How Winery Tourism Experience Builds Brand Image and Brand Loyalty
Bibliographic record
Abstract
This research examines the role of the winery tourism experience in the formation of brand image and brand loyalty. A qualitative analysis of 2540 TripAdvisor reviews—a user-generated form of electronic word of mouth—of four wineries of the Okanagan Valley posted over six years (2014-2020) reveals not only Pine and Gilmore’s (1999) four categories of consumer experiences (i.e., esthetics, education, entertainment, and escape), but also an additional factor (i.e., social interactions with employees and other visitors). The TripAdvisor reviews also show that—based on their winery tourism experiences—consumers express differentiated brand image impressions associated with wineries and brand loyalty. The contribution of this research lies in the identification of social interactions as a complementary dimension of winery tourism experiences, and in linking winery tourism experiences with brand image and brand loyalty. From a theoretical perspective, the findings encourage a greater integration of the consumer experience and the brand image and loyalty literature, as well as quantitative research examining their relation. The findings also have managerial implications for brand experience management in the wine tourism sector.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".