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A Go/No-Go Decision-Making Model Based on Risk and Multi-Criteria Techniques for Project Selection

Author

Listed:
  • Daouda KAMISSOKO

    (University of Toulouse, France)

  • Didier Gourc

    (University of Toulouse, France)

  • François Marmier

    (Université de Strasbourg, France)

  • Antoine Clement

    (University of Toulouse, France)

Abstract

The realization of infrastructures and the deployment of processes can follow project formalism. Generally, a project goes through a design and a realization phase. Between these two phases, there is a crucial milestone: Launching the project. Making this decision is not easy at all, and constitutes a real problem-- the main reasons to this are the numerous numbers of criteria (for technical, economic, social, environmental dimensions) and risks in the sense of feared events. Criteria and risks are most of the time not considered due to lack of time (for formalization) and the difficulty to handle them. The objective of this paper is to propose a relevant approach to make the decision of launching the project or not. The proposal outlined is innovative in that it can consider indicators based on several appropriate criteria, the associated risks, and their ways of management. The fact of considering several criteria and risks increases the probability of making the good decision.

Suggested Citation

  • Daouda KAMISSOKO & Didier Gourc & François Marmier & Antoine Clement, 2022. "A Go/No-Go Decision-Making Model Based on Risk and Multi-Criteria Techniques for Project Selection," International Journal of Decision Support System Technology (IJDSST), IGI Global Scientific Publishing, vol. 15(2), pages 1-21, December.
    • Handle: RePEc:igg:jdsst0:v:15:y:2022:i:2:p:1-21
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    References listed on IDEAS

    as
    1. Tom Waas & Jean Huge & Thomas BLOCK & Tarah Wright & Francisco Javier Benitez Capistros & Aviel Verbruggen, 2014. "Sustainability assessment and indicators: Tools in a decision-making strategy for sustainable development," ULB Institutional Repository 2013/189410, ULB -- Universite Libre de Bruxelles.
    2. Isihara, Paul & Shi, Chaojun & Ward, Jonathan & O'Malley, Leo & Laney, Skyler & Diedrichs, Danilo & Flores, Gabriel, 2020. "Identifying most typical and most ideal attribute levels in small populations of expert decision makers: Studying the Go/No Go decision of disaster relief organizations," Journal of choice modelling, Elsevier, vol. 35(C).
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