NBD404 R&D and Intellectual Property
Spring 2019Autumn 2019
Business innovation and success are massively affected by the characteristics of its institutional environment; subsidized funding possibilities and rewards for innovation such as prizes and intellectual property rights (e.g., patents) are among the prominent ones. In the course we work on understanding these institutions and their consequences for the innovation process. We discuss the benefits and challenges of cumulative innovation, patents- and copyright enforcement, and IP licensing. Furthermore, we analyze the interplay between specific business and market conditions (e.g., competition, network effects) and the incentives to innovate. Thereby, we also focus on the optimal organization of the innovation process (e.g., in joint ventures) and the importance of the market for innovation (specialization on innovation vs. in-house innovation). In a nutshell, the course provides a toolbox to analyze the ingredients for and threats to a successful commercial viability of innovations
Knowledge - Upon successful completion the student
- has advanced knowledge of theories on R&D and intellectual property.
- has thorough knowledge to reflect critically on theories and empirical findings.
- can demonstrate to be familiar with research in the fields of R&D and intellectual property.
Skills - Upon completion of the course the student
- has acquired skills in applying theories, knowledge and tools relevant within innovation and intellectual property.
- has developed good analytical skills.
- can undertake an research project on innovation and intellectual property.
Competences - Upon completion of the course the student
- can analyze relevant literature and has the insights to connect theory with practice.
- can reflect critical on theories, methods, tools and data within the field.
- has developed collaborative and co-creative skills.
Group project, 2-4 students in each group (30%) - grading scale A-F
Written school exam, 3 hours (70%) - grading scale A-F
Knowledge of a statistical software will be helpful for the group assignment.
To be announced
- ECTS Credits
- Teaching language
Autumn. Offered Autumn 2018
Associate Professor Steffen Juranek and Associate Professor Malin Arve, Department of Business and Management Science.