Retail Markdown Optimization

Retail Markdown Optimization is a quantitative decision-making framework within revenue management that prescribes the optimal timing, depth, and sequence of price reductions for retail inventory to maximize profitability or clear physical stock efficiently, distinguishing it from generic pricing or discounting strategies by its reliance on predictive analytics and demand modeling.

17

Publications

918

Citations

58

Authors

28

Institutions

Publications per year

2017–2026

7

Authors

58

  1. JG
    Jérémie Gallien

    London Business School, United Kingdom

    2 publications · 222 citations

    2

    h-index

  2. FC
    Felipe Caro

    University of California, Los Angeles, United States

    2 publications · 222 citations

    2

    h-index

  3. DJ
    David J. Closs

    Michigan State University, United States

    1 publications · 63 citations

    1

    h-index

  4. NK
    Nitin Kishore Sai Samala

    Walmart (United States), United States

    1 publications · 12 citations

    1

    h-index

  5. RY
    Rui Yin

    Arizona State University, United States

    1 publications · 48 citations

    1

    h-index

1–5 of 58

Venues

  1. Manufacturing & Service Operations Management

    2 publications · 51 citations

    2

    h-index

  2. INFORMS Journal on Applied Analytics

    IJAA · 2 publications · 36 citations

    2

    h-index

  3. Operations Research

    2 publications · 324 citations

    2

    h-index

  4. Journal of Revenue and Pricing Management

    1 publications · 51 citations

    1

    h-index

  5. IIE Transactions

    1 publications · 15 citations

    1

    h-index

1–5