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dc.contributor.authorTriulzi, Giorgioen_US
dc.contributor.authorScholz, Ramonen_US
dc.contributor.authorPyka, Andreasen_US
dc.description.abstractIn the last two decades, University-Industry Relationships have played an outstanding role in shaping innovation activities in Biotechnology and Pharmaceuticals. Despite the growing importance and the considerable scope of these relationships, there still is an intensive and open debate on their short and long term effects on the research system in life sciences. So far, the extensive literature on this topic has not been able to provide a widely accepted answer. This work introduces a new way to analyse University-Industry Relationships (UIRs) which makes use of an agent-based simulation model. With the help of simulation experiments and the comparison of different scenario results, new insights on the effects of these relationships on the innovativeness of the research system can be gained. In particular, focusing on knowledge interactions among heterogeneous actors, we show that: (i) universities tend to shift from a basic to an applied research orientation as a consequence of relationships with industry, (ii) universities' innovative capabilities benefit from industry financial resources but not so much from cognitive resources of the companies, (iii) biotech companies' innovative capabilities largely benefit from the knowledge interaction with universities and (iv) adequate policies in terms of public basic research funding can contrast the negative effects of UIRs on university research orientation.en_US
dc.publisher|aUniv. Hohenheim, Forschungszentrum Innovation und Dienstleistung |cStuttgarten_US
dc.relation.ispartofseries|aFZID discussion papers |x33-2011en_US
dc.subject.keywordUniversity-Industry Relationshipsen_US
dc.subject.keywordKnowledge Dynamicsen_US
dc.subject.keywordUniversity Patentingen_US
dc.subject.keywordTechnology Transferen_US
dc.subject.keywordAgent-Based Modellingen_US
dc.titleR&D and knowledge dynamics in university-industry relationships in biotech and pharmaceuticals: An agent-based modelen_US
dc.typeWorking Paperen_US

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