Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/872
Title: Diffusion of Innovations in Middle Eastern versus Western Markets: A Mathematical Computation Cellular Automata Simulation Model
Authors: Petridis, Konstantinos
Petridis, Nikolaos E.
Type: Article
Subjects: FRASCATI::Social sciences::Economics and Business::Econometrics
FRASCATI::Natural sciences::Mathematics::Applied Mathematics
FRASCATI::Natural sciences::Mathematics::Statistics and probability
Keywords: Cellular Automata models
Diffusion of innovative products
Small-world network
Innovators and denials
Survival analysis
Computational mathematics
Issue Date: 1-Nov-2020
Source: Operational Research
Abstract: Simulation modelling has gained ground over the years since it can provide various scenarios applied to any scientific area. In this study, a stochastic cellular automata model is proposed, in which agents fall into three distinct categories (adopters, non-adopters and denials). Based on Hofstede’s cultural dimension individualism, we characterize three major international markets, as perfectly clustered (collective) to perfectly random (individualistic). We investigate innovation diffusion speed, in each network topology. At each time step, the decision of non-adopters to purchase innovative products, is affected by their immediate neighborhood (von Neumman). The speed of diffusion is evaluated using time at which sales reach 50% of market. Effects of simulation parameters on speed of diffusion, are assessed using a log-normal accelerated failure time model. Results demonstrate that diffusion of innovative products accelerates when innovators of a virtual economic system are placed according to a random network and when amount of innovators and imitators in the economic system increases. Slower innovative products’ diffusion process is a result of a large amount of denials and of how imitators are placed in the in the virtual economic system. Diffusion in small-world virtual economic systems lead to small time inflexion points very close to those of a random networked market.
URI: https://doi.org/10.1007/s12351-020-00598-y
https://ruomo.lib.uom.gr/handle/7000/872
ISSN: 1109-2858
1866-1505
Other Identifiers: 10.1007/s12351-020-00598-y
Appears in Collections:Department of Applied Informatics



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