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Researchers should cite this work as follows:

• Kijek, A. (2023). 2010-Kijek-Kijek-Modelling of Innovation Diffusion. SIMIODE, QUBES Educational Resources. doi:10.25334/8EQF-2W79

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Kijek, A. and T. Kijek. 2010. Modelling of Innovation Diffusion. Operations Research and Decisions. 3-4:53-68.

See https://econpapers.repec.org/article/wutjournl/v_3a3-4_3ay_3a2010_3ap_3a53-68_3aid_3a169.htm . Accessed 28 March 2023.

Abstract: Since the publication of the Bass model in 1969, research on the modelling of the diffusion of innovation resulted in a vast body of scientific literature consisting of articles, books, and studies of real-world applications of this model. The main objective of the diffusion model is to describe a pattern of spread of innovation among potential adopters in terms of a mathematical function of time. This paper assesses the state-of-the-art in mathematical models of innovation diffusion and procedures for estimating their parameters. Moreover, theoretical issues related to the models presented are supplemented with empirical research. The purpose of the research is to explore the extent to which the diffusion of broadband Internet users in 29 OECD countries can be adequately described by three diffusion models, i.e. the Bass model, logistic model and dynamic model. The results of this research are ambiguous and do not indicate which model best describes the diffusion pattern of broadband Internet users but in terms of the results presented, in most cases the dynamic model is inappropriate for describing the diffusion pattern. Issues related to the further development of innovation diffusion models are discussed and some recommendations are given.

This paper offers a first order differential equation model for innovation diffusion, solves it, and offers qualitative analysis as well as approaches to estimating parameters with some data on final parameters for various countries on information and communication technology markets.