Dynamic Assortment Optimization
Dynamic Assortment Optimization is a formal framework in operations research and marketing science that dynamically determines the optimal subset of products to offer to consumers over time, distinguishing itself from static models by explicitly incorporating time-varying demand patterns, consumer learning, and adaptive behavior in response to changing market conditions.
32
Publications
2.4K
Citations
48
Authors
38
Institutions
Publications per year
2017–2026
20
Parents
32
1–5 of 32
48
6
h-index
6
h-index
5
h-index
4
h-index
4
h-index
1–5 of 48
38
Massachusetts Institute of Technology
Cambridge, United States
7 h-index
12 publications
641 citations
Columbia University
New York, United States
5 h-index
11 publications
524 citations

Cornell University
Ithaca, United States
5 h-index
7 publications
1.7K citations
London Business School
London, United Kingdom
5 h-index
5 publications
146 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
4 publications
77 citations
New York University
New York, United States
3 h-index
3 publications
64 citations
The University of Texas at Dallas
Richardson, United States
3 h-index
3 publications
58 citations
The University of Texas at Austin
Austin, United States
3 h-index
4 publications
544 citations
1–8 of 38
8 publications · 1.1K citations
8
h-index
Repository · 6 publications · 106 citations
6
h-index
4 publications · 648 citations
4
h-index
4 publications · 297 citations
4
h-index
Repository · 3 publications · 54 citations
3
h-index
1–5