An awareness based approach to sustainability
explicit assumptions , simulation does not prove theorems but instead generates data that can be analyzed inductively , as a way of conducting thought experiments ”. Some questions can however be answered with simulation experiments ( Bianchi , Cirillo , Gallegati , & Vagliasindi , 2007 ). According to Marks ( 2007 ) “... a simulation might attempt to explain a phenomenon ; it might attempt to predict the outcome of a phenomenon ; or it might be used to explore a phenomenon , to play , in order to understand the interactions of elements of the structure that produces the phenomenon ”. There are important classes of problems for which writing down equations is not a useful activity . In such circumstances , resort to agent-based computational models may be the only way available to explore such processes systematically , and constitute a third distinct usage of such models ( Axtell , 2000 ).
We present an exploratory model that might be used to play and explore different situations , in order to understand the interactions of elements of the structure that produces the phenomenon .
SAM4SN
We focus on an urban district or a geographically limited area of a “ North Global ” country , i . e . the economically developed societies of Europe , North America , and Australia where the prevailing is known not to be sustainable in terms of energy consumption , carbon dioxide emission , and depletion of scarce resources . The SAM4SN allows defining a set of scenarios , to study the emergence of collective phenomena that are impossible to foresee at individual level . Of course , there will be scenarios that lead to overuse of the resource , and scenarios where this does not happen because the social mechanism has a positive effect , i . e . sustainable behavior emerges .
The model can be applied to given real situation supplying the geographical position of all agents and under the hypothesis that all agents have the availability of the same set of smart metering functions . Consistently with the last statement , the network definition used here is that of the real neighborhood at the district level .
The goal is to observe at a macrolevel how awareness can spread in the community , how the dynamics of awareness affects individual reduction goals , and how the availability of different smart metering functions impact on such mechanisms . “ Green ” people , i . e . people with high environmental awareness , can decide to limit the privacy of their own consumption information and share with the community their own consumption data . Such voluntary mechanism of “ privacy versus reputation ” is an emerging trend in some Global North communities , where becoming a green opinion leader is perceived as a social recognition .
The agents of SAM4SN represent ( groups of ) people involved in the consumption of a limited or critical resource . Each agent models a household . Agent can be or not be supplied by smart functions of metering .
The space of agents is bidimentional . SAM4SN agents interact by proximity and change their awareness according to the number and the type of their neighbors . The initial position of each agent is chosen randomly , under the only condition of “ one household per patch ”. Once an agent ’ s awareness reaches a threshold , the agent joins a different type ( Fig 1 ). The awareness diffusion mechanism is a core point of our model . It is driven by the assumption that
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