Assessing the Long-Term Effect on Sales and CSR of a Nutrition Marketing Strategy in the Retailing Environment
Bibliographic record
Abstract
The present work aims to implement a ‘healthy checkout’ in a real retailing environment in order to demonstrate that this kind of intervention can be a win-win strategy for both shoppers and retailers in a long-term perspective. A field experiment has been conducted in five stores belonging to a leading Italian Retailer in the north of Italy, where all the unhealthy products have been removed from the checkouts. Both sales analysis and shoppers attitudes towards the intervention have been studied. Sales data have been analyzed for the ‘healthy checkout stores’ vs ‘traditional checkout stores’, and customers have been interviewed at the end of the shopping trip five months after the implementation. Our findings show that developing a healthy checkout can have a positive impact on sales, retailer’s reputation in terms of perceived CSR, and loyalty to the store. The present work provides some interesting results about the long-term effect of an in-store marketing strategy that aims to promote health among customers.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".