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2011/2012  KAN-SMC_SM58  Marketing Research in Innovation Processes

English Title
Marketing Research in Innovation Processes

Course Information

Language English
Point 7,5 ECTS (225 SAT)
Type Mandatory
Level Full Degree Master
Duration One Semester
Time Table Please see course schedule at e-Campus
Study Board
Study Board for MSc in Economics and Business Administration
Course Coordinator
  • Marcus Schmidt - Department of Marketing
Main Category of the Course
  • Marketing
Last updated on 29 maj 2012
Learning Objectives
At the end of the course the excellent student is expected to be able to:
1. Discuss the strategic as well as the operational meaning and implication of different qualitative research approaches (such as grounded theory, ethnography, etc.), and of different methods for collecting, analyzing, interpreting and reporting data.
2. Discuss the strategic as well as the operational meaning and implication of a quantitative market research process in general, and of methods of value in product innovation processes, as for example: cluster analysis, perceptual mapping, concept testing and conjoint analysis.
3. Discuss what kind of knowledge and why that is valuable in different stages and decision situations in a product innovation process, and implicitly, how to integrate and make us of different types of knowledge (qualitative and quantitative) about end-users in innovation processes.
Marketing Research in Innovation Processes:
Assessment Oral with Written Assignment
Marking Scale 7-step scale
Censorship External examiners
Exam Period Autumn Term
Aids Please, see the detailed regulations below
Duration 20 Minutes
Oral individual examination is based on a mini-project (max.15 pages) that has been worked out in a group of 2-4 students.  The duration of the individual oral exam is 20 minutes (including assessment).
The make-up/re-exam takes place in Februar-March. If a student is ill during the regular oral exam, s/he will be able to re-use the mini-project at the make-up/re-exam. If the student was ill during the writing of the mini-project and did not contribute to mini-project, the make-up mini-project can be written individually or in groups (provided that other students are taking the make-up/re-exam). If the student did not pass the regular exam a new or revised project, confer advice from the examiner at the regular exam, must be handed in to a new deadline specified by the SMC secretariat.
Course Content
Like the previous courses, the structure of this course is impressed by its propositions and objectives. Thus, the first part of the course deals with the following issues: What represent a qualitative and a quantitative research question and what set’s the two methodologies apart? What qualitative and quantitative methods for collecting, analysing and representing data exists when concerned with knowledge creation about end-users preferences, values and behaviours. In the second and major part of the course our focus is on a selection of qualitative and quantitative analytical models and methods (as for example emphatic design, MEC, cluster and conjoint analysis) for integrating knowledge about and from end-users: in the fuzzy-front-end (ideation), in the testing and in the evaluation of ideas for product, brand and channel innovation. During this part of the course emphasis is put on applying models and methods in relation to a concrete innovation project.

This course is directly linked to the course ‘Marketing, Creativity and Innovation’ in that the course acts as a frame of reference and knowledge base for one empirical part of the SM20 semester project.

Over the years, several studies have supported the notion that ‘marketing as a set of values, knowledge creating processes and assets (brand identities and images, customer relationships and trust etc.) play a key role in product, brand market channel innovation processes. The focus in this course concerns this role in relation to the bringing-in and making-use of end-user knowledge in innovation processes. Accordingly, one objective of the course is to further develop the students’ competencies and skills about qualitative and quantitative methods of data collection, analysis and representation. Another and related objective concerns the particular context and decision situation where knowledge about end-users is asked for in innovation processes. Thus, a second objective concerns to develop the students’ abilities to decide on what kind of knowledge and why that is valuable in different stages and decision situations in an innovation process, and implicitly, how to integrate and make us of different types of knowledge about end-users in innovation processes.
Teaching Methods
The course consists of lectures, seminars and case-works.
  • Qualitative Research Methods in Public Relations and Marketing Communications(2002), Christine Daymon and Immy Holloway, Routledge.
  • Analyzing Qualitative Data, (1994), Edited by Alan Bryman and Robert Burgess, Routledge

·Qualitative Research & Evaluation Methods, (2002), Michael Quinn Patton, Sage Publications

  • Product Development and Target Market Segmentation(2009), Marcus J Schmidt and Svend Hollensen, Pearson.

A selection of articles about conjoint analysis and multidimensional scaling:

  • Buser, Samuel Jackson(1989) “A Counseling Practitioner's Primer to the Use of Multidimensional Scaling.” Journal of Counseling and Development, March, Vol. 67 Issue 7, p420, 4p, 1 diagram; (AN 4969345)
  • Green, Paul E. and Abba M. Krieger (1999) “Segmenting Markets with Conjoint Analysis.Journal of Marketing, October, Vol. 55 Issue 4, p20-31.
  • Gustafsson, Anders; Frederik Ekdahl, and Bo Bergman (1999) “Conjoint Analysis: A Useful Tool in the Design Process. Total Quality Management, May, Vol. 10 Issue 3, p327-343.
  • AddedMcCullough, Dick(2002) “A User's Guide to Conjoint Analysis”.Marketing Research, Summer, Vol. 14 Issue 2, p18-23.
  • Pegels, C. Carl and Chandra Sekar (1989) “Determining Strategic Groups Using Multidimensional Scaling”. Interfaces, May/Jun, Vol. 19 Issue 3, p47-57,
  • Pullman, Madeleine E.; Kimberly J. Dodson and William L. A. Moore.(1999). “Comparison of Conjoint Methods When There Are Many Attributes.”Marketing Letters, May, Vol. 10 Issue 2, p125-138.
  • Vriens, Marco(1993) “Solving Marketing Problems with Conjoint Analysis.” Journal of Marketing Management, Jan-Apr, Vol. 10 Issue 1-3, p37-55.