2024/02/13 by Guilherme S. Y. Giardini, Giardini, Guilherme S. Y., Carlo Requião da Cunha +1 · 1 citation
Engineering · #FOS: Physical sciences #Statistical Mechanics (cond-mat.stat-mech) #Technology Assessment and Management
paper · pdf · doi:10.48550/arxiv.2402.08681
openalex publication_date 2024/02/13 · openalex created_date 2024/02/15 · openalex updated_date 2026/07/28
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 the 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.