System dynamics-based evaluation of interventions to promote appropriate waste disposal behaviors in low-income urban areas: A Baltimore case study. (October 2016)

• Record Type: Journal Article
• Authors: Guo, Huaqing; Hobbs, Benjamin F.; Lasater, Molly E.; Parker, Cindy L.; Winch, Peter J.
• Is Part Of: Waste management. Volume 56(2016)
• Page Start: 547
• Page End: 560
• Publication Date: 2016-10
• Subjects: System dynamics -- Household waste -- Litter -- Recycling -- Waste management intervention -- Social norms; Hazardous wastes -- Periodicals; Refuse and refuse disposal -- Periodicals; 363.728
• DOI: 10.1016/j.wasman.2016.05.019
• Languages: English
• ISSNs: 0956-053X

Abstract

Highlights: We present a system dynamics model for evaluating trash policy in poor neighborhoods. The framework incorporates technical, normative, and behavioral factors. The model quantifies impacts of interventions on residential behavior and outcomes. We identify synergisms and positive spillovers among policy interventions. Abstract: Inappropriate waste disposal is a serious issue in many urban neighborhoods, exacerbating environmental, rodent, and public health problems. Governments all over the world have been developing interventions to reduce inappropriate waste disposal. A system dynamics model is proposed to quantify the impacts of interventions on residential waste related behavior. In contrast to other models of municipal solid waste management, the structure of our model is based on sociological and economic studies on how incentives and social norms interactively affect waste disposal behavior, and its parameterization is informed by field work. A case study of low-income urban neighborhoods in Baltimore, MD, USA is presented. The simulation results show the effects of individual interventions, and also identify positive interactions among some potential interventions, especially information and incentive-based policies, as well as their limitations. The model can help policy analysts identify the most promising intervention packages, and then field test those few, rather than having to pilot test all combinations. Sensitivity analyses demonstrate large uncertainties about behavioral responses to some interventions, showing where information from survey research and social experiments would improve policy making.