Whether our Virtual Commercial Environments are Polite Enough or not? An Instrument for Gauging the Degree of Politeness in e-Tailers
Bibliographic record
Abstract
Politeness issues in virtual commercial contexts received rare attention from both practitioners and researchers. This work developed an instrument for gauging degree of politeness in online retailers’ storefronts. The instrument’s reliability and validity were confirmed through empirical data analysis. A second-order confirmatory factor analysis revealed that online consumers' tendency in paying relative more attention to their rights being respected and gaining useful information while they are assessing online retailers’ politeness. Using the instrument, online merchants and 3rd-parties can measure the degree of politeness in online retailers. In addition, patrons’ tendency in paying more attention to particular factors while they were evaluating the politeness guides online merchants to allocate limited resources more efficiently. Besides its practical applications, this work sets a stage for future studies trying to investigate the relationships between the politeness construct and other constructs such as customer satisfaction, trust, repurchase intention, profitability, and others that interest business administrators.
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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 | 0.003 | 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 | 0.000 |
| 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".