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Structural modeling of the value of patent

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  • Suzuki, Jun

Abstract

There is a considerable volume of prior research on the relationship between innovation and patents. Those research studies reveal that patents contain a great deal of noise, and unless a correction is made in terms of the value of individual patents, a simple count of the number of patents does not constitute a very useful indicator. From research that has been conducted for the purpose of finding such an indicator to show the value of individual patents (that is, research to identify the characteristics of valuable patents), many kinds of value indicators have been proposed. Nevertheless, research hitherto has focused primarily on business or private value derived from the possession of patents, and little attention has been paid to value in terms of technical knowledge or social value. In a survey of inventors conducted by RIETI in 2007, terminology describing broad concepts was used when questioning inventors about the value of individual patents, and this has provided an excellent opportunity to analyze the multiple factors lying behind the value of patents and how they impact one another. The purpose of this research is to use data from the RIETI survey of inventors and structural equation modeling methods to elucidate the relationships between the technological and business value of patents, and the latent factors that influence them. The findings show that a scientific-technological motive for inventors would have a positive effect on both the business and technological value, meanwhile, the monetary or promotion motive would not have any direct effects on the value of a patent. The model also suggests that academic linkage would have a strong positive effect on the technological value but a weak negative effect on the business value. Furthermore, these relationships differ more markedly according to technological field.

Suggested Citation

  • Suzuki, Jun, 2011. "Structural modeling of the value of patent," Research Policy, Elsevier, vol. 40(7), pages 986-1000, September.
  • Handle: RePEc:eee:respol:v:40:y:2011:i:7:p:986-1000
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    4. Achim Walter & Nicole Coviello & Monika Sienknecht & Thomas Ritter, 2024. "Leveraging the Lab: How Pre-Founding R&D Collaboration Influences the Internationalization Timing of Academic Spin-Offs," Entrepreneurship Theory and Practice, , vol. 48(1), pages 71-103, January.
    5. Su, Hsin-Ning, 2017. "Collaborative and Legal Dynamics of International R&D- Evolving Patterns in East Asia," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 217-227.
    6. Liu, Li-jun & Cao, Cong & Song, Min, 2014. "China's agricultural patents: How has their value changed amid recent patent boom?," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 106-121.
    7. Lee, Pei-Chun & Su, Hsin-Ning, 2014. "How to forecast cross-border patent infringement? — The case of U.S. international trade," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 125-131.
    8. Alessandra Scandura, 2019. "The role of scientific and market knowledge in the inventive process: evidence from a survey of industrial inventors," The Journal of Technology Transfer, Springer, vol. 44(4), pages 1029-1069, August.
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    11. Felix Poege & Dietmar Harhoff & Fabian Gaessler & Stefano Baruffaldi, 2019. "Science Quality and the Value of Inventions," Papers 1903.05020, arXiv.org, revised Apr 2019.
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