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CM_SM55 - Knowledge for Product Innovation* (Q2)

Faculty
Marcus Schmidt (Dept. of Marketing), Jesper Clement (Dept. of Marketing)
Course Coordinator
Marcus Schmidt (Dept. of Marketing)
Prerequisite/progression of the course
This course is directly linked to the course ‘Market Creation Management’ in that the course acts as a frame of reference and knowledge base for one empirical part of the SM20 semester project.
Course Period
Week 42-49
Class Hours
Three-four class hours, one-three days a week.
7.5 ECTS
Aim of the course
Over the years, several studies have supported the notion that ‘marketing is 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 of 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’ competences 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, the second objective concerns the development of the students’ abilities to decide on, what kind of knowledge and why that kind of knowlege is valuable at different stages and decision situations in an innovation process, and implicitly, how to integrate and make use of different types of knowledge about end-users in innovation processes.
Course content, structure and teaching
Like the previous courses, the structure of this course is impressed by its propositions and objectives. The first part of the course deals with the following issues: What does a qualitative research question and quantitative research question represent, and what sets the two methodologies apart? What kind of qualitative and quantitative methods exist for collecting, analysing and representing data, when concerned with knowledge creation about end-users preferences, values and behaviours? In the second and major part of the course, 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 products, 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.
Teaching methods
The course consists of lectures, seminars and caseworks.
Examination
Oral individual examination, which is based on a mini-project that has been worked out by a group of three-four students. The mini-project and the oral presentation and discussion of models and methods dealt with in the project make up one part of the exam. Another part of the exam deals with the students' overall insight into and understanding of the qualitative and the quantitative paradigm, and about related methods for collecting, analysing and representing data.
Course literature
Indicative Literature
  • Qualitative Research Methods in Public Relations and Marketing Communications, 2002, Christine Daymon and Immy Holloway, Routledge
  • PDMA Handbook of New Product Development, (2005), second edition, editor: Kenneth B Kahn, Part Three.
A selection of influential 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.

Last updated by Jeanne Schultz 03/05/2010