Diffusion models of innovation are an important tool used by companies to plan the introduction of novel products on the market. Under optimal conditions, companies will schedule their innovations in a way that a new one becomes available at the time when the previous one has reached a saturation phase and does not spread to any further. This is comparably easy to achieve in the case of standard products which are centrally planned, but not when products are customized or when users are involved to drive the innovation process in different directions.
This problem is described in a recent wi1 publication which can be found here: https://link.springer.com/chapter/10.1007/978-3-319-67798-9_14.
Students are invited to write a thesis in which they study the diffusion of innovations on the basis of detailed industrial sales data which will be provided to them. During their work, students are expected to perform the following tasks:
- Get some knowledge about software-based data analysis
- Process the source data and identify diffusion patterns on different levels
- Study interdependencies between the patterns and describe positive and negative effects
- Give recommendations for companies how to plan and manage their innovations
Student writing this thesis will not get around doing some basic programming work.