Demystifying the dynamic link between project value and design team networks: A socio-technical lean management framework
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
Construction projects are complex networks of people with various backgrounds, perceptions, objectives, and dynamically changing project value expectations. Attaining common project objectives that satisfy all stakeholders’ value propositions requires collaboration whether formally or informally. Although the need for collaborative approaches on projects seems like an intuitive thought, the actual foundations and drivers needed to achieve effective implementation of a collaborative and value-based environment are usually plagued with hurdles. Moreover, previous research work and common industry practices remain mostly focused on the ‘product’ or technical end of the project while marginalizing the human-centric processes that can make or break the project. This research aims to help project managers attain higher value on projects through analyzing and managing the social context of project teams. Specifically, this research investigates the links between design team communications and project value performance as well as analyzing the evolving dynamics of value and network structures. Data analytics was used to reveal a potential correlation between the communication structures of project teams and value fulfilment on projects. Findings revealed that the inherent social dynamics and social network composition can reflect the team’s reported level of fulfilling value on projects. Such structures affect a team's ability to effectively exchange knowledge and coordinate design tasks. The research's contribution lies in introducing a sociotechnical approach for delivering value on projects through developing value-based social networks that help improve design communications and presenting a reproducible framework that enables teams to advance and align value propositions among different stakeholders.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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