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Chain reaction of ideas: Can radioactive decay predict technological innovation?

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  • Giardini, G.S.Y.
  • da Cunha, C.R.

Abstract

This work demonstrates the application of a birth–death Markov process, inspired by radioactive decay, to capture the dynamics of innovation processes. Leveraging the Bass diffusion model, we derive a Gompertz-like function explaining long-term innovation trends. The validity of our model is confirmed using citation data, Google trends, and a recurrent neural network, which also reveals short-term fluctuations. Further analysis through an automaton model suggests these fluctuations can arise from the inherent stochastic nature of the underlying physics.

Suggested Citation

  • Giardini, G.S.Y. & da Cunha, C.R., 2024. "Chain reaction of ideas: Can radioactive decay predict technological innovation?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 654(C).
    • Handle: RePEc:eee:phsmap:v:654:y:2024:i:c:s0378437124006411
    DOI: 10.1016/j.physa.2024.130132
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