The AGP Model for Risk Management in Agile I.T. Projects
Bibliographic record
Abstract
The vast majority of articles on risk in agile-managed projects fail to adequately address the interplay between the agile methodology, the risk management process, and the elements that ultimately determine the success or failure of the project. Too frequently, processes and models are given undue priority over the human element. The aim of this article is to create a risk management model for agile I.T. projects (AGP model). The study sample consists of 1868 valid survey responses from European and Asian countries received between February 2022 and January 2023. We subjected the data to Exploratory Factor Analysis (EFA) and Cronbach’s alpha to identify four key factors for dealing with risks in I.T. projects and create the AGP model. The proposed AGP model outlines up to 76% variability in the potential risks that could arise during an I.T. project’s deployment. The findings of this study are critical for project managers, I.T. professionals, developers, and system architects involved in I.T. projects. Other stakeholders may be interested in understanding the risks associated with the project and developing strategies to mitigate these risks.
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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 | 0.002 | 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 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".