APPLIES TO ACADEMIC YEAR 2014/2015
DRE 2011 Marketing Models
Responsible for the course
Rutger Daniel van Oest, Auke Hunneman
Department of Marketing
According to study plan
Language of instruction
Please note that this course will be revised before it is offered again.
This course is designed to provide an introduction to the area of quantitative marketing models using secondary data. It will give students a fundamental understanding and hands-on experience with commonly used empirical models in business and social science.
A fundamental understanding and hands-on experience with commonly used empirical models in business and social science. After completion of the seminar, participants should be able to a) understand the conditions under which the various models are appropriate to apply, b) implement these models using statistical software, c) interpret the model outcomes, and d) be able to read quantitative papers in good marketing journals.
It is assumed that every student has basic statistical working knowledge.
Admission to a PhD Programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of admission to a PhD programme when signing up for a course with the doctoral administration. Other candidates may be allowed to sit in on courses by approval of the courseleader. Sitting in on courses does not permit registration for courses, handing in exams or gaining credits for the course. Course certificates or conformation letters will not be issued for sitting in on courses
A complete list of articles and book chapters will be distributed during the first meeting. Emphasis will be put on articles that have appeared in major quantitative outsets such as Marketing Science, Journal of Marketing Research, Journal of Marketing, Quantitative Marketing and Economics, International Journal of Research in Marketing, or Journal of Retailing.
An extensive list of recommended readings will be provided during the first meeting.
This seminar will discuss a broad range of quantitative models which can be applied to a wide variety of marketing decisions. The model selection reflects the variety of secondary data common in marketing; it distinguishes between individual consumer-level and aggregate sales-level models.
Standard statistical software and possibly a programming environment.
Learning process and workload
Lectures 30 hours, preparation 140 hours, total 170 hours.
The class will meet every other day for two weeks. The class will employ a combination of lectures and discussions of readings, as well as assignments to be completed outside class. There will also be a written exam.
The course grade will be based on the following:
- 40% - Assignments, which may include empirical analysis, analytical exercises, research proposal, and/or paper review
- 60% - Written 3 hour exam
All parts of the evaluation must be passed in order to get a grade in the course. The course will be graded A - F.
DRE 20111 accounts for 100% of the final grade in DRE 2011
Examination support materials
A bilingual dictionary and BI-approved exam calculator.
Exam aids at written examinations are explained under exam information in our web-based Student handbook. Please note use of calculator and dictionary. http://www.bi.edu/studenthandbook/examaids
Re-takes are only possible at the next time a course will be held. When the course evaluation has a separate exam code for each part of the evaluation it is possible to retake parts of the evaluation. Otherwise, the whole course must be re-evaluated when a student wants to retake an exam.
Academic honesty and trust are important to all of us as individuals, and represent values that are encouraged and promoted by the honor code system. This is a most significant university tradition. Students are responsible for familiarizing themselves with the ideals of the honor code system, to which the faculty are also deeply committed.
Any violation of the honor code will be dealt with in accordance with BI’s procedures for cheating. These issues are a serious matter to everyone associated with the programs at BI and are at the heart of the honor code and academic integrity. If you have any questions about your responsibilities under the honor code, please ask.