R&D and operational efficiency in China’s innovative high-tech enterprises: Empirical analysis with two-stage slack based measure data envelopment analysis and threshold regression

Nannan Liang, Yu Shi and Yao Chen

Omega, 2025, vol. 136, issue C

Abstract: This study applies a two-stage slack-based measure data envelopment analysis (SBM-DEA) model to evaluate the micro-level R&D and operational efficiency of 445 listed innovative high-tech enterprises in China's science and technology sector. A threshold regression model is then used to explore the impact of R&D investment intensity variables, such as R&D investment personnel intensity, R&D investment funds intensity and government subsidies intensity, and enterprise scale on efficiency. The findings indicate that the R&D and operational efficiency of China's innovative high-tech enterprises is generally low, with particularly significant room for improvement in R&D efficiency. Among the influencing factors, R&D personnel intensity and enterprise scale both have a significant negative impact on R&D activities and a significant positive impact on operational activities. Meanwhile, enterprise scale exhibits a single threshold effect on both R&D and operational efficiency. When the scale is below or above the threshold, the direction of the effect on efficiency remains the same, but the magnitude differs. Finally, government subsidies intensity did not significantly impact R&D and operational activities and failed to achieve effective incentives or generate positive effects.

Keywords: R&D efficiency; Government subsidies; Enterprise scale; SBM-DEA; Threshold regression model (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.omega.2025.103342

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