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Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System

Author

Listed:
  • Min-Sung Kim

    (POIST Task-force Team, POSCO (Pohang Iron and Steel Company), 6261 Donghaean-ro, Nam-gu, Pohang 37666, Korea)

  • Eul-Bum Lee

    (Graduate Institute of Ferrous Technology & Graduate School of Engineering Mastership, Pohang University of Science and Technology (POSTECH), 77 Cheongam-ro, Nam-gu, Pohang 37673, Korea)

  • In-Hye Jung

    (Graduate Institute of Ferrous Technology & Graduate School of Engineering Mastership, Pohang University of Science and Technology (POSTECH), 77 Cheongam-ro, Nam-gu, Pohang 37673, Korea)

  • Douglas Alleman

    (Construction Engineering and Management, Department of Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, CO 80309, USA)

Abstract

This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.

Suggested Citation

  • Min-Sung Kim & Eul-Bum Lee & In-Hye Jung & Douglas Alleman, 2018. "Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:12:p:4780-:d:190594
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    References listed on IDEAS

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    Cited by:

    1. Dong-Hyun Kim & Eul-Bum Lee & In-Hyeo Jung & Douglas Alleman, 2019. "The Efficacy of the Tolling Model’s Ability to Improve Project Profitability on International Steel Plants," Energies, MDPI, vol. 12(7), pages 1-18, March.
    2. Edwin Thomas Banobi & Wooyong Jung, 2019. "Causes and Mitigation Strategies of Delay in Power Construction Projects: Gaps between Owners and Contractors in Successful and Unsuccessful Projects," Sustainability, MDPI, vol. 11(21), pages 1-16, October.
    3. Sabriye Topal & Emine Atasoylu, 2022. "A Fuzzy Risk Assessment Model for Small Scale Construction Work," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
    4. da Cunha, Richard Alex & Rangel, Luís Alberto Duncan & Rudolf, Christian A. & Santos, Luiza dos, 2022. "A decision support approach employing the PROMETHEE method and risk factors for critical supply assessment in large-scale projects," Operations Research Perspectives, Elsevier, vol. 9(C).
    5. Justyna Kozłowska & Marco Antônio Benvenga & Irenilza de Alencar Nääs, 2022. "Investment Risk and Energy Security Assessment of European Union Countries Using Multicriteria Analysis," Energies, MDPI, vol. 16(1), pages 1-28, December.

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