The influence of a collaborative procurement approach using integrated design in construction on project team performance
Bibliographic record
Abstract
Purpose The purpose of the paper is to study the influence of procurement on the performance of integrated design teams. Design/methodology/approach The research paradigm is based on Russian socio‐constructivist approach to activity theory. Activity theory, as opposed to natural or social science, is a design science approach that focuses on the context aspect of project. A triangulation of qualitative research methods is used to investigate the dynamic of integrated teams in two different procurement contexts. Findings The paper is conclusive regarding the influence of procurement on team efficiency. It demonstrates that traditional procurement processes reinforce socio‐cognitive barriers that hinder team efficiency. It also illustrates how new procurement modes can transform the dynamic of relationships between the client and the members of the supply chain, and have a positive impact on team performance. Practical implications The paper demonstrates first that problems with integrated design team efficiency are related to context and not process – they are not technical but socio‐cognitive; second that fragmented transactional contracting increases socio‐cognitive barriers that hinder integrated design team performance; third that new forms of relational contracting may help to mitigate socio‐cognitive barriers and improve integrated design team performance, fourth that changing the context through procurement does not address the problem of obsolete design practices. Originality/value The paper brings together theories of production in lean construction and social learning as a rival approach to traditional project management theory for demonstrating the importance of context on team performance.
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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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".