The Effect of E-Service Quality and E-Wom on Purchase Decisions Through the Tiktok Shop Application among College Students in Surabaya
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
The purpose of this script is to explore how E-Service Quality and Electronic Word of Mouth (E-WOM) influence purchasing decisions through the TikTok Shop app. TikTok Shop experienced a decline of 12.4% in the first quarter of 2022, demonstrating that this does not guarantee that TikTok Shop will always be at the top. Kotler & Armstrong (2016:177) found that buying decisions focus on how individuals and groups choose, acquire, and use experiences, services, ideas, and products to meet desires and needs that are part of consumer behavior. Quantitative analysis is the method used in this study. Non-probability sampling and Purposive Sampling techniques are used for sample collection. The survey used a Likert scale questionnaire with a sample of 100 respondents and the population of students in the city of Surabaya. Partial Least squares (PLS) are used to check research findings. It has been found that E-Service Quality and E-WOM have been shown to influence purchasing decisions through TikTok Shop positively.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it