CEJOR (2015) 23:501–522 DOI 10.1007/s10100-015-0391-x ORIGINAL PAPER Simulating resistances in innovation diffusion over multiple generations: an agent-based approach for fuel-cell vehicles Martin Zsifkovits · Markus Günther Published online: 22 April 2015 © Springer-Verlag Berlin Heidelberg 2015 Abstract Innovation resistances play a major role in innovation diffusion, as they do not only hinder the adoption, but might also change a decision maker’s evaluation. Although these influences are widely accepted, previous models on the diffusion of new technologies and products have either reduced these multiple dimensions of uncertain- ties to only one parameter, or have completely neglected them altogether. Both might lead to a pro-innovation bias. Therefore we present an agent-based approach that takes several different innovation resistances in a multi-generation environment into account. Hydrogen vehicles and the necessity of setting up a corresponding infrastruc- ture were chosen for a sample application as they incorporate a band of various dimen- sions of innovation resistance. Examples are the uncertain infrastructure situation, the uncertainty arising from new and improved features, the uncertainty about the tech- nologies’ real ecological benefit, the unknown maintenance cycles and costs, or the ambiguous technical parameters such as vehicle range. These various uncertainties are even more distinctive if multiple technology generations are considered. Our results indicate that a short-term decrease in the adoption rate can be observed although the technological parameters of a later product generation might be more beneficial for the consumers. As we show, this effect can be eased through timing variation of the com- munication measures. Therefore we conclude that considering multiple innovation resistance factors in innovation diffusion might reduce the pro-innovation bias. M. Zsifkovits (B ) Department of Computer Science, Institute for Operations Research, Universität der Bundeswehr München, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany e-mail: martin.zsifkovits@unibw.de M. Günther Department of Business Administration and Economics, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany e-mail: markus.guenther@uni-bielefeld.de 123