30332 - MARKETING RESEARCH SKILLS FOR PUBLIC POLICY
BIG
Department of Marketing
Course taught in English
Go to class group/s: 23
Course Director:
THOMAS EICHENTOPF
THOMAS EICHENTOPF
Course Objectives
Marketing research is the art of understanding how people make decisions. For good policy makers, such skills are just as crucial to design and evaluate new policies. Therefore, this course explains qualitative and quantitative tools as we commonly use them in marketing and help students to apply them to the political domain. For that purpose, lectures are interactive: students analyze typical problems, select and apply statistical techniques to investigate empirical data, and identify relevant managerial conclusions. Furthermore, the course devotes reasonable space to discuss nudging as a political tool that recently grew to prominence.
Intended Learning Outcomes
Course Content Summary
- Identifying and analyzing marketing research problems in public policy.
- Designing research projects.
- Collecting and using different types of data (internal vs external, primary vs secondary).
- Analyzing public policy data with appropriate (multivariate) statistical techniques.
- Explaining and transferring results to practitioners in public policy.
- Understanding benefits and conditions of various research strategies.
- Discussing recent trends and ethical constraints of marketing research for public policy.
Teaching methods
Assessment methods
Detailed Description of Assessment Methods
For attending students
As part of the course, students submit a group assignment.
Furthermore, one written exam concludes the course.
For both components, students must achieve a pass to pass the course.
I consider all students that submitted a group assignment as attending students unless they register for the exam for non-attending students.
For non attending students
Final exam (100%): the exam consists of an individual written test with standardized and open questions that covers all the mandatory literature.
As part of the course, students submit a group assignment.
Furthermore, one written exam concludes the course.
For both components, students must achieve a pass to pass the course.
I consider all students that submitted a group assignment as attending students unless they register for the exam for non-attending students.
- Team Project: 50%;
- Short-case presentation: 5%;
- Final exam: open-ended + multiple choice questions. 45% (Students can consult notes and the Tweepy documentation during the exam);
- Extra-credit opportunity: Twitter participation – 1 point.
For non attending students
Final exam (100%): the exam consists of an individual written test with standardized and open questions that covers all the mandatory literature.
Textbooks
The exact readings are indicated at the beginning of the course.
Prerequisites
This is not a course on statistics, but students should feel advised to have a basic understanding of key statistical concepts, i.e. multivariate statistics and linear regression models, which we use throughout the course.
Last change 12/06/2017 12:14