Halal food supply chains: A literature review of sustainable measures and future research directions
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
Introduction. Although sustainability represents a high-profile topic in supply chain management, it remains an unexplored research area for Halal food supply chains (HFSCs). Hence, to bridge this knowledge gap, we conducted a systematic literature review to identify the measures necessary for the development of sustainable HFSCs and potential research gaps at the nexus of sustainability and Halal food literature. Study objects and methods. We carefully analyzed forty (40) papers selected from leading, highly-ranked journals to answer the following research question: “What are the measures necessary for the development of sustainable Halal food supply chains?” Results and discussion. The findings revealed that the improvement of Halal processes through the implementation of quality management systems, the effectiveness of Halal labeling, and the use of technology could enhance the economic performance of HFSCs. Furthermore, HFSC’s sustainability efforts are strengthened by enhancing trust and transparency benefitting human resource skills development, promoting animal welfare issues, and increasing regulatory compliance. The implementation of environmental protection measures is a primary driving factor for environmental sustainability activities. Environmental sustainability could be fostered by a shift to the application of greening practices and the support of environmentalism in the Halal food industry. Conclusion. The findings of this study provide critical managerial implications for Halal food practitioners as they can have a summary of the previous studies and thus use it as a benchmark for introducing sustainable measures in their Halal food firms.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it