Attribute Perceptions, Customer Satisfaction and Intention to Recommend E-Services
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
Academic research has focused on the quality perceptions that drive customer satisfaction as the key to achieving e-service success. This paper develops a process-based model that relates perceptions of managerially actionable site characteristics to online satisfaction, which mediates the effects of site characteristics on intention to recommend e-services. A unique data set provided by Web Mystery Shoppers International Inc. ( webmysteryshoppers.com ), a market research supplier, enables the model to be refined using data from samples of responses to each of the competitive websites for one financial service, and then to be tested using similar data for another financial e-service and then for a travel e-service. The model, which accounts for most of the variance in online satisfaction and online intention to recommend in the fitted data, is largely confirmed on cross validation. Process evaluations and satisfaction mediate the effects of actionable website characteristics on intention to recommend e-services.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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