 Evaluating university industry collaborative research centersElizabeth Gibson, Tugrul U. Daim and Marina Dabic () Technological Forecasting and Social Change, 2019, vol. 146, issue C, 181-202 Abstract: This research provides performance metrics for cooperative research centers that enhance translational research through partnerships formed by government, industry and academia. Centers are part of complex ecosystems and vary greatly in the type of science conducted, organizational structures and expected outcomes. The ability to realize their objectives depends on transparent measurement systems to assist in decision making in research translation. We introduce a hierarchical decision model that uses both quantitative and qualitative metrics. A generalizable model is developed based upon program goals. The results are validated through consultation with experts. The method is illustrated using data from the National Science Foundation's industry/university cooperative research center (IUCRC) program. The methodology provides a basis for a generalizable model and measurement system to compares performance of university science and engineering focused research centers supported by industry and government. Keywords: Research and Development Management; Hierarchical Decision Modeling; Industry University Collaboration; National Science Foundation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:146:y:2019:i:c:p:181-202 DOI: 10.1016/j.techfore.2019.05.014 Access Statistics for this article Technological Forecasting and Social Change is currently edited by Fred Phillips More articles in Technological Forecasting and Social Change from Elsevier |
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