Agent-Based Modeling for Simulating Eco-Innovation Diffusion: A Review on the case of Green Mobility

Modeling the diffusion of eco-innovations is a very challenging task, as there are various influencing factors to consider. The problem gets even more severe when the considered eco-innovation is of high technological complexity and comes along with the need of a supplementary good such as infrastructure. This is the case for alternative mobility concepts such as electric vehicles or hydrogen powered vehicles, where the technology is very innovative and unknown to the consumers and the need of infrastructure leads to a chicken-and-egg problem on the market. In literature various models and methodologies are presented that might tackle this problem. Thereby, Agent-Based modeling turned out to be one of the most promising approaches as it allows for considering various influences on the adoption on a micro level. However, the existing Agent-Based models differ strongly in their architecture and their settings and therefore also differ in their predictive power and their conclusions. For example, several models do not specifically consider the interconnection between consumers and fuel stations operating on the market, hence they ignore the initial chicken-and-egg problem. The technological progress over time is ignored in most of the models, which might also bias their predicting power. The majority of the models does not consider the complex interactions of different market players on the mobility market among each other. Another well-known problem is the pro-innovation bias that is caused by neglecting innovation resistances. This article aims for giving a general overview on the existing models, comparing them and finally identifying the research gap on the field which might lead to new models giving new insights into the diffusion process.