Several studies have shown that connecting to people in other networks foster creativity and innovation. However, it is often difficult to tell what the prospective value of such alliances is. Cooperative game theory offers an a priori estimation of the value of future collaborations. We present an agent-based social simulation approach to recommending valuable peers in networked innovation. Results indicate that power as such does not lead to a winning coalition in networked innovation. The recommendation proved to be successful for low-strength agents, which connected to high-strength agents in their network. Future work includes tests in real-life and other recommendation strategies.
|Journal||Journal of Universal Computer Science|
|Publication status||Published - Jan 2011|
- open innovation
- networked innovation
- artificial intelligence
- recommender system
- coalition formation