Tailoring new websites to appeal to those most likely to shop online
Bibliographic record
Abstract
This study extends the conventional wisdom concerning how a commercial website can be configured to attract online shoppers, and specifically, initial shoppers. Based on past research [Inform. Syst. Res. 13 (2002) 187] and theory [Diffusion of Innovations (1995)], a number of ‘form ’ and ‘substantive ’ website features were assessed as to their attractiveness to consumers of varying (a) Internet experience and (b) innovativeness. A self-administered survey was completed by a convenience sample of 363 residents of the US and Canada. A discriminant analysis confirms that two functions, generally representing form and substantive features, each discriminate between (a) high and low innovativeness (DF1) and (b) high and low Internet experience (DF2). Further, those with more Internet experience show a stronger preference for substantive features than do those with less experience. But high and low experience groups do not differ noticeably with regard to preference for form features. It was also found that, conversely, the more innovative shoppers reveal a stronger preference for form features. But high and low innovativeness groups do not differ appreciably in respect to desire for substantive features. This suggests the dynamics underlying the attraction of initial Internet users to particular shopping sites. Both theoretical and practical implications of the findings are discussed.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".