Internal and External Factors Influencing Millennials’ Sharing Behaviour of Online Video Advertisements
Bibliographic record
Abstract
This study aimed to uncover the internal and external factors driving Millennial consumers to engage in Online Video Advertisements (OVAs) sharing. Underpinned by the Theory of Planned Behaviour (TPB), the internal factors tested in this study were attitude, subjective norms, and perceived behavioural control. The external factors predicted to influence consumers’ intention and actual sharing behaviour of OVAs were company reputation, brand awareness, and celebrity endorsement were underpinned by Stimulus Organism Response Model (S-O-R). The study included perceived intrusiveness as a moderator between the aforementioned antecedents and the sharing behaviour of OVAs. A total of 220 Millennial respondents was collected in Selangor, Malaysia. Partial Least Squares Structural Equation Modelling (PLS-SEM) analysis showed that attitude and subjective norms significantly predict consumers’ intention to share OVAs. In terms of external antecedents, only celebrity endorsements were found to positively influence the sharing intention of OVAs. The study also revealed that perceived intrusiveness negatively moderates the effects of attitude and social norms on the intention to share OVAs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".