Analyzing waste prevention behaviors by applying an ABMS framework

Nature and society have undergone fast and intense changes in the last decades. Consumption is expanding at a hyperbolic rate. Technological innovation has bypassed some environmental problems, but it is hardly sufficient to solve them. As a result, understanding the factors related to people's behavior is imperative when finding a novel approach for intervention policies that can effectively alleviate environmental impacts caused by human activities. A promising alternative to designing waste prevention (WP) policies is to develop strategies to endure behavioral change through collective actions. This paper briefly reviews some WP status worldwide and highlights the possibility of using agent-based modeling and simulation (ABMS) to plan WP policies and programs. ABMS enables a more in-depth analysis since experiments with a large sample in real situations are financial, temporal, and social cost-demanding. Preliminary results show an influence of the social norm on the adoption of reusable bags by individuals with medium and lower pro-environmental motivations. Understanding these dynamics relations in which WP policy is embedded makes it possible to forecast future waste generation and composition scenarios. Also, a framework for planning WP with ABMS is proposed.