Machine Learning Adoption

Machine Learning Adoption is the systematic integration and utilization of machine learning techniques within an organization or domain, distinguished from broader artificial intelligence adoption by its specific focus on data-driven algorithms that improve through experience.

200

Publications

13.4K

Citations

696

Authors

365

Institutions

Publications per year

2017–2026

191

Authors

696

  1. MS
    Marc Schmitt

    University of Oxford, United Kingdom

    5 publications · 230 citations

    5

    h-index

  2. FK
    Foutse Khomh

    Polytechnique Montréal, Canada

    3 publications · 122 citations

    3

    h-index

  3. AK
    Arpan Kumar Kar

    Indian Institute of Technology Delhi, India

    2 publications · 564 citations

    2

    h-index

  4. NZ
    Nikolas Zolas

    United States Census Bureau, United States

    2 publications · 181 citations

    2

    h-index

  5. HH
    Hennie Huijgens

    Delft University of Technology, Netherlands

    2 publications · 110 citations

    2

    h-index

1–5 of 696

Venues

  1. arXiv (Cornell University)

    Repository · 11 publications · 277 citations

    11

    h-index

  2. SSRN Electronic Journal

    Repository · 10 publications · 315 citations

    10

    h-index

  3. Technological Forecasting and Social Change

    6 publications · 1.5K citations

    6

    h-index

  4. Materials Today Proceedings

    4 publications · 379 citations

    4

    h-index

  5. Journal of Business Research

    JBR · 4 publications · 226 citations

    4

    h-index

1–5