Agent-based Modeling Automated: Data-driven Generation of Innovation Diffusion Models
Thorben Jensen (TU Delft - Technology, Policy and Management, Wuppertal Institut für Klima, Umwelt, Energie)
Emile Chappin (Wuppertal Institut für Klima, Umwelt, Energie, TU Delft - Technology, Policy and Management)
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Abstract
Simulation modeling is useful to gain insights into driving mechanisms of diffusion of innovations. This study aims to introduce automation to make identification of such mechanisms with agent-based simulation modeling less costly in time and labor. We present a novel automation procedure in which the generation of diffusion models is automated. It comprises three phases: (1) preprocessing of empirical data on the diffusion of a specific innovation, taken out be the user; (2) automated inverse modeling of decision models from a decision model library for their capability of explaining these data; (3) policy simulation automatically assesses user-chosen policy interventions in their potential of influencing the spreading of the innovation. We present a working software implementation of this procedure. We applied this tool to data-analysis on the diffusion of a sustainable innovation, water-saving showerheads. The proposed procedure successfully generated simulation models that explained available diffusion data. This provided a proof of concept. Further, it progresses agent-based modeling by providing model validation by design and by enabling detailed bottom-down modeling at the lower complexity of top-down modeling. We believe the proposed approach can widen the circle of persons that can use simulation modeling and better understand and shape innovation.