制造企业创新效率测度与影响因素研究——基于数字化转型的视角

基于数字化转型视角，以我国制造业上市公司为研究样本，运用三阶段DEA模型对企业创新效率进行测算和分解，并采用Tobit回归模型对企业创新效率影响因素进行分析。研究发现：（1）传统DEA模型结果显示，2007-2020年企业创新效率呈现出“U”型发展趋势，且整体上处于较低水平，具有较大的提升空间。在数字经济和数字化转型的环境中，国有企业相对于民营企业的规模效率仍保持较大优势，但民营企业相对于国有企业的纯技术效率优势正逐步被替代。（2）似SFA模型结果显示，数字经济、政府支持、行业竞争、教育环境和开放环境等是影响企业创新效率的重要外部环境因素。（3）调整后DEA模型结果显示，整体上剔除环境因素后企业创新效率有所提升，但仍处于较低水平。创新环境的改善主要通过提升企业的管理效率、技术适应能力等来提升创新效率。（4）Tobit回归模型的结果显示，企业规模、企业年龄、资产收益率、负债结构、独立董事比例、股权集中度和机构持股比例等因素是影响调整后创新效率的重要因素。

Research on Measurement and Influencing Factors of Innovation Efficiency in Manufacturing Enterprises: Based on the Perspective of Digital Transformation

Based on the perspective of digital transformation, taking Chinese listed manufacturing enterprises as research samples, the three-stage DEA model was used to measure the innovation efficiency of manufacturing enterprises. The dynamic evolution characteristics of innovation efficiency and its decomposition efficiency were analyzed, and the influencing factors were analyzed by Tobit regression model. The research findings are as follows: (1) The results of traditional DEA model show that the innovation efficiency of Chinese manufacturing enterprises shows a U-shaped development trend from 2007 to 2020, which is at a low level on the whole and has a large room for improvement. In the environment of digital economy and digital transformation, the scale efficiency of state-owned manufacturing enterprises is still relatively superior to that of private enterprises, but the pure technical efficiency advantage of private enterprises is gradually being replaced. (2) The results of SFA model show that digital economy, government support, industry competition, education environment and open environment are important external environmental factors that affect the innovation efficiency of manufacturing enterprises. (3) The results of DEA model after adjustment show that, on the whole, the innovation efficiency of Chinese manufacturing enterprises has been improved after removing environmental factors, but it is still at a low level. The improvement of innovation environment mainly improves the innovation efficiency by improving the management efficiency and technological adaptability of manufacturing enterprises. (4) The results of Tobit regression model show that enterprise size, enterprise age, return on assets, debt structure, proportion of independent directors, ownership concentration and institutional shareholding are important factors affecting the innovation efficiency after adjustment.