Influencing the Power of Celebrity Endorsers on Saudi’s Purchasing Behavior
Bibliographic record
Abstract
Presently, influencer marketing is widely used to increase brand purchasing. Marketers employ various strategies using social media and celebrity endorsers for consumer engagement. This study has been conducted to understand the role and influence of celebrity endorsers through social media on the purchase behavior of Saudi consumers based on the advancing role of sustainability in the luxury industry. In this regard, a cross-sectional study design was employed and data was collected from 50 Saudi consumers using an online survey. A close-ended questionnaire was distributed to Saudi consumers based on celebrity credibility, familiarity, attitude towards celebrity endorsement, brand awareness, brand attitude, and purchase intentions. Factor analysis and path analysis were done using SPSS and AMOS version 25.0 to analyze the data collected. The findings show a positive and significant impact of celebrity credibility, familiarity, attitude, brand awareness, and brand attitude on the purchase intentions of Saudi consumers.
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How this classification was reachedexpand
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 | 0.007 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".