Employee Selection Analytics

Employee Selection Analytics is a scholarly methodological framework within talent analytics that systematically leverages data, statistical models, and algorithmic techniques to optimize the identification, assessment, and prediction of job candidate suitability and performance potential during organizational hiring processes.

41

Publications

2.6K

Citations

100

Authors

53

Institutions

Publications per year

2017–2026

11

Authors

100

  1. RM
    Roy M. Dorcus

    University of California, Los Angeles, United States

    2 publications · 39 citations

    2

    h-index

  2. ED
    Emily D. Campion

    Purdue University West Lafayette, United States

    2 publications · 162 citations

    2

    h-index

  3. MA
    Michael A. Campion

    Purdue University West Lafayette, United States

    2 publications · 162 citations

    2

    h-index

  4. MJ
    Margaret Jones

    King's College London, United Kingdom

    2 publications · 39 citations

    2

    h-index

  5. MH
    Michael Harvey

    University of Mississippi, United States

    1 publications · 31 citations

    1

    h-index

1–5 of 100

Venues

  1. Journal of Applied Psychology

    5 publications · 285 citations

    5

    h-index

  2. Human Resource Management Review

    2 publications · 117 citations

    2

    h-index

  3. Personnel Psychology

    2 publications · 173 citations

    2

    h-index

  4. 2

    h-index

  5. 2

    h-index

1–5