Truthful Feedback for Sanctioning Reputation Mechanisms

Jens Witkowski
Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, PMLR R8:657-664, 2010.

Abstract

For product rating environments, similar to that of Amazon Reviews, it has been shown that the truthful elicitation of feed- back is possible through mechanisms which pay buyer reports contingent on the reports of other buyers. We study whether similar mechanisms can be designed for reputation mechanisms at online auction sites where the buyers’ experiences are partially determined by a strategic seller. We show that this is impossible for the basic setting. However, in- troducing a small prior belief that the seller is a cooperative commitment player leads to a payment scheme with a truthful perfect Bayesian equilibrium.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR8-witkowski10a, title = {Truthful Feedback for Sanctioning Reputation Mechanisms}, author = {Witkowski, Jens}, booktitle = {Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence}, pages = {657--664}, year = {2010}, editor = {Grünwald, Peter and Spirtes, Peter}, volume = {R8}, series = {Proceedings of Machine Learning Research}, month = {08--11 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/r8/main/assets/witkowski10a/witkowski10a.pdf}, url = {https://proceedings.mlr.press/r8/witkowski10a.html}, abstract = {For product rating environments, similar to that of Amazon Reviews, it has been shown that the truthful elicitation of feed- back is possible through mechanisms which pay buyer reports contingent on the reports of other buyers. We study whether similar mechanisms can be designed for reputation mechanisms at online auction sites where the buyers’ experiences are partially determined by a strategic seller. We show that this is impossible for the basic setting. However, in- troducing a small prior belief that the seller is a cooperative commitment player leads to a payment scheme with a truthful perfect Bayesian equilibrium.}, note = {Reissued by PMLR on 04 October 2026.} }
Endnote
%0 Conference Paper %T Truthful Feedback for Sanctioning Reputation Mechanisms %A Jens Witkowski %B Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence %C Proceedings of Machine Learning Research %D 2010 %E Peter Grünwald %E Peter Spirtes %F pmlr-vR8-witkowski10a %I PMLR %P 657--664 %U https://proceedings.mlr.press/r8/witkowski10a.html %V R8 %X For product rating environments, similar to that of Amazon Reviews, it has been shown that the truthful elicitation of feed- back is possible through mechanisms which pay buyer reports contingent on the reports of other buyers. We study whether similar mechanisms can be designed for reputation mechanisms at online auction sites where the buyers’ experiences are partially determined by a strategic seller. We show that this is impossible for the basic setting. However, in- troducing a small prior belief that the seller is a cooperative commitment player leads to a payment scheme with a truthful perfect Bayesian equilibrium. %Z Reissued by PMLR on 04 October 2026.
APA
Witkowski, J.. (2010). Truthful Feedback for Sanctioning Reputation Mechanisms. Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, in Proceedings of Machine Learning Research R8:657-664 Available from https://proceedings.mlr.press/r8/witkowski10a.html. Reissued by PMLR on 04 October 2026.

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