Project Risk and Opportunity Management: The Owner's Perspective
Bibliographic record
Abstract
Effective risk and opportunity management is key to the successful delivery of any major engineering and construction project. This book looks at how all those involved can manage risk and capitalise on the opportunities that uncertainty present. The authors of this book highlight that uncertainties should be managed rather than avoided. This book will look at simple projects with a small team, to megaprojects where some hundreds of people are involved, and the consequences of delays or unforeseen costs. However, while the obvious risks can be planned for, the authors argue that it is often the opportunities in these situations that can have unexploited potential. This book is about opportunity management seen from the owner’s perspective. It will be an invaluable resource for those studying Engineering both undergraduate and postgraduate and set out ways in which projects should be managed from planning to completion. This book is also a great tool for those working in project management and the construction industry. While there are many books that demonstrate effective construction management, this book is the first of its kind to emphasise that there is opportunity in uncertainty, and possibility in the unexpected.
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 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 | 0.007 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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; both teacher heads agree on what is shown here.
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".