The Impact of Digitalization on Processes and Organizational Structures of Architecture and Engineering Firms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The digitalization of the architecture, engineering, and construction (AEC) industry leads to new forms of process through which buildings are designed, constructed, and operated, and to new forms of organization through which professionals work and interact. Certain activities of the conventional building process disappear, while others appear, distribution of work is reviewed, and new relationships, roles, and responsibilities emerge. Although many architecture and engineering (A/E) firms claim that they have already undertaken a digital transformation, there is still little awareness of the new forms of process and organization associated with digitalization. This lack of knowledge about the process-oriented and organizational changes makes it difficult to establish a work environment within and between firms that is conducive to digital innovation. Given the above considerations, the main objective of this research project has been to understand the process-oriented and organizational changes that the adoption of digital technologies bring on, as well as the new forms of process and organization associated with the digital transformation of architectural and engineering firms. To achieve this, a case-study analysis of two A/E firms—one in Italy and one in Canada—has been performed.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it