Consumer knowledge and use of country‐of‐origin information at the point of purchase
Bibliographic record
Abstract
Abstract This paper reports an investigation of American and Canadian consumer acquisition and/or knowledge of the country of origin of products at the time of purchase. Consumer knowledge of the country of origin of purchased products was tested as purchasers left the cash register. If the purchaser knew the country of origin of the product just purchased, they were further questioned to discover the role such knowledge might have played in their choice between alternatives. More than 93 per cent of 1,248 purchasers intercepted at the cash register had not acquired while shopping, or did not know from prior experience, the country of origin of a product they had just purchased. Of the 91 (6.5 per cent) who had acquired or knew the country of origin of a product they had just purchased, only 27 (2.2 per cent of the total) indicated that their knowledge of the product's country of origin possibly might have played a role in their product choice. These findings reveal that the country of origin of products is not an important attribute in the choice processes of the great majority of North American consumers. Confirmation of these findings by replication with less obtrusive and more externally valid measures of consumer acquisition and use of product information prior to purchase is needed. Copyright © 2004 Henry Stewart Publications.
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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 | 0.001 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".