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Under the background of the rapid development of innovation economy promoted by education science and technology, this paper uses the DEA Malmquist index model to build an evaluation index system based on the research object of the Education Science and technology industry of 31 provinces in China from 2010 to 2019. It makes a static analysis of its input–output efficiency from the aspects of comprehensive efficiency, pure technical efficiency and scale efficiency. Also, the Malmquist index method is used to analyse the changes of comprehensive efficiency, technical efficiency and technological progress. It is found that the development of the educational science and technology industry in different regions of China has its own characteristics. The efficiency of educational science and technology in some regions is good, but the growth rate slows down, and some efficiency lags behind, so there is a lot of space for improvement. On the whole, technological progress is an important factor affecting the change in total input–output efficiency. It is suggested that regional cooperation should be strengthened to optimise the allocation of educational science and technology resources. It should accelerate the deployment of next-generation technology to promote overall high-quality development. [ABSTRACT FROM AUTHOR]

Continuous improvement of technological innovation ability, adjustment of the development strategy, and enhancement of operational performance are of great theoretical and practical significance for logistics enterprises. This paper aims to analyze and evaluate the innovation efficiency of the logistics industry. The study utilizes the static three‐stage DEA model and the dynamic Malmquist index model, considering a total of 12 indicators related to innovation input, output, and environmental variables. A dataset of 2940 entries from 49 listed logistics enterprises from 2017 to 2021 was calculated. The analysis provides insights into the innovation efficiency of logistics enterprises from a static perspective and the innovation total factor productivity from a dynamic perspective and decomposition terms. Based on the analysis of environmental variables by the SFA model, it was found that DEA inefficiency is the combined result of environmental factors and management inefficiency. Environmental variables have both positive and negative effects on innovation. The improvement of the economic development level will lead to excess R&D investment. Increased government simple fund subsidies are not conducive to the efficient allocation of innovation resources within enterprises. The expansion of enterprise scale will increase R&D personnel and investment in fixed assets. A thriving technology market can encourage enterprises to improve their own conversion rate of scientific and technological output and give full play to their innovation ability. The dynamic Malmquist model analysis reveals a recution in the overall innovation efficiency of listed logistics enterprises over 5 years. The changes in total factor productivity and technological progress efficiency of all listed logistics enterprises are synchronized, with most enterprises exhibiting higher technological progress efficiency compared to comprehensive technical efficiency. The total factor productivity of logistics enterprise innovation is mainly affected by comprehensive technical efficiency. [ABSTRACT FROM AUTHOR]