Charitable Motives and Bidding in Charity Auctions
Bibliographic record
Abstract
Research on bidding in auctions has generally relied on the assumption of self-interested bidders. This work relaxes that assumption in the context of charity auctions. Because understanding charitable motives has important implications for auction design and charities' fundraising strategies, this study investigates bidders' specific types of charitable motives and the strength of these motives. We carry out three controlled field experiments consisting of real-life auctions conducted on a local Internet auction site. We use a novel design in which we simultaneously run charity and noncharity auctions for identical products and vary the percentage donated to charity. Results show that auctions with proceeds donated to charity lead to significantly higher selling prices, a result due to a higher bidding by bidders with charitable motives rather than to increased bidder entry. We also find that increased prices only occur when the charitable donation is a percentage of the auction revenue, and that a fixed charitable donation associated with each auction has no effect on prices. Furthermore, we find that prices are increasing in the percentage donated to charity. We find considerable support for a model of voluntary shill-like bidding, where charitable bidders try to increase proceeds in charity auctions. We also find that auctions with 25% of revenue donated to charity had higher net revenue than noncharity auctions. Hence, companies may be able to use charity auctions as part of a corporate social responsibility strategy and at the same time increase profitability even though they donate part of the proceeds to charity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".