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An integrated approach for risk response development in project planning

Author

Listed:
  • I Ben-David

    (Tel Aviv University)

  • T Raz

    (Tel Aviv University)

Abstract

The risk response development phase is a major phase in the project risk management process. We present a model that integrates project work contents, risk events, and risk reduction actions and their effects into a comprehensive framework. The model allows the representation of the overlapping effects of multiple risk reduction actions and of the impacts of secondary risk events, and supports the evaluation of the total risk exposure of the project under various combinations of risk reduction actions. The model can be treated with optimisation techniques in order to generate the most cost-effective combination of risk reduction actions. In this work we describe the model, outline a solution procedure and illustrate its application with an example taken from the software industry.

Suggested Citation

  • I Ben-David & T Raz, 2001. "An integrated approach for risk response development in project planning," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(1), pages 14-25, January.
    • Handle: RePEc:pal:jorsoc:v:52:y:2001:i:1:d:10.1057_palgrave.jors.2601029
    DOI: 10.1057/palgrave.jors.2601029
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    Citations

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    Cited by:

    1. Zhang, Yao & Zuo, Fei & Guan, Xin, 2020. "Integrating case-based analysis and fuzzy optimization for selecting project risk response actions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    2. Seyed Mohammad Seyedhoseini & Siamak Noori & Mohammad Ali Hatefi, 2009. "An Integrated Methodology for Assessment and Selection of the Project Risk Response Actions," Risk Analysis, John Wiley & Sons, vol. 29(5), pages 752-763, May.
    3. Dengsheng Wu & Xiaoqian Zhu & Jie Wan & Chunbing Bao & Jianping Li, 2019. "A Multiobjective Optimization Approach for Selecting Risk Response Strategies of Software Project: From the Perspective of Risk Correlations," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 339-364, January.
    4. Mahsa Parsaei Motamed & Shahrooz Bamdad, 2022. "A multi-objective optimization approach for selecting risk response actions: considering environmental and secondary risks," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 266-303, March.
    5. Zuo, Fei & Zio, Enrico & Xu, Yue, 2023. "Bi-objective optimization of the scheduling of risk-related resources for risk response," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    6. Ji-Myong Kim & Junseo Bae & Seunghyun Son & Kiyoung Son & Sang-Guk Yum, 2021. "Development of Model to Predict Natural Disaster-Induced Financial Losses for Construction Projects Using Deep Learning Techniques," Sustainability, MDPI, vol. 13(9), pages 1-12, May.
    7. Creemers, Stefan & De Reyck, Bert & Leus, Roel, 2015. "Project planning with alternative technologies in uncertain environments," European Journal of Operational Research, Elsevier, vol. 242(2), pages 465-476.
    8. Ji-Myong Kim & Taehui Kim & Kiyoung Son & Sang-Guk Yum & Sungjin Ahn, 2019. "Measuring Vulnerability of Typhoon in Residential Facilities: Focusing on Typhoon Maemi in South Korea," Sustainability, MDPI, vol. 11(10), pages 1-11, May.
    9. Kosztyán, Zsolt T. & Pribojszki-Németh, Anikó & Szalkai, István, 2019. "Hybrid multimode resource-constrained maintenance project scheduling problem," Operations Research Perspectives, Elsevier, vol. 6(C).
    10. Ji-Myong Kim & Taehui Kim & Sungjin Ahn, 2020. "Loss Assessment for Sustainable Industrial Infrastructure: Focusing on Bridge Construction and Financial Losses," Sustainability, MDPI, vol. 12(13), pages 1-16, July.
    11. Alan J. Card & James R. Ward & P. John Clarkson, 2014. "Trust‐Level Risk Evaluation and Risk Control Guidance in the NHS East of England," Risk Analysis, John Wiley & Sons, vol. 34(8), pages 1469-1481, August.

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