Multi-item Forecasting

Multi-Item Forecasting is a retail forecasting methodology that jointly predicts demand for multiple distinct products by leveraging shared patterns and dependencies across items, thereby improving accuracy through cross-series information pooling.

7

Publications

348

Citations

15

Authors

12

Institutions

Publications per year

2017–2026

2

Authors

15

  1. AI
    Angelos I. Vassilopoulos

    London Business School, United Kingdom

    2 publications · 75 citations

    2

    h-index

  2. DW
    Derek W. Bunn

    London Business School, United Kingdom

    2 publications · 75 citations

    2

    h-index

  3. IS
    Inderjit S. Dhillon

    The University of Texas at Austin, United States

    1 publications · 23 citations

    1

    h-index

  4. CW
    Charles W. Gross

    University of Virginia, United States

    1 publications · 141 citations

    1

    h-index

  5. SR
    Shubhankar Ray

    Texas A&M University, United States

    1 publications · 23 citations

    1

    h-index

1–5 of 15

Venues

  1. International Journal of Forecasting

    2 publications · 75 citations

    2

    h-index

  2. Operations Research

    1 publications · 24 citations

    1

    h-index

  3. Journal of the Operational Research Society

    OR · 1 publications · 24 citations

    1

    h-index

  4. Decision Support Systems

    1 publications · 61 citations

    1

    h-index

  5. Journal of Forecasting

    1 publications · 141 citations

    1

    h-index

1–5