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Choosing a project risk-handling strategy: An analytical model

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  • Fan, Miao
  • Lin, Neng-Pai
  • Sheu, Chwen

Abstract

Project risk management includes the process of risk identification, analysis, and handling (response). Risk handling/response is the choice of a proper strategy to reduce the likelihood of the occurrence of risk events and/or the magnitude of their negative impact. Research on risk handling is mostly opinion- or case-based and, as such, it offers scant guidelines for making the decision. Managers often choose a risk-handling strategy based on their experience or preference toward risk, with no consideration of project characteristics (e.g., project size, slack, or technical complexity) and the associated financial implications. This study assumes that the choice of the risk-handling strategy should be aligned with unique project characteristics. This study constructed a conceptual framework that defines the relationship between risk-handling strategy and relevant project characteristics. A conceptual model was developed to describe the quantitative relationships among all variables. Accordingly, optimization analysis is performed to derive a minimum-cost risk-handling strategy for a particular risk event. The findings provide insights into how various project characteristics and risk situation affect the choice of a risk-handling strategy.

Suggested Citation

  • Fan, Miao & Lin, Neng-Pai & Sheu, Chwen, 2008. "Choosing a project risk-handling strategy: An analytical model," International Journal of Production Economics, Elsevier, vol. 112(2), pages 700-713, April.
    • Handle: RePEc:eee:proeco:v:112:y:2008:i:2:p:700-713
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    References listed on IDEAS

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    Cited by:

    1. Curto, D. & Acebes, F. & González-Varona, J.M. & Poza, D., 2022. "Impact of aleatoric, stochastic and epistemic uncertainties on project cost contingency reserves," International Journal of Production Economics, Elsevier, vol. 253(C).
    2. 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).
    3. Ellinas, Christos & Allan, Neil & Johansson, Anders, 2016. "Project systemic risk: Application examples of a network model," International Journal of Production Economics, Elsevier, vol. 182(C), pages 50-62.
    4. Nguyen, Trong-Hung & Marmier, François & Gourc, Didier, 2013. "A decision-making tool to maximize chances of meeting project commitments," International Journal of Production Economics, Elsevier, vol. 142(2), pages 214-224.
    5. Bi, Kexin & Huang, Ping & Ye, Hui, 2015. "Risk identification, evaluation and response of low-carbon technological innovation under the global value chain: A case of the Chinese manufacturing industry," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 238-248.
    6. Huang, Min & Ip, W.H. & Yang, Hongmei & Wang, Xingwei & Lau, Henry C.W., 2008. "A fuzzy synthetic evaluation embedded tabu search for risk programming of virtual enterprises," International Journal of Production Economics, Elsevier, vol. 116(1), pages 104-114, November.
    7. Liu, Zhixue & Ding, Ronggui & Wang, Lei & Song, Rui & Song, Xinyi, 2023. "Cooperation in an uncertain environment: The impact of stakeholders' concerted action on collaborative innovation projects risk management," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    8. 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).

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