Reputation and relative price positioning of small wineries in Québec, Canada
Bibliographic record
Abstract
Purpose In a highly competitive market, the price of wine is a variable controlled by suppliers to suggest a level of quality. An index of relative firm position in the market based on relative prices is calculated for a sample of wine producers. The purpose of the paper is to analyze some of the factors related to the characteristics of a firm and quality that may explain the price strategy of wine producers in a new and small wine region, i.e. Québec province in Canada. Design/methodology/approach Data on types of wines and prices are collected from a sample of 40 small wine producers in Québec, Canada for the selected years 2008, 2010 and 2015. Findings The authors demonstrate that a high price strategy is significantly related to the reputation of the vineyard rather than the age of the domain, the size or the number of wines produced. Research limitations/implications The analysis has been carried out based on a data set of only 40 firms for which the price-position index could be calculated. Unfortunately, only limited information is available on producers and production volumes. Practical implications This analysis is of particular relevance for small or new wine-producing regions, which lack an established reputation. Because wine quality and taste differ by geographic origin and variety, new wine-producing regions may have opportunities to define a wine’s image (or a winery image) and the producer must inform the market on quality of the wine by reflecting it on the final selling price. Originality/value Prior works on the analysis of the price-quality relationship give rise to various and sometimes contradictory results. This analysis is of particular relevance to explain the price strategy of small wine producers in a strongly competitive market where the price remains an obvious commercial argument to signal the quality of a wine.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".