Revenue Enhancement via Asymmetric Signaling in Interdependent-Value Auctions
Authors: Zhuoshu Li, Sanmay Das2093-2100
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We consider the problem of designing the information environment for revenue maximization in a sealed-bid second price auction with two bidders. ... We show that in a standard common-value auction setting, there is no beneļ¬t to the auctioneer in terms of expected revenue from sharing information with the bidders, although there are effects on the distribution of revenues. In an interdependent-value model with mixed privateand common-value components, however, we show that asymmetric, information-revealing signals can increase revenue. |
| Researcher Affiliation | Academia | Zhuoshu Li, Sanmay Das Washington University in St. Louis {zhuoshuli, sanmay}@wustl.edu |
| Pseudocode | No | The paper presents theoretical models and proofs, but does not include pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating that source code for the described methodology is publicly available. |
| Open Datasets | No | This is a theoretical paper that does not involve training models on datasets. |
| Dataset Splits | No | This is a theoretical paper and does not involve dataset splits for validation. |
| Hardware Specification | No | This is a theoretical paper that does not describe running experiments on specific hardware. |
| Software Dependencies | No | This is a theoretical paper and does not mention specific software dependencies with version numbers for replication. |
| Experiment Setup | No | This is a theoretical paper and does not describe an experimental setup with hyperparameters or training configurations. |