Information or Prices, Which Is Most Powerful in Increasing Consumer Demand for Organic Vegetables?
Bibliographic record
Abstract
Based on a unique and very detailed panel dataset covering consumption of organically and conventionally produced vegetables in the years 2005 - 2007, we examine the effects of information about positive health effects of consuming organic vegetables and information about negative health effects of consuming conventional vegetables on demand for organic foods for six different segments of Danish households. Three of these segments are positive towards organics whereas the remaining three segments are negative or indifferent. Using the double hurdle model we estimate partial effects of both directly and indirectly obtained information as well as prices. The results show, that there are larger effects of information for households where the information is in accordance with initial knowledge and attitudes, hence the positive segments react more to information whereas the negative segments react more to prices. “New” consumers can be persuaded to buy organic vegetables by providing information about the negative health effects of consuming conventional vegetables since it increases the probability of an organic purchase. Once consumers have entered the organic marked for vegetables, information that link health and the consumption of organic vegetables will increase consumption. The results are important for firms and producers who want to successfully target information to different consumer groups with the aim of increasing the market share for organic food.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".