Bibliographic record
Abstract
Several measurement scales have been designed by both practitioners and researchers to evaluate perceptions of electronic service Quality. This chapter tests three of the main academically developed scales: Sitequal (Yoo & Donthu, 2001), Webqual 4 (Barnes & Vidgen, 2003) and EtailQ (Wolfinbarger & Gilly, 2003) and compares them against the scale ensuing from our research: NetQual (Bressolles, 2006). Based on 204 evaluations of consumers that participated in a laboratory experiment involving two Canadian Websites in travel and online insurance, NetQual best fits the data and offers the highest explanatory power. Then the impact of nature of task and success or failure to complete the task on the evaluation process of electronic service quality and attitude toward the site is examined and discussed on over 700 respondents that navigated on six different Websites.
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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 | 0.015 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".