Investigating the impact of building information modeling on collaboration in the architecture, engineering, construction and operations industry
Bibliographic record
Abstract
The research work presented in this thesis investigates collaboration in the Architecture, Engineering, Construction and Operations (AECO) industry. More precisely, it investigates the characteristics of collaboration, their dynamics in the context of temporary and permanent organizations as well as the impact that the transition to innovative project delivery approaches, namely Building Information Modeling (BIM), is having on this collaboration. The research was practically motivated through our industrial partners’ desire to better understand the impact of BIM and other innovative project delivery approaches on project outcomes. The research was theoretically motivated by the lack of a clear definition of collaboration in the AECO industry and its seemingly amorphous nature. This scarcity of systematic and structured approaches to investigate collaboration and its outcomes in the literature confirmed this. \n \nThe research was therefore both exploratory and prescriptive in nature. Its principal aim was to develop an artifact that allows consistent development, management and assessment of innovation enabled collaboration. As such, the research project was conducted using a design science research design. The research process continuously iterated between the development and building of the artifact and its local evaluation in context. In parallel, the artifact was concurrently evaluated to ensure its relevance and maintain the rigor of its development. A critical realist perspective was adopted to frame the epistemic and ontological foundation of knowledge being developed and also contradistinguish the predominantly pragmatic perspective traditionally adopted in design science research. The development and building of the artifact followed a systematic combining methodology. Showing similarities with grounded theory, this particular methodology accepts the a priori framing of knowledge to inform the investigation. It recognizes also that the knowledge held within this frame will evolve as the project progresses and as new insight is gained into the phenomena Under investigation. Mixed-methods of data collection were conducted on two main research sites to inform and support the research project. The first site was that of a large institutional designbuild project located in Edmonton, Alberta. Data collection on this site started in February 2013 and is still being carried out. The data collected on this site allowed an in-depth investigation of collaboration within a temporary project organization having fully implemented BIM. The second site was that of a specialty mechanical contracting small enterprise located in Vancouver, British Columbia. Data collection on this site started in April 2012 and ended in April 2015. The data collected on this site allowed a breadth of investigation into collaboration from an organizational perspective. Data was collected on four other sites to support relevance checks of the artifact being developed. \n \nThe findings of the work are presented through the artifact, namely the constructs developed to characterize collaboration, a multi-layered model representing the relationships between the constructs and the method of operationalization of this model. The artifact serves to inform, manage and assess BIM-based collaboration in the context of this particular research work, though it could be extended to include other innovative project delivery approaches as future work. The artifact also evokes a substantive theory of collaboration in the AECO industry in the form of alignments amongst constructs developed in the model. Lastly, the artifact is operationalized to investigate the impact of BIM on collaboration in the AECO industry. The evolution of the different constructs and indicators, both measured and perceived, the alignments and misalignments uncovered as well as the outcomes of collaboration are evaluated through the artifact. Furthermore, the evolution of the constructs and the alignments uncovered through the artifact can serve as an indicator of performance within collaborative environments. Thus, the artifact developed in this research project solves the problem that was set out by the industrial partners. It also addresses the gap that was uncovered in the literature with respects to collaboration through innovation. Further work is required to fully evaluate the artifact, however, it is believed that the groundwork to move towards a more systematic and structured investigation into collaboration in the AECO industry has been laid.
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 | 0.020 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".