Web design and its effect on key variables associated with online consumer behavior in the retail sector
Bibliographic record
Abstract
This study examines the effect of web design on the generation of electronic word of mouth (E-WOM) through the satisfaction of e-commerce consumers in the retail sector. To this end, three main objectives were proposed: (1) Evaluate the effect of web design on the perception of security, perceived enjoyment, perceived usefulness and perceived risk of the e-commerce consumer in the retail sector; (2) Evaluate the effect of customer service, perception of security, perceived enjoyment and perceived usefulness on consumer satisfaction in e-commerce in the retail sector; and (3) Explain the positive effect of customer satisfaction and the negative effect of perceived risk on the generation of E-WOM. A study was carried out using a quantitative approach with a non-experimental and cross-sectional design. Through non-probabilistic convenience sampling, a total of 422 questionnaires from consumers in the retail sector were collected. A partial approach was used to analyze the data. Least Squares PLS-SEM by using SmartPLS. The results show the significant positive effect of web design on the perceptions of security, customer service, and customer satisfaction. And a negative effect on risk perception. Furthermore, this study revealed the mediating effects of risk perception, security perception, and quality of customer service in the retail sector. This study has theoretical, practical, social, and customer management implications, so it will be useful in academic, social, and business areas. The results show the positive and significant effect of web design on the perception of security, enjoyment, and usefulness of online shopping. The negative and significant effect of web design on risk perception was also demonstrated; furthermore, this study revealed the positive and significant effect of perceived usefulness, enjoyment, security, and electronic service on customer satisfaction in online shopping. Finally, the negative and significant effect of risk perception on the generation of electronic word of mouth and the positive and significant effect of satisfaction on the generation of electronic word of mouth were demonstrated.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".