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Evaluating efficiency and efficiency change pattern of US universities: early stage performance of university technology transfer

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  • Jisun Kim
  • Tugrul U. Daim
  • Timothy R. Anderson

Abstract

Universities have different research environments and attitudes toward commercialisation of their discoveries than to industries. These differences are inherent in the distinctive missions, roles, and organisational structures. Therefore, performance of technology transfer of universities depends on different organisational setting and their perceptions of usage of their knowledge or technology for commercial purpose. There have been intensive academic efforts to measure the performance of technology transfer efforts using well-known evaluation methods such as stochastic frontier efficiency and data envelopment analysis (DEA). This paper adopt similar approach with those studies using DEA, but different in two ways. First, this research focuses on early stage of university technology transfer by measuring how many disclosures a university produced given research expenditure over years using DEA and Malmquist index. It is assumed that a university with more intention to licensing will have more disclosures. Second, classifications of universities' performance in disclosing their research results are suggested to provide better understanding of their behaviour in technology transfer. The result presents 12 different groups of 28 US universities with discussion of their organisational setting.

Suggested Citation

  • Jisun Kim & Tugrul U. Daim & Timothy R. Anderson, 2011. "Evaluating efficiency and efficiency change pattern of US universities: early stage performance of university technology transfer," International Journal of Transitions and Innovation Systems, Inderscience Enterprises Ltd, vol. 1(3), pages 253-270.
  • Handle: RePEc:ids:ijtisy:v:1:y:2011:i:3:p:253-270
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    Cited by:

    1. Shui‐ying Jin & Xiao‐lin Zhou & Yung‐ho Chiu, 2021. "The parent–subsidiary knowledge transfer efficiency of Chinese–African multinational enterprises based on a metafrontier epsilon‐based measure model," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(2), pages 479-492, March.

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