Comparative analysis on beverage store owners towards sustainable packaging using multicriteria decision techniques
Bibliographic record
Abstract
Abstract In recent years, the food and beverage industry has been experiencing rapid growth. The consumption of plastic or Styrofoam cups also grew with the observed market growth. In Canada, an approximate CAD $147.12 million worth of plastic cups and lids are produced yearly but only 9% end up being recycled. Therefore, there is a growing need for a more sustainable beverage packaging. To analyze if such decisions are warranted in small to medium sized café in the Philippines, the multi-criteria decision-making (MCDM) methods such as ELECTRE III and TOPSIS will be used in this research. With the data of both storeowner and supplier perspective, it was found that quality has the most affect at 36.3% followed by the availability of sizes at 32.6%. As it turns out, the result of this study favored the more plastic-oriented traditional cups and lids. Even though the initial hypothesis favored the more sustainable packaging, the analysis and methodology were still successfully carried out. Thus, prompting the importance of future research regarding the pursuit of sustainable packaging.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".