Barriers to Green Implementation in Highway Construction in Cambodia: Identification of Root Causes
Bibliographic record
Abstract
Recently, infrastructure systems in developing countries have been substantially reformed, resulting in increased pollution to the environment from heavy equipment usage and construction operations that generate high emissions. Consequently, a green concept is necessary to address this issue. However, contractors and project owners involved in highway construction in Cambodia still encounter many barriers to the adoption of green concepts. This paper determined the differences between the perspectives of contractors and project owners on green concept adoption for Cambodian highway construction and sought to identify the root causes of high-impact barriers. A questionnaire was developed identifying 27 barriers covering 6 categories. Statistical analyses were undertaken of the data from 82 respondents who were professional contractors or project owners with experience in highway construction projects in Cambodia. The findings showed that the Training and knowledge and the Green material resource categories were high-impact for the project owners, while contractors identified Green material resource and Government management as high-impact categories. Identification of the root causes from the high-impact categories was developed using causeand-effect diagrams to assist policymakers to comprehend the main root causes of barriers to the green concept. Competent solutions were suggested to assist the Cambodian community move toward greater sustainability.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 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".