Module 7500
Applied Choice Analysis

Instructors

Prof. Dr. Jutta Roosen, Marketing and Consumer Research, Technical University of Munich
In addition, guest lectures will contribute to specific topics of the course.

Module Description

The course will introduce choice modelling techniques for consumer and marketing analysis. After starting with the theory of consumer choice, the course will discuss different types of choice data available. The main part of the course will focus on choice experiments. It discuss the specifics of choice experiments, possible experimental designs and data collection procedures. Participants will be familiarized with data handling and analysis considering conditional logit, random parameters logit and latent class analysis. To obtain an overview of the literature, participants will present papers from their respective field.

Course Outline

1. Introduction
2. Decision data and choice models
3. Setting up stated choice experiments: Experimental design, alternatives, attributes and levels
4. Exercise: Handling choice data, Brand choice
5. Conditional logit model
6. Random parameters logit model
7. Latent class model
8. Information search and choice behavior

Teaching methods

Lectures (40%), seminars (20%), PC-demonstrations (20%), hands-on-exercises (20%)

Grading

Presentation (40%), assignments (40%), participation (20%)

Credit points: 3

Requirements

Consumer Behavior, Econometrics, Microeconomics, Basic Stata Skills.

Software: Stata.

Language: English.

Organization and time

Students will receive a paper assignment two weeks prior to the course. These papers are presented throughout the week. In addition about 40% of the course is done in the computer lab using the software Stata. The course is planned for Mo 13:30-16, Tu-Th 9-12 and 13:30-16, Fr 9-12 and will take place in Freising-Weihenstephan. For further information please contact Helga Brandstetter (hbrandstetter@tum.de, 08161 / 71 3316).

References

• Bettman, J. R., Luce, M. F., Payne, J. W. (1998). Constructive Consumer Choice Processes. Journal of Consumer Research, 25(3), 187-217.
  Chintagunta, P. K., Nair, H. S. (2011). Discrete-Choice Models of Consumer Demand in Marketing. Marketing Science, 30(6), 977-996. doi: 10.1287/mksc.1110.0674
• Hensher, D. A. (2006). How Do Respondents Process Stated Choice Experiments? Attribute Consideration under Varying Information Load. Journal of Applied Econometrics, 21(6), 861-878. doi: 10.1002/jae.877
• Hensher, D. A., Rose, J. M., Greene, W. H. (2005). Applied choice analysis: A primer. Cambridge: Cambridge University Press.
• Louviere, J., Hensher, D., & J. Swait (2000). Stated Choice Methods. Cambridge: Cambridge University Press.
• Reutskaja, E., Nagel, R., Camerer, C. F., Rangel, A. (2011). Search Dynamics in Consumer Choice under Time Pressure: An Eye-Tracking Study. American Economic Review, 101(2), 900-926. doi: 10.1257/aer.101.2.900
• Scarpa, R., Thiene, M., Hensher, D. A. (2010). Monitoring Choice Task Attribute Attendance in Nonmarket Valuation of Multiple Park Management Services: Does It Matter? Land Economics, 86(4), 817-839.
• Swait, J., Louviere, J. (1993). The role of the scale parameter in the estimation and comparison of multinomial logit models. Journal of Marketing Research, XXX(August), 305-314.