Return Visits: A Review of how Web Site Design Can Engender Visitor Loyalty
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Both the use of Web sites and the empirical knowledge as to what constitutes effective Web site design has grown exponentially in recent years. The aim of the current article is to outline the history and key elements of Web site design in an e-commerce context - primarily in the period 2002-2012. It was in 2002 that a Special Issue of ISR was focused on ‘Measuring e-Commerce in Net-Enabled Organizations.’ Before this, work was conducted on Web site design, but much of it was anecdotal. Systematic, empirical research and modeling of Web site design to dependent variables like trust, satisfaction, and loyalty until then had not receive substantial focus - at least in the information systems domain. In addition to an overview of empirical findings, this article has a practical focus on what designers must know about Web site elements if they are to provide compelling user experiences, taking into account the site's likely users. To this end, the article elaborates components of effective Web site design, user characteristics, and the online context that impact Web usage and acceptance, and design issues as they are relevant to diverse users including those in global markets. Web site elements that result in positive business impact are articulated. This retrospective on Web site design concludes with an overview of future research directions and current developments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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 it