Defining Dimensions in Expertise Recommender Systems for Enhancing Open Collaborative Innovation

نویسندگان

  • Jennifer Nguyen
  • A. Pereda
  • Germán Sánchez
  • Cecilio Angulo
چکیده

In open innovation a firm’s R&D crosses not only internal boundaries but disciplines. It is an interactive process of knowledge generation and transfer between internal and external firms. However, the search for an external partner can be time consuming and costly. Open innovation marketplaces broker relationships between seekers and solvers of challenges. Seekers have a problem which they need to solve and solvers are a community of people with the right skills to discover innovative ideas to address them. Despite the assistance of open innovation marketplaces, the process of matching seekers and solvers remains a challenge. It will be argued in this article that expertise recommender systems in an open innovation marketplace can facilitate finding the “right partner” leading to benefits not only for the seeker and the solver but also for the marketplace. With this aim, a list of appropriated dimensions to be considered for the expertise recommender system are defined. An illustrative example is also provided.

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تاریخ انتشار 2014