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

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.