Consumer flexibility and the effectiveness of limited time offers: the role of psychological reactance
Bibliographic record
Abstract
• The positive effect of limited time offers on product evaluation is attenuated or reversed into a negative effect when consumer flexibility is restricted by reduced purchase timing flexibility, store layout flexibility, return policy flexibility, and personal time flexibility. • Psychological reactance to restrictions drives the negative effect of limited time offers on product evaluation. • The negative effect of limited time offers on product evaluation can be reversed into a positive effect by including a statement in the offer that highlights future regret if the offer is missed. Retailers, e-commerce platforms, and television shopping channels often advertise limited time offers. Past research indicates that limited time offers generally increase product evaluation by prompting consumers to make inferences of product value. We show across eight studies that the positive effect of limited time offers is attenuated or reversed into a negative effect when consumer flexibility is restricted by lower purchase timing flexibility, store layout flexibility, return policy flexibility, and personal time flexibility. We also show that psychological reactance to restrictions drives the negative effect of limited time offers on product evaluation. Finally, we show that the negative effect of limited time offers on product evaluation can be reversed back into a positive effect by including a statement that highlights future regret if the offer is missed.
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 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 | 0.006 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".