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Evaluating university industry collaborative research centers

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  • Gibson, Elizabeth
  • Daim, Tugrul U.
  • Dabic, Marina

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.

Suggested Citation

  • Gibson, Elizabeth & Daim, Tugrul U. & Dabic, Marina, 2019. "Evaluating university industry collaborative research centers," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 181-202.
    • Handle: RePEc:eee:tefoso:v:146:y:2019:i:c:p:181-202
    DOI: 10.1016/j.techfore.2019.05.014
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    7. Heidary Dahooie, Jalil & Mohammadi, Navid & Daim, Tugrul & Vanaki, Amir Salar & Zavadskas, Edmundas Kazimieras, 2021. "Matching of technological forecasting technique to a technology using fuzzy multi-attribute decision-making methods: Case study from the aerospace industry," Technology in Society, Elsevier, vol. 67(C).
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