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Comparison of external R&D and internal R&D: Based on the perspective of S&T development of China’s pharmaceutical manufacturing industry

Author

Listed:
  • Di Wu
  • Su Wang
  • Senhao Chang
  • Guiyu Lian
  • Yuwen Chen

Abstract

Purpose: The science and technology (S&T) innovation in China’s pharmaceutical industry has entered a bottleneck. The choice between external and internal research and development (R&D) has become a significant challenge for S&T development. To provide scientific suggestions for companies to choose an R&D strategy and enhance S&T development, we analyzed and compared the impacts of two R&D strategies on S&T output. Methods: We selected the data related to China’s pharmaceutical manufacturing industry from 2000 to 2019, established regression equations by the E-G two-step method, and used the VAR model for impulse responses and variance decompositions to research the relationship between two R&D strategies and S&T output. Results: There is a stable long-term equilibrium relationship between two R&D strategies, including external and internal R&D, and S&T output in China’s pharmaceutical manufacturing industry. When internal R&D increases by 1%, S&T output increases by 0.7382% with a 5-year lag. When S&T output increases by 1%, external R&D increases by 2.0749% with a 2-year lag. Conclusion: Compared with external R&D, internal R&D can boost S&T output.

Suggested Citation

  • Di Wu & Su Wang & Senhao Chang & Guiyu Lian & Yuwen Chen, 2022. "Comparison of external R&D and internal R&D: Based on the perspective of S&T development of China’s pharmaceutical manufacturing industry," PLOS ONE, Public Library of Science, vol. 17(6), pages 1-13, June.
    • Handle: RePEc:plo:pone00:0270271
    DOI: 10.1371/journal.pone.0270271
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    References listed on IDEAS

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    1. Chen, Kaihua & Zhang, Yi & Zhu, Guilong & Mu, Rongping, 2020. "Do research institutes benefit from their network positions in research collaboration networks with industries or/and universities?," Technovation, Elsevier, vol. 94.
    2. Kilian, Lutz, 2001. "Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(3), pages 161-179, April.
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