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Measuring Multiple-Path Technology Transfer Efficiency in Chinese Universities: A Network DEA-Tobit Approach

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Abstract

China possesses one of the largest university systems globally, and the focus of numerous previous studies has been on technology transfer from these universities. However, limited attention has been given to these aspects due to the absence of official data on spin-offs, technology transfer offices (TTOs), and research fields of universities. This paper aims to address this research gap by utilizing network DEA-Malmquist and Tobit models. The study specifically focuses on multiple-path of technology transfer, including patent sale and licensing, collaborative and contract research, and spin-offs. Furthermore, it measures the impact of various factors, including TTOs and research fields of universities, on efficiency. The findings are as follows: (1) The efficiency analysis reveals significant variations in the efficiency of the R&D stage and technology transfer stage among Chinese universities. The efficiency of the technology transfer stage is notably unsatisfactory. From 2011 to 2018, the efficiency of the R&D stage increased by 8.4%, while the efficiency of the technology transfer stage decreased by 3.5%. The overall efficiency witnessed a slight decline of 1.2%. (2) The Malmquist analysis demonstrates that 56.9% of universities experience efficiency growth in the R&D stage, whereas only 33% of universities exhibit efficiency growth in the technology transfer stage. The remaining universities either experience efficiency stagnation or a slight decline. (3) The analysis of influencing factors reveals that TTO capacity and the research fields significantly impact the technology transfer efficiency. This implies that it is crucial to consider not only the TTO but also the influence of the research fields of study on the efficiency and paths of technology transfer.

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Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Notes

  1. https://www.most.gov.cn/

  2. It refers to a group of universities directly under the management of the Ministry of Education of the People’s Republic of China, with the aim of taking the first step in exploring reforms and playing a model role in improving teaching, scientific research and social services.

  3. https://www.tianyancha.com/

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Acknowledgements

We appreciate the reviewers for their insightful suggestions.

Funding

This work was financially supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region (Grant No. 2023D01C28), the Ph.D. Scientific research Start-up Project of Xinjiang University (Grant No. BS202104), the Tianchi Doctoral Project of Xinjiang (Grant No. TCBS202050), the Xinjiang High-level Talents Tianchi Program (Grant No. TCBR202104), and the National Natural Science Foundation Project (Grant No. 72071196).

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Authors and Affiliations

  1. School of Politics and Public Administration, Xinjiang University, Urumqi, 830046, China

    Kun Chen, Abduhalik Wupur & Xu Liu

  2. Collaborative Innovation Center for National Security Research, Xinjiang University, Urumqi, 830046, China

    Kun Chen, Abduhalik Wupur & Xu Liu

  3. Institutes of Science and Development, Chinese Academy of Sciences, Beijing, 100190, China

    Guo-liang Yang

  4. School of Economics, Beijing Technology and Business University, Beijing, 100048, China

    Guo-liang Yang

  5. University of Chinese Academy of Sciences, Beijing, 100049, China

    Guo-liang Yang

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  1. Kun Chen
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Contributions

Kun Chen (First Author): conceptualization, methodology, investigation, formal analysis, writing—original draft.  Abduhalik Wupur (Corresponding Author): data curation, formal analysis, writing—original draft, writing—review and editing.  Xu Liu: data curation, writing—review and editing.  Guo-liang Yang: supervision, conceptualization, methodology, review and editing.

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Correspondence to Abduhalik Wupur.

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Appendix

Appendix

Table 6 Full name and abbreviation of key universities of China
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Chen, K., Wupur, A., Liu, X. et al. Measuring Multiple-Path Technology Transfer Efficiency in Chinese Universities: A Network DEA-Tobit Approach. J Knowl Econ (2024). https://doi.org/10.1007/s13132-024-01971-4

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