specifically, convex) disutility for payments participate in mechanisms designed for quasi-linear agents. We first show that any mechanism that is truthful for quasi-linear buyers has a simple best response function for buyers with non-linear disutility from payments, in which each bidder simply scales down her value for each potential outcome by a fixed factor, equal to her target return on investment (ROI). We call such a strategy ROI-optimal. We prove the existence of a Nash equilibrium in which agents use ROI-optimal strategies for a general class of allocation problems. Motivated by online marketplaces, we then focus on simultaneous second-price auctions for additive bidders and show that all ROI-optimal equilibria in this setting achieve constant-factor approximations to suitable welfare and revenue benchmarks.
@InProceedings{babaioff_et_al:LIPIcs.ITCS.2021.84,
author = {Babaioff, Moshe and Cole, Richard and Hartline, Jason and Immorlica, Nicole and Lucier, Brendan},
title = {{Non-Quasi-Linear Agents in Quasi-Linear Mechanisms}},
booktitle = {12th Innovations in Theoretical Computer Science Conference (ITCS 2021)},
pages = {84:1--84:1},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-177-1},
ISSN = {1868-8969},
year = {2021},
volume = {185},
editor = {Lee, James R.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2021.84},
URN = {urn:nbn:de:0030-drops-136230},
doi = {10.4230/LIPIcs.ITCS.2021.84},
annote = {Keywords: Return on investment, Non-quasi-linear agents, Transferable Welfare, Simultaneous Second-Price Auctions}
}