Determinants of an Organization’s Website Ease of Use: The Moderating Role of Product Tangibility
Bibliographic record
Abstract
The ease of use of an organization’s website is central to determining users’ experiences and behavioral intentions. Understanding how the site-related factors contribute to shaping perceived ease of use is thus critical. Nonetheless, we contend that the relative importance of these factors in shaping ease of use may vary according to the product offered by the organization. This research hypothesizes that the information quality of a website and its interactivity and aesthetics are antecedents to perceived ease of use and that the relative tangibility of the offered products moderates these relationships. The hypotheses are examined by performing a large-scale study in which each participant performs a task on one of 59 organizational websites. The study’s hypotheses were supported, and the results were then replicated using a second study conducted on a French-speaking sample. Site information quality is the strongest predictor of perceived ease of use, followed by the site interactivity and aesthetics. The results, however, underscore the moderating role of product tangibility. While the effects of interactivity and aesthetics are greater for sites offering services (e.g., communication, travel, insurance, and financial services), the effect of information quality is stronger for sites offering tangible products (e.g., electronics, books, and home improvement goods). The findings suggest that organizations offering tangible products should focus on providing their sites’ visitors with quality information, whereas organizations offering services should primarily focus on their sites’ aesthetics, interactive, and personalization features.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".