Environmental Management Accounting Adoption Barriers Among Malaysian Hotel Companies
Bibliographic record
Abstract
Environmental management has become a main concern to the hotel industry with regards to waste reduction, energy savings and water conservation. The hotel industry is frequently accompanied by many adverse environmental impacts as hotel companies extensively consume large amounts of energy, water and non-durable products. Environmental Management Accounting (EMA) is tools that can be used to assist these companies to trace, collect, and analyse physical and monetary environmental information for decision-making purpose and consequently, improves financial and environmental performances. However, there are barriers to EMA adoption. This study aims to examine level of EMA adoption among the hotel companies and the barriers influencing EMA adoption. This study utilises the quantitative research design; using questionnaire survey. A total of 212 usable questionnaires were collected from the hotel companies in Selangor and Kuala Lumpur. Multiple regression analysis was conducted for hypotheses testing. The results of this study show that EMA has yet to be extensively adopted among the hotel companies in Malaysia. The result also shows that the adoption level of both Physical EMA (PEMA) and Monetary EMA (MEMA) are still low. The result further indicates that the low adoption of EMA is caused by the lack of institutional pressures. Specifically, this study shows that financial barrier, informational barrier and institutional barrier significantly influence EMA adoption among the hotel companies in Malaysia. This study is significant to the hotel managers, government authorities and environmental regulatory agencies in understanding the level of EMA adoption in the Malaysian hotel industry. In addition, this study provides valuable contributions to the existing literature by providing useful insights on the barriers influencing EMA adoption in the hotel industry in developing countries.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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 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".