Agent-based simulation of innovation diffusion: a review

Mathematical modeling of innovation diffusion has attracted strong academic interest since the early 1960s. Traditional diffusion models have aimed at empirical generalizations and hence describe the spread of new products parsimoniously at the market level. More recently, agent-based modeling and simulation has increasingly been adopted since it operates on the individual level and, thus, can capture complex emergent phenomena highly relevant in diffusion research. Agent-based methods have been applied in this context both as intuition aids that facilitate theory-building and as tools to analyze realworld scenarios, support management decisions and obtain policy recommendations. This review addresses both streams of research. We critically examine the strengths and limitations of agent-based modeling in the context of innovation diffusion, discuss new insights agent-based models have provided, and outline promising opportunities for future research. The target audience of the Elmar Kiesling, Lea M. Wakolbinger University of Vienna Department of Business Administration Bruenner Str. 72 Vienna, 1210, AUSTRIA E-mail: {elmar.kiesling,lea.wakolbinger}@univie.ac.at Markus Günther, Christian Stummer (*corresponding author) Bielefeld University Department of Business Administration and Economics Universitaetsstr. 25 Bielefeld, 33615, GERMANY Tel. +49 521.106-4892; Fax +49 521.106-154891 E-mail: {markus.guenther,christian.stummer}@uni-bielefeld.de