Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156917
Title: A data-driven method for pricing with mixed choice model
Authors: Ng, Jia Qi
Keywords: Science::Mathematics
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Ng, J. Q. (2022). A data-driven method for pricing with mixed choice model. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156917
Abstract: The mixed choice model is a popular choice model to simulate consumer choice in many domains. This paper aims to investigate the pricing problem with mixed choice model. The mixed logit model estimation and marginal distribution model (MDM) estimation methods are carefully studied and implemented into a set of synthetic data that is generated to demonstrate their prediction capabilities. To solve the pricing problem, we employ the “Marginal Estimation + Price Optimization” framework developed by Yan et al. (2022), which is based on MDM. The framework has been shown to work well for heterogeneous consumer population, hence we apply it to a mixed logit model price optimization problem.
URI: https://hdl.handle.net/10356/156917
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)

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