The effects of online shopping on the customer loyalty
Bibliographic record
Abstract
This paper investigates the use of Online Shopping as one of electronic marketing techniques as well as the effect of applying this shopping method and marketing on customer loyalty in Iran. The variables are extracted according to the review of literature and studies conducted in the field of shopping through cyberspace. A questionnaire is designed by applying these variables and distributed among a sample of service providers and users after testing its reliability and validity. Performing the statistical tests on the results of investigation led to the identification of effective factors. In addition, another questionnaire is distributed according to the obtained components in order to achieve a structural model for the impact of components on the customer loyalty. The structural equation modeling (SEM) is designed to learn the impact of obtained components on customer loyalty as a basis influencing on the survival of business space using SEM method. The study identified different components affected by utilization of online shopping websites including comprehensive information system, system development, choice power, viability and system optimization.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".