Monte Carlo Simulation for Project Risk Prioritisation
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-57996-7_78
Reference15 articles.
1. Acebes, F., De Antón, J., Villafáñez, F., Poza, D.: A matlab-based educational tool for quantitative risk analysis. In: Márquez, F.P.G., Ramírez, I.S., Sánchez, P.J.B., Muñoz, A., del Río, (eds.) IoT and Data Science in Engineering Management: Proceedings of the 16th International Conference on Industrial Engineering and Industrial Management and XXVI Congreso de Ingeniería de Organización, pp. 42–46. Springer International Publishing, Cham (2023). https://doi.org/10.1007/978-3-031-27915-7_8
2. Axelos: Managing Successful Projects with PRINCE2®. 6th Editio. Edited by AXELOS Limited. TSO (The Stationery Office) (2017)
3. Ball, D.J., Watt, J.: Further thoughts on the utility of risk matrices. Risk Anal. 33(11), 2068–2078 (2013). https://doi.org/10.1111/risa.12057
4. Cox, L.A.: What’s wrong with risk matrices? Risk Anal. 28(2), 497–512 (2008). https://doi.org/10.1111/j.1539-6924.2008.01030.x
5. Cox, L.A., Babayev, D., Huber, W.: Some limitations of qualitative risk rating systems. Risk Anal. 25(3), 651–662 (2005). https://doi.org/10.1111/j.1539-6924.2005.00615.x
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