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A Study of Supply Chain Risk in the Brazilian Wind Power Projects by Interpretive Structural Modeling and MICMAC Analysis

Author

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  • Jorge Arnaldo Troche-Escobar

    (Postgraduate Program in Industrial Engineering (PEI), Federal University of Bahia (UFBA), Salvador (BA) 40210-630, Brazil)

  • Herman Augusto Lepikson

    (National Industrial Learning Service (SENAI-CIMATEC), Av. Orlando Gomes, 1845—Piatã, Salvador (BA) 41650-010, Brazil)

  • Francisco Gaudêncio Mendonça Freires

    (Polytechnic School, Federal University of Bahia (UFBA), Salvador (BA) 40210-630, Brazil)

Abstract

This paper aims to present an approach to the supply chain risk modeling of Brazilian wind power projects. Risk factors were assessed by literature review and analysis through the Interpretive Structural Modeling (ISM) and the Matrix-based Multiplication Applied to a Classification (MICMAC) methodologies, with a group of professionals of the field. The ISM model represented the relationships between twenty-two risk factors, and their position in the system, from higher to lower-level risks. The MICMAC analysis identified independent, autonomous, linkage and dependent risk factors according to their driving and dependence power. Data collected also allowed for the recognition of indirect influences between risk factors, complementing the system’s understanding, in special the strongest linkages. The paper also integrated both outputs to create a better representation of the risks factors into the system. The research characterizes current risk factors’ status on the Brazilian wind power supply chain, and the understanding of their implications into the system. It is a guide to implement effective mitigation strategies into the supply chain and more accurate and cautious decision-making in organizations.

Suggested Citation

  • Jorge Arnaldo Troche-Escobar & Herman Augusto Lepikson & Francisco Gaudêncio Mendonça Freires, 2018. "A Study of Supply Chain Risk in the Brazilian Wind Power Projects by Interpretive Structural Modeling and MICMAC Analysis," Sustainability, MDPI, vol. 10(10), pages 1-24, September.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3442-:d:172327
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    References listed on IDEAS

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    Cited by:

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    5. Hassan Al-Zarooni & Hamdi Bashir, 2020. "An integrated ISM fuzzy MICMAC approach for modeling and analyzing electrical power system network interdependencies," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1204-1226, December.
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