Exogenous Driver Modeling

Exogenous Driver Modeling is a predictive modeling approach that identifies and incorporates external, non-internal organizational factors—such as economic indicators, regulatory changes, or technological advancements—into workforce demand forecasts to improve accuracy by accounting for influences beyond the organization’s immediate control.

4

Publications

107

Citations

13

Authors

14

Institutions

Publications per year

2017–2026

3

Authors

13

  1. CB
    Chiara Berti

    University of Chieti-Pescara, Italy

    1 publications · 14 citations

    1

    h-index

  2. JW
    Jiqian Wang

    Southwest Jiaotong University, China

    1 publications · 28 citations

    1

    h-index

  3. KT
    Karen Turner

    University of Strathclyde, United Kingdom

    1 publications · 30 citations

    1

    h-index

  4. XG
    Xiaozhu Guo

    Southwest Jiaotong University, China

    1 publications · 28 citations

    1

    h-index

  5. GB
    Gunawan Baharuddin

    University of Malaya, Malaysia

    1 publications · 35 citations

    1

    h-index

1–5 of 13

Venues

  1. Entrepreneurial Business and Economics Review

    EBER · 1 publications · 35 citations

    1

    h-index

  2. Energy Economics

    1 publications · 28 citations

    1

    h-index

  3. International journal of organizational analysis

    IJOA · 1 publications · 14 citations

    1

    h-index

  4. Regional Studies

    1 publications · 30 citations

    1

    h-index

1–4