Store Traffic Forecasting

Store Traffic Forecasting is a quantitative predictive methodology within retail workforce planning that estimates the future volume of customer arrivals at a retail location by leveraging historical visitation patterns, temporal trends, and external influencing factors to optimize staffing and operational efficiency.

6

Publications

305

Citations

16

Authors

7

Institutions

Publications per year

2017–2026

1

Variants

Retail Footfall Forecasting

Authors

16

  1. AN
    Agostino Nuzzolo

    University of Rome Tor Vergata, Italy

    1 publications · 24 citations

    1

    h-index

  2. PM
    Phillip M. Yelland

    Oracle (United States), United States

    1 publications · 12 citations

    1

    h-index

  3. SP
    Steven Postrel

    University of California, Los Angeles, United States

    1 publications · 14 citations

    1

    h-index

  4. LW
    L. Winston Ring

    Columbia University, United States

    1 publications · 74 citations

    1

    h-index

  5. MR
    Michael R. Pearce

    City University of Hong Kong, Hong Kong SAR China

    1 publications · 74 citations

    1

    h-index

1–5 of 16

Venues

  1. Marketing Science

    1 publications · 14 citations

    1

    h-index

  2. Foresight

    1 publications · 12 citations

    1

    h-index

  3. Production and Operations Management

    POMS · 1 publications · 107 citations

    1

    h-index

  4. Operations Research

    1 publications · 74 citations

    1

    h-index

  5. Journal of Retailing

    1 publications · 74 citations

    1

    h-index

1–5