Real Options Framework for Dealing with Uncertainty in Project Management: A Moroccan Infrastructure Project
Bibliographic record
Abstract
The Real Options Valuation allows for the consideration of possible options that are instinctively embedded in investment projects, in which the decision-makers have the flexibility to respond to the outcome of uncertainty. The business managers’ abilities to react to future market conditions tend to impact the value of the investment project by maintaining or improving the upside potential and limiting the downside loss. This process must be regulated by a decision analysis model, capable of capturing the particularities of each project. This paper presents detailed literature review of the real options, includes their area of applications in the literature, then proposes a framework to ease the understanding and the use of this method. Later, a case study of a Moroccan infrastructure project, that had already undergone an evaluation, is outlaid. The paper fully addresses the gaps of the previous study, provides a corrected model for an improved valuation of this project and a suitable use of real options. It also illustrates its application and analyzes the obtained results.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".