Skip to main content

Abstract

Qualitative project risk assessment is standard practice in project management and involves prioritising risks using a probability and impact matrix. Due to the shortcomings of using this tool for risk prioritisation (poor resolution, errors, suboptimal resource allocation or ambiguous inputs and outputs, among others), we propose a quantitative prioritisation of project risks in this article, analysing the impact of each risk on the project’s duration and cost objectives.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

Download references

Acknowledgements

This research has been partially financed by Junta de Castilla y León (Spain) and the European Regional Development Fund (ERDF, FEDER) with grant VA180P20.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fernando Acebes .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Acebes, F., Curto, D., González-Varona, J.M., Pajares, J. (2024). Monte Carlo Simulation for Project Risk Prioritisation. In: Bautista-Valhondo, J., Mateo-Doll, M., Lusa, A., Pastor-Moreno, R. (eds) Proceedings of the 17th International Conference on Industrial Engineering and Industrial Management (ICIEIM) – XXVII Congreso de Ingeniería de Organización (CIO2023). CIO 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 206. Springer, Cham. https://doi.org/10.1007/978-3-031-57996-7_78

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-57996-7_78

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-57995-0

  • Online ISBN: 978-3-031-57996-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics