Building a relational contracting culture and integrated teams
Bibliographic record
Abstract
Targeting integration in construction, this study compares the suitability of various factors and strategies to provide suitable contractual and noncontractual incentives for building a relational contracting (RC) culture and fostering effective teamwork. Results from statistical analyses of 96 questionnaire responses from Singapore contractors, consultants, and clients are presented. Despite obvious differences in perceptions among different groups of respondents on the relative usefulness of individual factors, it was observed that trust should broadly be at the core of RC and team-building. Although some factors appear to be more important than others, the overall results indicate that Singaporean industry participants prefer to target integration in construction through (i) trust-based contractual and operational arrangements and (ii) extended use of relational qualities in team selection for postcontract partnering-type RC arrangements between clients and contractors. The results also suggest the need for an interrelated and consolidated approach, both for propagating RC and for building integrated project teams. Like many other countries, the results indicate the readiness of Singaporean industry participants to incorporate RC and team-building techniques in a move towards improved performance and value for money. The results may be applicable to other countries or contracting regimes, especially where the practice of RC is at an early stage. Outcomes of this study are expected to benefit both industry practitioners and researchers in exploring, designing, and implementing suitable contractual and noncontractual incentives.Key words: construction, culture, integration, relational contracting, Singapore, team-building.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".