The Relative Importance of Indicators of Perceived Jordanian Islamic Garments Quality: An Application of Non-Jordanian Consumers in Foreign Markets
Bibliographic record
Abstract
This study aims at identifying the relative importance of quality measures elements of the Jordanian Islamic garments as perceived by non-Jordanian consumers in foreign markets. In addition, it examines the moderating effect of demographic characteristics and the country of citizenship on the perceived quality of Jordanian garments. The study's population consists of consumers of Islamic women garments in the UK and Canada. A structured questionnaire was sent to several Islamic women clothes retail shops, in both the UK and Canada, where Jordanian Islamic clothes are being displayed. Depending on this study type and hypotheses, frequency table, percentages, t-Test, and ANOVA test, were used for hypotheses testing. The reliability and validity of the scales were found to be satisfactory. The study found that the four most important quality indicators as perceived by Non-Jordanian consumers of the Islamic women' garments are: The product attributes (design, appearance, sizing and textile factor), price (value), store attributes, and promotion . It was also found that all of the study’s quality indicators of Jordanian Islamic garments were positively perceived by Non- Jordanian consumers in foreign markets. Furthermore, the perceived quality indicators were found to differe in terms of the demographic variables (age, education level, income level, and marital status) .
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".