The Interplay of Aesthetics, Usability and Credibility in Mobile Websites and the Moderation by Culture
Bibliographic record
Abstract
The relationships between aesthetics, usability and credibility have been widely investigated in human-computer interaction (HCI). However, in the mobile domain, limited empirical evidence exists showing the interplay among these three constructs and the role culture plays. To address this, we carried out a survey on four systematically designed mobile websites among 233 subjects from Canada and Nigeria, which belong to low- and high-context cultures respectively. Using path modeling, we investigated the relationships among the perceptions of these three HCI constructs and the possible differences that exist between the two cultures. Our results show: 1) it is the perception of aesthetics that predominantly drives the judgment of mobile web credibility at the global and subgroup levels, with the effect size being greater for the Canadian group than for the Nigerian group; 2) the direct effect of aesthetics on usability is moderated by culture, with the magnitude being stronger for the Nigerian group than for the Canadian group; and 3) our models explain 29-83% of the variance of credibility.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".