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<p>Enhancing the innovation quality of high-tech industries (HTI) is crucial for optimizing China’s industrial structure and promoting high-quality economic growth. This study provides a comprehensive evaluation of the innovation quality of China’s HTI across three dimensions: technology development, innovation achievement transformation, and persistent innovation. Methodologically, we construct a meta-assurance region parallel two-stage dynamic slack-based measure (SBM) network data envelopment analysis (DEA) window model. Compared to traditional models, this approach adds a parallel stage to assess persistent innovation, providing a more systematic and comprehensive evaluation of innovation quality. The findings indicate that: (1) The overall innovation quality of China’s HTI is relatively low, with significant regional disparities. From 2015 to 2021, innovation quality initially increased but declined thereafter, with a noticeable downturn after 2019. (2) In specific dimensions, technology development and innovation achievement transformation performed relatively well, while persistent innovation remained weak. (3) Excessive industrial electricity consumption and insufficient output from internal R&amp;D institutions were identified as key factors negatively affecting innovation quality. Finally, this study offers governmental, regulatory, industrial, and corporate policy recommendations to improve HTI innovation quality.</p>

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Evaluation of innovation quality in China’s high-tech industries—technological development, innovation achievement transformation, and persistent innovation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月12日

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  • Li Ji,
  • Shigui Tao,
  • Miaoyi Li,
  • Clifford James Gere,
  • Yung-ho Chiu

摘要

Enhancing the innovation quality of high-tech industries (HTI) is crucial for optimizing China’s industrial structure and promoting high-quality economic growth. This study provides a comprehensive evaluation of the innovation quality of China’s HTI across three dimensions: technology development, innovation achievement transformation, and persistent innovation. Methodologically, we construct a meta-assurance region parallel two-stage dynamic slack-based measure (SBM) network data envelopment analysis (DEA) window model. Compared to traditional models, this approach adds a parallel stage to assess persistent innovation, providing a more systematic and comprehensive evaluation of innovation quality. The findings indicate that: (1) The overall innovation quality of China’s HTI is relatively low, with significant regional disparities. From 2015 to 2021, innovation quality initially increased but declined thereafter, with a noticeable downturn after 2019. (2) In specific dimensions, technology development and innovation achievement transformation performed relatively well, while persistent innovation remained weak. (3) Excessive industrial electricity consumption and insufficient output from internal R&D institutions were identified as key factors negatively affecting innovation quality. Finally, this study offers governmental, regulatory, industrial, and corporate policy recommendations to improve HTI innovation quality.