Yes, we have no bananas: Consumer responses to restoration of freedom
Bibliographic record
Abstract
Abstract When stockouts restrict consumers' freedoms, two independent responses can occur: product desirability, or a reactance‐based increase in the desire for the unavailable option, and source negativity, or general frustration with the source of the restriction. In four studies, we provide a novel investigation of consumer responses to stockout‐restoration and examine how these two forces combine to affect consumer responses after freedoms are restored. To do so, we investigate two moderators that influence the activation and strength of product desirability and source negativity, respectively: trait reactance and attributions. While all consumers experience source negativity in response to stockouts, only consumers high in reactance experience product desirability, leading to differential responses to stockout‐restoration. Compared to an in‐stock condition, high reactance consumers respond positively to stockout‐restoration, while low reactance consumers respond negatively to stockout‐restoration, in terms of store and product evaluations and store choice. However, when high reactants attribute a stockout to the store, thereby increasing source negativity relative to product desirability, they respond negatively to stockout‐restoration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".