On the evaluation of the takeoff time and of the peak time for innovation diffusion on assortative networks
Maria Letizia Bertotti and
Giovanni Modanese
Mathematical and Computer Modelling of Dynamical Systems, 2019, vol. 25, issue 5, 482-498
Abstract:
This paper deals with a generalization of the Bass model for the description of the diffusion of innovations. The generalization keeps into account heterogeneity of the interactions of the consumers and is expressed by a system of several nonlinear differential equations on complex networks. The following contributions can be singled out: first, explicit algorithms are provided for the construction of various families of assortative scale-free networks; second, a method is provided for the identification of the takeoff time and of the peak time, which represent important turning points in the life cycle of an innovation/product; third, the emergence of specific patterns in connection with networks of the same family is observed, whose tentative interpretation is then given. Also, a comparison with an alternative approach is given, within which adoption times of different communities are evaluated of a network describing firm cooperations in South Tyrol.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://hdl.handle.net/10.1080/13873954.2019.1660997 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:nmcmxx:v:25:y:2019:i:5:p:482-498
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/NMCM20
DOI: 10.1080/13873954.2019.1660997
Access Statistics for this article
Mathematical and Computer Modelling of Dynamical Systems is currently edited by I. Troch
More articles in Mathematical and Computer Modelling of Dynamical Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().