Using Price Promotions to Drive Children's Healthy Choices in a Developing Economy
Bibliographic record
Abstract
This research examines how price discounts—a classic marketing incentive—drive children's healthy choices in the understudied context of a developing economy. The authors partnered with UNICEF to launch three field experiments in Panamá among 2,418 children to examine four pillars of price discount promotions for children: what to discount (product selection), how to discount (message design), whom to target (children's age), and whether to discount again (repetition). They uncovered four previously undocumented insights. First, price discounts alone effectively increase demand among children 6–11 years of age, reconciling conflicting findings in prior literature. Second, product selection based on relative price—a particularly crucial factor in developing regions—drives opposing postpromotion effects: ironically, marketers should not discount expensive healthy options but rather moderately priced ones. Third, different from prior literature's practice of directly communicating final prices, discount messages that require older children to derive final prices are more effective. Fourth, repetition can amplify or undermine discounts’ efficacy depending on message complexity and children's age. This research offers concrete guidelines for researchers and practitioners, uncovering both positive and negative effects of price promotions on children, and shedding light on price promotion interventions that most powerfully nudge children of different ages to act.
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How this classification was reachedexpand
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 | 0.022 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".