Performance of public-private collaborations in advanced technology research networks : network analyses of Genome Canada projects
| Document Type |
Thesis |
| Author |
Ryan, Camille |
| Email Address |
cami.ryan@usask.ca |
| URN |
etd-04272007-091239 |
| Title |
Performance of public-private collaborations in advanced technology research networks : network analyses of Genome Canada projects |
| Degree |
Doctor of Philosophy |
| Department |
Interdisciplinary Studies |
| Advisory Committee |
| Advisor Name
| Title
|
| Kerr, William A. |
Committee Chair |
| Ballantyne, Anne |
Committee Member |
| Dobni, Brooke |
Committee Member |
| Partridge, Mark |
Committee Member |
| Isaac, Grant E. |
Supervisor |
| Phillips, Peter W. B. |
Supervisor |
|
| Keywords |
- Genome Canada
- Public/Private Networks
- Intellectual Property
|
| Copyright Date |
2007-04-27 |
| Availability |
unrestricted |
Abstract
Globalisation and the quest for competitiveness in a global market represents a new era of connectedness within public-private networks of experts in an effort to pursue research objectives in advanced technology industries. Balancing the competing interests of public good and private gain, reducing the barriers in terms of access to knowledge and intellectual property and ensuring that efforts result in socially valuable outcomes in the form of new innovations can be difficult, to say the least. Although widely advocated and implemented, collaborations have not, as yet, been fully examined nor have appropriate performance evaluation models been developed to evaluate them. This dissertation hypothesizes that a history of social relationships or collaborative activity amongst network actors is positively correlated with high performance in networks. Incorporating descriptive statistics with the social network analysis tool, this dissertation proposes and tests a novel framework and compares two distinct Genome Canada funded research networks. Other factors explored are the roles of proximity, institution and research focus in characterizing network structure and in affecting performance.
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