Comparing a simulation model with various analytic models of the international diffusion of consumer technology

Chris Swinerd and Ken R. McNaught

Technological Forecasting and Social Change, 2015, vol. 100, issue C, 330-343

Abstract: In this paper we propose and evaluate a method for studying technology adoption at the national level using hybrid simulation. A hybrid simulation model is developed which combines elements of system dynamics and agent-based modelling, and treats nations as adopting agents. International diffusion is modelled as a social system where the adoption of an innovation, or even just growing pressure to adopt an innovation, in one nation can then influence its adoption in others. The model is used to investigate nine different technological innovations for which sufficient international data are available. Using the available empirical data, the method of differential evolution is used to configure the model which allows the parameter space to be explored in an efficient manner, without bias or subjective disagreement. Good agreement is found between the parameters derived in this way and those reported to configure analytic models. For each of the nine innovations, we report the rank order correlation between the actual order of adoption of the innovations by nations and the order predicted by the simulation model. We also report the rank order correlations between the actual order and the order predicted by a much simpler statistical model. Improvements in the rank order correlation are shown when some form of social influence between nations is included, although there is no significant difference in results between the four different types of social influence considered by the simulation. The nine technologies investigated also appear to fall into two groups with significantly different uptake speeds. Advantages and limitations of the approach are discussed along with suggested implications for practice.

Keywords: International diffusion; Analytic modelling; Simulation modelling; Agent-based simulation; System dynamics; Differential evolution (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:100:y:2015:i:c:p:330-343

DOI: 10.1016/j.techfore.2015.08.003

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