Current Practices of Sustainable Procurement in the Sri Lankan Construction Industry
Bibliographic record
Abstract
Construction project procurement is a fundamental process in construction project management. The current conventional procurement practices have been widely criticised due to associated issues including disregarding sustainability. Even if, Sustainable Procurement (SP) has been emerged as one of the best solutions for such issues, current practice level of SP in Sri Lanka (SL) is unclear. Therefore, the aim of this study is to review SP practices in Sri Lankan construction industry. Concurrent triangulation mixed method was used in this study by combining both qualitative and quantitative research approaches. Data was collected through questionnaire surveys and semi-structured interviews and analysed using statistical analysis and content analysis respectively. Data triangulation was used to combine the results of all three research tools. The study proved that SP principles have been used in Sri Lankan construction industry at a moderate level. Limited sustainability initiatives were used in the project procurement, while economical sustainability criteria were given the prominence. Furthermore, SL is at a lower level of practicing SP when compared with most of developed countries like United Kingdom (UK) and Canada. Non-availability of policies, procedures and legislations in regional or national levels is the main factor that limit the SP practices. Further, the study identified drivers which influence the practice level of SP in SL.Thus, the study recommended that strengthening drivers and mitigating constrains are the appropriate strategies to increase the level of practice of SP in Sri Lankan construction industry.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".