Innovation Management
- UE code EINGM200
-
Schedule
30Quarter 2
- ECTS Credits 5
-
Language
Français
- Teacher Castiaux Annick
- Capacity to analyse the situation of an organisation and to develop, at a strategic level, a relevant innovation project, including a prospective analysis of its possible impacts ;
- Understanding of the various factors influencing the innovation dynamics ;
- Understanding og the opportunities and limits of collaborations for innovation ;
- Integration of society challenges in innovation (ethical dimension of innovation) ;
- Large vision of methods and tools for innovation management.
The main objectives of the course are
This course analyses the different facettes of the innovation process. It includes five theoretical parts: (1) Innovation Dynamics ; (2) Innovation Strategy ; (3) Open Innovation ; (4) Sustainable Innovation ; (5) Managerial Innovation. Additionnally, methods and tools to manage innovation will be studied, looking at their relevance following the context and innovation type. In particular, we will consider new agile methods that are more and more in use in the digital industry and are spreading in other sector.
The final evaluation is a written work realised by groups of 3 to 4 students. The written work can be either a field of innovation management that has not been covered in the course (literature review of this field) or a case study (which means interviews of relevant actors of the case). The evaluation of the final work will be based on the evalution of the paper (60%) and an individual oral exam (40%).
Reading 1 : Christensen (1999). “The Innovator’s Dilemma.” Harvard Business School Press.
Reading 2 : Markides & Geroski (2003). “Colonizers and consolidators: The two cultures of Corporate Strategy,” Strategy+Business Issue 3
Reading 3 : Teece and Pisano (1997). “Dynamic Capabilities and Strategic Management”
Reading 4 : Von Hippel (2005). “Democratizing Innovation.” The MIT Press.
Reading 5 : Birkinshaw, Hamel and Mol (2008). “Management innovation,” The Academy of Management Review, Vol. 33(3)
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 |