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A study on patent term prediction by survival time analysis using neural hazard model

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  • Marusaki, Koji
  • Nakai, Kensei
  • Kataoka, Shotaro
  • Kawano, Seiya
  • Hentona, Asahi
  • Sakumoto, Takeshi
  • Yamamoto, Yuta
  • Mori, Kaede
  • Nonaka, Hirofumi

Abstract

Patent term is considered one of the factors that determine the private value of a patent. Predicting it can therefore be used as an indicator of corporate management. However, since ordinary regression analysis methods use time series data as the objective variable, it was common to apply the survival time analysis such as the Cox proportional hazards model (CPH) for patent term prediction. On the other hand, CPH cannot incorporate the nonlinear elements of the explanatory variables in the estimation of the risk function, and there is a risk that it may be too simple as a model to predict patent terms from each explanatory variable.

Suggested Citation

  • Marusaki, Koji & Nakai, Kensei & Kataoka, Shotaro & Kawano, Seiya & Hentona, Asahi & Sakumoto, Takeshi & Yamamoto, Yuta & Mori, Kaede & Nonaka, Hirofumi, 2024. "A study on patent term prediction by survival time analysis using neural hazard model," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    • Handle: RePEc:eee:tefoso:v:203:y:2024:i:c:s0040162524001860
    DOI: 10.1016/j.techfore.2024.123390
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