Bibliographic record
Abstract
Abstract Product returns incur a substantial financial loss for retailers. We demonstrate how, when, and why cross‐selling during the product returns process can reduce this loss in revenue. We find consumers more readily spend money refunded from product returns than unspent money. We theorize that this refund effect occurs because consumers psychologically realize the loss of money when purchasing products and earmark that money for spending. Thus, consumers feel a smaller psychological loss when spending refunded money than unspent money on a subsequent purchase. In six experiments, we find consumers spend refunded money more freely than unspent money, even more than windfall gains like lottery winnings, on products in similar and different product categories (e.g., groceries vs. apparel). However, the refund effect only holds when consumers do not expect to return products at the point of purchase and before refunded money is commingled with money in other accounts. Our findings identify a new fungibility violation due to mental accounting (i.e., a new source effect), and illustrate its value for generating, validating, and explaining revenue retention strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".