Abstract: Universities are the source of R&D and innovation and an important part of the national innovation system. How to improve and evaluate the efficiency of universities′ S&T achievements transformation has become a topic of intense importance for the academic as well as the scientific management departments. Series of laws and regulations has issued to promote the transformation of S&T achievements. One requires that it is necessary to establish a performance evaluation system for scientific research institutions and universities on S&T achievements transformation, which shall be used as a reference for supporting the units. The establishment of an evaluation system needs to clarify the concepts related to the transformation of scientific and technological achievements, establish a reasonable evaluation index system, and support decision-making with credible results. 9 articles using DEA method to evaluate the efficiency of universities′ S&T achievements transformation in China over last decade have been examined. The index selection, however, is controversial. Many articles include basic research data, process data as well as counting indicators in the assessment, which hardly provides robust support for the performance management. According to the Law on the Promotion of theS&T Achievements Transformation, scientific and technological achievements refer to the practical value produced through research and development. This view does not include the process of production of scientific knowledge. In order to accurately assess the efficiency of the transformation of scientific and technological achievements in universities, it is more reasonable to adopt this narrow view. Therefore, basic research data related to the production process of results should not be used for efficiency evaluation.Most of the literature use the income amount of transformation in combination with various process indicators and counting indicators. Some literatures even only have counting indicators at the input or output end, and there is no indicator reflecting the amount or scale, which is easy to weaken the scale indicators to achieve performance assessment. The counting index is difficult to reflect the scale effect of the transformation results, and may lead to be countable but not effective for evaluation. Also, the process indicators are used in parallel with the input and output indicators at different stages, which could weaken the core indicators. In addition to the above-mentioned types of problems, the correlations of some indicator with the transformation of S&T achievements are relatively low.This paper proposes a refined candidate index system, uses the super-efficient SBM DEA method, evaluates the transformation efficiency of the S&T achievements in 24 Chinese universities directly under the Ministry of Education. The type of universities is divided according to the Chinese Education Online. The indicator data of this paper is derived from the annual report of "Collection of Science and Technology Statistics of Colleges and Universities" by the Ministry of Education and "the National Research and Development Institutions and Higher Education Institutions′ Achievements Report" (2017) by the Ministry of Finance and the Ministry of Science and Technology. Data from 2010 to 2014 within the collection is selected as the relevant input indicators, the output data is summed up from 2015 to 2016 within the report.This paper constructs a single “input-output” indicator system. According to the definition of narrow results transformation, the default indicator system does not contain basic research data; it highlights the transformation income performance orientation, excluding process measurement indicators. The input index of the default system is the manpower and capital investment of applied research and experimental development, R&D results application and technology service; the output indicator is the contract value of transfer, licensing, and investment in S&A achievements transformation. The manpower input is set to reflect the scale of the university′s achievements transformation activities, and the amount of funding contracts is mainly set to reflect the effectiveness of the results transformation activities. In order to compare and analyze the impact of the basic research data, the process counting index and the “three technology” service contract amount to the efficiency results of transformation, other 3 indicator systems have been set as comparation. Based on the default system, basic research data has been added into the input indicators in the reference system A, the reference system B adds the number of patent grants within output indicators, and the reference system C adds the amount of “three technology” service contracts within output indicators.The results show that in the default index system 4 universities are considered to be relatively effective. Appropriate DEA analysis can suggest the typical universities in practice. Tsinghua University and China University of Geosciences (Wuhan) are relatively effective but not referenced, which showed under the established input-output index system they has its own characteristics, and that is in line with the actual practice.Compared with the default group, the overall transformation efficiency of the A group decreased slightly, the order changed slightly and the overall order of the comprehensive colleges declined. Compared with the default group, the overall transformation efficiency of the B group was greatly improved, the number of relatively effective colleges increased significantly, the order changed obviously, and the relative order was statistically different. Compared with the default group, the overall transformation efficiency of the C group was is improved, the number of relatively effective colleges is increasing, and the order changed apparent. The conclusion is that in order to accurately assess the efficiency of S&T achievements transformation in universities, it is necessary to clarify notions of indicators. It is not appropriate to mix basic research, process indicators and counting indicators into efficiency evaluation in the single stage DEA. The analysis also exemplifies that the process indicators and counting indicators have a significant impact on the results, mixing the basic research data will be difficult to accurately reflect the efficiency of various universities.For universities and S&T management departments, the “three technology” contract identification and statistical norms should be clarified to avoid pseudo-S&T achievements transformation activities taking free riders.

Key words: data envelopment analysis, university, S&T achievements transformation, transformation efficiency