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Using structural diversity to measure the complexity of technologies.

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  • 1Department of Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht University, Utrecht, The Netherlands.

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Summary

This study introduces structural diversity to measure technological complexity using network analysis. The Network Diversity Score (NDS) effectively captures technology evolution, R&D investment, and collaboration patterns.

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Area of Science:

  • Economics of Technology
  • Network Science
  • Innovation Studies

Background:

  • Quantifying technological complexity is crucial for understanding innovation dynamics.
  • Existing measures may not fully capture the intricate structure of technologies.
  • A novel approach is needed to assess technology complexity and its evolution.

Purpose of the Study:

  • To introduce structural diversity as a new metric for quantifying technological complexity.
  • To develop and validate the Network Diversity Score (NDS) using empirical data.
  • To explore the relationship between structural diversity and key innovation indicators.

Main Methods:

  • Modeling technologies as combinatorial networks.
  • Deriving a measure of complexity based on (sub-)network topology diversity.
  • Empirically approximating the measure with the Network Diversity Score (NDS).
  • Analyzing European patent data from 1980 to 2015.

Main Results:

  • Structural diversity replicates stylized facts of technological complexity.
  • Technological complexity increases over time; younger technologies are more complex.
  • Higher complexity correlates with increased R&D investment and collaboration.
  • Complex technologies exhibit spatial concentration when controlling for size.

Conclusions:

  • Structural diversity offers a robust framework for measuring technological complexity.
  • The NDS provides valuable insights into technology evolution and innovation ecosystems.
  • This approach enhances our understanding of R&D dynamics and knowledge diffusion.