Methods for Service and Marketing Research
- UE code ELMSM407
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Schedule
30Quarter 1
- ECTS Credits 5
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Language
Français
- Teacher
Regarding student’s competences, the course mainly develops knowledge and reasoning, scientific and systematic approaches and personal development and to a lesser extent the other competences of the competency framework, i.e., corporate citizenship, innovation and entrepreneurship, professional development, teamwork and leadership as well as communication and interpersonal skills.
The course Methods for Service & Marketing Research has two main objectives. First of all, it aims at training students in quantitative methods that are useful for solving marketing/service research problems. The second objective is to confront student with marketing/service problems, real data and statistical softwares in a decision-making perspective. This course thus deals with concepts, methods, and applications of decision modelling to address current issues faced by marketing managers. It provides students with skills to translate conceptual understanding into specific operational plans. Through the use of SAS for case studies and classroom exercises, students are trained to get the prestigious SAS Certification Young Potential (SCYP).
The course starts with a general introduction to the marketing research process with a service perspective as well as to marketing decision models and modelling (the so called “marketing engineering” approach). The methods (and topics) covered are exploratory and confirmatory factor analysis methods (measurement), regression analysis, simulation and optimization techniques (pricing), regression analysis with dummies and analysis of variance techniques (testing relationships between service marketing constructs), cluster and discriminant analysis (segmentation & targeting), judgment-based models (advertising budgeting). More specifically, this course aims at helping students understand by means of various examples and case studies, how analytical techniques and computer decision models can enhance decision making by converting data and information about markets to insights and decisions. It also provides students with software tools (SAS and Excel) that will enable them to apply the methodological approaches taught in the course to real marketing decision problems.
The topics covered are (2-hour session - example of content):
The evaluation of students is made by means of an ongoing assessment and a final written examination:
Course material and recommended readings
The course pack (slides) is available before the course on the web platform.
Reference textbooks (non-exhaustive list) are:
+ journal articles in Journal of Service Research, Journal of Marketing, Journal of Retailing, Recherche et Applications en Marketing (English version), etc.
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 |