Discrete Choice Analysis: Predicting Individual Behavior and Market Demand
In the wake of Covid-19, the course will be offered in a live, all-virtual format.
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Discrete choice models are used in many fields such as economics, engineering, environmental management, marketing, urban planning, and transportation. Most applications are performed offline and often involve stated preferences surveys. This program also covers online applications where predictions of individual choice behavior are used as inputs for online optimization and personalization.
The course is designed for modelers who wish to acquire in-depth knowledge of the latest developments. It is intended for academics and professionals interested in learning new discrete choice techniques. Recent additions to the course include “Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis” by Moshe Ben-Akiva, Daniel McFadden and Kenneth Train, and estimation algorithms using machine learning methods.
Scholarships: Half-tuition scholarships are available for junior faculty, postdocs, and doctoral students. To apply for the scholarship, please email a CV and a letter stating the relevance of the course to your research to email@example.com. The deadline to apply for the scholarship is June 8. Please email us for further info.
Requirements: Please note that laptops are required for this course. Participants will need to install Biogeme. Installation instructions will be provided before the course start date
The course runs daily from 9:30 am – 5:00 pm.
The course consists of a series of lectures and lab sessions that develop discrete choice concepts and techniques and demonstrate their applications. Lab sessions offer hands-on experience in applying the material covered in the lectures using discrete choice software and real-world data sets.
Prof. Moshe Ben-Akiva
June 15 - 19, 2020
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Who Should Attend?
This program is intended for academics and professionals interested in learning new discrete choice techniques and how to predict choice and forecast demand. It is particularly suited for academics engaged in research, especially PhD students in economics, planning, civil engineering, management, behavioral science, health science, and political science. This course will also benefit professionals in market research, transportation consulting, planning, and any government agencies.
Participants will gain hands-on experience in applying discrete choice software in real-world case studies. A working knowledge of basic statistical methods is needed.