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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorBroekel, T
dc.contributor.authorLewis, C.Z.
dc.date.accessioned2018-09-03T17:00:50Z
dc.date.available2018-09-03T17:00:50Z
dc.date.issued2018
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/30820
dc.description.abstractThis study provides theoretical argumentation for the use of multilateral proximity measures when studying tie formation in knowledge networks. This study also argues for a distinction between successful and unsuccessful collaboration when studying tie formation in knowledge networks. These theoretical arguments are tested on a sample of organisations collaborating in consortia which applied for a subsidy under the FP7 (2007-2013) “space” programme using promising exponential random graph models methodology. Evidence is found to support the claim that it is useful to study knowledge networks in a multilateral as opposed to a bilateral manner. Both organisation level and consortia level variables have significant effects on tie formation in the studied knowledge network. Evidence is also found to support the claim that it is useful to distinguish between successful and unsuccessful collaboration in knowledge networks.Variables are found to have effect on both successful and unsuccessful collaboration, raising questions about the economic value of collaboration ties in knowledge networks.
dc.description.sponsorshipUtrecht University
dc.format.extent1993443
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleComplicating Innovative Knowledge Networks: Evidence from the FP7 (2007-2013) “space” Programme
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsExponential random graph models, proximity, network analysis, space, multilateral, success
dc.subject.courseuuHuman Geography


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