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Lehrende: Jasper David Brüns; Prof. Dr. Martin Meißner
Veranstaltungsart:
Seminar
Orga-Einheit: Corporate Management & Economics
Anzeige im Stundenplan:
VSCME_I
Semesterwochenstunden:
3
Credits:
9,0
Hinweis: In Ihrer Prüfungsordnung können abweichende Credits festgelegt sein.
Standort:
Campus der Zeppelin Universität
Unterrichtssprache:
Englisch
Min. | Max. Teilnehmerzahl:
8 | 22
Prioritätsschema: Standard-Priorisierung
Inhalte:
Are you planning to run your own start-up, and would you like to find out which product or service components have value for your potential customers? Would you like to understand how companies make decisions which products to create? Would you like to learn how to measure customers willingness-to-pay?
Participants of this course develop a sound understanding of the benefits that conjoint analytic preferences measurement approaches and alternative advanced compositional approaches have to offer. As a participant, you gain practical experience how to use conjoint-analytic methods and developed a better understanding of the value of measuring preferences.
The course starts with introducing the basic concepts behind the measurement of stated preferences, specifically focusing on conjoint analysis. The most often used approaches, i.e. traditional conjoint analysis, adaptive conjoint analysis and choice-based conjoint analysis are introduced. We deliberate on advantages and disadvantages of the approaches and discuss advanced compositional approaches, like pairwise-comparison based preference measurement. We will further discuss important stages of designing a preference measurement study. We pay special attention to the types of practical questions that conjoint analysis can answer. We also discuss the most important questions you should answer before setting up your preference measurement/conjoint study: What is the optimal choice of attributes and attribute level? What is a good experimental design? How should I design my survey and present potential choice scenarios? How do I analyze the results?
You will work together in groups of three or four students and run a small-scale preference measurement study. You can pick a product or service that interests you the most and test it in your empirical project. You will present the results in class and document them in a short seminar report. Grading will be based on the presentation in class (30%) and the seminar report (70%).
The lectures deal with the following subjects:
· Introduction – Marketing research basics
· Preference measurement – Overview and basic concepts
· Most often used preference measurement techniques
· Complexity in consumer product choice
· Most often used techniques for complex products
· Which preference measurement approach should I use?
· Comparison of preference measurement approaches
· Build your own preference measurement study
Lernziele:
· Learn about important theories, models and strategies for measuring consumer preferences.
· Be able to discuss advantages and disadvantages of alternative preference measurement approaches.
· Be able to design and run a preference measurement study for a product of your choice.
· Be able to analyze preference measurement data and report the results.
Weitere Informationen zu den Prüfungsleistungen:
Grading will be based on:
1. Presentation in class (30%)
Your task is to present your preference measurement design as well as the empirical results in class. Students work in groups of three or four. Every group is expected to give a 25 minutes presentation in class followed by questions from the audience. Students are supposed to motivate the relevance of carrying out the empirical study, present the design of the study, document the empirical findings and discuss related managerial implications.
2. Seminar report (70%)
The report should not be longer than 15 pages, doubles-spaced, Calibri font, 11-point size (excluding cover pages, table of contents, appendix material).
Literatur:
· Bradlow, Eric T. (2005), “Current Issues and a ‘Wish List’ for Conjoint Analysis,” Applied Stochastic Models in Business and Industry, 21 (4-5), 319-323.
· Hauser, John R. and Vithala Rao (2003), “Conjoint Analysis, Related Modeling, and Applications,” in Advances in Marketing Research: Progress and Prospects, in Marketing Research and Modeling: Progress and Prospects, Wind, Jerry and Paul Green (eds.), New York: Springer, 141-168.
· Huber, Joel (1997), “What We Have Learned from 20 Years of Conjoint Research: When to Use Self-Explicated, Graded Pairs, Full Profiles or Choice Experiments,” Sawtooth Software Conference Proceedings, Sequim, WA., 243-256.
· Scholz, Sören W., Martin Meissner, and Reinhold Decker (2010), “Measuring Consumer Preferences for Complex Products: A Compositional Approach Based on Paired Comparisons,” Journal of Marketing Research, 47 (4), 685-698.
· Steiner, Michael, and Martin Meißner (2018), “A User’s Guide to the Galaxy of Conjoint Analysis and Compositional Preference Measurement,” Marketing ZfP, 40 (2), 3-25.
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