IDEAS home Printed from https://ideas.repec.org/a/wly/syseng/v13y2010i4p353-368.html
   My bibliography  Save this article

Monitoring risk response actions for effective project risk management

Author

Listed:
  • Edouard Kujawski
  • Diana Angelis

Abstract

Complex projects typically involve high‐consequence, project‐specific risks that require detailed analysis and for which risk response actions (RRAs) need to be developed and implemented. The risk picture is dynamic. The sources and consequences of risks evolve and change over the project lifecycle; thus, it is necessary to constantly monitor risk. RRAs that do not keep pace with the changing project situation are a major cause of risk management failures. This paper extends traditional cost risk analysis from a purely macroscopic perspective by evaluating and tracking project‐specific risks and RRAs at the microscopic level. The key elements of the method are (i) develop risk scenarios, (ii) model them using generalized decision trees, and (iii) quantify the risks using Monte Carlo simulation. For each risk the probability and cost values are conditional on the specific RRA and the preceding outcomes. The use of fractional factorial design provides a subset of all possible RRA combinations for efficiently determining the preferred total project RRA solution. Risk curves are generated to provide the necessary information to analyze, track, and manage the performance of the selected RRAs over time. Project managers and team leaders can use this information to dynamically manage the RRAs to keep pace with the changing project situation, thereby increasing the probability of project success in a cost‐effective manner. The approach is detailed using a realistic but simplified case of a project examined first with one and then expanded to three technical risks. © 2009 Wiley Periodicals, Inc. Syst Eng 13

Suggested Citation

  • Edouard Kujawski & Diana Angelis, 2010. "Monitoring risk response actions for effective project risk management," Systems Engineering, John Wiley & Sons, vol. 13(4), pages 353-368, December.
  • Handle: RePEc:wly:syseng:v:13:y:2010:i:4:p:353-368
    DOI: 10.1002/sys.20154
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/sys.20154
    Download Restriction: no

    File URL: https://libkey.io/10.1002/sys.20154?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Edouard Kujawski, 2002. "Selection of technical risk responses for efficient contingencies," Systems Engineering, John Wiley & Sons, vol. 5(3), pages 194-212.
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Michael J. Pennock & Yacov Y. Haimes, 2002. "Principles and guidelines for project risk management," Systems Engineering, John Wiley & Sons, vol. 5(2), pages 89-108.
    4. M.‐Elisabeth Paté‐Cornell & Peter J. Regan, 1998. "Dynamic Risk Management Systems: Hybrid Architecture and Offshore Platform Illustration," Risk Analysis, John Wiley & Sons, vol. 18(4), pages 485-496, August.
    5. Avner Engel & Miryam Barad, 2003. "A methodology for modeling VVT risks and costs," Systems Engineering, John Wiley & Sons, vol. 6(3), pages 135-151.
    6. Yacov Y. Haimes, 1991. "Total Risk Management," Risk Analysis, John Wiley & Sons, vol. 11(2), pages 169-171, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Edouard Kujawski & Gregory A. Miller, 2007. "Quantitative risk‐based analysis for military counterterrorism systems," Systems Engineering, John Wiley & Sons, vol. 10(4), pages 273-289, December.
    2. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Wang, 2002. "Consistent testing for stochastic dominance: a subsampling approach," CeMMAP working papers 03/02, Institute for Fiscal Studies.
    3. van den Bergh, J.C.J.M. & Botzen, W.J.W., 2015. "Monetary valuation of the social cost of CO2 emissions: A critical survey," Ecological Economics, Elsevier, vol. 114(C), pages 33-46.
    4. Heiko Karle & Georg Kirchsteiger & Martin Peitz, 2015. "Loss Aversion and Consumption Choice: Theory and Experimental Evidence," American Economic Journal: Microeconomics, American Economic Association, vol. 7(2), pages 101-120, May.
    5. Shoji, Isao & Kanehiro, Sumei, 2016. "Disposition effect as a behavioral trading activity elicited by investors' different risk preferences," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 104-112.
    6. Muhammad Kashif & Thomas Leirvik, 2022. "The MAX Effect in an Oil Exporting Country: The Case of Norway," JRFM, MDPI, vol. 15(4), pages 1-16, March.
    7. Jonathan Meng & Feng Fu, 2020. "Understanding Gambling Behavior and Risk Attitudes Using Cryptocurrency-based Casino Blockchain Data," Papers 2008.05653, arXiv.org, revised Aug 2020.
    8. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    9. Robert Gazzale & Julian Jamison & Alexander Karlan & Dean Karlan, 2013. "Ambiguous Solicitation: Ambiguous Prescription," Economic Inquiry, Western Economic Association International, vol. 51(1), pages 1002-1011, January.
    10. Boone, Jan & Sadrieh, Abdolkarim & van Ours, Jan C., 2009. "Experiments on unemployment benefit sanctions and job search behavior," European Economic Review, Elsevier, vol. 53(8), pages 937-951, November.
    11. Castro, Luciano de & Galvao, Antonio F. & Kim, Jeong Yeol & Montes-Rojas, Gabriel & Olmo, Jose, 2022. "Experiments on portfolio selection: A comparison between quantile preferences and expected utility decision models," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    12. Jos'e Cl'audio do Nascimento, 2019. "Behavioral Biases and Nonadditive Dynamics in Risk Taking: An Experimental Investigation," Papers 1908.01709, arXiv.org, revised Apr 2023.
    13. Luigi Guiso, 2015. "A Test of Narrow Framing and its Origin," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 1(1), pages 61-100, March.
    14. Breaban, Adriana & van de Kuilen, Gijs & Noussair, Charles, 2016. "Prudence, Personality, Cognitive Ability and Emotional State," Other publications TiSEM 9a01a5ab-e03d-49eb-9cd7-4, Tilburg University, School of Economics and Management.
    15. Martín Egozcue & Sébastien Massoni & Wing-Keung Wong & RiÄ ardas Zitikis, 2012. "Integration-segregation decisions under general value functions: "Create your own bundle — choose 1, 2, or all 3!"," Documents de travail du Centre d'Economie de la Sorbonne 12057, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    16. Howard Kunreuther & Erwann Michel-Kerjan, 2015. "Demand for fixed-price multi-year contracts: Experimental evidence from insurance decisions," Journal of Risk and Uncertainty, Springer, vol. 51(2), pages 171-194, October.
    17. Choo, Weihao & de Jong, Piet, 2015. "The tradeoff insurance premium as a two-sided generalisation of the distortion premium," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 238-246.
    18. Francesco GUALA, 2017. "Preferences: Neither Behavioural nor Mental," Departmental Working Papers 2017-05, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    19. Shi, Yun & Cui, Xiangyu & Zhou, Xunyu, 2020. "Beta and Coskewness Pricing: Perspective from Probability Weighting," SocArXiv 5rqhv, Center for Open Science.
    20. Simplice Asongu & Nicholas M. Odhiambo, 2020. "Financial access, governance and insurance sector development in sub-Saharan Africa," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(4), pages 849-875, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:syseng:v:13:y:2010:i:4:p:353-368. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6858 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.