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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| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2022
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/156917 |
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| 總結: | 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. |
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