Adapting and Validating Scale of Customer Engagement in Online Travel Communities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Increasing attention towards customer engagement has caused its measurement to remain a highly debated issue among scholars. This study adapts and validates measurement scales for customer engagement in Online Travel Communities. It builds on previous studies on scale development for customer engagement. Data were collected from 450 members of Online Travel Communities in eight countries: Australia, Canada, Hong Kong (Chinese territory), New Zealand, Singapore, South Africa, the United Kingdom and the United States of America. The process of adapting and validating the scale involved exploratory factor analysis, testing for differential item functioning, examination of item response theory, confirmatory factor analysis, testing for invariance and criterion validity. The results found that three dimensions (affection, absorption, and interaction) suitably and adequately measure customer engagement in Online Travel Communities.
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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 | 0.016 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it