Towards a Framework for Managing Knowledge Integration in University-Industry Collaboration Projects
Abstract
Previous studies have called for more research on knowledge management in collaborative projects between university and industry. The scientific community urges the development of managerial mechanisms that will stimulate innovation outcomes and make government-funded projects to generate more long-term value for the society. This study is intended to contribute to close this gap through development of a practical framework for management of universityindustry collaboration with knowledge transformation in focus. It concentrates on how to manage the innovation process by leveraging creation, accumulation, dissemination, application, storing, and retrieving of knowledge in university-industry innovation projects. The context for this investigation was a Norwegian region with a local university campus and local maritime/marine companies, mostly concerned with mechanical engineering. Ten in-depth interviews with CEO’s, project managers and researches experienced in such projects were undertaken. The questions covered different topics, including project strategy, objectives, facilitation and accumulation of knowledge. The study reviewed knowledge management models in the literature, and found Wallin and Von Krogh’s five-step model for the integration of knowledge in open innovation setting suitable for the university-industry context chosen. The results propose a conceptual process model of knowledge management in university-industry innovation projects, which addresses the initiation of specific strategic efforts on organisational, collaborative and project levels. These efforts are intended to ensure the partners’ commitment to the project, which in turn enables and leverages knowledge co-creation and exploitation. The findings provide the potential to contribute to more effective and efficient management of the innovation processes between industry and university and reinforce a knowledge-based society. The sample size will be extended be more interviews to extend the data basis in the future.