Bibliographic record
Abstract
This paper analyzes the impact of risk and ambiguity aversion - Knightian uncertainty - on the choice of optimal quality and timing of market entry in the agri-food sector. Irreversibility of the investment in product development is introduced in a continuous-time stochastic model applying the real option literature. We consider a market characterized by a duopoly with a Stackelberg-Nash game for quality choice. When the follower provides a higher- quality good, the level of quality is decreasing in ambiguity aversion while it is a non-monotonic function of the level of risk. For low levels of risk, the increase of product quality is an efficient response. Up to certain threshold level of risk, risk and ambiguity aversion reduce the optimal quality level and increase the value of waiting when the follower supplies a higher-quality good. The implication is that risk and ambiguity aversion allow the leader to make a sustainable monopoly pro t. When the follower supplies a lower-quality good, there is no value for it to wait. It should therefore provide the lowest-quality good possible. In a vertically integrated supply chain rms provide higher quality, and the di¤erence between vertically integrated and non-integrated rms is increasing in risk and ambiguity aversion.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".