5.00 credits
30.0 h
Q1
Teacher(s)
Gailly Benoît;
Language
English
Prerequisites
This course is reserved for students with a bachelor's degree in business engineering or students with equivalent quantitative method skills.
This class cannot be taken without LLSMS2040
This class cannot be taken without LLSMS2040
Main themes
See LLSMS2040
Learning outcomes
At the end of this learning unit, the student is able to : | |
| 1 | See LLSMS2040 |
Content
See LSMS 2040
Teaching methods
See LSMS 2040
Evaluation methods
Evaluation criteria
By submitting an assignment for evaluation:
you assert that it accurately reflects the facts and to do so you need to have verified the facts, especially if they originate from generative AI resources;
you assert that all your sources that go beyond common knowledge are suitably attributed. Common knowledge is what a knowledgeable reader can assess without requiring confirmation from a separate source;
you assert that you have respected all specific requirements of your assigned work, in particular requirements for transparency and documentation of process, or have explained yourself where this was not possible.
If any of these assertions are not true, whether by intent or negligence, you have violated your commitment to truth, and possibly other aspects of academic integrity. This constitutes academic misconduct.
- Relevance, originality and ambition of the group project
- Mobilization of key innovation management concepts and methods
- Quality and scope of data, references and sources used
- Professionalism and rigor of methodological approach
- Ability to synthesize results and draw implications and limitations
- Critical thinking, ability to nuance and entrepreneurial mindset
- Clarity, style and structure of presentations (written and oral)
- Compliance to guidelines
- Type of evaluation: Preparation of group readings and group work presentation
- Comments: Compulsory attendance for group workshops and corporate testimonials
- The evaluation includes class participation (up to two bonus points)
- Oral: No
- Written: No
- Unavailability or comments: No
- Oral: No (See LSMS2040)
- Written: No
- Unavailability or comments: Teacher-run schedule
By submitting an assignment for evaluation:
you assert that it accurately reflects the facts and to do so you need to have verified the facts, especially if they originate from generative AI resources;
you assert that all your sources that go beyond common knowledge are suitably attributed. Common knowledge is what a knowledgeable reader can assess without requiring confirmation from a separate source;
you assert that you have respected all specific requirements of your assigned work, in particular requirements for transparency and documentation of process, or have explained yourself where this was not possible.
If any of these assertions are not true, whether by intent or negligence, you have violated your commitment to truth, and possibly other aspects of academic integrity. This constitutes academic misconduct.
Other information
This class is coupled with LSMS 2040 Innovation Management I
Online resources
See LSMS 2040
Bibliography
See LSMS 2040
Faculty or entity
CLSM
