Advanced Marketing Decision Models
Aims
Advanced Marketing Decision Model is an intensive, in-depth, hands-on graduate course focusing on key types of marketing decision models. The overall goal of the course is to provide students with an in-depth insight into a wide array of areas of marketing decision models. For each domain discussed, our focus spans entire research process including research problem definition, conceptual development, model specification, data collocation, coding and results reporting.
Information
• Large scale variable selection problems (Enric Junqué de Fortuny)
• Machine learning problems in marketing (Pieter Schoonees)
• Bayesian learning models (Maciej Szymanowski)
• Mathematical modeling of consumer behavior (Alina Ferecatu)
• Multiarm bandit problems in marketing (Gui Liberali)
• Economic approach to network theory (Xi Chen)
• Model selection (Aurélie Lemmens (guest speaker))
• Using Bayesian methods for behavioral decision models (Robert Rooderkerk)
Assessment
Students will be evaluated based on attendance, class participation and assignments.
Materials
Further reading and resources will be posted on Blackboard after each lecture.
Additional info
Prerequisites:
Students are expected to have working knowledge of Matlab and R.
Students should have through knowledge of linear regression.
Computer Requirements:
Students need to be equipped with laptops with Matlab and R installed. 10GB of free drive and 4GB of RAM will be sufficient for the course.
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More information and detailed timetables can be found here.
ERIM PhD candidates and Research Master students can register for this course via SIN Online.
External (non-ERIM) participants are welcome to this course. To register, please fill in the registration form and e-mail it to miizuka@rsm.nl by four weeks prior to the start of the course. Please note that the number of places for this course is limited. For external participants, the course fee is 260 euro per ECTS credit.
