How Questions and Answers Shape Online Marketplaces: The Case of Amazon Answer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper uses data from two online shopping platforms to investigate the economic implications of the Q&A system. This research problem becomes increasingly important as many websites start to adopt the Q&A system. Yet, its economic implications have not been discussed in the previous literature. We employ the difference-in-differences analysis to examine the effect of Q&A elements on product sales. We find that question elements negatively affect sales while answer elements have a positive impact. Also, an increase in the number of question is positively correlated with the number of reviews. Meanwhile, an increase in the number of answers reduces the average length of reviews. Our findings suggest that incorporating the Q&A system could be a potential approach to drive sales. However, it is crucially important for managers to develop appropriate policies to gather necessary answers to questions asked on the platform in order to capitalize on such system.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.011 | 0.002 |
| 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 it