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Innovation diffusion modeling: the deterministic, stochastic and chaotic case
Christos H Skiadas1, Charilaos Skiadas
1Technical University of Crete, Chania, Greece. skiadas@asmda.net
Abstract:
The field of innovation diffusion modeling showed a tremendous growth process during the last decades. Numerous qualitative and quantitative studies have been presented followed by significant applications in various scientific fields. This review paper explores the main quantitative developments on innovation diffusion and the gradual progress from the original deterministic models to their stochastic and chaotic alternatives. Related applications are presented.
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