| Report ID: | 08-08-271635-43 |
| Initial Submission Date: | 2008-08-27 |
| Title: | Designing Reputation Mechanisms for Efficient Trade |
| Summary: | A seller in an online marketplace with an effective reputation
mechanism should expect that dishonest behavior results in higher
payments now, while honest behavior results in higher
reputation---and thus higher payments---in the future. We study
two widely used classes of reputation mechanisms. First, we show
that weighting all past ratings equally gives sellers an
incentive to falsely advertise. This result supports the
recent decision of eBay to base the Positive Feedback percentage on the
past 12 months of feedback, rather than the entire lifetime of
the seller. We then study reputation mechanisms that weight
recent ratings more heavily. We show the following dichotomy:
under increasing returns to reputation the optimal strategy of a
sufficiently patient and sufficiently high quality seller is to
always advertise honestly, while under decreasing returns to
reputation the seller will not always be honest. Finally, we
suggest approaches for designing a reputation mechanism that
maximizes the range of parameters for which it is optimal for the
seller to be truthful. We show that mechanisms that use
information from a larger number of past transactions tend to
provide incentives for patient sellers to be more truthful, but
for higher quality sellers to be less truthful. |
| Authors: | Aperjis, Christina; Johari, Ramesh |
| Contact email: | ramesh.johari@stanford.edu |
| | Number of views : 330 Number of downloads : 152 |
