The Effects of Perceived Quality of Performance on Price-Value, Satisfaction, and Behavioural Intentions by Golfers' Resident Type
Bibliographic record
Abstract
A model is developed that considers the effects of perceived quality of performance on price-value, satisfaction, and behavioural intentions. The model was tested using data from 3,235 surveys of golfers on Prince Edward Island, a golfing destination in Canada. Three golfer types were identified: tourists, permanent residents, and seasonal residents. An exploratory factor analysis was completed to develop five measures of perceived golf course quality. Three multiple regression models were then used to examine the relationships among the constructs. This appears to be the first study that models golfer behaviors and intentions by resident type. The results indicate a significant positive relationship between perceived quality and the feeling that value was received for the golf fee paid. The significant positive relationship was also observed between perceived quality, price-value, and satisfaction; and between perceived quality, price-value, satisfaction, and intentions to return to golf and to recommend the course. Overall, the results provide support for a causal relationship between the constructs. The study contributes to a better understanding of golfers’ perceptions and behavioural intentions by resident type.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".