The impact of fees on customer purchasing behavior and beliefs in winery tasting rooms: A scoping review
Bibliographic record
Abstract
Purpose: This scoping review presents a summary of studies that examined the impact or influence of tasting fees in wineries on the purchasing behaviour, beliefs, obligation to buy wine, and willingness to pay for such fees.Methods: A search was conducted in August 2021 and updated in March 2022 of databases (i.e., Academic Search Complete, Scopus) and hand searching using terms such as wine, tasting fees, and charges. Documents were included if they were databased studies, published in English, and related to the research question. They were then coded for characteristics of the document, design, sample, winery, purchasing behaviour and beliefs, and findings. The coding and analysis were conducted between August 2021 and March 2022. Findings: Of 195 possible documents, 16 remained after a title and abstract scan, and 12 were included after a full-article scan. The reviewed studies were conducted primarily in Australasia (60%) and North America (28%) and a majority of findings were derived from surveys or interviews. A majority of the findings suggested that customers and industry professionals did not support the adoption of tasting fees at the cellar door (64%). Though, mixed impact was noted for purchasing behaviour (i.e., volume, money spent), slightly stronger negative associations were seen for intention to visit the winery or purchase wine in the future, willingness to pay for fees, and obligation to buy wine.Originality: This is the first systematic review to examine the impact or influence of tasting fees on purchasing behaviour and beliefs in wineries.
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 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 | 0.012 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".