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A novel operational risk assessment model based on evidence reasoning for multi-objective and dynamic operational scenarios

Author

Listed:
  • Guicang Peng

    (University of Stavanger)

  • Jon T.ømmerås Selvik

    (University of Stavanger)

  • Eirik Bjorheim Abrahamsen

    (University of Stavanger)

  • Tore Markeset

    (University of Stavanger)

Abstract

Operational risk assessment (ORA) practices have traditionally focused on assessing risks within a single operational objective, often overlooking the complexities and interdependencies present in modern operational environments. This study explores the challenges of ORA within a multi-objective and dynamic context, where risks need to be balanced and integrated across varied operational objectives and decision gates. Furthermore, the study addresses the challenges posed by incomplete knowledge and conflicting assessments, which are prevalent in real-world ORA scenarios. Utilizing evidence reasoning (ER) as a multi-criteria decision analysis framework, the paper presents a novel ER-ORA mathematical model to aggregate individual risk beliefs across various operational objectives and decision gates dynamically. The approach resolves conflicts between individual risk assessments and quantifies overall uncertainties and conflicts of the assessment. The ER-ORA model is validated through a dataset reflecting the aforementioned ORA challenges. The paper conclude on the ER-ORA’s functionality and propose future research directions.

Suggested Citation

  • Guicang Peng & Jon T.ømmerås Selvik & Eirik Bjorheim Abrahamsen & Tore Markeset, 2025. "A novel operational risk assessment model based on evidence reasoning for multi-objective and dynamic operational scenarios," 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. 16(5), pages 1711-1727, May.
    • Handle: RePEc:spr:ijsaem:v:16:y:2025:i:5:d:10.1007_s13198-025-02750-3
    DOI: 10.1007/s13198-025-02750-3
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    References listed on IDEAS

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    1. Guicang Peng & Jon Tømmerås Selvik & Eirik Bjorheim Abrahamsen & Knut Erik Bang & Tore Markeset, 2024. "Integrating structure time series forecasting and multicriteria decision analysis for adaptive operational risk assessment: an empirical study using real-time data," 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. 15(7), pages 3162-3181, July.
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