Clarifying Project Management in the Crisis Situations: Concentrating on Covid-19 Pandemic
Bibliographic record
Abstract
The COVID-19 pandemic has had a major impact on business and project activities, particularly due to the lack of information about it. The experience of the pandemic indicated that due to the unknown nature of it and lack of suitable models, there was no clear strategy for managing projects in the crisis condition. Thus, the main objective of this paper is to develop a project management model for crisis situations and identify effective strategies to reduce project vulnerability during the pandemic period. For this purpose, a systematic review method was used. Based on this method, first the relevant articles were searched, then the relationships between their key concepts were plotted using VOSviewer, and finally 78 sources were selected in several steps. The results are presented in the form of answering research questions as well as developing a conceptual model that includes project management strategies in pre-crisis, crisis time and post-crisis situations. Accordingly, it can be said that Covid-19 pandemic has all characteristics of a serious crisis. Its origin is often external, and it usually happens all at once, so it reduces the opportunity for planning. Finally, it can last and continue. In addition, the model identifies key policy makers, participants, and project implementers in times of pandemic crisis. It is expected that the use of this model and strategies increase the PM’s knowledge and capabilities in crisis management in projects.
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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 | 0.016 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".