Assessment of Awareness and Adoption Levels of Environmental Sustainability Practices (ESP) in Large-Sized Hotels (LSH) in Lagos, Nigeria
Bibliographic record
Abstract
The hotel sub-sector is fast implementing ESP to preserve the natural environment and meet the needs of green-conscious guests.In a developing country like Nigeria, hotel operators' knowledge of awareness and adoption of green practices is unknown.This study investigated the awareness level and adoption extent of ESP for energy reduction (ER), water conservation (WC) and waste minimisation (WM) using data from 130 managers in 20 LSH in Lagos, Nigeria.The data were subjected to descriptive analysis and the results revealed that participants were aware of and adopted ER, WM and WC practices in hotel buildings.However, the practices with the highest awareness and adoption levels are occupancy sensors, energy-saving bulbs, sorting of wastes and low-flush toilets.The least adopted practices were wind turbines, covering swimming pools and waste composting.Therefore, hotel managers' knowledge of green practices should be improved with a growing emphasis on ER practices in hotels.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".