Data-driven Risk Analysis

Data-Driven Risk Analysis is a systematic methodology within the field of risk assessment that distinguishes itself by employing empirical data and quantitative analytics to identify, evaluate, and prioritize risks, as opposed to relying primarily on expert judgment or theoretical assumptions.

88

Publications

4.3K

Citations

314

Authors

180

Institutions

Publications per year

2017–2026

67

Authors

314

  1. TA
    Terje Aven

    University of Stavanger, Norway

    3 publications · 115 citations

    3

    h-index

  2. ZY
    Zaili Yang

    Liverpool John Moores University, United Kingdom

    3 publications · 169 citations

    3

    h-index

  3. GX
    Gangyan Xu

    Harbin Institute of Technology, China

    2 publications · 86 citations

    2

    h-index

  4. SD
    Seth D. Guikema

    Johns Hopkins University, United States

    2 publications · 136 citations

    2

    h-index

  5. ZM
    Zahra Mohaghegh

    University of Illinois Urbana-Champaign, United States

    2 publications · 57 citations

    2

    h-index

1–5 of 314

Venues

  1. Reliability Engineering & System Safety

    13 publications · 814 citations

    13

    h-index

  2. International Journal of Production Economics

    3 publications · 68 citations

    3

    h-index

  3. Chaos Solitons & Fractals

    3 publications · 529 citations

    3

    h-index

  4. Risk Analysis

    3 publications · 166 citations

    3

    h-index

  5. Safety Science

    3 publications · 146 citations

    3

    h-index

1–5