How can simulation be sold to policy decision makers? How can simulation be sold to other social scientists that do not accept simulation as a complement to accepted techniques (Repenning, 2003)?
Simulation provides a means to gain insight into the past behaviour and future trajectories of complex social systems. The simulation process is one of discovery: individual mental models are communicated, formalised, and simulated under a range of scenarios. There are two main approaches to social simulation: system dynamics, centred on the feedback perspective, and agent based computational modelling, which uses the individual and their interactions as the basic building block. This short paper describes a new simulation tool that can accommodate both perspectives, and where all model building is achieved using an equation-based approach. The system design is summarised and an example based on the SIR model is described.
Social-ecological resilience is an increasingly central paradigm for understanding sustainable resource management. While previous works on resilience have observed that sudden shocks or gradual stressors may force a system over a critical threshold, natural variations may have similar results. This paper aims to better understand the effect of environmental variability on the resilience of fishery systems, and the important role that social institutions play. To explore these issues, we build a System Dynamics Model of the mollusc fishery of the indigenous Seri people in the Gulf of California, Mexico. This model includes the dynamics of the two dominant species of penn shell in the fishery (Atrina tuberculosa and Pinna rugosa), several institutional rules that the Seri use, and a number of key stochastic variables derived from empirical data. We find that modeling with multiple species, rather than the standard one-species model, uncovers more resilience in the system. However, while we expected stochasticity to be detrimental to resilience, we find that endogenous environmental variability can also increase resilience. We examine possible reasons for this finding, and discuss additional insights our study revealed about managing multiple-species artisanal fisheries.
Maize is widely grown in Africa including in drier areas where alternate crops will often perform better. Although maize will fail in drought years, it produces substantially higher yields than alternates, like sorghum and millet, in wet years. Although people tend to select which crops to grow based on recent experience with crop harvests and market prices, there is a widespread preference for maize even in areas where planting it is risky. This can lead to crop failures when rainfall varies from year to year. Introduction of higher yielding maize varieties might, under some conditions, cause increases in food shortages by further incentivizing the planting of maize in inappropriate situations. A preliminary model helps to investigate this and related issues.
This paper describes a system dynamics model designed to test policies that could potentially limit, halt, or reverse the growth of human trafficking (and more broadly female exploitation for sex) in Washington, D.C and elsewhere. Human trafficking has been deemed a crime against humanity, yet despite prevention programs around the world the practice has continued to flourish. We believe these policies have had limited impact because of the variety of variables and causal structures that influence the system as a whole. Through the study of the trafficking/exploitation sex market in Washington, D.C., we have identified some key drivers and limiters in the system, as well as some of the complex interactions between them. A computerized version of our model allows policy makers to virtually test how new policies are likely to influence the system before actually implementing them in the real world. System dynamics presents a new tool in the effort to combat human trafficking/exploitation around the world, and our model is the first step towards fully comprehending and eventually eliminating this modern form of slavery.
In this paper, we apply system dynamics to model a queuing system wherein the manager of a service facility adjusts capacity based on his perception of the queue size; while potential and current customers react to the managers decisions. Current customers update their perception based on their own experience and decide whether to remain patronizing the facility, whereas potential customers estimate their expected waiting time through word of mouth and decide whether to join the facility or not. We simulate the model and analyze the evolution of the backlog of work and the available service capacity. Based on this analysis we propose two alternative decision rules to maximize the managers cumulative profits. Then, we illustrate how we have developed an experiment to collect information about the way human subjects taking on the role of a manager in a lab environment face a situation in which they must adjust the capacity of a service facility.
This work evaluates the impact of existing policies in the Brazilian National Plan for Logistics and Transport (PNLT) on CO2 emissions due to the transport of domestic cargo. We build a formal system dynamics model capturing the causal relationships influencing the modal shift from road to cabotage transport of cargo in Brazil. Scenarios are charted to understand the impact of PNLT policies on CO2 emissions(?) and the implications for the transport infrastructure. Our analysis shows that pressure to reduce CO2 emissions plays a critical role accelerating the modal shift from road to cabotage.