Consumer Behaviour and Experience
- UE code ELMSM408
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Schedule
30Quarter 2
- ECTS Credits 5
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Language
Français
- Teacher Decrop Alain
Regarding learning outcomes for students, the course mainly aims at the acquisition of knowledge, the application of a scientific approach and the reasoning as a socially responsible stakeholder. To a lesser extent, it also aims to enhance students’ communication skills as well as their personal and professional self-development.
The aim of this course is to broaden students' knowledge of concepts and processes related to the study of consumers and consumption, mainly borrowed from cognitive psychology, social psychology, and postmodern research. This course objective is to distance students from the classic paradigm of homo oeconomicus to get them to consider the consumer as much from its cognitive as emotional and behavioral aspects.
The outset of the course offers an introduction to basic concepts, to the history and to the discipline’s dominant trends. The course is built around consumers’ decision-making processes. A global model is proposed in the first part that will be used as a framework for the other lectures. The second part of the course focuses on mental/cognitive and social processes that underlie decisions and behaviors (i.e., motivation, beliefs and attitudes, information processing, learning). The third part is concerned with individual differences in behavior, related to consumers’ personality, lifestyles, values, emotions etc. Finally, the last part of the course examines environmental factors that influence decisions and behaviors (culture, social classes, group influences etc.). While lecturing, we will take a particular care in examining the importance and implications of analyzing consumer behavior for marketing strategy and operations.
The evaluation of students will be made by means of a paper and a written examination.
Course pack (slides) is available before the course on the webcampus platform.
The reference textbooks are
Training | Study programme | Block | Credits | Mandatory |
---|---|---|---|---|
Master 120 en ingénieur de gestion, à finalité spécialisée en data science | Standard | 0 | 5 | |
Master 60 en sciences de gestion | Standard | 0 | 5 | |
Master 120 en sciences de gestion, à finalité didactique | Standard | 0 | 5 | |
Master 120 en ingénieur de gestion, à finalité spécialisée en Analytics & Digital Business | Standard | 0 | 5 | |
Master 120 en sciences de gestion, à finalité spécialisée en Business Analysis & Integration | Standard | 0 | 5 | |
Master 60 en sciences de gestion | Standard | 1 | 5 | |
Master 120 en sciences de gestion, à finalité didactique | Standard | 1 | 5 | |
Master 120 en ingénieur de gestion, à finalité spécialisée en Analytics & Digital Business | Standard | 1 | 5 | |
Master 120 en sciences de gestion, à finalité spécialisée en Business Analysis & Integration | Standard | 1 | 5 | |
Master 120 en ingénieur de gestion, à finalité spécialisée en data science | Standard | 1 | 5 | |
Master 120 en sciences de gestion, à finalité didactique | Standard | 2 | 5 |