The customer-brand relationship in the gambling industry: positive play predicts attitudinal and behavioral loyalty
Bibliographic record
Abstract
This research draws on the model of positive play (i.e. responsible gambling) to investigate whether positive play beliefs (e.g. accurate understanding about the odds of success on games of chance) and behavior (e.g. setting a limit on gambling expenditures) are associated with attitudinal loyalty and behavioral loyalty. Results from Study 1 indicated that among American casino loyalty program members (N = 188), positive play was predictive of attitudinal loyalty when controlling for disordered gambling symptomatology. In Study 2, using survey and player-account data from 383 members of a Canadian casino loyalty program, we found that positive play was negatively associated with behavioral loyalty, but that this association was eliminated after accounting for disordered gambling symptomatology. These results suggest that fostering positive play may help increase positive perceptions of a casino and its loyalty program without undermining the amount of money a player spends at that casino.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".