Machine Learning of Choice Economics
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-4059-0_4
Reference49 articles.
1. Cleland, J. A., Foo, J., Ilic, D., et al. (2020). “You can’t always get what you want”: Economic thinking, constrained optimization and health professions education. Advances in Health Science Education, 25, 1163–1175.
2. van den Broek-Altenburg, E., & Atherly, A. (2020). Using discrete choice experiments to measure preferences for hard to observe choice attributes to inform health policy decisions. Health Economics Review, 10, 18.
3. Koemle, D., & Yu, X. (2020). Choice experiments in non-market value analysis: Some methodological issues. Forestry Economics Review, 2(1), 3–31.
4. van Cranenburgh, S., Wang, S., Vij, A., Pereira, F., & Walker, J. (2022). Choice modelling in the age of machine learning—Discussion paper. Journal of Choice Modelling, 42.
5. Thaler, R. H., & Sunstein, C. R. (2009). Nudge. Penguin.
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