From E-Shopping System Quality to the Consumer's Intention to Return: A Meta-Analytic Study of the Mediation of Attitude, Usefulness, Enjoyment, and Trust
Bibliographic record
Abstract
This research aims at clarifying the respective role of e-shopping system quality and attitude, usefulness, enjoyment, and trust to explain the consumer's intention to return to an online merchant. A meta-analytical regression based on 83 published studies is used to integrate, in one single model, concepts from two streams of information system (IS) research which are the technology acceptance model (TAM) and the IS success model. Results demonstrate that the sequence, consisting of e-shopping system quality (system quality, information quality, and customer service quality) -- behavioral beliefs and attitude -- intention to return, is theoretically and empirically founded and that customer service quality is the quality dimension that influences trust and enjoyment the most while information quality is the quality dimension that is the most influential on usefulness.
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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 | 0.004 | 0.002 |
| 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 | 0.000 |
| Open science | 0.001 | 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".