Supply risk management: A case study of halal food industry in Malaysia
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
The purpose of this study is to identify the types of halal food supply risks, types of mitigation strategies for the upstream supply chain and to examine the relationship between halal supply risk and mitigation strategy efforts using the lens of the agency theory. Exploratory factor analysis (EFA) is used to validate the variables of the study and regression is performed to analyze the relationship of halal food supply risk and mitigation strategy. It is identified that halal food supply risk (agency uncertainties) consists of quality risk, delivery risk, and price/cost risk. The mitigation strategy efforts consist of behavior-based management, buffer-based management, and traceability-based management. Results indicate that halal food supply risk significantly increase mitigation strategy efforts of firms. However, price & cost risk does not significantly increase behavior-based management. Practical implications include suggesting the firms to invest more in buffer-oriented so as to mitigate the agency uncertainties.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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