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Measuring the system resilience of project portfolio network considering risk propagation

Author

Listed:
  • Xingqi Zou

    (Kunming University of Science and Technology)

  • Qing Yang

    (University of Science and Technology Beijing)

  • Qinru Wang

    (University of Science and Technology Beijing)

  • Bin Jiang

    (DePaul University)

Abstract

The paper presents the model resilience measurement based on the complex network theory and analyzes the resilience of project portfolio network considering risk propagation. The model can be used to evaluate the resilience and improve its success probability of projects in the portfolio network. Firstly, the research analyzes the dynamic changes of the portfolio network derived from the construction of the project portfolio matrix, as well as the main factors to be taken into consideration in measuring the resilience of the project portfolio. Further, the research measures the resilience of the project portfolio network according to the node attributes (project) and the relationship attributes (the relationship that one project will impact another in the portfolio network) respectively. Then, to integrate the resilience of the projects and influence relationship between projects, the research proposes the dynamic PageRank algorithm to analyze the resilience of the project portfolio based on the analysis of traditional PageRank algorithm. In addition, resilience is not only affected by the projects and its influence relationship between them, but is also affected by risk propagation. Therefore, the research presents a model for analyzing the portfolio network resilience considering multiple risk propagation. Finally, a research and development project portfolio are taken as an example to demonstrate the effectiveness of the method presented in this research. Our approach can be used by managers to identify the scores of project resilience capacity in portfolio network. Our method explicitly allows to uncover the most resilient projects considering the resilience of project (node) and their influence relationship (network structure), and the risk propagation. Utilizing the outcomes of this research can enhance the capacity of the whole project portfolio to manage risks and improve the success probability of the whole project portfolio by enhancing network resilience.

Suggested Citation

  • Xingqi Zou & Qing Yang & Qinru Wang & Bin Jiang, 2024. "Measuring the system resilience of project portfolio network considering risk propagation," Annals of Operations Research, Springer, vol. 340(1), pages 693-721, September.
    • Handle: RePEc:spr:annopr:v:340:y:2024:i:1:d:10.1007_s10479-022-05100-9
    DOI: 10.1007/s10479-022-05100-9
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    References listed on IDEAS

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    1. Foroogh Ghasemi & Mohammad Hossein Mahmoudi Sari & Vahidreza Yousefi & Reza Falsafi & Jolanta Tamošaitienė, 2018. "Project Portfolio Risk Identification and Analysis, Considering Project Risk Interactions and Using Bayesian Networks," Sustainability, MDPI, vol. 10(5), pages 1-23, May.
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