Abstract
Social norms govern collective behaviour by guiding individual behaviour in the absence of a central enforcing authority, which makes them powerful self-regulating mechanisms for societies. This is in stark contrast to policy or legislative norms - also targeted at governing behaviour in society - which are issued by a central
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authority who also then needs to enforce compliance. Enforcing compliance is expensive. Also, these norms might come into conflict with existing social norms, which causes issues. It is therefore not surprising that much research is aimed at understanding existing social norms around behaviours connected to important issues like health or climate change. Designing policy that piggybacks on existing norms to promote behaviour is faster and cheaper than using the classic carrot-and-stick approach of most policy design. The modelling community has invested quite a bit of effort into developing normative frameworks, models and simulations. Yet, very little of this effort has been directed towards the study of the norm life-cycle. Besides, these research efforts have omitted explicit representation of norms and the assessment of norm stability and reactivity in the face of some environmental changes. Values as a stabilizing factor, must be considered while studying the reactivity and stability of social norms. Without such stabilizing elements, modeled norms react swiftly to any change in the environment and are mere behavioural patterns rather than social norms. In this thesis, I use values as drivers of behavioural choices, and Schwartz’s theory of abstract values as a basis. As these values are very abstract, there is a need to translate them to more concrete values and assign behavioural choices to them. A theory or methodology for this step has not been developed in a way that is widely applicable. Thus, a precise way of such a translation is necessary for practical purposes. I designed a practical but formal framework that can be used to study the value-driven behaviour of agents in social simulations. I showed how this formal design can be used in practice to implement multi-agent simulations. Then, I continued with proposing a social norm framework that is focused on finding an explanation for norm dynamics - their emergence, perpetuation, and eventual disappearance. I operationalized the framework by way of a multi-agent simulation in the context of environmental change and absence of sanctions for deviant behaviour. I showed that the values are an intuitive stabilizing factor that allow norms to persist through changes in the agents’ environment and perpetuate and spread even in the absence of punishment. A norm will, however, change, evolve or disappear altogether if it becomes impossible to perform or if the value priorities of the agents change. I explained the norm dynamic and its strong connection to values by implementing various multi-agent simulation scenarios.
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