Talent Forecasting

Talent Forecasting is a predictive methodology within the field of talent identification that systematically projects future individual or organizational performance potential based on historical, behavioral, cognitive, and contextual indicators, distinguishing itself through its forward-looking analytics and data-driven modeling techniques.

46

Publications

2.3K

Citations

119

Authors

66

Institutions

Publications per year

2017–2026

26

Authors

119

  1. HZ
    Hengshu Zhu

    Baidu (China), China

    10 publications · 305 citations

    10

    h-index

  2. HX
    Hui Xiong

    Rutgers, The State University of New Jersey, United States

    9 publications · 287 citations

    9

    h-index

  3. LZ
    Le Zhang

    Baidu (China), China

    3 publications · 68 citations

    3

    h-index

  4. CQ
    Chuan Qin

    University of Science and Technology of China, China

    3 publications · 69 citations

    3

    h-index

  5. YS
    Ying Sun

    Baidu (China), China

    3 publications · 57 citations

    3

    h-index

1–5 of 119

Venues

  1. Journal of Quantitative Analysis in Sports

    2 publications · 46 citations

    2

    h-index

  2. Procedia Computer Science

    2 publications · 75 citations

    2

    h-index

  3. SSRN Electronic Journal

    Repository · 2 publications · 29 citations

    2

    h-index

  4. Zenodo (CERN European Organization for Nuclear Research)

    Repository · 2 publications · 63 citations

    2

    h-index

  5. Mobile Information Systems

    1 publications · 22 citations

    1

    h-index

1–5