Agent-based modeling is useful to simulate the human role in socio-technical systems. Thereby, the complexity of such systems can be captured. For instance, it has shown to be useful at simulating innovation in socio-technical systems. We develop a next step in which laborious model building is automated. We present a working example on innovation diffusion leading to consumers changing their heating behavior.@en

Simulation modeling is useful to understand the mechanisms of the diffusion of innovations, which can be used for forecasting the future of innovations. This study aims to make the identification of such mechanisms less costly in time and labor. We present an approach that automates the generation of diffusion models by: (1) preprocessing of empirical data on the diffusion of a specific innovation, taken out by the user; (2) testing variations of agent-based models for their capability of explaining the data; (3) assessing interventions for their potential to influence the spreading of the innovation. We present a working software implementation of this procedure and apply it to the diffusion of water-saving showerheads. The presented procedure successfully generated simulation models that explained diffusion data. This progresses agent-based modeling methodologically by enabling detailed modeling at relative simplicity for users. This widens the circle of persons that can use simulation to shape innovation.@en

Feedback devices can be used to inform households about their energy-consumption behavior. This may persuade them to practice energy conservation. The use of feedback devices can also—via word of mouth—spread among households and thereby support the spread of the incentivized behavior, e.g. energy-efficient heating behavior. This study investigates how to manage the impact of these environmental innovations via marketing. Marketing activities can support the diffusion of devices. This study aims to identify the most effective strategies of marketing feedback devices. We did this by adapting an agent-based model to simulate the roll-out of a novel feedback technology and heating behavior within households in a virtual city. The most promising marketing strategies were simulated and their impacts were analyzed. We found it particularly effective to lend out feedback devices to consumers, followed by leveraging the social influence of well-connected individuals, and giving away the first few feedback devices for free. Making households aware of the possibility of purchasing feedback devices was found to be least effective. However, making households aware proved to be most cost-efficient. This study shows that actively managing the roll-out of feedback devices can increase their impacts on energy-conservation both effectively and cost-efficiently.@en

Feedback devices can be used to inform households about their energy-consumption behavior. This may persuade them to practice energy conservation. The use of feedback devices can also—via word of mouth—spread among households and thereby support the spread of the incentivized behavior, e.g. energy-efficient heating behavior. This study investigates how to manage the impact of these environmental innovations via marketing. Marketing activities can support the diffusion of devices. This study aims to identify the most effective strategies of marketing feedback devices. We did this by adapting an agent-based model to simulate the roll-out of a novel feedback technology and heating behavior within households in a virtual city. The most promising marketing strategies were simulated and their impacts were analyzed. We found it particularly effective to lend out feedback devices to consumers, followed by leveraging the social influence of well-connected individuals, and giving away the first few feedback devices for free. Making households aware of the possibility of purchasing feedback devices was found to be least effective. However, making households aware proved to be most cost-efficient. This study shows that actively managing the roll-out of feedback devices can increase their impacts on energy-conservation both effectively and cost-efficiently.@en

n this paper we present a procedure that enables a systematic and partially automated parameterization and selection of agent-based models of the diffusion of innovations and policies to support diffusion processes. A prototype on the diffusion of water saving shower heads is presented. Our results suggest that the presented approach can adequately and systematically evaluate different sets of parameters and model structures against known diffusion data. @en

The German Energiewende is a deliberate transformation of an established industrial economy towards a nearly CO2-free energy system accompanied by a phase out of nuclear energy. Its governance requires knowledge on how to steer the transition from the existing status quo to the target situation (transformation knowledge). The energy system is, however, a complex socio-technical system whose dynamics are influenced by behavioural and institutional aspects, which are badly represented by the dominant techno-economic scenario studies. In this paper, we therefore investigate and identify characteristics of model studies that make agent-based modelling supportive for the generation of transformation knowledge for the Energiewende. This is done by reflecting on the experiences gained from four different applications of agent-based models. In particular, we analyse whether the studies have improved our understanding of policies’ impacts on the energy system, whether the knowledge derived is useful for practitioners, how valid understanding derived by the studies is, and whether the insights can be used beyond the initial case-studies. We conclude that agent-based modelling has a high potential to generate transformation knowledge, but that the design of projects in which the models are developed and used is of major importance to reap this potential. Well-informed and goal-oriented stakeholder involvement and a strong collaboration between data collection and model development are crucial.@en

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.@en