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Technological impact of biomedical research: The role of basicness and novelty

Citations

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Cited by:

  1. Krzysztof Szczygielski & Jerzy Mycielski, 2024. "The mutual reinforcement of scientific and technological knowledge—a technology-level analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 6533-6549, November.
  2. Li, Bing & Ding, Kun & Larivière, Vincent, 2026. "Interdisciplinary research and technological change," Technological Forecasting and Social Change, Elsevier, vol. 225(C).
  3. Wang, Fang, 2024. "Does the recombination of distant scientific knowledge generate valuable inventions? An analysis of pharmaceutical patents," Technovation, Elsevier, vol. 130(C).
  4. Wang, Dan & Zhou, Xiao & Zhao, Pengwei & Pang, Juan & Ren, Qiaoyang, 2025. "Early identification of breakthrough technologies: Insights from science-driven innovations," Journal of Informetrics, Elsevier, vol. 19(1).
  5. Lorenzo Ardito & Roger Svensson, 2024. "Sourcing applied and basic knowledge for innovation and commercialization success," The Journal of Technology Transfer, Springer, vol. 49(3), pages 959-995, June.
  6. Jianwei DANG & Kazuyuki MOTOHASHI & Quihan ZHAO, 2025. "Patent Information Disclosure and Market Reactions: Empirical investigation by using text-based novelty and impact indicators," Discussion papers 25097, Research Institute of Economy, Trade and Industry (RIETI).
  7. Lian, Xiangpeng & Zhang, Yi & Wu, Mengjia & Guo, Ying, 2025. "Do scientific knowledge flows inspire exploratory innovation? Evidence from US biomedical and life sciences firms," Technovation, Elsevier, vol. 140(C).
  8. Qing Ke, 2023. "Interdisciplinary research and technological impact: evidence from biomedicine," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2035-2077, April.
  9. René Belderbos & Nazareno Braito & Jian Wang, 2024. "Heterogeneous university research and firm R&D location decisions: research orientation, academic quality, and investment type," The Journal of Technology Transfer, Springer, vol. 49(5), pages 1959-1989, October.
  10. Wang, Jian & Verberne, Suzan, 2024. "Comparing patent in-text and front-page references to science," Journal of Informetrics, Elsevier, vol. 18(4).
  11. Geng, Yu & Yin, Yixian & Cai, Ruonan & Wang, Xianwen, 2026. "Tracing scientific knowledge flow in patents: An explainable machine learning study of citation types and their temporal dynamics," Journal of Informetrics, Elsevier, vol. 20(1).
  12. Li, Xian & Du, Haixing & Bu, Yi & Ai, Mingshu & Huang, Junjie & Jia, Tao, 2025. "Innovation lineage structure: A graph structure in publications of scholars and its association with disruptiveness," Journal of Informetrics, Elsevier, vol. 19(4).
  13. Ke, Qing & Pan, Tianxing & Mao, Jin, 2026. "The geography of novel and atypical research," Research Policy, Elsevier, vol. 55(1).
  14. Keye Wu & Ziyue Xie & Jia Tina Du, 2024. "Does science disrupt technology? Examining science intensity, novelty, and recency through patent-paper citations in the pharmaceutical field," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5469-5491, September.
  15. Higashide, Noriyuki & Zhang, Yi & Asatani, Kimitaka & Miura, Takahiro & Sakata, Ichiro, 2024. "Quantifying advances from basic research to applied research in material science," Technovation, Elsevier, vol. 135(C).
  16. Zheng, Zhejun & Ma, Yaxue & Ba, Zhichao & Pei, Lei, 2024. "Tree knowledge structure for better insight: Capturing biomedical science-technology knowledge linkage with MeSH," Journal of Informetrics, Elsevier, vol. 18(4).
  17. Yi Zhao & Chengzhi Zhang, 2025. "A review on the novelty measurements of academic papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(2), pages 727-753, February.
  18. Wang, Zhiqi & Chen, Yue & Yang, Chun, 2025. "The role of preprints in open science: Accelerating knowledge transfer from science to technology," Journal of Informetrics, Elsevier, vol. 19(2).
  19. Chen, Xi & Mao, Jin & Ma, Yaxue & Li, Gang, 2024. "The knowledge linkage between science and technology influences corporate technological innovation: Evidence from scientific publications and patents," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
  20. Shin, Hyunjin & Woo, Hyun Goo & Sohn, Kyung-Ah & Lee, Sungjoo, 2023. "Comparing research trends with patenting activities in the biomedical sector: The case of dementia," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
  21. Chen, Xi & Mao, Jin & Li, Gang, 2024. "A co-citation approach to the analysis on the interaction between scientific and technological knowledge," Journal of Informetrics, Elsevier, vol. 18(3).
  22. Jiang, Wenbo & Hong, Yong & Cui, Miao & Qu, Yongyi, 2026. "To be similar or unique? Exploring firms' pursuit of optimal technological relatedness to enhance technological impact: The role of firm size and competitor density," Technological Forecasting and Social Change, Elsevier, vol. 222(C).
  23. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
  24. Bing Li & Shiji Chen & Vincent Larivière, 2023. "Interdisciplinarity affects the technological impact of scientific research," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(12), pages 6527-6559, December.
  25. Yuan Xu & Xi Chen & Jin Mao & Gang Li, 2025. "Will patents with more interdisciplinary scientific knowledge have higher technological impact? Empirical evidence from USPTO patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(4), pages 2037-2068, April.
  26. Roh, Taeyeoun & Yoon, Byungun, 2023. "Discovering technology and science innovation opportunity based on sentence generation algorithm," Journal of Informetrics, Elsevier, vol. 17(2).
  27. Xingyu Gao & Qiang Wu & Yuanyuan Liu & Ruilu Yang, 2024. "Pasteur’s quadrant in AI: do patent-cited papers have higher scientific impact?," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(2), pages 909-932, February.
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