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Research on the relationship between defense technology innovation and high‐quality economic development: Gray correlation analysis based on panel data

Author

Listed:
  • Daran Cai
  • Jin Hu
  • Hongtao Jiang
  • Fengyi Ai
  • Tingting Bai

Abstract

Based on panel data from 2010 to 2019, this study examines the relationship between defense science and technology innovation and high‐quality economic development at the provincial level in China. Using the gray correlation analysis method of panel data and an evaluation index system of high‐quality economic development, we calculate the gray correlation coefficient and decompose its time‐series gray correlation degree and cross‐sectional. Our findings indicate that the correlation between defense science and technology innovation and high‐quality economic development in China is generally stable during 2010–2019. However, Beijing stands out as an exception with a correlation coefficient of less than 0.5. Furthermore, there is regional gray correlation heterogeneity with the smallest correlation degree found in the eastern region and the largest in the northeast region. Based on our results, we propose three countermeasure suggestions: first, to balance national defense construction and economic construction; second, to optimize national defense science and technology strategy according to local conditions; and third, to effectively utilize industrial structure advantages. In summary, our study contributes to the literature by highlighting the relationship between defense science and technology innovation and high‐quality economic development in China. Our findings provide implications for policymakers and practitioners to make informed decisions in achieving sustainable and high‐quality economic development.

Suggested Citation

  • Daran Cai & Jin Hu & Hongtao Jiang & Fengyi Ai & Tingting Bai, 2023. "Research on the relationship between defense technology innovation and high‐quality economic development: Gray correlation analysis based on panel data," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(7), pages 3867-3877, October.
    • Handle: RePEc:wly:mgtdec:v:44:y:2023:i:7:p:3867-3877
    DOI: 10.1002/mde.3925
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    References listed on IDEAS

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    2. Akram, Rabia & Li, Qiyuan & Srivastava, Mohit & Zheng, Yulu & Irfan, Muhammad, 2024. "Nexus between green technology innovation and climate policy uncertainty: Unleashing the role of artificial intelligence in an emerging economy," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    3. Jinhui Zheng & Shikuan Zhao & Yan Tan & Daniel Balsalobre-Lorente, 2026. "Does the digital economy promote synergy between pollution control and carbon reduction? Evidence from China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 28(2), pages 2683-2716, February.
    4. Zhang, Mindan & Ma, Xiang & Mai, Shunhao & Qing, Lingli, 2025. "Drivers of supply chain, environmental innovation, and digital population: The role of inflation and renewable energy on GHG emission in Indonesia," Energy Economics, Elsevier, vol. 145(C).

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