Emerging Project Procurement Trends in the Canadian Construction Industry
Bibliographic record
Abstract
Construction procurement is recognized as a complex business process. Traditional procurement methodologies have received wide criticism although it remains popular with owners/clients, regardless of the published disadvantages and criticisms. This study assesses the future of traditional procurement and also evaluates the current popularity of traditional procurement against alternative approaches to construction procurement. To achieve research objectives, a questionnaire survey was conducted within British Columbia, Canada, to gauge the perspective of construction industry stakeholders. Respondents were asked to gauge 50 statements on a five-point Likert scale. A Web-based survey service was employed to ensure anonymity while providing a single point of contact for gathering results. As a majority of the interviewees were positioned professionally at management level or higher, a certain level of accuracy in the data collected was assured. Research findings revealed that the traditional procurement methods do not meet the need of the Canadian construction industry. Traditional procurement alone cannot support the unique needs of each and every project in Canada, thus the Canadian construction industry. The paper identifies alternative methods that offer similar value while maintaining competitive practices that permit contractors to compete equitably for work. Recommendations for further research include conducting case studies into traditional, partnering, and management specimens of procurement methods. Additionally, national level surveys of industry stakeholders would further benefit this research, thus providing an indication of the procurement status quo, as well as a better understanding of what the future may hold. The study is valuable for all the professionals involved with the construction industry in general.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".