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Will patent family be dormant? Research on the identification and characteristics of sleeping beauty’s patent family

Author

Listed:
  • Jianhua Hou

    (SUN Yat-Sen University)

  • Xiucai Yang

    (SUN Yat-Sen University)

  • Haoyang Song

    (SUN Yat-Sen University)

  • Haiyue Yao

    (SUN Yat-Sen University)

Abstract

Studying the Sleeping Beauty phenomenon of scientific accomplishments can promote advanced and transformative technologies identification. Although there are significant researches focused on scientific Sleeping Beauty, they have limited concern toward the measurement or characteristic description of Sleeping Beauty patent (SBP) or patent family. This study aims to combine them and identify the Sleeping Beauty patent family (SBPF). Accordingly, we constructed a patent family knowledge diffusion burst detection model by patent family’s citation and assignment indexes, which are based on the burst of the Sleeping Beauty literature during technical knowledge diffusion. We took polymerase chain reaction technology as an example, identifying sleeping–waking phenomenon and characteristics of the SBPF in this field, as well as revealing the relationship between SBPF and SBP. Our findings revealed that in the process of technological knowledge diffusion, SBP and their family exhibited significant combined effects and cumulative effects of geographical advantages. In addition, the knowledge burst of SBP is a crucial factor that promotes the formation of the SBPF and can continuously enlarge its influence. This study expands the theoretical framework of technological knowledge diffusion by identifying the Sleeping Beauty phenomenon of technological innovations and provides theoretical and methodology support for identifying advanced and transformative technologies based on patent data.

Suggested Citation

  • Jianhua Hou & Xiucai Yang & Haoyang Song & Haiyue Yao, 2023. "Will patent family be dormant? Research on the identification and characteristics of sleeping beauty’s patent family," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5361-5387, October.
    • Handle: RePEc:spr:scient:v:128:y:2023:i:10:d:10.1007_s11192-023-04784-5
    DOI: 10.1007/s11192-023-04784-5
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