Conceptualising attitudes towards brand genuinuity: scale development and validation
Bibliographic record
Abstract
Abstract This paper aims to conceptualise attitudes towards brand genuinuity by developing and validating a psychometric scale through four studies. Study 1 generates a pool of potential scale items through a review of the literature, thesaurus search, focus groups, and expert surveys. Study 2 confirms the unidimensionality of the scale items using confirmatory factor analysis. Study 3 establishes convergent, discriminant, predictive, and nomological validity. Finally, Study 4 confirms the generalisability of the scale by applying it in a different context. The process resulted in a 5-item unidimensional scale measuring attitudes towards the brand’s genuinuity. The results demonstrated that brand genuinuity is a unique construct, and distinct from related concepts, brand sincerity, and brand heritage. The development and validation of the current scale fill an important gap in the advertising literature. It provides a better understanding of and mechanism to measure attitudes towards brand genuinuity, which could not be measured with previous scales. Likewise, the scale provides important insights for brand managers and will be an important tool for managers to test and confirm the degree to which new advertising material exhibits brand genuinuity.
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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 | 0.032 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".