The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
I Won the Auction But Don't Want the Prize
Abstract
The “winner's curse” occurs in competitive situations when a successful buyer finds that he or she has paid too much for a commodity of uncertain value. This study provides an experimental demonstration of the winner's curse, and identifies factors that affect the existence and magnitude of this bidding abnormality. In an auction setting, two factors are shown to affect the incidence and magnitude of the winner's curse: (1) the degree of uncertainty concerning the value of the item up for bid and (2) the number of competing bidders. Increasing either factor will increase the range of value estimates and bids, making it more likely that the winning bidder will overestimate the true value of the commodity and thus overbid.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241
Cited by
Timid choices and bold forecasts: a cognitive perspective on risk taking.
Kahneman, D., & Lovallo, D. (1993) · Management Science · doi:10.1287/mnsc.39.1.17 · Cited by 2,043
Lohmueller, K. E., Pearce, C. L., Pike, M., Lander, E. S., & Hirschhorn, J. N. (2003) · Nature Genetics · doi:10.1038/ng1071 · Cited by 1,900
Quantifying and correcting for the winner's curse in genetic association studies
Xiao, R., & Boehnke, M. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20398 · Cited by 192
Imitation and luck: An experimental study on social sampling
Offerman, T., & Schotter, A. (2009) · Games and Economic Behavior · doi:10.1016/j.geb.2008.03.004 · Cited by 52
Metadata
- Authors
- Bazerman, M. H., & Samuelson, W. F.
- Venue
- Journal of Conflict Resolution
- Publisher
- SAGE Publications
- Published
- 1983-12
- Volume
- 27
- Issue
- 4
- Pages
- 618-634
- ISSN
- 0022-0027 (ISSN-L)
- 1552-8766
- OpenAlex
- W2112980279
- Cited by
- 311
- References
- 1
- FWCI
- 2.96
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: I Won the Auction But Don't Want the Prize. https://app.cochat.ai/papers/10.1177/0022002783027004003
- The paper
- Bazerman, M. H., & Samuelson, W. F. (1983). I Won the Auction But Don't Want the Prize. Journal of Conflict Resolution. https://doi.org/10.1177/0022002783027004003
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.