Dynamic increasing returns and innovation diffusion: bringing Polya Urn processes to the empirical data

Elena Stepanova, Giovanni Dosi, Alessio Moneta

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

2 Citazioni (Scopus)

Abstract

The patterns of innovation diffusion are well approximated by the logistic curves. This is the robust empirical fact confirmed by many studies in innovations dynamics. Here, we show that the logistic pattern of innovation diffusion can be replicated by the time-dependent stochastic process with positive feedbacks along the diffusion trajectory. The dynamic increasing returns process is modelled by Polya Urns. So far, Urn models have been mostly used to study the [path-dependent] limit properties. On the contrary, this work focuses on the transient [finite time] properties studying the conditions under which urn models capture the logistic trajectories which often track empirical diffusion process. As examples, we calibrate the process to match several cases of diffusion of motor ships in European countries.
Lingua originaleEnglish
pagine (da-a)461-478
Numero di pagine18
RivistaIndustry and Innovation
Volume26
DOI
Stato di pubblicazionePubblicato - 2019

Keywords

  • Business, Management and Accounting (all)
  • Management of Technology and Innovation
  • Polya Urn
  • dynamic increasing returns
  • innovation diffusion
  • logistic diffusion pattern

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