Can Buyers Reveal for a Better Deal?
Authors: Daniel Halpern, Gregory Kehne, Jamie Tucker-Foltz
IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study market interactions in which buyers are allowed to credibly reveal partial information about their types to the seller. Previous recent work has studied the special case of one buyer and one good, showing that such communication can simultaneously improve social welfare and ex ante buyer utility. However, with multiple buyers, we find that the buyer-optimal signalling schemes from the one-buyer case are actually harmful to buyer welfare. Moreover, we prove several impossibility results showing that, with either multiple i.i.d. buyers or multiple i.i.d. goods, maximizing buyer utility can be at odds with social efficiency, which is surprising in contrast with the one-buyer, one-good case. Finally, we investigate the computational tractability of implementing desirable equilibrium outcomes. We find that, even with one buyer and one good, optimizing buyer utility is generally NPhard but tractable in a practical restricted setting. |
| Researcher Affiliation | Academia | Daniel Halpern , Gregory Kehne , Jamie Tucker-Foltz Harvard University {dhalpern, gkehne}@g.harvard.edu, jtuckerfoltz@gmail.com |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use or provide access information for a publicly available or open dataset for training purposes. |
| Dataset Splits | No | The paper is theoretical and does not provide specific dataset split information for validation. |
| Hardware Specification | No | The paper does not provide specific hardware details used for running any experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not contain specific experimental setup details like hyperparameter values or training configurations. |