Non-Muslims’ acceptance of imported products with halal logo
Bibliographic record
Abstract
Purpose This study aims to examine whether citizens of non-Muslim countries accept products with a “halal” logo. In the era of globalization, one of the most crucial issues for Muslim travelers is reliable halal foods when visiting non-Muslim countries. If people in non-Muslim countries accept imported products containing halal certification logos, and such products are readily available in shops, this issue could be substantially improved. Design/methodology/approach Malaysia and Japan were selected as Muslim and non-Muslim countries, respectively, to conduct a choice experiment (CE) for 656 non-Muslim subjects, and estimated willingness to pay (WTP) for mineral water with and without the halal logo. A random parameter logit model was used for estimation. Findings The difference between the WTP for mineral water with and without the halal logo was ¥5; however, the associated coefficient is not statistically significant. This implies that the halal logo has no impact on non-Muslim subjects’ purchasing behavior. From this, we can infer that the halal products with certification logo would be accepted in Japanese shops, which may foster foreign Muslim visits. Research limitations/implications As the results are based on a couple of countries (Malaysia and Japan) and only one product (mineral water), further investigation using other products in different countries would be necessary. However, as suggested in the main text, the results enjoy a degree of generalizability. Originality/value The results of this study support the possibility of circulating halal products in non-Muslim countries and thus promoting Muslim travel abroad. No such study has examined this issue using CE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.007 | 0.001 |
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".