A data-driven method for pricing with mixed choice model
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 in...
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/156917 |
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sg-ntu-dr.10356-1569172023-02-28T23:11:07Z A data-driven method for pricing with mixed choice model Ng, Jia Qi Yan Zhenzhen School of Physical and Mathematical Sciences yanzz@ntu.edu.sg Science::Mathematics 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. Bachelor of Science in Mathematical Sciences 2022-04-27T07:50:03Z 2022-04-27T07:50:03Z 2022 Final Year Project (FYP) 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 https://hdl.handle.net/10356/156917 en application/pdf Nanyang Technological University |
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Science::Mathematics Ng, Jia Qi A data-driven method for pricing with mixed choice model |
| description |
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. |
| author2 |
Yan Zhenzhen |
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Yan Zhenzhen Ng, Jia Qi |
| format |
Final Year Project |
| author |
Ng, Jia Qi |
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Ng, Jia Qi |
| title |
A data-driven method for pricing with mixed choice model |
| title_short |
A data-driven method for pricing with mixed choice model |
| title_full |
A data-driven method for pricing with mixed choice model |
| title_fullStr |
A data-driven method for pricing with mixed choice model |
| title_full_unstemmed |
A data-driven method for pricing with mixed choice model |
| title_sort |
data-driven method for pricing with mixed choice model |
| publisher |
Nanyang Technological University |
| publishDate |
2022 |
| url |
https://hdl.handle.net/10356/156917 |
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