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Measuring the performance of project risk management: a preliminary model

Author

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  • Serpell Alfredo Federico

    (Facultad de Ingeniería, Universidad del Desarrollo, Santiago, Chile)

  • Ferrada Ximena

    (Facultad de Ingeniería, Universidad del Desarrollo)

  • Rubio Larissa

    (Depto. Ingeniería y Gestión de la Construcción, Pontificia Universidad Católica de Chile)

Abstract

The function of project risk management (PRM) is to understand the uncertainty that surrounds a project and to identify the potential threats than can affect it as well as to know how to handle these risks in an appropriate way. Then, the measurement of the performance of PRM becomes an important concern, an issue that has not yet been addressed in the research literature. It is necessary to know how successful the application of the PRM process is and how capable is the process within the organization. Regarding construction projects, it is essential to know whether the selected responses to mitigate or eliminate identified risks were suitable and well implemented after the execution of the project. This paper presents a critical analysis of the relevance of measuring the performance of PRM and the benefits of doing so. Additionally, it presents a preliminary and pioneering methodology to measure the performance of PRM through the evaluation of the adequacy of responses applied to mitigate risks as well as to evaluate the resulting impacts as indicators of the effectiveness of these actions at the end of the project. This knowledge will allow construction companies to incorporate good practices, generate lessons learned, and thereby to promote a continuous improvement of the whole PRM process.

Suggested Citation

  • Serpell Alfredo Federico & Ferrada Ximena & Rubio Larissa, 2019. "Measuring the performance of project risk management: a preliminary model," Organization, Technology and Management in Construction, Sciendo, vol. 11(1), pages 1984-1991, January.
  • Handle: RePEc:vrs:otamic:v:11:y:2019:i:1:p:1984-1991:n:10
    DOI: 10.2478/otmcj-2019-0005
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    References listed on IDEAS

    as
    1. Nerija Banaitiene & Audrius Banaitis, 2012. "Risk Management in Construction Projects," Chapters, in: Nerija Banaitiene (ed.), Risk Management - Current Issues and Challenges, IntechOpen.
    2. Richard M. Van Slyke, 1963. "Letter to the Editor---Monte Carlo Methods and the PERT Problem," Operations Research, INFORMS, vol. 11(5), pages 839-860, October.
    3. Aven, Terje, 2010. "On how to define, understand and describe risk," Reliability Engineering and System Safety, Elsevier, vol. 95(6), pages 623-631.
    4. Aven, Terje, 2016. "Risk assessment and risk management: Review of recent advances on their foundation," European Journal of Operational Research, Elsevier, vol. 253(1), pages 1-13.
    5. D. G. Malcolm & J. H. Roseboom & C. E. Clark & W. Fazar, 1959. "Application of a Technique for Research and Development Program Evaluation," Operations Research, INFORMS, vol. 7(5), pages 646-669, October.
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