Understanding consumer reactions to premium‐based promotional offers
Bibliographic record
Abstract
Reports the results of a three‐study research program whose purpose is to gain a better understanding of consumer reactions to premium‐based promotional offers. In the first study, elaborates and evaluates a comprehensive typology of premium‐based promotional offers with respect to its content and predictive validity. In the next study, explores the semantics that are used by consumers when they are presented with premium promotions and develops a series of research hypotheses from qualitative interviews with 12 consumers. In the final study, conducts a survey of 182 adult consumers to test these research hypotheses. The results reveal that consumer appreciation of premium‐based promotional offers is more positive when the premium is direct than when it is delayed, when there is a relatively lower quantity of product to purchase, when the value of the premium is mentioned, when brand attitude is positive, when interest in the premium is great, and when consumers are characterized by deal‐proneness and compulsive buying tendencies. Consumers’ perception of manipulation intent is affected mainly by directness of the premium, mention of the value of the premium, interest in the premium, and deal‐proneness.
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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 | 0.002 | 0.008 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".