An Integrated Thesis Examining the Influence of Casino Loyalty Program Membership on Gamblers’ Attitudinal and Behavioural Loyalty
Bibliographic record
Abstract
Every major casino corporation offers their customers the opportunity to enroll in a brand-affiliated loyalty program.These programs serve as marketing strategies designed to foster attitudinal (i.e., trust and satisfaction with the brand) and behavioural (i.e., purchase intentions and actions) loyalty among customers by way of granting members rewards in exchange for making purchases.It is the hope that through granting members rewards, gambling expenditure will be increased, thus generating profits for the casino.However, unlike loyalty programs in other industries, casino loyalty programs reward members for engaging in gambling-an inherently addictive activity.Despite this, there is a paucity of research that has applied knowledge from the field of responsible gambling studies to help us understand how loyalty program membership influences the attitudinal and behavioural loyalty of members.In the current work, I present an integrated thesis that includes three manuscripts (six studies in total) that sought to expand the knowledge base on the aforementioned issue.In the first manuscript, I used two studies to test the hypothesis that loyalty program tier status and disordered gambling symptomatology would have an interactive effect on the attitudinal and behavioural loyalty of members, such that the highest level of loyalty would be observed among high tier status, high risk gamblers.In the second manuscript, I investigated whether positive play (i.e., responsible gambling beliefs and behaviours) is predictive of attitudinal (Study 1) and behavioural loyalty (Study 2), and whether this predictive utility would be maintained after accounting for disordered gambling symptomatology.In the final manuscript, I examined the potential benefits of belonging to a casino loyalty program for both players and industry.In two studies, I tested whether incentivizing responsible gambling tool use increases both willingness to use responsible gambling v Table of Contents
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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 | 0.006 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".