NeurIPS 2019poster21 citations

Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer

Arsenii Vanunts, Alexey Drutsa

Abstract

We study revenue optimization pricing algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation. When the participants non-equally discount their cumulative utilities, we show that the optimal constant pricing (which offers the Myerson price) is no longer optimal. In the case of more patient seller, we propose a novel multidimensional optimization functional --- a generalization of the one used to determine Myerson's price. This functional allows to find the optimal algorithm and to boost revenue of the optimal static pricing by an efficient low-dimensional approximation. Numerical experiments are provided to support our results.

BibTeX
@inproceedings{NEURIPS2019_33e8075e,
 author = {Vanunts, Arsenii and Drutsa, Alexey},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer},
 url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/33e8075e9970de0cfea955afd4644bb2-Paper.pdf},
 volume = {32},
 year = {2019}
}