Identification of key variables and constructs in the context of wine tasting room: importance-performance analysis
Bibliographic record
Abstract
Purpose Relying on importance–performance theory, this paper uses a distinctive statistical analysis instrument to investigate the importance and performance of crucial wine tasting room constructs and indicators with a purpose to make real and tangible recommendations for wine tasting room managers to improve the winery visit experience. Design/methodology/approach The surveys (N = 402) were conducted among 14 wineries in British Columbia, Canada. The data was analysed by using partial least squares structural equation modelling software SmartPLS with importance–performance functionality embedded in it. Findings The findings indicate the importance and performance of the service quality constructs, assurance, empathy, reliability, responsiveness, and tangibility and their respective indicator variables in importance–performance map analysis (IPMA). The responsiveness construct showed the highest need for improvement in terms of performance of exogenous service quality constructs in wine tasting rooms. Empathy, value for money and reliability constructs got “no change” recommendation and “tangibility” and “education” recommendation. The assurance construct was not significantly related to customer satisfaction and was not included in the IPMA analysis. Originality/value The approach provides an easy to use and visual tool for wineries to assess the importance and performance of the various service quality elements. The tool provides the management of wineries guidance for the identification of strategic areas of service quality improvement.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".