Syllabus

Title
5295 Advanced Marketing Research Methods
Instructors
Univ.Prof. Dr. Nadia Abou Nabout, Univ.Prof.i.R. Dr. Sylvia Frühwirth-Schnatter
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/17/16 to 02/26/16
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Dates
Day Date Time Room
Tuesday 03/01/16 03:00 PM - 06:30 PM LC.-1.038
Tuesday 03/15/16 03:00 PM - 06:30 PM LC.-1.038
Friday 03/18/16 09:00 AM - 01:00 PM D2.0.392
Tuesday 04/05/16 03:00 PM - 06:30 PM LC.-1.038
Tuesday 04/12/16 03:00 PM - 06:30 PM LC.-1.038
Tuesday 05/03/16 03:00 PM - 07:30 PM D2.0.392
Contents
This course covers a set of quantitative research methods considered to be important for both marketing researchers and practitioners. Such methods include market response modeling, binary logit/probit and discrete choice models.

The course builds on the content already covered in the “marketing research” and “marketing engineering” courses, but expands them along two dimensions: (1) The conceptual and statistical assumptions underlying methods discussed in previous classes are challenged and the portfolio of available data analytical methods is extended. (2) The course offers opportunities to train the application of these methods in various marketing decision making contexts and to derive managerial conclusions.

Learning outcomes

The emphasis in this course is on a more thorough understanding of marketing research techniques and to demonstrate why extensions of standard models are necessary and useful in specific marketing environments.

By the end of this course, students will be able to:

  • Understand the assumptions, limitations and possible extensions of standard marketing research methods
  • Integrate the components discussed in this course into the topics covered in the basic marketing research course
  • Understand the practical importance and relevance of the discussed methods in real-world marketing decision making contexts
  • Familiarize themselves with suitable computer software environments (SPSS, R) to analyze marketing data sets and to interpret the results
  • Further improve their presentation and team working skills
Teaching/learning method(s)

The course is taught using a mix of interactive lectures, business cases, class discussions, computer exercises, and student presentations.

The structure of this course is organized in two major parts:

  1. The first part is made up of three to four introductory sessions. Each of these sessions focuses on one specific quantitative research method. Students will have to be prepared for class discussion (there will be reading assignments for each session). While in the first half of each session we will discuss the conceptual idea, the statistical properties, and interpretative aspects of the focused method, the second half trains students to use and apply it in a marketing context. The latter is accomplished by data case assignments, which are completed in class under supervision and assistance by the instructors. The results of the data case assignments are presented and discussed at the end of the session.
  2. The second part builds on the introductory sessions, but is organized in breakout groups. Each group of students will work on a typical business case mimicking a real-world marketing research issue using the concepts and methods learned throughout the program. The findings will be presented in a final presentation session.
Assessment

Grading of this course is based on the following components:

  • In-class participation (10%)
  • In-class data case assignments (20%)
  • Documentation and performance on final presentation (70%)
Prerequisites for participation and waiting lists
Sucessful completion of the courses "Marketing Research and Data Analysis" is a prerequisite to attend this course.
Last edited: 2015-11-30



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