The effectiveness of “scratch and save” promotions: the moderating roles of price consciousness and expected savings
Bibliographic record
Abstract
Purpose The main purpose of this paper is to examine consumer perceptions of “scratch and save” (SAS) promotions, which are popular store‐level promotional tools. This paper particularly focuses on investigating the moderating effects of consumers' price consciousness and savings expectations. Design/methodology/approach Two laboratory experimental studies were employed to examine consumer responses to SAS promotions. Findings The results of two experiments show that SAS promotions positively affect consumer perceptions of offer value and store prices, and consumers' intentions to shop and spread positive word‐of‐mouth. In particular, the effects of SAS promotions are moderated by consumer price consciousness and expected savings. Furthermore, the first study shows that the level of claimed savings of SAS promotions does not favorably affect consumer reactions. The second study also shows that consumers' discounting of expected savings increases as the level of claimed savings of SAS promotions increases. Research limitations/implications Although SAS promotions are widely used by various types of retailers, there really is little known as to how consumers respond to SAS promotions. By providing evidence of the effectiveness of SAS promotions, this paper enables pricing researchers to extend issues related to such promotional tools. Practical implications For retailers, the most distinctive finding of this paper is that the level of claimed savings may not significantly affect consumer perceptions and shopping intentions, although an SAS promotion would be an effective promotional tool. Originality/value As a preliminary effort to examine the effects of SAS promotions, this paper offers a discussion of the future research opportunities.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".