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Tracing Technological Development Trajectories: A Genetic Knowledge Persistence-Based Main Path Approach.

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Area of Science:

  • Technology Management
  • Bibliometrics
  • Innovation Studies

Background:

  • Patent analysis is crucial for understanding technological evolution.
  • Existing main path analysis methods have limitations in identifying dominant patents and managing network complexity.

Purpose of the Study:

  • To propose a new method for identifying main paths in technological domains using patent citations.
  • To overcome the limitations of previous approaches in identifying dominant patents and simplifying trajectory analysis.

Main Methods:

  • Developed a novel method based on identifying high-persistence patents using a genetic knowledge persistence algorithm.
  • Searched backward and forward paths from these high-persistence patents.
  • Applied and compared the method to desalination and solar photovoltaic domains against a prior method.

Main Results:

  • The proposed method dramatically reduces network complexity (almost 10x less complex in test cases).
  • It successfully identifies all dominantly important patents, unlike prior methods that missed ~20%.

Conclusions:

  • The new method offers a more effective and less complex way to analyze technological trajectories.
  • It enhances the identification of critical patents and simplifies the qualitative tracing of innovation pathways.