Collaborative Interorganizational Relationships in a Project-Based Industry
Bibliographic record
Abstract
The project-based construction industry finds itself in a paradoxical situation: while it weighs heavily in the world economy, it does have a history of low productivity. One important issue that plagues the industry is related to the challenges that stem from collaborative efforts (or lack thereof) between actors. The objective of this paper is to explore how actors of the construction industry organize their inter-firm relationships while examining the characteristics of such interactions and the elements affecting them (drivers, barriers, facilitators, outcomes). These interactions and elements were uncovered using a systematic literature review. A qualitative content analysis was carried out to categorize these elements and to generate dimensions describing the forms. The 139 articles retrieved depicted 12 relational forms established between construction companies (in descending order of citation): partnering, alliancing, project delivery methods, supply chain integration, joint ventures, integrated project delivery, joint risk management, collaborative design, contingent collaboration, quasi-fixed network, resource sharing, and collaborative planning. A multitude of drivers, barriers, facilitators, and outcomes were found. An analysis of the results led to the conceptualization of a multidimensional profile, which allows for a practical and flexible identification of the relationship form potential partners in the construction sector intend to establish. To provide guidelines for the implementation of this profile, a three-step framework was developed.
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 | 0.019 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| 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".