Examining the efficiency of regional university technology transfer in China: A mixed-integer generalized data envelopment analysis framework

In university technology transfer performance assessment, some variables, such as labor and contracts, must be treated as integer-valued variables. Usually, the reference points obtained by the conventional data envelopment analysis (DEA) method are unrealistic when one of the input/output measures is an integer value. As a result, several integer DEA models have been proposed over the last decade. However, these models are based only on self-evaluation. In some cases, when a large gap exists between the best- and worst-performing units, the improvement path based on self-evaluation can be inappropriate. To overcome this issue, we propose a mixedinteger generalized DEA model based on peer evaluation to evaluate the efficiency level of regional university technology transfer in China. A sample of 27 provinces in China from 2008 to 2015 is used in the study. The results reveal that the eastern region, on average, obtained the highest level of efficiency among the three regions in China, whereas the western region presented a poor efficiency level. This is consistent with the current stage of development. Several recommendations are suggested for promoting technology transfer in the western region.

Automated summary

This article discusses the issues in performance assessment of university technology transfer and proposes a mixed-integer generalized DEA model based on peer evaluation to address the problem. The study uses a sample of 27 provinces in China and finds that the eastern region has the highest level of efficiency in technology transfer, while the western region lags behind.