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Technology transfer efficiency of universities in China: A three-stage framework based on the dynamic network slacks-based measurement model

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  • Ma, Ding
  • Cai, Zhishan
  • Zhu, Chengkai

Abstract

Despite being considered as the key provider of industry technology, universities still have a prominent issue of low efficiency in technology transfer. Understanding university technology transfer (UTT) efficiency from a decomposed perspective is essential because it traces the specific difficulties and UTT's improvement path. This study quantifies UTT efficiency from a sequential process encompassing research innovation, experimental development, and value creation stages in 31 Chinese universities. Based on the Dynamic Network Slacks-based Measurement (DNSBM) model, the stage efficiencies, inter-stage linkage efficiencies, and inter-period carry-over efficiencies can be evaluated. A Malmquist decomposition is further carried out to infer the paths and restrictions of efficiency enhancement. The results reveal that: 1) performance varies greatly across the three stages of UTT in China and the detachment of R&D and value creation efficiencies is prominent; 2) inter-stage linking efficiency losses manifest themselves in R&D output redundancy and trial contract inadequacy, while carry-over efficiency losses are primarily reflected in insufficient dynamic accumulation of funds; and 3) technical efficiency improvement plays a dominant role in total factor productivity (TFP) growth, particularly in the value creation stage. Breaking the barriers of TFP growth in the research innovation and experimental development stages hinges on technology progress, implying more resources should be allocated to improving R&D quality and trial success.

Suggested Citation

  • Ma, Ding & Cai, Zhishan & Zhu, Chengkai, 2022. "Technology transfer efficiency of universities in China: A three-stage framework based on the dynamic network slacks-based measurement model," Technology in Society, Elsevier, vol. 70(C).
    • Handle: RePEc:eee:teinso:v:70:y:2022:i:c:s0160791x22001725
    DOI: 10.1016/j.techsoc.2022.102031
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    3. Lei Ye & Ting Zhang & Xianzhong Cao & Senlin Hu & Gang Zeng, 2024. "Mapping the landscape of university technology flows in China using patent assignment data," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    4. See, Kok Fong & Ma, Zhanxin & Tian, Yuzhen, 2023. "Examining the efficiency of regional university technology transfer in China: A mixed-integer generalized data envelopment analysis framework," Technological Forecasting and Social Change, Elsevier, vol. 197(C).

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