In the last 10 years a new paradigm for creating innovations by also using external sources and paths to market has emerged and became popular. This paradigm is known as open innovation. Through the possible inclusion of these external sources for the innovation process a larger number of people (and thereby knowledge and skills) are available. People and organizations are connected in a network (so called open innovation network) of collaboration. These networks are valuable and provide an important source for composing teams, working on specific open innovation projects inside an open innovation community. We address the problem of composing such a team given the complexity of the network and innovation tasks with algorithmic team recommendation. Thereby different challenges have to be regarded such as including different aspects of team composition that were subject of research in the social and psychological sciences. We base this article on our previous work on the categorization of influencing team composition aspects and create a team composition model based uniquely on social aspects as an example for mapping classical team composition models onto our categorization. Furthermore, we describe typical issues arising when creating team composition models from scratch when mapping them onto our proposed meta model that represents the main component of our recommender approach.
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