Social media marketing activities, perceived innovativeness, and perceived enjoyment: Predicting the con-sumers’ intention to purchase Muslim apparel through TikTok live
Bibliographic record
Abstract
This study examines the factors influencing Muslim consumers' purchase intentions for Muslim apparel products through TikTok live streaming. Data were collected in Jakarta, with 225 participants selected using convenient sampling. The collected data underwent analysis using exploratory factor analysis, confirmatory factor analysis, and structural equation modelling. The results revealed several key findings. Firstly, the hypothesis that TikTok marketing activities significantly influence perceived innovativeness was supported. Additionally, it was found that TikTok marketing activities significantly affect perceived enjoyment. However, the hypothesis that perceived innovativeness significantly impacts purchase intention was rejected. Furthermore, it was established that perceived innovativeness significantly influences perceived enjoyment, and perceived enjoyment significantly affects purchase intention. These findings contribute to expanding knowledge in social commerce, particularly in understanding the dynamics of consumer behavior within the context of Muslim apparel products marketed through TikTok live streaming. The acceptance of hypotheses regarding the influence of TikTok marketing activities on perceived innovativeness and enjoyment underscores the importance of social media marketing strategies in shaping consumer perceptions and experiences. However, rejecting the hypothesis concerning the direct impact of perceived innovativeness on purchase intention suggests that other factors may mediate this relationship, warranting further investigation.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".