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
Parents
6
Optimal Category Pricing with Endogenous Store Traffic
Edward J. Fox, Steven Postrel, John H. Semple · Marketing Science · 2008 · 14 citations
1–5 of 6
16
1
h-index
1
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1
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1
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1
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1–5 of 16
7

Western University
London, Canada
1 h-index
3 publications
222 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
1 h-index
2 publications
214 citations

University of Rome Tor Vergata
Rome, Italy
1 h-index
2 publications
48 citations
University of California, Los Angeles
Los Angeles, United States
1 h-index
1 publications
14 citations

Pennsylvania State University
State College, United States
1 h-index
1 publications
107 citations
Southern Methodist University
Dallas, United States
1 h-index
2 publications
28 citations

City University of Hong Kong
Hong Kong, Hong Kong
1 h-index
3 publications
222 citations
1–7 of 7
1 publications · 14 citations
1
h-index
1 publications · 12 citations
1
h-index
POMS · 1 publications · 107 citations
1
h-index
1 publications · 74 citations
1
h-index
1 publications · 74 citations
1
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1–5