The effect of e-commerce service quality on customer satisfaction, trust and loyalty
Bibliographic record
Abstract
This study aims to explain the effect of service quality on satisfaction, service quality on trust, service quality on loyalty, satisfaction on loyalty and trust on loyalty. The population in this study are all consumers who have made transactions at an Indonesian marketplace, Shopee.co.id. The number of respondents used as a sample is 300 respondents. The results showed a significant influence between variables in the four interaction effects, namely service quality on satisfaction, service quality on trust, satisfaction with loyalty, and trust in loyalty. Meanwhile the insignificant effect was service quality on loyalty, the results of the total effect calculation also showed that Trust is a mediating variable between service quality and loyalty. marketing stimuli that can be carried out include maintaining cash on delivery services to increase customer trust, optimizing customer satisfaction through service improvement, providing more organized information so that consumers are easier and more comfortable in transacting, providing a 'tracking order' stage for customers, so that customers can monitor the progress of product orders. For further research, it is hoped that it can develop more variables under study and make comparisons of other e-commerce both in Indonesia and internationally.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".