Context dependent discrete choice models and assortment optimization for online retail
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Authors
Mushtaque, Uzma
Issue Date
2017-12
Type
Electronic thesis
Thesis
Thesis
Language
ENG
Keywords
Industrial and management engineering
Alternative Title
Abstract
The primary objective of this research is to develop descriptive mathematical models capturing context-effects associated with individual user selection behavior found in marketing and behavioral research. These models are then used as inputs to assortment optimization problems to optimize personalized recommendations in an online retail environment. Our work makes contributions at the intersection of three fields: (1) discrete choice models (2) recommender systems and (3) e-commerce assortment planning.
Description
December 2017
School of Engineering
School of Engineering
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY