Meal Consumer Research
Course content
An introduction to food consumer research as a scientific discipline that deals in a multi-disciplinary way with the understanding of the food choices made by consumers. Focus will be on presenting general and current food consumer research highlighting the importance of product cues (healthiness, sustainability and ethics) for consumer’s choices. Further, the course will introduce examples of consumer driven food innovation using relevant consumer methodologies. The role of consumer science in evidence-based policy making will be addressed.
The course will provide the students with an understanding of how individual factors and product cues can be used to segment consumers in the population of interest using online questionnaires combined with cluster analysis and profiling clusters with logistic regression.
An introduction to hedonic evaluation of foods and meals as well as classic scaling methods will be given. The course will focus on solving practical problems related to consumer driven innovative meal and food product design and evaluation.
At the end of the course the students will have designed their own questionnaire to evaluate consumer perceptions towards the characteristics of meals, have collected consumer data online, analysed their data using the appropriate statistical methods and software (R/R Studio), and have communicated written and orally their research results.
MSc Programme in Integrated Food Studies
After the completion of the course the student will have acquired the following knowledge, skills and competences
Knowledge
- Understand and describe food consumer science, different theories of food consumer behaviour and relevant consumer segments
- Reflect scientifically on consumer issues (e.g. health, sustainability, ethics) and their drive towards innovative food supply
- Explain the role of food and nutrition policy in food-related consumer decision making
- Understand and explain the design, testing and implementation of a questionnaire based consumer survey
- Indicate the appropriate methods for consumer survey data analysis (descriptive and inferential statistics)
- Implement hedonic evaluation of foods applying affective scales and rapid sensory methods
- Understand the role of food marketing on consumer decision making.
Skills
- Able to apply relevant consumer behaviour theories around food issues in the formulation, design of questionnaires and in planning data analysis
- Able to design consumer research taking in to account GDPR and ethical considerations
- Able to administer questionnaires and collect consumer data using IT platforms
- Able to apply principles of experimental design and statistical evaluation of consumer perceptions towards the characteristics of foods and meals
- Able to profile consumer segments by e.g. their socio-economic status, their attitudes, values, knowledge, hedonic responses to foods, liking of food products, etc.
- Able to use affective scales for the evaluation of foods and meals by consumers
- Able to use consumer research to support marketing strategies in food companies
- Communicate research results in scientific writing.
Competences
- Students will be able to provide evidence-based advice to the food sector, the public sector and the societal actors regarding the relevant consumer segments
- Students will be able to study consumer behaviour in relation to food, taking into account individual characteristics
- Students will be able to handle data following national and international ethical and GDPR standards
- Students should be able to collaborate and contribute effectively in team work.
The course with consists of lectures given by researchers
working within the overlapping fields of consumer and sensory
sciences, exercises and team work.
Lectures are designed to encourage participation and support active
student learning. Theoretical concepts and methods are taught in
the lectures, and examples of food consumer research will be
illustrated with most recent peer-reviewed publications.
Problem-based learning approach will be implemented to enable
students to apply the knowledge, skills and competences of the
course in solving a specific practical food or meal related
challenge.
See Absalon for a list of course literature.
It is recommended to have basic statistical knowledge and to be
acquainted with R software.
It is recommended to have understanding of the determinants of food
intake and food choices.
It is recommended to have knowledge about the Sociology of Food and
Eating, and of Qualitative, Quantitative, and Case-based Social
Science Methods.
Academic qualifications equivalent to a BSc degree is
recommended.
For the data analysis in this course you need a laptop and download R and R Studio.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Written examination, 2 hours under invigilationWritten assignment, during the courseThe exam grade comprises of two parts, a challenge document/report and an individual written exam.
The challenge document/report in teams (30% of the grade).
The individual written examination, which will be a multiple choice questionnaire (70% of the grade).
Both parts must be passed in order for the student to pass the course. - Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners.
Criteria for exam assessment
See Learning Outcome
Single subject courses (day)
- Category
- Hours
- Lectures
- 42
- Preparation
- 74
- Exercises
- 20
- E-Learning
- 2
- Project work
- 62
- Guidance
- 4
- Exam
- 2
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NFOK20002U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Schedulegroup
-
A
- Capacity
- No limitation
- Studyboard
- Study Board of Food, Human Nutrition and Sports
Contracting department
- Department of Food Science
- Department of Nutrition, Exercise and Sports
Contracting faculty
- Faculty of Science
Course Coordinators
- Armando Perez-Cueto (4-647366684369727267316e7831676e)
- Helene Christine Reinbach (15-6a676e6770673074676b706463656a4268717166306d7730666d)
- Bodil Helene Allesen-Holm
(4-656b646b4369727267316e7831676e)
(Course coordinator)
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