Comparison of consumer perceptions and preference toward organic versus conventionally produced foods: A review and update of the literature
Bibliographic record
Abstract
Abstract Growing interest in organic agriculture has prompted numerous studies that compare various aspects of organic and conventionally produced foods. This paper provides a comprehensive evaluation of empirical studies comparing organic products and conventionally grown alternatives. The emphasis is on key organic consumer demand and marketing issues, including: (1) the implications of an economic definition of organically grown food for consumer demand; (2) attributes that shoppers consider most when comparing organic with conventionally grown products; (3) level and characteristics of consumer knowledge and awareness about organic food; (4) assessment methods and characteristics of organic consumer attitudes and preferences; (5) size of price premium and characteristics of consumers’ willingness-to-pay for organic products; and (6) profile of organic consumers. Overall, although there is some knowledge and awareness about organic products, consumers are not consistent in their interpretation of what is organic. Secondly, while consumers typically understand the broad issues about organic foods, many tend not to understand the complexities and niceties of organic farming practices and organic food quality attributes. Uncertainty regarding the true attributes of organic, and skepticism about organic labels, part of which stems from reported cases of (inadvertent) mislabeling, and product misrepresentation, and partly because of nonuniform organic standards and certification procedures, may hold some consumers back from purchasing organic. Thirdly, concern for human health and safety, which is a key factor that influences consumer preference for organic food, is consistent with observed deterioration in human health over time and, therefore, motivates consumers to buy organic food as insurance and/or investment in health. Fourthly, the proportion of consumers who are willing to pay a price premium for organic food decreases with premium level. On the other hand, premiums tend to increase with (combinations of) preferred attributes. In addition, demand tends to depend more on the price differential with respect to conventionally grown products, than on actual price. In contrast to sensitivity of demand to changes in price, income elasticity of demand for organic foods is generally small. Finally, it is important for policy analysts and researchers to note that organic fresh fruits and vegetables currently dominate the organic consumer's food basket. Furthermore, it is not clear whether frequent buyers consider particular organic products (e.g., organic meat) as normal goods, or if consumers consider such products as luxury goods.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".