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Émile J.L. Chappin
Delft University of Technology
This is a broad collection of agent-based models related to sustainability. The editors make note of it themselves: the volume contains a strikingly large number of domains and approaches. The first chapters study particular behaviours related to energy use and material waste, such as behaviour at the workplace. These are typically fuelled by empirical data. In later chapters, the relation to sustainability is primarily found in avoiding, e.g., emissions or waste caused by system inefficiencies. The foci there are on techniques to be smarter in balancing supply and demand for services in transport and electricity.
The first overarching theme is how to root agent-based models related to sustainable behaviour in relevant theory. This is an important line of work as it is one of the ways in which we can explore the applicability of particular theories and find out where and possibly how to improve them and how to translate theories to modelling frameworks. For consumers, existing theories and frameworks exist (such as the theory of planned behaviour and the Consumat Framework (Jager, 2000). Modellers may find inspiration in the range of theories and frameworks that are relevant to sustainable behaviour.
The second overarching theme is connecting agent-based modelling to methods from other fields, i.e. structural equation modelling, machine learning techniques for decision trees, life-cycle analyses and 3D visualisation. These seem to be the enablers for using empirical data in the modelling process, culminating to the question: what data is needed for a particular model? And, one step further, how can data be used to structure a model. The approaches presented are relevant and are useful experiences. Authors are very transparent in describing their experience, exploring some of the multidisciplinary challenges. This can be very useful for agent-based modellers considering such techniques.
One ought to be critical about the loose conceptualisation of sustainable behaviour throughout the book; about the diversity in how models are developed and how they are described. The ODD protocol (Polhill et al., 2008), for instance, has been applied in two chapters only. This may correspond to the status quo in the field of agent-based modelling, but one expects something more from an edited volume like this. We simply have to go beyond the observation that agent-based modelling can be meaningfully applied to a variety of domains.
A missed opportunity is to synthesise the topics of sustainable behaviour and to establish a research agenda. What specificities to sectors, actor groups, countries, etc. matter with respect to sustainable behaviour? How does agent-based modelling help in finding crucial levers for behavioural change in this context? How are these findings different to other methods, modelling or otherwise? What new theoretical questions emerge from the modelling work, from confronting various theories and frameworks? What are the methodological challenges in using the empirical data and applying methods from other fields to structure the models? These are challenges that go beyond (the wide variety of) individual models and are key for the understanding and supporting of sustainable behaviour.
POLHILL G. J., Parker D., Brown D. and V. Grimm (2008). Using the ODD Protocol for Describing Three Agent-Based Social Simulation Models of Land-Use Change. Journal of Artificial Societies and Social Simulation, 12(2), 3: https://www.jasss.org/11/2/3.html.
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