Comparing the service experience of satisfied and non-satisfied customers in the context of wine tasting rooms using the SERVQUAL model
Bibliographic record
Abstract
Purpose The purpose of this study is to compare satisfied and non-satisfied customers in the context of wine tasting rooms using the SERVQUAL model and to examine the relationships in the model in terms of service experience to better understand customer needs. Design/methodology/approach The data used in this study were derived from a survey conducted among wineries in British Columbia, Canada. Analysis of survey results using the partial least squares structural equation modeling was undertaken. Sample size was 402. Findings The findings show that the SERVQUAL constructs that had the most impact on customer satisfaction and dissatisfaction were tangibility and assurance. Somewhat surprisingly, the perceived value for money construct was not significantly related to customer satisfaction but was significantly related to repurchase intent. Furthermore, all SERVQUAL constructs, except the reliability construct, were significantly related to customer satisfaction. Originality/value This study provides an overview of how wineries can improve their services to increase the number of satisfied customers.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".