Culinary Knowledge and Sustainability: Chef-Led Food Waste Management in Serbia’s Hospitality Sector
Bibliographic record
Abstract
The challenge of food waste poses significant economic, environmental, and ethical concerns worldwide, with the hospitality sector being particularly affected. This study explores food waste prevention and management practices in five-star hotels in Serbia, focusing on the knowledge, attitudes, and resourcefulness of head chefs as key actors in implementing sustainable solutions. A qualitative exploratory design was applied, combining semi-structured interviews with eight head chefs and hotel managers, in-kitchen field observations, and food waste audits conducted in eight luxury hotels in Belgrade. The food waste hierarchy framework was used to assess how head chefs understand and act upon food waste issues. Findings reveal that while food waste policies vary across hotels, head chefs demonstrate varying levels of awareness and resourcefulness, often shaped by corporate policies, training, and personal experience. Despite limitations in policy enforcement, many head chefs apply practical strategies such as FIFO stock rotation, local sourcing, and creative reuse of ingredients. This study advances the theoretical understanding of food waste management in hospitality by linking practice theory with culinary knowledge and corporate influence. It also provides practical implications for training, policy development, and sustainable hospitality operations in transitional economies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".